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Jason Brownlee ["Q-05 Who require all of the code to work and keep working ! ?"] "
Jason Brownlee ["Q-06 Who keep working ! ?"] "
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Link ["Q-01 Who \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Scott Aaronson) Published on October 7 2019 616 PM UTCScott Aaronson ["Q-02 Who uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
bookThis ["Q-03 What is the bookthis about Ai and Ai risk ?"] "
The bookThis ["Q-04 Who is a book about Ai and Ai risk ?"] "
can't ["Q-05 What but it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
a dual purpose ["Q-06 What does the book has gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-07 Who has a dual purpose it gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-08 Who gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
the rationalist community ["Q-09 Who informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-10 Who is to talk about Scott A ?"] "
opinions ["Q-11 What does in the review he gives about the book including his relationship with the rationalist community and his somewhat changing views on Ai risk ?"] "
Reading Chivers’s ["Q-12 Who prompted me to reflect on your own relationship to the rationalist community ?"] "
me ["Q-13 Whom progress in deep learning and reinforcement learning and Gans which caused ( like everyone else perhaps ) to update in the direction of human - level Ai in your lifetimes being an actual live possibility ?"] "
human-level AI ["Q-14 Who being an actual live possibility ?"] "
Tom Chivers ["Q-01 [ Link ] Book Review \u2018 the Ai Does not by what Hate i \u2019 ( Scott Aaronson ) published on October 7 2019 616 Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Published on October 7 2019 616 PM UTCScott Aaronson ["Q-02 [ Link ] Book Review \u2018 the Ai Does not on what Hate i \u2019 by Tom Chivers ( Scott Aaronson ) Published uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
PM UTCScott Aaronson ["Q-03 [ Link ] Book Review \u2018 the Ai Does not Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 about what Pm Utcscott Aaronson uploaded a review not Hate i a book by Tom Chivers ?"] "
PM UTCScott Aaronson ["Q-04 [ Link ] Book Review \u2018 the Ai Does not Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 by what Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book ?"] "
UTCScott Aaronson ["Q-05 [ Link ] Book Review \u2018 the Ai Does not Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 what Pm Utcscott Aaronson uploaded about the Ai Does not Hate i a book by Tom Chivers ?"] "
Link ["Q-06 Who \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Scott Aaronson) Published on October 7 2019 616 PM UTCScott Aaronson ["Q-07 Who uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
The bookThis is a book about AI and AI risk ["Q-08 [ Link ] Book Review \u2018 the Ai Does not how much Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Reading Chivers’s ["Q-09 ]
AI ["Q-010 About what is the bookthis a book and Ai risk ?"] "
bookThis ["Q-011 What is the bookthis about Ai and Ai risk ?"] "
The bookThis ["Q-012 Who is a book about Ai and Ai risk ?"] "
Reading Chivers’s ["Q-013 ]
a community ["Q-014 About what but it & apos ; s also more importantly of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-015 Of what but it & apos ; s also more importantly about a community who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
intelligence ["Q-016 About what but it & apos ; s also more importantly about a community of people who are trying to think rationally and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
these thoughts ["Q-017 That what but it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-018 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can about what ; t give us of the human race over the next few years ?"] "
can't ["Q-019 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can of what ; t give us about the future over the next few years ?"] "
can't ["Q-020 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can over what ; t give us about the future of the human race ?"] "
can't ["Q-021 What but it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-022 But it & apos ; s also more importantly about a community of people who are trying to think rationally what are about intelligence and the places that these thoughts taking and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
it's ["Q-023 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what whom you you N N can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-024 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can what ; t N about the future of the human race over the next few years ?"] "
Discuss ["Q-025 ]
the most important events ["Q-026 The book has of what does a dual purpose it gives an account that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
the rationalist community ["Q-027 The book has on what does a dual purpose it gives an account of the most important events that happened while informing on the current state of the Ai risk field ?"] "
a dual purpose ["Q-028 The book has while what does a dual purpose it gives an account of the most important events that happened on the rationalist community on the current state of the Ai risk field ?"] "
current state of the AI risk field ["Q-029 The book has a dual purpose it gives an account of the most important events that happened on what on the rationalist community while informing informing of the Ai risk field ?"] "
the AI risk field ["Q-030 The book has a dual purpose it gives an account of the most important events that happened of what on the rationalist community while informing informing on the current state ?"] "
a dual purpose ["Q-031 What does the book has gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
a dual purpose ["Q-032 The book has what does a dual purpose it gives of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-033 Who has a dual purpose it gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-034 Who gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
the rationalist community ["Q-035 Who informing on the current state of the Ai risk field ?"] "
Discuss ["Q-036 ]
Reading Chivers’s ["Q-037 ]
Scott A. post ["Q-038 About what is this to talk ?"] "
There's a Lesswrong ["Q-039 Who is to talk about Scott A ?"] "
Scott Aaronson) Published on October 7 2019 616 PM UTCScott ["Q-040 ]
Scott Aaronson) Published on October 7 2019 616 PM UTCScott Aaronson uploaded a review about The AI Does Not Hate You a book by Tom Chivers.The bookThis is a book about AI and AI risk. But it's also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can't give us about the future of the human race over the next few years.The book has a dual purpose it gives an account of the most important events that happened on the rationalist community while informing on the current state of the AI risk field. There's ["Q-041 ]
the book including his relationship ["Q-042 About what does in the review he gives his opinions with the rationalist community and his somewhat changing views on Ai risk ?"] "
rationalist community ["Q-043 In the review he gives with what his opinions about the book including including his relationship and his somewhat changing views on Ai risk ?"] "
AI risk ["Q-044 In the review he gives on what his opinions about the book including his relationship with the rationalist community and his somewhat changing including views ?"] "
opinions ["Q-045 What does in the review he gives about the book including his relationship with the rationalist community and his somewhat changing views on Ai risk ?"] "
his relationship ["Q-046 In the review he gives what his opinions about the book including including with the rationalist community and his somewhat changing views on Ai risk ?"] "
his opinions about the book including his relationship with the rationalist community and his somewhat changing views ["Q-047 In the review he gives what his opinions about the book including his relationship with the rationalist community and his somewhat changing including on Ai risk ?"] "
Scott A. post ["Q-048 In the review he gives his opinions about the book including his relationship with the rationalist community and whose somewhat changing views on Ai risk ?"] "
Reading Chivers’s ["Q-049 ]
the rationalist community ["Q-050 Reading Chivers & # x2019 ; to what did s book prompted me to reflect on your own relationship ?"] "
AI risk ["Q-051 Reading Chivers & # x2019 ; on what did s book prompted me to reflect own relationship to the rationalist community ?"] "
Scott A. ["Q-052 Reading Chivers & # x2019 ; whom did s book prompted to reflect on your own relationship to the rationalist community ?"] "
Reading Chivers’s ["Q-053 Who prompted me to reflect on your own relationship to the rationalist community ?"] "
Reading Chivers’s ["Q-054 ]
everyone ["Q-055 Like what progress in deep learning and reinforcement learning and Gans which caused me ( else perhaps ) to update in the direction of human - level Ai in your lifetimes being an actual live possibility ?"] "
astounding progress ["Q-056 In what progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update of human - level Ai in your lifetimes being an actual live possibility ?"] "
astounding progress ["Q-057 Of what progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction in your lifetimes being an actual live possibility ?"] "
astounding progress ["Q-058 In what progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction of human - level Ai actual live possibility ?"] "
me ["Q-059 Whom progress in deep learning and reinforcement learning and Gans which caused ( like everyone else perhaps ) to update in the direction of human - level Ai in your lifetimes being an actual live possibility ?"] "
Reading Chivers’s book prompted me to reflect on my own relationship to the rationalist community.The astounding progress in deep learning and reinforcement learning and GANs which caused me (like everyone else perhaps) to update in the direction of human-level AI ["Q-060 The astounding progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction of what human - level Ai in your lifetimes being being ?"] "
our lifetimes ["Q-061 The astounding progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction of human - level Ai in whose lifetimes being an actual live possibility ?"] "
human-level AI ["Q-062 Who being an actual live possibility ?"] "
Discuss ["Q-063 ]
Reading Chivers’s ["Q-064 ]
Link ["Q-01 Who \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Scott Aaronson) Published on October 7 2019 616 PM UTCScott Aaronson ["Q-02 Who uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
bookThis ["Q-03 What is the bookthis about Ai and Ai risk ?"] "
The bookThis ["Q-04 Who is a book about Ai and Ai risk ?"] "
can't ["Q-05 What but it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
a dual purpose ["Q-06 What does the book has gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-07 Who has a dual purpose it gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-08 Who gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
the rationalist community ["Q-09 Who informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-10 Who is to talk about Scott A ?"] "
opinions ["Q-11 What does in the review he gives about the book including his relationship with the rationalist community and his somewhat changing views on Ai risk ?"] "
Reading Chivers’s ["Q-12 Who prompted me to reflect on your own relationship to the rationalist community ?"] "
me ["Q-13 Whom progress in deep learning and reinforcement learning and Gans which caused ( like everyone else perhaps ) to update in the direction of human - level Ai in your lifetimes being an actual live possibility ?"] "
human-level AI ["Q-14 Who being an actual live possibility ?"] "
Tom Chivers ["Q-01 [ Link ] Book Review \u2018 the Ai Does not by what Hate i \u2019 ( Scott Aaronson ) published on October 7 2019 616 Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Published on October 7 2019 616 PM UTCScott Aaronson ["Q-02 [ Link ] Book Review \u2018 the Ai Does not on what Hate i \u2019 by Tom Chivers ( Scott Aaronson ) Published uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
PM UTCScott Aaronson ["Q-03 [ Link ] Book Review \u2018 the Ai Does not Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 about what Pm Utcscott Aaronson uploaded a review not Hate i a book by Tom Chivers ?"] "
PM UTCScott Aaronson ["Q-04 [ Link ] Book Review \u2018 the Ai Does not Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 by what Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book ?"] "
UTCScott Aaronson ["Q-05 [ Link ] Book Review \u2018 the Ai Does not Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 what Pm Utcscott Aaronson uploaded about the Ai Does not Hate i a book by Tom Chivers ?"] "
Link ["Q-06 Who \u2019 by Tom Chivers ( Scott Aaronson ) published on October 7 2019 616 Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Scott Aaronson) Published on October 7 2019 616 PM UTCScott Aaronson ["Q-07 Who uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
The bookThis is a book about AI and AI risk ["Q-08 [ Link ] Book Review \u2018 the Ai Does not how much Hate i \u2019 by Tom Chivers ( Scott Aaronson ) published on October Pm Utcscott Aaronson uploaded a review about the Ai Does not Hate i a book by Tom Chivers ?"] "
Reading Chivers’s ["Q-09 ]
AI ["Q-010 About what is the bookthis a book and Ai risk ?"] "
bookThis ["Q-011 What is the bookthis about Ai and Ai risk ?"] "
The bookThis ["Q-012 Who is a book about Ai and Ai risk ?"] "
Reading Chivers’s ["Q-013 ]
a community ["Q-014 About what but it & apos ; s also more importantly of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-015 Of what but it & apos ; s also more importantly about a community who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
intelligence ["Q-016 About what but it & apos ; s also more importantly about a community of people who are trying to think rationally and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
these thoughts ["Q-017 That what but it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-018 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can about what ; t give us of the human race over the next few years ?"] "
can't ["Q-019 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can of what ; t give us about the future over the next few years ?"] "
can't ["Q-020 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can over what ; t give us about the future of the human race ?"] "
can't ["Q-021 What but it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-022 But it & apos ; s also more importantly about a community of people who are trying to think rationally what are about intelligence and the places that these thoughts taking and what insight they can and can & apos ; t give us about the future of the human race over the next few years ?"] "
it's ["Q-023 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what whom you you N N can and can & apos ; t give us about the future of the human race over the next few years ?"] "
can't ["Q-024 But it & apos ; s also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can what ; t N about the future of the human race over the next few years ?"] "
Discuss ["Q-025 ]
the most important events ["Q-026 The book has of what does a dual purpose it gives an account that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
the rationalist community ["Q-027 The book has on what does a dual purpose it gives an account of the most important events that happened while informing on the current state of the Ai risk field ?"] "
a dual purpose ["Q-028 The book has while what does a dual purpose it gives an account of the most important events that happened on the rationalist community on the current state of the Ai risk field ?"] "
current state of the AI risk field ["Q-029 The book has a dual purpose it gives an account of the most important events that happened on what on the rationalist community while informing informing of the Ai risk field ?"] "
the AI risk field ["Q-030 The book has a dual purpose it gives an account of the most important events that happened of what on the rationalist community while informing informing on the current state ?"] "
a dual purpose ["Q-031 What does the book has gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
a dual purpose ["Q-032 The book has what does a dual purpose it gives of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-033 Who has a dual purpose it gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
Scott A. post ["Q-034 Who gives an account of the most important events that happened on the rationalist community while informing on the current state of the Ai risk field ?"] "
the rationalist community ["Q-035 Who informing on the current state of the Ai risk field ?"] "
Discuss ["Q-036 ]
Reading Chivers’s ["Q-037 ]
Scott A. post ["Q-038 About what is this to talk ?"] "
There's a Lesswrong ["Q-039 Who is to talk about Scott A ?"] "
Scott Aaronson) Published on October 7 2019 616 PM UTCScott ["Q-040 ]
Scott Aaronson) Published on October 7 2019 616 PM UTCScott Aaronson uploaded a review about The AI Does Not Hate You a book by Tom Chivers.The bookThis is a book about AI and AI risk. But it's also more importantly about a community of people who are trying to think rationally about intelligence and the places that these thoughts are taking them and what insight they can and can't give us about the future of the human race over the next few years.The book has a dual purpose it gives an account of the most important events that happened on the rationalist community while informing on the current state of the AI risk field. There's ["Q-041 ]
the book including his relationship ["Q-042 About what does in the review he gives his opinions with the rationalist community and his somewhat changing views on Ai risk ?"] "
rationalist community ["Q-043 In the review he gives with what his opinions about the book including including his relationship and his somewhat changing views on Ai risk ?"] "
AI risk ["Q-044 In the review he gives on what his opinions about the book including his relationship with the rationalist community and his somewhat changing including views ?"] "
opinions ["Q-045 What does in the review he gives about the book including his relationship with the rationalist community and his somewhat changing views on Ai risk ?"] "
his relationship ["Q-046 In the review he gives what his opinions about the book including including with the rationalist community and his somewhat changing views on Ai risk ?"] "
his opinions about the book including his relationship with the rationalist community and his somewhat changing views ["Q-047 In the review he gives what his opinions about the book including his relationship with the rationalist community and his somewhat changing including on Ai risk ?"] "
Scott A. post ["Q-048 In the review he gives his opinions about the book including his relationship with the rationalist community and whose somewhat changing views on Ai risk ?"] "
Reading Chivers’s ["Q-049 ]
the rationalist community ["Q-050 Reading Chivers & # x2019 ; to what did s book prompted me to reflect on your own relationship ?"] "
AI risk ["Q-051 Reading Chivers & # x2019 ; on what did s book prompted me to reflect own relationship to the rationalist community ?"] "
Scott A. ["Q-052 Reading Chivers & # x2019 ; whom did s book prompted to reflect on your own relationship to the rationalist community ?"] "
Reading Chivers’s ["Q-053 Who prompted me to reflect on your own relationship to the rationalist community ?"] "
Reading Chivers’s ["Q-054 ]
everyone ["Q-055 Like what progress in deep learning and reinforcement learning and Gans which caused me ( else perhaps ) to update in the direction of human - level Ai in your lifetimes being an actual live possibility ?"] "
astounding progress ["Q-056 In what progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update of human - level Ai in your lifetimes being an actual live possibility ?"] "
astounding progress ["Q-057 Of what progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction in your lifetimes being an actual live possibility ?"] "
astounding progress ["Q-058 In what progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction of human - level Ai actual live possibility ?"] "
me ["Q-059 Whom progress in deep learning and reinforcement learning and Gans which caused ( like everyone else perhaps ) to update in the direction of human - level Ai in your lifetimes being an actual live possibility ?"] "
Reading Chivers’s book prompted me to reflect on my own relationship to the rationalist community.The astounding progress in deep learning and reinforcement learning and GANs which caused me (like everyone else perhaps) to update in the direction of human-level AI ["Q-060 The astounding progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction of what human - level Ai in your lifetimes being being ?"] "
our lifetimes ["Q-061 The astounding progress in deep learning and reinforcement learning and Gans which caused me ( like everyone else perhaps ) to update in the direction of human - level Ai in whose lifetimes being an actual live possibility ?"] "
human-level AI ["Q-062 Who being an actual live possibility ?"] "
Discuss ["Q-063 ]
Reading Chivers’s ["Q-064 ]
Amazon SageMaker ml.p3dn.24xlarge ["Q-01 Who optimized for distributed machine learning with up to 4x the network bandwidth of ml ?"] "
Amazon SageMaker now ["Q-02 Who optimized for machine learning applications ?"] "
faster networking ["Q-03 What does this instance provides which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
P3 ["Q-04 What does this instance provides faster networking which helps remove data transfer bottlenecks and o you of Gpus to deliver maximum performance for training deep learning models ?"] "
Amazon SageMaker now ["Q-05 Who provides faster networking which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
Amazon SageMaker now ["Q-01 ]
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4x the network bandwidth ["Q-03 24xlarge instances optimized for to what did distributed machine learning with distributed of ml ?"] "
distributed machine learning ["Q-04 24xlarge for what did instances optimized with up to 4x the network bandwidth of ml ?"] "
Amazon SageMaker ml.p3dn.24xlarge ["Q-05 24xlarge of what did instances optimized for distributed machine learning with up to 4x the network bandwidth ?"] "
Amazon SageMaker ml.p3dn.24xlarge ["Q-06 Who optimized for distributed machine learning with up to 4x the network bandwidth of ml ?"] "
Amazon SageMaker now ["Q-07 ]
Amazon SageMaker now ["Q-08 ]
Amazon SageMaker now ["Q-09 ]
Amazon SageMaker now ["Q-010 ]
machine learning applications ["Q-011 24xlarge the most for what did powerful P3 instance optimized ?"] "
Amazon SageMaker now ["Q-012 Who optimized for machine learning applications ?"] "
Amazon SageMaker now ["Q-013 ]
data transfer bottlenecks ["Q-014 This instance provides faster networking which helps remove of what the utilization to deliver maximum performance for training deep learning models ?"] "
data transfer bottlenecks ["Q-015 This instance provides faster networking which helps remove for what the utilization of Gpus to deliver maximum performance deep learning models ?"] "
faster networking ["Q-016 What does this instance provides which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
P3 ["Q-017 This instance provides faster networking which what h h N N N and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
P3 ["Q-018 What does this instance provides faster networking which helps remove data transfer bottlenecks and o you of Gpus to deliver maximum performance for training deep learning models ?"] "
data transfer bottlenecks ["Q-019 This instance provides faster networking which helps remove what the utilization of Gpus to d R for training deep learning models ?"] "
data transfer bottlenecks ["Q-020 This instance provides faster networking which helps remove what the utilization of Gpus to deliver maximum performance for training ?"] "
Amazon SageMaker now ["Q-021 Who provides faster networking which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
Amazon SageMaker now ["Q-022 ]
Amazon SageMaker now ["Q-023 ]
Amazon SageMaker ml.p3dn.24xlarge ["Q-01 Who optimized for distributed machine learning with up to 4x the network bandwidth of ml ?"] "
Amazon SageMaker now ["Q-02 Who optimized for machine learning applications ?"] "
faster networking ["Q-03 What does this instance provides which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
P3 ["Q-04 What does this instance provides faster networking which helps remove data transfer bottlenecks and o you of Gpus to deliver maximum performance for training deep learning models ?"] "
Amazon SageMaker now ["Q-05 Who provides faster networking which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
Amazon SageMaker now ["Q-01 ]
Amazon SageMaker now ["Q-02 ]
4x the network bandwidth ["Q-03 24xlarge instances optimized for to what did distributed machine learning with distributed of ml ?"] "
distributed machine learning ["Q-04 24xlarge for what did instances optimized with up to 4x the network bandwidth of ml ?"] "
Amazon SageMaker ml.p3dn.24xlarge ["Q-05 24xlarge of what did instances optimized for distributed machine learning with up to 4x the network bandwidth ?"] "
Amazon SageMaker ml.p3dn.24xlarge ["Q-06 Who optimized for distributed machine learning with up to 4x the network bandwidth of ml ?"] "
Amazon SageMaker now ["Q-07 ]
Amazon SageMaker now ["Q-08 ]
Amazon SageMaker now ["Q-09 ]
Amazon SageMaker now ["Q-010 ]
machine learning applications ["Q-011 24xlarge the most for what did powerful P3 instance optimized ?"] "
Amazon SageMaker now ["Q-012 Who optimized for machine learning applications ?"] "
Amazon SageMaker now ["Q-013 ]
data transfer bottlenecks ["Q-014 This instance provides faster networking which helps remove of what the utilization to deliver maximum performance for training deep learning models ?"] "
data transfer bottlenecks ["Q-015 This instance provides faster networking which helps remove for what the utilization of Gpus to deliver maximum performance deep learning models ?"] "
faster networking ["Q-016 What does this instance provides which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
P3 ["Q-017 This instance provides faster networking which what h h N N N and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
P3 ["Q-018 What does this instance provides faster networking which helps remove data transfer bottlenecks and o you of Gpus to deliver maximum performance for training deep learning models ?"] "
data transfer bottlenecks ["Q-019 This instance provides faster networking which helps remove what the utilization of Gpus to d R for training deep learning models ?"] "
data transfer bottlenecks ["Q-020 This instance provides faster networking which helps remove what the utilization of Gpus to deliver maximum performance for training ?"] "
Amazon SageMaker now ["Q-021 Who provides faster networking which helps remove data transfer bottlenecks and optimizes the utilization of Gpus to deliver maximum performance for training deep learning models ?"] "
Amazon SageMaker now ["Q-022 ]
Amazon SageMaker now ["Q-023 ]
FabreX support ["Q-01 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
Xilinx FPGA developers ["Q-02 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides with remote cloud access to the Fabrex platform ?"] "
GigaIO Optimizes Scalability ["Q-03 Who introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
adaptable accelerator cards Xilinx developers ["Q-04 Who will use Fabrex to enhance proof of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
concept software ["Q-05 Who testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
Xilinx Alveo FPGAs ["Q-06 Who appeared first on insidehpc ?"] "
an exclusive offering ["Q-01 To what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
the FabreX platform ["Q-02 To what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access ?"] "
Xilinx Alveo Accelerators ["Q-03 For what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
FabreX ["Q-04 In what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
remote cloud access ["Q-05 With what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers to the Fabrex platform ?"] "
FabreX support ["Q-06 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
Xilinx FPGA developers ["Q-07 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides with remote cloud access to the Fabrex platform ?"] "
GigaIO Optimizes Scalability ["Q-08 Who introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
. ["Q-09 ]
concept software testing ["Q-010 In conjunction with the Xilinx Alveo family of of what will adaptable accelerator cards Xilinx developers use Fabrex to enhance proof and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
proof ["Q-011 In conjunction with the Xilinx Alveo family of adaptable accelerator cards Xilinx developers will use Fabrex to enhance in what proof of concept software testing testing and scale - out deployments like artificial intelligence deep learning inference and high - performance computing ?"] "
proof ["Q-012 In conjunction with the Xilinx Alveo family of adaptable accelerator cards Xilinx developers will use Fabrex to enhance like what proof of concept software testing testing and scale - out deployments in applications deep learning inference and high - performance computing ?"] "
FabreX ["Q-013 In conjunction with the Xilinx Alveo family of what will adaptable accelerator cards Xilinx developers use to enhance proof of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
enhance proof ["Q-014 In conjunction with the Xilinx Alveo family of what will adaptable accelerator cards Xilinx developers use Fabrex to e N of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
adaptable accelerator cards Xilinx developers ["Q-015 Who will use Fabrex to enhance proof of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
concept software ["Q-016 Who testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
. ["Q-017 ]
insideHPC ["Q-018 On what did the post Gigaio Optimizes Scalability of Xilinx Alveo Fpgas appeared first ?"] "
Xilinx Alveo FPGAs ["Q-019 Who appeared first on insidehpc ?"] "
GigaIO Optimizes Scalability of Xilinx Alveo FPGAs Today GigaIO ["Q-020 ]
. ["Q-021 ]
FabreX support ["Q-01 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
Xilinx FPGA developers ["Q-02 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides with remote cloud access to the Fabrex platform ?"] "
GigaIO Optimizes Scalability ["Q-03 Who introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
adaptable accelerator cards Xilinx developers ["Q-04 Who will use Fabrex to enhance proof of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
concept software ["Q-05 Who testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
Xilinx Alveo FPGAs ["Q-06 Who appeared first on insidehpc ?"] "
an exclusive offering ["Q-01 To what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
the FabreX platform ["Q-02 To what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access ?"] "
Xilinx Alveo Accelerators ["Q-03 For what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
FabreX ["Q-04 In what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
remote cloud access ["Q-05 With what did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers to the Fabrex platform ?"] "
FabreX support ["Q-06 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
Xilinx FPGA developers ["Q-07 What did Gigaio Optimizes Scalability of Xilinx Alveo Fpgas Today Gigaio introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides with remote cloud access to the Fabrex platform ?"] "
GigaIO Optimizes Scalability ["Q-08 Who introduced Fabrex support for Xilinx Alveo Accelerators in addition to an exclusive offering that provides Xilinx Fpga developers with remote cloud access to the Fabrex platform ?"] "
. ["Q-09 ]
concept software testing ["Q-010 In conjunction with the Xilinx Alveo family of of what will adaptable accelerator cards Xilinx developers use Fabrex to enhance proof and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
proof ["Q-011 In conjunction with the Xilinx Alveo family of adaptable accelerator cards Xilinx developers will use Fabrex to enhance in what proof of concept software testing testing and scale - out deployments like artificial intelligence deep learning inference and high - performance computing ?"] "
proof ["Q-012 In conjunction with the Xilinx Alveo family of adaptable accelerator cards Xilinx developers will use Fabrex to enhance like what proof of concept software testing testing and scale - out deployments in applications deep learning inference and high - performance computing ?"] "
FabreX ["Q-013 In conjunction with the Xilinx Alveo family of what will adaptable accelerator cards Xilinx developers use to enhance proof of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
enhance proof ["Q-014 In conjunction with the Xilinx Alveo family of what will adaptable accelerator cards Xilinx developers use Fabrex to e N of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
adaptable accelerator cards Xilinx developers ["Q-015 Who will use Fabrex to enhance proof of concept software testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
concept software ["Q-016 Who testing and scale - out deployments in applications like artificial intelligence deep learning inference and high - performance computing ?"] "
. ["Q-017 ]
insideHPC ["Q-018 On what did the post Gigaio Optimizes Scalability of Xilinx Alveo Fpgas appeared first ?"] "
Xilinx Alveo FPGAs ["Q-019 Who appeared first on insidehpc ?"] "
GigaIO Optimizes Scalability of Xilinx Alveo FPGAs Today GigaIO ["Q-020 ]
. ["Q-021 ]
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post ["Q-01 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
your pipeline ["Q-02 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement and downloaded the datasets i mentioned in the post ?"] "
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI ["Q-03 Who was trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-04 Who downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-05 Who mentioned in the post ?"] "
public data ["Q-06 What did you just did not know how to convert into tfrecords ?"] "
jay hiI ["Q-07 Who just did not know how to convert the public data into tfrecords ?"] "
jay hiI ["Q-08 Who named pascalvoc ?"] "
Comment ["Q-09 Who found that this script was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post. I just did not know how to convert the public data into tfrecords. There is a script in lumi named pascalvoc.py ["Q-10 Who was rectangle for rectangle bounding box which is not suitable for the polygon annotations ?"] "
Could u ["Q-11 Whom me how u did ? thanks a lot ! ?"] "
the post ["Q-01 Comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii was trying to implement my pipeline and downloaded in what did the datasets i mentioned ?"] "
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post ["Q-02 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
your pipeline ["Q-03 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement and downloaded the datasets i mentioned in the post ?"] "
the datasets ["Q-04 Comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii was trying to implement what did my pipeline and downloaded in the post ?"] "
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI ["Q-05 Who was trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-06 Who downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-07 Who mentioned in the post ?"] "
pascalvoc.py ["Q-08 ]
tfrecords ["Q-09 Into what did you just did not know how to convert the public data ?"] "
public data ["Q-010 What did you just did not know how to convert into tfrecords ?"] "
jay hiI ["Q-011 Who just did not know how to convert the public data into tfrecords ?"] "
pascalvoc.py ["Q-012 ]
pascalvoc.py ["Q-013 There is what did a script in lumi named named ?"] "
jay hiI ["Q-014 Who named pascalvoc ?"] "
pascalvoc.py ["Q-015 ]
pascalvoc.py ["Q-016 ]
this script ["Q-017 Anyway that what you found was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
rectangle bounding box ["Q-018 Anyway you found for what did that this script was prepared which is not suitable for the polygon annotations ?"] "
the polygon annotations ["Q-019 Anyway you found for what did that this script was for rectangle bounding box which is not suitable ?"] "
Thanks a lot ["Q-020 Anyway you found what did that this script was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
pascalvoc.py ["Q-021 Who found that this script was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post. I just did not know how to convert the public data into tfrecords. There is a script in lumi named pascalvoc.py ["Q-022 Who was rectangle for rectangle bounding box which is not suitable for the polygon annotations ?"] "
pascalvoc.py ["Q-023 ]
Could u ["Q-024 Whom me how u did ? thanks a lot ! ?"] "
rectangle bounding box ["Q-025 Could u tell me how u did it ? what T T N N N ! ?"] "
pascalvoc.py ["Q-026 ]
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post ["Q-01 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
your pipeline ["Q-02 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement and downloaded the datasets i mentioned in the post ?"] "
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI ["Q-03 Who was trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-04 Who downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-05 Who mentioned in the post ?"] "
public data ["Q-06 What did you just did not know how to convert into tfrecords ?"] "
jay hiI ["Q-07 Who just did not know how to convert the public data into tfrecords ?"] "
jay hiI ["Q-08 Who named pascalvoc ?"] "
Comment ["Q-09 Who found that this script was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post. I just did not know how to convert the public data into tfrecords. There is a script in lumi named pascalvoc.py ["Q-10 Who was rectangle for rectangle bounding box which is not suitable for the polygon annotations ?"] "
Could u ["Q-11 Whom me how u did ? thanks a lot ! ?"] "
the post ["Q-01 Comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii was trying to implement my pipeline and downloaded in what did the datasets i mentioned ?"] "
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post ["Q-02 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
your pipeline ["Q-03 What was comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii trying to implement and downloaded the datasets i mentioned in the post ?"] "
the datasets ["Q-04 Comment on Cell Nuclei Detection on Whole - slide Histopathology Images Using Histomicstk and Faster R - cnn Deep Learning Models by jay hii was trying to implement what did my pipeline and downloaded in the post ?"] "
Comment on Cell Nuclei Detection on Whole-Slide Histopathology Images Using HistomicsTK and Faster R-CNN Deep Learning Models by jay hiI ["Q-05 Who was trying to implement my pipeline and downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-06 Who downloaded the datasets i mentioned in the post ?"] "
jay hiI ["Q-07 Who mentioned in the post ?"] "
pascalvoc.py ["Q-08 ]
tfrecords ["Q-09 Into what did you just did not know how to convert the public data ?"] "
public data ["Q-010 What did you just did not know how to convert into tfrecords ?"] "
jay hiI ["Q-011 Who just did not know how to convert the public data into tfrecords ?"] "
pascalvoc.py ["Q-012 ]
pascalvoc.py ["Q-013 There is what did a script in lumi named named ?"] "
jay hiI ["Q-014 Who named pascalvoc ?"] "
pascalvoc.py ["Q-015 ]
pascalvoc.py ["Q-016 ]
this script ["Q-017 Anyway that what you found was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
rectangle bounding box ["Q-018 Anyway you found for what did that this script was prepared which is not suitable for the polygon annotations ?"] "
the polygon annotations ["Q-019 Anyway you found for what did that this script was for rectangle bounding box which is not suitable ?"] "
Thanks a lot ["Q-020 Anyway you found what did that this script was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
pascalvoc.py ["Q-021 Who found that this script was prepared for rectangle bounding box which is not suitable for the polygon annotations ?"] "
jay hiI was trying to implement your pipeline and downloaded the datasets you mentioned in the post. I just did not know how to convert the public data into tfrecords. There is a script in lumi named pascalvoc.py ["Q-022 Who was rectangle for rectangle bounding box which is not suitable for the polygon annotations ?"] "
pascalvoc.py ["Q-023 ]
Could u ["Q-024 Whom me how u did ? thanks a lot ! ?"] "
rectangle bounding box ["Q-025 Could u tell me how u did it ? what T T N N N ! ?"] "
pascalvoc.py ["Q-026 ]
AbstractNatural products ["Q-01 Who represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
AbstractNatural products ["Q-02 Who utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
microbial secondary metabolites ["Q-03 What are these molecules by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
immunomodulatory agents ["Q-04 Who are microbial secondary metabolites synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
microbial secondary metabolites ["Q-05 Who synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
co-localized genes ["Q-06 Who termed Biosynthetic Gene Clusters ( Bgcs ) ?"] "
The increase in full microbial genomes and similar resources ["Q-07 Who has led to development of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
precision and ability to identify novel BGC classes ["Q-08 Who could be improved ?"] "
random forest ["Q-09 Who present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-10 Who offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-11 Who identify novel Bgc classes compared to existing machine - learning tools ?"] "
novel BGC classes ["Q-12 Who compared to existing machine - learning tools ?"] "
deep learning strategy ["Q-13 What did you supplemented with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
BGC product classes ["Q-14 What did you supplemented this with random forest classifiers that accurately predicted and potential chemical activity ?"] "
DeepBGC ["Q-15 Who supplemented this with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
in-silico BGC identification ["Q-16 Where does the improved accuracy and classification ability of Deepbgc represents a major addition ?"] "
major addition ["Q-17 What does the improved accuracy and classification ability of Deepbgc represents to in - silico Bgc identification ?"] "
ability of DeepBGC ["Q-18 Who represents a major addition to in - silico Bgc identification ?"] "
Biosynthetic Gene Clusters ["Q-01 A deep learning genome - mining strategy for of what biosynthetic gene cluster prediction Abstractnatural products represent a rich reservoir utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
antimicrobial drugs anticancer therapies ["Q-02 A deep learning genome - mining strategy for biosynthetic gene cluster prediction Abstractnatural products represent a rich reservoir of as what small molecule drug candidates utilized and immunomodulatory agents ?"] "
biosynthetic gene cluster prediction AbstractNatural products represent a rich reservoir ["Q-03 A deep learning genome - mining strategy for what N of small molecule drug candidates utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
AbstractNatural products ["Q-04 Who represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
AbstractNatural products ["Q-05 Who utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
Biosynthetic Gene Clusters ["Q-06 ]
co-localized genes ["Q-07 These molecules are by what did microbial secondary metabolites synthesized biosynthetic Gene Clusters ( Bgcs ) ?"] "
microbial secondary metabolites ["Q-08 What are these molecules by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
Biosynthetic Gene Clusters ["Q-09 These molecules are microbial secondary metabolites synthesized by what did co - localized genes termed ( Bgcs ) ?"] "
immunomodulatory agents ["Q-010 Who are microbial secondary metabolites synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
microbial secondary metabolites ["Q-011 Who synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
co-localized genes ["Q-012 Who termed Biosynthetic Gene Clusters ( Bgcs ) ?"] "
. ["Q-013 ]
development ["Q-014 The increase in full microbial genomes and to what has similar resources led of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
BGC prediction algorithms ["Q-015 The increase in full microbial genomes and where has similar resources led to development although their precision and ability to identify novel Bgc classes could be improved ?"] "
precision ["Q-016 The increase in full microbial genomes and although what has similar resources led to development of Bgc prediction algorithms and ability to identify novel Bgc classes could be improved ?"] "
similar resources ["Q-017 The increase in full microbial genomes and what has similar resources led to development of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
similar resources has led to development of BGC prediction algorithms although their precision and ability to identify novel BGC classes ["Q-018 The increase in full microbial genomes and what has similar resources led to development of Bgc prediction algorithms although their precision and ability to identify could be improved ?"] "
novel BGC classes ["Q-019 The increase in full microbial genomes and similar resources has led to development of Bgc prediction algorithms although their precision and ability to identify what could novel Bgc classes be improved ?"] "
The increase in full microbial genomes and similar resources ["Q-020 Who has led to development of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
precision and ability to identify novel BGC classes ["Q-021 Who could be improved ?"] "
Biosynthetic Gene Clusters ["Q-022 ]
BGC prediction algorithms although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers reduced false positive rates in BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing machine-learning tools ["Q-023 Here you present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify did novel Bgc classes compared compared ?"] "
random forest classifiers ["Q-024 Here you present a deep learning strategy ( Deepbgc ) where offers that reduced false positive rates and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
deep learning strategy ["Q-025 Here what you present ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
reduced false positive rates ["Q-026 Here you present a deep learning strategy ( Deepbgc ) that what o o N N N in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
novel BGC classes ["Q-027 Here you present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate what do and identify to existing machine - learning tools ?"] "
machine-learning tools ["Q-028 Here you present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify did novel Bgc classes compared compared to existing ?"] "
random forest ["Q-029 Who present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-030 Who offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-031 Who identify novel Bgc classes compared to existing machine - learning tools ?"] "
novel BGC classes ["Q-032 Who compared to existing machine - learning tools ?"] "
. ["Q-033 ]
random forest classifiers ["Q-034 With what did you supplemented this that accurately predicted Bgc product classes and potential chemical activity ?"] "
deep learning strategy ["Q-035 What did you supplemented with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
BGC product classes ["Q-036 What did you supplemented this with random forest classifiers that accurately predicted and potential chemical activity ?"] "
DeepBGC ["Q-037 Who supplemented this with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
. ["Q-038 ]
. ["Q-039 ]
in-silico BGC identification ["Q-040 Where does the improved accuracy and classification ability of Deepbgc represents a major addition ?"] "
major addition ["Q-041 What does the improved accuracy and classification ability of Deepbgc represents to in - silico Bgc identification ?"] "
ability of DeepBGC ["Q-042 Who represents a major addition to in - silico Bgc identification ?"] "
. ["Q-043 ]
Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy ["Q-044 ]
AbstractNatural products ["Q-01 Who represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
AbstractNatural products ["Q-02 Who utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
microbial secondary metabolites ["Q-03 What are these molecules by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
immunomodulatory agents ["Q-04 Who are microbial secondary metabolites synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
microbial secondary metabolites ["Q-05 Who synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
co-localized genes ["Q-06 Who termed Biosynthetic Gene Clusters ( Bgcs ) ?"] "
The increase in full microbial genomes and similar resources ["Q-07 Who has led to development of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
precision and ability to identify novel BGC classes ["Q-08 Who could be improved ?"] "
random forest ["Q-09 Who present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-10 Who offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-11 Who identify novel Bgc classes compared to existing machine - learning tools ?"] "
novel BGC classes ["Q-12 Who compared to existing machine - learning tools ?"] "
deep learning strategy ["Q-13 What did you supplemented with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
BGC product classes ["Q-14 What did you supplemented this with random forest classifiers that accurately predicted and potential chemical activity ?"] "
DeepBGC ["Q-15 Who supplemented this with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
in-silico BGC identification ["Q-16 Where does the improved accuracy and classification ability of Deepbgc represents a major addition ?"] "
major addition ["Q-17 What does the improved accuracy and classification ability of Deepbgc represents to in - silico Bgc identification ?"] "
ability of DeepBGC ["Q-18 Who represents a major addition to in - silico Bgc identification ?"] "
Biosynthetic Gene Clusters ["Q-01 A deep learning genome - mining strategy for of what biosynthetic gene cluster prediction Abstractnatural products represent a rich reservoir utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
antimicrobial drugs anticancer therapies ["Q-02 A deep learning genome - mining strategy for biosynthetic gene cluster prediction Abstractnatural products represent a rich reservoir of as what small molecule drug candidates utilized and immunomodulatory agents ?"] "
biosynthetic gene cluster prediction AbstractNatural products represent a rich reservoir ["Q-03 A deep learning genome - mining strategy for what N of small molecule drug candidates utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
AbstractNatural products ["Q-04 Who represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
AbstractNatural products ["Q-05 Who utilized as antimicrobial drugs anticancer therapies and immunomodulatory agents ?"] "
Biosynthetic Gene Clusters ["Q-06 ]
co-localized genes ["Q-07 These molecules are by what did microbial secondary metabolites synthesized biosynthetic Gene Clusters ( Bgcs ) ?"] "
microbial secondary metabolites ["Q-08 What are these molecules by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
Biosynthetic Gene Clusters ["Q-09 These molecules are microbial secondary metabolites synthesized by what did co - localized genes termed ( Bgcs ) ?"] "
immunomodulatory agents ["Q-010 Who are microbial secondary metabolites synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
microbial secondary metabolites ["Q-011 Who synthesized by co - localized genes termed biosynthetic Gene Clusters ( Bgcs ) ?"] "
co-localized genes ["Q-012 Who termed Biosynthetic Gene Clusters ( Bgcs ) ?"] "
. ["Q-013 ]
development ["Q-014 The increase in full microbial genomes and to what has similar resources led of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
BGC prediction algorithms ["Q-015 The increase in full microbial genomes and where has similar resources led to development although their precision and ability to identify novel Bgc classes could be improved ?"] "
precision ["Q-016 The increase in full microbial genomes and although what has similar resources led to development of Bgc prediction algorithms and ability to identify novel Bgc classes could be improved ?"] "
similar resources ["Q-017 The increase in full microbial genomes and what has similar resources led to development of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
similar resources has led to development of BGC prediction algorithms although their precision and ability to identify novel BGC classes ["Q-018 The increase in full microbial genomes and what has similar resources led to development of Bgc prediction algorithms although their precision and ability to identify could be improved ?"] "
novel BGC classes ["Q-019 The increase in full microbial genomes and similar resources has led to development of Bgc prediction algorithms although their precision and ability to identify what could novel Bgc classes be improved ?"] "
The increase in full microbial genomes and similar resources ["Q-020 Who has led to development of Bgc prediction algorithms although their precision and ability to identify novel Bgc classes could be improved ?"] "
precision and ability to identify novel BGC classes ["Q-021 Who could be improved ?"] "
Biosynthetic Gene Clusters ["Q-022 ]
BGC prediction algorithms although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers reduced false positive rates in BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing machine-learning tools ["Q-023 Here you present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify did novel Bgc classes compared compared ?"] "
random forest classifiers ["Q-024 Here you present a deep learning strategy ( Deepbgc ) where offers that reduced false positive rates and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
deep learning strategy ["Q-025 Here what you present ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
reduced false positive rates ["Q-026 Here you present a deep learning strategy ( Deepbgc ) that what o o N N N in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
novel BGC classes ["Q-027 Here you present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate what do and identify to existing machine - learning tools ?"] "
machine-learning tools ["Q-028 Here you present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify did novel Bgc classes compared compared to existing ?"] "
random forest ["Q-029 Who present a deep learning strategy ( Deepbgc ) that offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-030 Who offers reduced false positive rates in Bgc identification and an improved ability to extrapolate and identify novel Bgc classes compared to existing machine - learning tools ?"] "
DeepBGC ["Q-031 Who identify novel Bgc classes compared to existing machine - learning tools ?"] "
novel BGC classes ["Q-032 Who compared to existing machine - learning tools ?"] "
. ["Q-033 ]
random forest classifiers ["Q-034 With what did you supplemented this that accurately predicted Bgc product classes and potential chemical activity ?"] "
deep learning strategy ["Q-035 What did you supplemented with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
BGC product classes ["Q-036 What did you supplemented this with random forest classifiers that accurately predicted and potential chemical activity ?"] "
DeepBGC ["Q-037 Who supplemented this with random forest classifiers that accurately predicted Bgc product classes and potential chemical activity ?"] "
. ["Q-038 ]
. ["Q-039 ]
in-silico BGC identification ["Q-040 Where does the improved accuracy and classification ability of Deepbgc represents a major addition ?"] "
major addition ["Q-041 What does the improved accuracy and classification ability of Deepbgc represents to in - silico Bgc identification ?"] "
ability of DeepBGC ["Q-042 Who represents a major addition to in - silico Bgc identification ?"] "
. ["Q-043 ]
Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy ["Q-044 ]
MIOpen ["Q-01 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established to be a common occurrence in the business lexicon ?"] "
MIOpen ["Q-02 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established itself to be in the business lexicon ?"] "
MIOpen An Open Source Library For Deep Learning Primitives Deep Learning ["Q-03 Who has established itself to be a common occurrence in the business lexicon ?"] "
deep learning ["Q-04 Who can be attributed to abundance of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
compute capabilities ["Q-05 Who offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
Deep neural networks ["Q-06 What can deep neural networks be decomposed into [ & # 8230 ; ] ?"] "
Deep neural networks ["Q-07 Who can be decomposed into [ & # 8230 ; ] ?"] "
the business lexicon ["Q-01 In what has miopen an open Source Library for Deep Learning Primitives Deep Learning established itself to be a common occurrence ?"] "
MIOpen ["Q-02 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established to be a common occurrence in the business lexicon ?"] "
MIOpen ["Q-03 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established itself to be in the business lexicon ?"] "
MIOpen An Open Source Library For Deep Learning Primitives Deep Learning ["Q-04 Who has established itself to be a common occurrence in the business lexicon ?"] "
[… ["Q-05 ]
abundance ["Q-06 The unprecedented success of deep learning in to what can recent years be attributed of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
data availability ["Q-07 The unprecedented success of deep learning in of what can recent years be attributed to abundance of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
gargantuan compute capabilities ["Q-08 The unprecedented success of deep learning in of what can recent years be attributed to abundance of data availability by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
GPUs ["Q-09 The unprecedented success of deep learning in recent years can be attributed to abundance of data availability of by what did gargantuan compute capabilities offered and adoption of open - source philosophy by the researchers and industry ?"] "
open-source philosophy ["Q-010 The unprecedented success of deep learning in recent years can be attributed to abundance of data availability of of what did gargantuan compute capabilities offered by Gpus and adoption by the researchers and industry ?"] "
researchers and industry ["Q-011 The unprecedented success of deep learning in recent years can be attributed to abundance of data availability of by what did gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy and industry ?"] "
business lexicon ["Q-012 The unprecedented success of deep learning in what can recent years be attributed to abundance of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
deep learning ["Q-013 Who can be attributed to abundance of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
compute capabilities ["Q-014 Who offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
[… ["Q-015 ]
[ ["Q-016 Into what can deep neural networks be decomposed & # 8230 ; ] ?"] "
Deep neural networks ["Q-017 What can deep neural networks be decomposed into [ & # 8230 ; ] ?"] "
Deep neural networks ["Q-018 Who can be decomposed into [ & # 8230 ; ] ?"] "
Deep neural networks ["Q-019 ]
MIOpen ["Q-01 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established to be a common occurrence in the business lexicon ?"] "
MIOpen ["Q-02 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established itself to be in the business lexicon ?"] "
MIOpen An Open Source Library For Deep Learning Primitives Deep Learning ["Q-03 Who has established itself to be a common occurrence in the business lexicon ?"] "
deep learning ["Q-04 Who can be attributed to abundance of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
compute capabilities ["Q-05 Who offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
Deep neural networks ["Q-06 What can deep neural networks be decomposed into [ & # 8230 ; ] ?"] "
Deep neural networks ["Q-07 Who can be decomposed into [ & # 8230 ; ] ?"] "
the business lexicon ["Q-01 In what has miopen an open Source Library for Deep Learning Primitives Deep Learning established itself to be a common occurrence ?"] "
MIOpen ["Q-02 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established to be a common occurrence in the business lexicon ?"] "
MIOpen ["Q-03 What has miopen an open Source Library for Deep Learning Primitives Deep Learning established itself to be in the business lexicon ?"] "
MIOpen An Open Source Library For Deep Learning Primitives Deep Learning ["Q-04 Who has established itself to be a common occurrence in the business lexicon ?"] "
[… ["Q-05 ]
abundance ["Q-06 The unprecedented success of deep learning in to what can recent years be attributed of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
data availability ["Q-07 The unprecedented success of deep learning in of what can recent years be attributed to abundance of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
gargantuan compute capabilities ["Q-08 The unprecedented success of deep learning in of what can recent years be attributed to abundance of data availability by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
GPUs ["Q-09 The unprecedented success of deep learning in recent years can be attributed to abundance of data availability of by what did gargantuan compute capabilities offered and adoption of open - source philosophy by the researchers and industry ?"] "
open-source philosophy ["Q-010 The unprecedented success of deep learning in recent years can be attributed to abundance of data availability of of what did gargantuan compute capabilities offered by Gpus and adoption by the researchers and industry ?"] "
researchers and industry ["Q-011 The unprecedented success of deep learning in recent years can be attributed to abundance of data availability of by what did gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy and industry ?"] "
business lexicon ["Q-012 The unprecedented success of deep learning in what can recent years be attributed to abundance of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
deep learning ["Q-013 Who can be attributed to abundance of data availability of gargantuan compute capabilities offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
compute capabilities ["Q-014 Who offered by Gpus and adoption of open - source philosophy by the researchers and industry ?"] "
[… ["Q-015 ]
[ ["Q-016 Into what can deep neural networks be decomposed & # 8230 ; ] ?"] "
Deep neural networks ["Q-017 What can deep neural networks be decomposed into [ & # 8230 ; ] ?"] "
Deep neural networks ["Q-018 Who can be decomposed into [ & # 8230 ; ] ?"] "
Deep neural networks ["Q-019 ]
novel communication strategies ["Q-01 What you Exascale Deep Learning for Scientific Inverse Problems you N in synchronous distributed Deep Learning consisting of decentralized gradient reduction orchestration and computational graph - aware grouping of gradient tensors ?"] "
optimal overlap ["Q-02 What these new techniques produce between computation and communication and result in near - linear scaling ( 0 ?"] "
Exascale Deep Learning for Scientific Inverse Problems ["Q-03 Who produce an optimal overlap between computation and communication and result in near - linear scaling ( 0 ?"] "
NVIDIA ["Q-04 What you d N & # 8230 ; ] ?"] "
NVIDIA V100 GPUs ["Q-05 Who demonstrate [ & # 8230 ; ] ?"] "
synchronous ["Q-01 In what Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies of decentralized gradient reduction orchestration and computational graph - aware grouping of gradient tensors ?"] "
synchronous distributed Deep Learning ["Q-02 Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies in of what Deep learning consisting consisting and computational graph - aware grouping of gradient tensors ?"] "
synchronous distributed Deep Learning ["Q-03 Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies in of what Deep learning consisting of decentralized consisting gradient reduction orchestration and computational graph - aware grouping ?"] "
novel communication strategies ["Q-04 What you Exascale Deep Learning for Scientific Inverse Problems you N in synchronous distributed Deep Learning consisting of decentralized gradient reduction orchestration and computational graph - aware grouping of gradient tensors ?"] "
synchronous distributed Deep Learning ["Q-05 Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies in what Deep learning consisting of decentralized consisting and computational graph - aware grouping of gradient tensors ?"] "
NVIDIA ["Q-06 ]
computation ["Q-07 Between what these new techniques produce an optimal overlap and communication and result in near - linear scaling ( 0 ?"] "
near-linear scaling ["Q-08 In what these new techniques produce an optimal overlap between computation and communication and result ( 0 ?"] "
optimal overlap ["Q-09 What these new techniques produce between computation and communication and result in near - linear scaling ( 0 ?"] "
Exascale Deep Learning for Scientific Inverse Problems ["Q-010 Who produce an optimal overlap between computation and communication and result in near - linear scaling ( 0 ?"] "
NVIDIA ["Q-011 ]
27600 NVIDIA V100 GPUs ["Q-012 93 ) to what did of distributed training distributed on the Summit Supercomputer ?"] "
the Summit Supercomputer ["Q-013 93 ) on what up to 27600 Nvidia V100 Gpus ?"] "
near-linear scaling ["Q-014 93 ) what did of distributed distributed up to 27600 Nvidia V100 Gpus on the Summit Supercomputer ?"] "
NVIDIA ["Q-015 ]
NVIDIA ["Q-016 What you d N & # 8230 ; ] ?"] "
NVIDIA V100 GPUs ["Q-017 Who demonstrate [ & # 8230 ; ] ?"] "
NVIDIA ["Q-018 ]
novel communication strategies ["Q-01 What you Exascale Deep Learning for Scientific Inverse Problems you N in synchronous distributed Deep Learning consisting of decentralized gradient reduction orchestration and computational graph - aware grouping of gradient tensors ?"] "
optimal overlap ["Q-02 What these new techniques produce between computation and communication and result in near - linear scaling ( 0 ?"] "
Exascale Deep Learning for Scientific Inverse Problems ["Q-03 Who produce an optimal overlap between computation and communication and result in near - linear scaling ( 0 ?"] "
NVIDIA ["Q-04 What you d N & # 8230 ; ] ?"] "
NVIDIA V100 GPUs ["Q-05 Who demonstrate [ & # 8230 ; ] ?"] "
synchronous ["Q-01 In what Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies of decentralized gradient reduction orchestration and computational graph - aware grouping of gradient tensors ?"] "
synchronous distributed Deep Learning ["Q-02 Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies in of what Deep learning consisting consisting and computational graph - aware grouping of gradient tensors ?"] "
synchronous distributed Deep Learning ["Q-03 Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies in of what Deep learning consisting of decentralized consisting gradient reduction orchestration and computational graph - aware grouping ?"] "
novel communication strategies ["Q-04 What you Exascale Deep Learning for Scientific Inverse Problems you N in synchronous distributed Deep Learning consisting of decentralized gradient reduction orchestration and computational graph - aware grouping of gradient tensors ?"] "
synchronous distributed Deep Learning ["Q-05 Exascale Deep Learning for Scientific Inverse Problems you introduce novel communication strategies in what Deep learning consisting of decentralized consisting and computational graph - aware grouping of gradient tensors ?"] "
NVIDIA ["Q-06 ]
computation ["Q-07 Between what these new techniques produce an optimal overlap and communication and result in near - linear scaling ( 0 ?"] "
near-linear scaling ["Q-08 In what these new techniques produce an optimal overlap between computation and communication and result ( 0 ?"] "
optimal overlap ["Q-09 What these new techniques produce between computation and communication and result in near - linear scaling ( 0 ?"] "
Exascale Deep Learning for Scientific Inverse Problems ["Q-010 Who produce an optimal overlap between computation and communication and result in near - linear scaling ( 0 ?"] "
NVIDIA ["Q-011 ]
27600 NVIDIA V100 GPUs ["Q-012 93 ) to what did of distributed training distributed on the Summit Supercomputer ?"] "
the Summit Supercomputer ["Q-013 93 ) on what up to 27600 Nvidia V100 Gpus ?"] "
near-linear scaling ["Q-014 93 ) what did of distributed distributed up to 27600 Nvidia V100 Gpus on the Summit Supercomputer ?"] "
NVIDIA ["Q-015 ]
NVIDIA ["Q-016 What you d N & # 8230 ; ] ?"] "
NVIDIA V100 GPUs ["Q-017 Who demonstrate [ & # 8230 ; ] ?"] "
NVIDIA ["Q-018 ]
Multi-tenant GPU clusters ["Q-01 Who are common nowadays due to the huge success of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning and training jobs ["Q-02 Who are usually conducted with multiple distributed Gpus ?"] "
multiple distributed GPUs ["Q-03 What are these Gpu clusters managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-04 Who are managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-05 Who including short Jct high resource utilization and quick response to small jobs ?"] "
small jobs ["Q-06 What in this paper you show that elasticity which is & # 8230 ; ] ?"] "
GPU clusters ["Q-07 Who show that elasticity which is the ability [ & # 8230 ; ] ?"] "
huge success ["Q-01 Elastic deep learning in to what are multi - tenant Gpu cluster Multi - tenant Gpu clusters common nowadays due of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning ["Q-02 Elastic deep learning in of what are multi - tenant Gpu cluster Multi - tenant Gpu clusters common nowadays due to the huge success and training jobs are usually conducted with multiple distributed Gpus ?"] "
multiple distributed GPUs ["Q-03 Elastic deep learning in multi - tenant Gpu cluster Multi - tenant Gpu clusters are common nowadays due to the huge success of with what are deep learning and training jobs usually conducted ?"] "
multi-tenant GPU cluster Multi-tenant GPU clusters are common nowadays ["Q-04 Elastic deep learning in what are multi - tenant Gpu cluster Multi - tenant Gpu clusters due to the huge success of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning ["Q-05 Elastic deep learning in multi - tenant Gpu cluster Multi - tenant Gpu clusters are common nowadays due to the huge success of what are deep learning and training jobs with multiple distributed Gpus ?"] "
GPUs ["Q-06 Elastic deep learning in multi - tenant Gpu cluster Multi - tenant Gpu clusters are common nowadays due to the huge success of what are deep learning and training jobs usually conducted with multiple distributed ?"] "
Multi-tenant GPU clusters ["Q-07 Who are common nowadays due to the huge success of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning and training jobs ["Q-08 Who are usually conducted with multiple distributed Gpus ?"] "
elasticity ["Q-09 ]
small jobs ["Q-010 These Gpu clusters are managed with to what various goals including including short Jct high resource utilization and quick response ?"] "
various goals ["Q-011 With what are these Gpu clusters managed short Jct high resource utilization and quick response to small jobs ?"] "
multiple distributed GPUs ["Q-012 What are these Gpu clusters managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
various goals including short JCT ["Q-013 These Gpu clusters are managed with what various goals including including high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-014 Who are managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-015 Who including short Jct high resource utilization and quick response to small jobs ?"] "
elasticity ["Q-016 ]
elasticity ["Q-017 That what in this paper you show which is the ability [ & # 8230 ; ] ?"] "
small jobs ["Q-018 What in this paper you show that elasticity which is & # 8230 ; ] ?"] "
GPU clusters ["Q-019 Who show that elasticity which is the ability [ & # 8230 ; ] ?"] "
elasticity ["Q-020 ]
Multi-tenant GPU clusters ["Q-01 Who are common nowadays due to the huge success of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning and training jobs ["Q-02 Who are usually conducted with multiple distributed Gpus ?"] "
multiple distributed GPUs ["Q-03 What are these Gpu clusters managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-04 Who are managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-05 Who including short Jct high resource utilization and quick response to small jobs ?"] "
small jobs ["Q-06 What in this paper you show that elasticity which is & # 8230 ; ] ?"] "
GPU clusters ["Q-07 Who show that elasticity which is the ability [ & # 8230 ; ] ?"] "
huge success ["Q-01 Elastic deep learning in to what are multi - tenant Gpu cluster Multi - tenant Gpu clusters common nowadays due of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning ["Q-02 Elastic deep learning in of what are multi - tenant Gpu cluster Multi - tenant Gpu clusters common nowadays due to the huge success and training jobs are usually conducted with multiple distributed Gpus ?"] "
multiple distributed GPUs ["Q-03 Elastic deep learning in multi - tenant Gpu cluster Multi - tenant Gpu clusters are common nowadays due to the huge success of with what are deep learning and training jobs usually conducted ?"] "
multi-tenant GPU cluster Multi-tenant GPU clusters are common nowadays ["Q-04 Elastic deep learning in what are multi - tenant Gpu cluster Multi - tenant Gpu clusters due to the huge success of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning ["Q-05 Elastic deep learning in multi - tenant Gpu cluster Multi - tenant Gpu clusters are common nowadays due to the huge success of what are deep learning and training jobs with multiple distributed Gpus ?"] "
GPUs ["Q-06 Elastic deep learning in multi - tenant Gpu cluster Multi - tenant Gpu clusters are common nowadays due to the huge success of what are deep learning and training jobs usually conducted with multiple distributed ?"] "
Multi-tenant GPU clusters ["Q-07 Who are common nowadays due to the huge success of deep learning and training jobs are usually conducted with multiple distributed Gpus ?"] "
deep learning and training jobs ["Q-08 Who are usually conducted with multiple distributed Gpus ?"] "
elasticity ["Q-09 ]
small jobs ["Q-010 These Gpu clusters are managed with to what various goals including including short Jct high resource utilization and quick response ?"] "
various goals ["Q-011 With what are these Gpu clusters managed short Jct high resource utilization and quick response to small jobs ?"] "
multiple distributed GPUs ["Q-012 What are these Gpu clusters managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
various goals including short JCT ["Q-013 These Gpu clusters are managed with what various goals including including high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-014 Who are managed with various goals including short Jct high resource utilization and quick response to small jobs ?"] "
GPU clusters ["Q-015 Who including short Jct high resource utilization and quick response to small jobs ?"] "
elasticity ["Q-016 ]
elasticity ["Q-017 That what in this paper you show which is the ability [ & # 8230 ; ] ?"] "
small jobs ["Q-018 What in this paper you show that elasticity which is & # 8230 ; ] ?"] "
GPU clusters ["Q-019 Who show that elasticity which is the ability [ & # 8230 ; ] ?"] "
elasticity ["Q-020 ]
Deep Learning Engineer - Deeplite Inc. - Quebec City QC The platform ["Q-01 Who is in development phase where you are implementing academic works and your patent portfolio into your technology ?"] "
Deep Learning Engineer - Deeplite Inc. - Quebec City QC ["Q-02 Who are implementing academic works and your patent portfolio into your technology ?"] "
Quebec City QC ["Q-03 Who need to see ?"] "
Quebec City QC jobs ["Q-01 ]
Deep Learning Engineer - Deeplite ["Q-02 - in what is Quebec City Qc the platform where you are implementing academic works and your patent portfolio into your technology ?"] "
our technology ["Q-03 - quebec City Qc the platform is in development phase where into what are you implementing academic works and your patent portfolio ?"] "
academic works ["Q-04 - quebec City Qc the platform is in development phase where what are you implementing and your patent portfolio into your technology ?"] "
Deep Learning Engineer - Deeplite Inc. - Quebec City QC The platform ["Q-05 Who is in development phase where you are implementing academic works and your patent portfolio into your technology ?"] "
Deep Learning Engineer - Deeplite Inc. - Quebec City QC ["Q-06 Who are implementing academic works and your patent portfolio into your technology ?"] "
Quebec City QC jobs ["Q-07 ]
Quebec City QC ["Q-08 Who need to see ?"] "
Quebec City QC jobs ["Q-09 ]
Quebec City QC jobs ["Q-010 ]
Quebec City QC jobs ["Q-011 ]
Deep Learning Engineer - Deeplite Inc. - Quebec City QC The platform ["Q-01 Who is in development phase where you are implementing academic works and your patent portfolio into your technology ?"] "
Deep Learning Engineer - Deeplite Inc. - Quebec City QC ["Q-02 Who are implementing academic works and your patent portfolio into your technology ?"] "
Quebec City QC ["Q-03 Who need to see ?"] "
Quebec City QC jobs ["Q-01 ]
Deep Learning Engineer - Deeplite ["Q-02 - in what is Quebec City Qc the platform where you are implementing academic works and your patent portfolio into your technology ?"] "
our technology ["Q-03 - quebec City Qc the platform is in development phase where into what are you implementing academic works and your patent portfolio ?"] "
academic works ["Q-04 - quebec City Qc the platform is in development phase where what are you implementing and your patent portfolio into your technology ?"] "
Deep Learning Engineer - Deeplite Inc. - Quebec City QC The platform ["Q-05 Who is in development phase where you are implementing academic works and your patent portfolio into your technology ?"] "
Deep Learning Engineer - Deeplite Inc. - Quebec City QC ["Q-06 Who are implementing academic works and your patent portfolio into your technology ?"] "
Quebec City QC jobs ["Q-07 ]
Quebec City QC ["Q-08 Who need to see ?"] "
Quebec City QC jobs ["Q-09 ]
Quebec City QC jobs ["Q-010 ]
Quebec City QC jobs ["Q-011 ]
Intel ["Q-01 Who need to knowintel today unveiled its new w-2200 xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel ["Q-02 What time unveiled its new w-2200 xeon chip series ?"] "
W-2200 Xeon chip series ["Q-03 What that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
Intel ["Q-04 Who offer 2x faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
4K ["Q-05 Who editing ?"] "
Intel touts of the new W-2200 ["Q-06 How much that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
97% faster 4K video editing ["Q-07 What could the W-2200 Xeon chips be included in future refreshed models of the imac Pro ?"] "
The W-2200 Xeon chips ["Q-08 Who could be included in future refreshed models of the imac Pro ?"] "
the ultimate creator platform ["Q-09 What did Today Intel took off its brand new W-2200 Xeon chip series ?"] "
the ultimate creator platform ["Q-10 What did Today Intel took the wraps o you new w-2200 xeon chip series ?"] "
Intel ["Q-11 What time took the wraps off its brand new W-2200 Xeon chip series ?"] "
Intel ["Q-12 Who off its brand new W-2200 Xeon chip series ?"] "
the new chips ["Q-13 What is the new chip series compatible with the imac Pro which could add as a refresh looms for Apples most powerful desktop ?"] "
The new chip series ["Q-14 Who is compatible with the imac Pro which could add the new chips as a refresh looms for Apples most powerful desktop ?"] "
18 AVC 512 ["Q-15 How much enabled cores along with Turbo Boost Max 3 ?"] "
18 AVC 512 ["Q-16 What the w-2200 Xeon chips f N enabled cores along with Turbo Boost Max 3 ?"] "
cores ["Q-17 What 18 avc 512 enabled along with Turbo Boost Max 3 ?"] "
18 AVC 512 enabled cores along with Turbo Boost Max 3.0 48 PCIe lanes and AI acceleration ["Q-18 How much the w-2200 Xeon chips f N Avc 512 enabled cores along with Turbo Boost Max 3 ?"] "
Intel ["Q-19 Who is 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-20 Who rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-21 Who connects to the imac Pro Apple currently uses Intel Xeon - w chips ?"] "
iMac Pro Apple ["Q-22 Who currently uses Intel Xeon - w chips ?"] "
What you need to knowIntel today unveiled its new W-2200 Xeon chip series.That new chips offer 2x faster 3D architecture rendering and 97% faster 4K video editing ["Q-01 Intel unveils new powerful w-2200 Xeon chip series what what time i need to k N unveiled its new w-2200 xeon chip series ?"] "
What you ["Q-02 Intel unveils new powerful w-2200 Xeon chip series what what i need to knowintel today unveiled new W-2200 Xeon chip series ?"] "
Intel ["Q-03 Who need to knowintel today unveiled its new w-2200 xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel ["Q-04 What time unveiled its new w-2200 xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-05 ]
chip series ["Q-06 What that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
Intel ["Q-07 Who offer 2x faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
4K ["Q-08 Who editing ?"] "
4K video editing ["Q-09 How much that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-010 ]
future refreshed models ["Q-011 In what could the W-2200 Xeon chips be included of the imac Pro ?"] "
iMac Pro ["Q-012 Of what could the W-2200 Xeon chips be included in future refreshed models ?"] "
97% faster 4K video editing ["Q-013 What could the W-2200 Xeon chips be included in future refreshed models of the imac Pro ?"] "
W-2200 Xeon chips ["Q-014 Who could be included in future refreshed models of the imac Pro ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-015 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-016 ]
the ultimate creator platform ["Q-017 What did Today Intel took off its brand new W-2200 Xeon chip series ?"] "
the ultimate creator platform ["Q-018 What did Today Intel took the wraps o you new w-2200 xeon chip series ?"] "
Intel ["Q-019 What time took the wraps off its brand new W-2200 Xeon chip series ?"] "
Intel ["Q-020 Who off its brand new W-2200 Xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-021 ]
iMac Pro ["Q-022 With what is the new chip series compatible which could add the new chips as a refresh looms for Apples most powerful desktop ?"] "
iMac Pro which could add the new chips as a refresh looms ["Q-023 As what is the new chip series compatible with the imac Pro which could add the new chips looms for Apples most powerful desktop ?"] "
Apples ["Q-024 For what is the new chip series compatible with the imac Pro which could add the new chips as a refresh looms most powerful desktop ?"] "
the new chips ["Q-025 What is the new chip series compatible with the imac Pro which could add as a refresh looms for Apples most powerful desktop ?"] "
The new chip series ["Q-026 Who is compatible with the imac Pro which could add the new chips as a refresh looms for Apples most powerful desktop ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-027 ]
18 AVC 512 ["Q-028 How much enabled cores along with Turbo Boost Max 3 ?"] "
Turbo Boost Max 3.0 48 PCIe lanes ["Q-029 Along what 18 avc 512 enabled cores ?"] "
18 AVC 512 ["Q-030 What the w-2200 Xeon chips f N enabled cores along with Turbo Boost Max 3 ?"] "
cores ["Q-031 What 18 avc 512 enabled along with Turbo Boost Max 3 ?"] "
18 AVC 512 enabled cores along with Turbo Boost Max 3.0 48 PCIe lanes and AI acceleration ["Q-032 How much the w-2200 Xeon chips f N Avc 512 enabled cores along with Turbo Boost Max 3 ?"] "
thi ["Q-033 ]
thi ["Q-034 ]
97% ["Q-035 Among the benefits Intel touts of what is the new w-2200 series faster 4k video editing and 2 ?"] "
Intel ["Q-036 Who is 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-037 Who rendering 97 % faster 4k video editing and 2 ?"] "
thi... ["Q-038 ]
thi ["Q-039 ]
iMac Pro Apple ["Q-040 To what as it connects currently uses Intel Xeon - w chips ?"] "
Intel Xeon-W chips ["Q-041 As it connects to what the imac Pro Apple currently u N ?"] "
Intel ["Q-042 Who connects to the imac Pro Apple currently uses Intel Xeon - w chips ?"] "
iMac Pro Apple ["Q-043 Who currently uses Intel Xeon - w chips ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-044 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-045 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-046 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-047 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-048 ]
Intel ["Q-01 Who need to knowintel today unveiled its new w-2200 xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel ["Q-02 What time unveiled its new w-2200 xeon chip series ?"] "
W-2200 Xeon chip series ["Q-03 What that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
Intel ["Q-04 Who offer 2x faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
4K ["Q-05 Who editing ?"] "
Intel touts of the new W-2200 ["Q-06 How much that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
97% faster 4K video editing ["Q-07 What could the W-2200 Xeon chips be included in future refreshed models of the imac Pro ?"] "
The W-2200 Xeon chips ["Q-08 Who could be included in future refreshed models of the imac Pro ?"] "
the ultimate creator platform ["Q-09 What did Today Intel took off its brand new W-2200 Xeon chip series ?"] "
the ultimate creator platform ["Q-10 What did Today Intel took the wraps o you new w-2200 xeon chip series ?"] "
Intel ["Q-11 What time took the wraps off its brand new W-2200 Xeon chip series ?"] "
Intel ["Q-12 Who off its brand new W-2200 Xeon chip series ?"] "
the new chips ["Q-13 What is the new chip series compatible with the imac Pro which could add as a refresh looms for Apples most powerful desktop ?"] "
The new chip series ["Q-14 Who is compatible with the imac Pro which could add the new chips as a refresh looms for Apples most powerful desktop ?"] "
18 AVC 512 ["Q-15 How much enabled cores along with Turbo Boost Max 3 ?"] "
18 AVC 512 ["Q-16 What the w-2200 Xeon chips f N enabled cores along with Turbo Boost Max 3 ?"] "
cores ["Q-17 What 18 avc 512 enabled along with Turbo Boost Max 3 ?"] "
18 AVC 512 enabled cores along with Turbo Boost Max 3.0 48 PCIe lanes and AI acceleration ["Q-18 How much the w-2200 Xeon chips f N Avc 512 enabled cores along with Turbo Boost Max 3 ?"] "
Intel ["Q-19 Who is 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-20 Who rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-21 Who connects to the imac Pro Apple currently uses Intel Xeon - w chips ?"] "
iMac Pro Apple ["Q-22 Who currently uses Intel Xeon - w chips ?"] "
What you need to knowIntel today unveiled its new W-2200 Xeon chip series.That new chips offer 2x faster 3D architecture rendering and 97% faster 4K video editing ["Q-01 Intel unveils new powerful w-2200 Xeon chip series what what time i need to k N unveiled its new w-2200 xeon chip series ?"] "
What you ["Q-02 Intel unveils new powerful w-2200 Xeon chip series what what i need to knowintel today unveiled new W-2200 Xeon chip series ?"] "
Intel ["Q-03 Who need to knowintel today unveiled its new w-2200 xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel ["Q-04 What time unveiled its new w-2200 xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-05 ]
chip series ["Q-06 What that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
Intel ["Q-07 Who offer 2x faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
4K ["Q-08 Who editing ?"] "
4K video editing ["Q-09 How much that new chips o N faster 3d architecture rendering and 97 % faster 4k video editing ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-010 ]
future refreshed models ["Q-011 In what could the W-2200 Xeon chips be included of the imac Pro ?"] "
iMac Pro ["Q-012 Of what could the W-2200 Xeon chips be included in future refreshed models ?"] "
97% faster 4K video editing ["Q-013 What could the W-2200 Xeon chips be included in future refreshed models of the imac Pro ?"] "
W-2200 Xeon chips ["Q-014 Who could be included in future refreshed models of the imac Pro ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-015 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-016 ]
the ultimate creator platform ["Q-017 What did Today Intel took off its brand new W-2200 Xeon chip series ?"] "
the ultimate creator platform ["Q-018 What did Today Intel took the wraps o you new w-2200 xeon chip series ?"] "
Intel ["Q-019 What time took the wraps off its brand new W-2200 Xeon chip series ?"] "
Intel ["Q-020 Who off its brand new W-2200 Xeon chip series ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-021 ]
iMac Pro ["Q-022 With what is the new chip series compatible which could add the new chips as a refresh looms for Apples most powerful desktop ?"] "
iMac Pro which could add the new chips as a refresh looms ["Q-023 As what is the new chip series compatible with the imac Pro which could add the new chips looms for Apples most powerful desktop ?"] "
Apples ["Q-024 For what is the new chip series compatible with the imac Pro which could add the new chips as a refresh looms most powerful desktop ?"] "
the new chips ["Q-025 What is the new chip series compatible with the imac Pro which could add as a refresh looms for Apples most powerful desktop ?"] "
The new chip series ["Q-026 Who is compatible with the imac Pro which could add the new chips as a refresh looms for Apples most powerful desktop ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-027 ]
18 AVC 512 ["Q-028 How much enabled cores along with Turbo Boost Max 3 ?"] "
Turbo Boost Max 3.0 48 PCIe lanes ["Q-029 Along what 18 avc 512 enabled cores ?"] "
18 AVC 512 ["Q-030 What the w-2200 Xeon chips f N enabled cores along with Turbo Boost Max 3 ?"] "
cores ["Q-031 What 18 avc 512 enabled along with Turbo Boost Max 3 ?"] "
18 AVC 512 enabled cores along with Turbo Boost Max 3.0 48 PCIe lanes and AI acceleration ["Q-032 How much the w-2200 Xeon chips f N Avc 512 enabled cores along with Turbo Boost Max 3 ?"] "
thi ["Q-033 ]
thi ["Q-034 ]
97% ["Q-035 Among the benefits Intel touts of what is the new w-2200 series faster 4k video editing and 2 ?"] "
Intel ["Q-036 Who is 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-037 Who rendering 97 % faster 4k video editing and 2 ?"] "
thi... ["Q-038 ]
thi ["Q-039 ]
iMac Pro Apple ["Q-040 To what as it connects currently uses Intel Xeon - w chips ?"] "
Intel Xeon-W chips ["Q-041 As it connects to what the imac Pro Apple currently u N ?"] "
Intel ["Q-042 Who connects to the imac Pro Apple currently uses Intel Xeon - w chips ?"] "
iMac Pro Apple ["Q-043 Who currently uses Intel Xeon - w chips ?"] "
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-044 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-045 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-046 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-047 ]
Intel unveils new powerful W-2200 Xeon chip series What you need to knowIntel today unveiled its new W-2200 Xeon chip series ["Q-048 ]
fondo que tiene ["Q-01 Who por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-02 Who y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-03 Who preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
de alta ["Q-04 Who finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansi& , Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansión internacional. Además tendrán
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. , fondo que tiene compromisos de inversión por cerca de 20 millones de euros " ["Q-08 How much n N puente ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros ["Q-09 How much n N puente ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-10 Who n N a ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. , Las startups participadas " ["Q-12 Who por Conexo Ventures contar & aacute ; n con un soporte legal de recursos humanos y ventas para su expansi & oacute ; n internacional ?"] "
Las startups participadas por Conexo Ventures ["Q-13 Who y ventas para su expansi & oacute ; n internacional ?"] "
Joaquim Hierro Lopes managing ["Q-14 Who tiempo queriendo expandir nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo ["Q-15 Who en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ["Q-16 Who ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups ["Q-17 Who en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Una ["Q-18 Who y acompa & ntilde ; amiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos de a & ntilde ; o ?"] "
y cinco ["Q-19 Who en menos de a & ntilde ; o ?"] "
GED ["Q-01 Ged Capital invierte Bnext Buguroo Y Kushki a trav\u00e9s de Conexo Ventures La Gestora ib & eacute ; de what Ged Capital lanza su primer fondo ?"] "
fondo de ["Q-02 Ged Capital you N Bnext Buguroo Y Kushki a trav\u00e9s de Conexo Ventures La gestora you N & eacute ; what N de venture capital Conexo Ventures ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , Esta nueva actividad de GED " ["Q-04 De what nueva Esta actividad en el segmento del & nbsp ; venture capital & nbsp ; se suma a las estrategias ya existentes en la gestora de inversi & oacute ; n en & nbsp ; private equity & nbsp ; e infraestructuras ?"] "
ya existentes ["Q-05 Esta nueva actividad de Ged Capital en el segmento del & nbsp ; venture capital & nbsp ; what existentes en la gestora de inversi & oacute ; n en & nbsp ; private equity & nbsp ; e infraestructuras ?"] "
GED Capital invierte BNext Buguroo y Kushki ["Q-06 ]
Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos ["Q-07 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos financieros aseguradores y relacionados con viajes & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; n del fraude bancario Mediante & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; rica Latina con inteligencia artificial ) ?"] "
Buguroo (prevención ["Q-08 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos what financieros aseguradores y N De Espa & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; n del fraude bancario Mediante & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; rica Latina con inteligencia artificial ) ?"] "
Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos hecho ya han ["Q-09 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos financieros aseguradores y relacionados con viajes de Espa & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; what N & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; rica Latina con inteligencia artificial ) ?"] "
Una ["Q-010 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos financieros aseguradores y relacionados c N viajes de Espa & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; n del fraude bancario Mediante & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; what N ) ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas " ["Q-012 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; de what n por cerca de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y"
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-013 & nbsp ; what N de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospe
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-014 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; what n p N de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-015 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; what N disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y ho
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma ["Q-016 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio what escalables y N preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-017 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y what defendibles p N sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "passag
Buguroo (prevención ["Q-018 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta what demanda como ciberseguridad pagos y marketplaces f N & oacute ; n y viajes y hospedaje ?"] "
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-019 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal what y y N N administra
fondo que tiene ["Q-020 Who por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-021 Who y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-022 Who preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
de alta demanda como ciberseguridad pagos y marketplaces ["Q-023 Who finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de re , Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas " ["Q-025 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; de how much n por cerca millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oac
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que " ["Q-027 Su foco se centra en la inversi & oacute ; n en Series A En aquellas & nbsp ; startups & nbsp ; que tengan en what y generen ingresos tras haber demostrado su aceptaci & oacute ; n & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que ["Q-028 Su foco se centra en la inversi & oacute ; what n e J & nbsp ; startups & nbsp ; que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptaci & oacute ; n en el mercado con m & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"]
en startups ibéricas ["Q-029 Su foco se centra en la inversi & oacute ; n en Series A En aquellas & nbsp ; startups & nbsp ; what J relevantes tras haber demostrado su aceptaci & oacute ; n en el mercado con m & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"] "
ya han ["Q-030 Su foco se centra en la inversi & oacute ; n en Series A En aquellas & nbsp ; startups & nbsp ; que tengan productos desarrollados y generen ingresos what r r N N N & oacute ; n en el mercado con m & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"] "
Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansión internacional. Además tendrán , Los partners de Conexo Ventures tendrán una participación activa en la estrategia de las compañías y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la vía rápida. Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalización servirá
y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la vía rápida. Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalización servirá entre otras cosas para obtener mayores múltiplos a la inversión mediante salidas en mercados más avanzados. Una prue , Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí " ["Q-034 Conexo Ventures buscar & aacute ; apoyar a e N de emprendedores formados que sean what e e N N N & iacute ; lograr las siguientes rondas de financiaci & oacute ; n ( series B Y C ) y finalmente los & nbsp ; exit ?"] "
Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación ["Q-035 Conexo Ventures buscar & aacute ; apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos Y ah & iacute ; lograr what l l N N N rondas de financiaci & oacute ; n ( series B Y C ) y finalmente los & nbsp ; exit ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , . " ["Q-037 ]
fondo que tiene compromisos de inversión por cerca de 20 millones de euros ["Q-038 How much n N puente ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros ["Q-039 How much n N puente ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-040 Este puente a & eacute ; Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-041 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; compa & ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-042 Este puente a & eacute ; Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-043 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; compa & ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-044 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; compa & n N ; & iacute ; & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-045 Este p p N N N & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-046 Este puente a & e N ; N & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-047 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n n N N N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-048 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para l l N N N & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-049 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & n n N N N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-050 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & whose ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-051 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & whose ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-052 Who n N a ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco ["Q-053 Who n N a ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-054 Este puente a & eacute ; n how much Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-055 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; n how much compa & ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-056 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & how much n n N N N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-057 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & how much n n N N N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Llevábamos ["Q-058 ]
Las startups participadas ["Q-059 Las & nbsp ; startups & nbsp ; what participadas p N & aacute ; n con un soporte legal de recursos humanos y ventas para su expansi & oacute ; n internacional ?"] "
Las startups participadas ["Q-060 Las & nbsp ; startups & nbsp ; participadas por Conexo Ventures contar & aacute ; n con un soporte legal de recursos what humanos y N para su expansi & oacute ; n internacional ?"] "
Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansión ["Q-061 Las & nbsp ; startups & nbsp ; participadas por Conexo Ventures contar & aacute ; n con un soporte legal de recursos humanos y ventas p N & oacute ; n internacional ?"] "
Las startups participadas ["Q-062 Who por Conexo Ventures contar & aacute ; n con un soporte legal de recursos humanos y ventas para su expansi & oacute ; n internacional ?"] "
Las startups participadas por Conexo Ventures ["Q-063 Who y ventas para su expansi & oacute ; n internacional ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , privado " ["Q-065 Adem & aacute ; s tendr & aacute ; n el apoyo del equipo gestor para La Sindicaci & oacute ; n de futuras rondas de financiaci & oacute ; de what fondos ?"] "
Además tendrán el apoyo del equipo gestor para la sindicación ["Q-066 Adem & aacute ; s tendr & aacute ; what n e J & oacute ; n de futuras rondas de financiaci & oacute ; n con fondos de capital privado norteamericanos ?"] "
Además ["Q-067 Adem & aacute ; s tendr & aacute ; n el apoyo del equipo gestor para La Sindicaci & oacute ; n de futuras rondas de financiaci & oacute ; what n c N de capital privado norteamericanos ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , compuesto por tres partners con " ["Q-069 El C s & eacute ; nior ejecutivo de Conexo Ventures & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-070 El C s & eacute ; nior ejecutivo de Conexo Ventures & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-071 El e C C s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; en what en el mundo del emprendimiento y la inversi & oacute ; n de la Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-072 El e C C s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; de what en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-073 El e e N N N s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-074 El e C C s & e N ; nior ejecutivo de Conexo Ventures e N & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-075 El e C C s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; N & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-076 El whose s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-077 El e C S & eacute ; nior ejecutivo de Conexo Ventures whose & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-078 El e how much C s & eacute ; nior ejecutivo de Conexo Ventures & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-079 El how much e e N N N s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-080 El e C C s & e N ; nior ejecutivo de how much Conexo Ventures e N & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables
Llevábamos ["Q-083 En este sentido Joaquim Hierro Lopes & nbsp ; managing partner & nbsp ; de Ged Capital ha expresado Llev & aacute ; de what bamos tiempo queriendo expandir nuestra actividad al venture capital Y cuando conocimos al equipo ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí , Los partners de Conexo Ventures tendrán una participación activa en la estrategia de las compañías y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED " ["Q-085 En este sentido Joaquim Hierro Lopes & nbsp ; managing partner & nbsp ; de Ged Capital ha expresado Llev & aacute ; what J nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Los partners de Conexo Ventures tendrán una participación activa en la estrategia de las compañías y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED ["Q-086 En e N sentido Joaquim Hierro Lopes & nbsp ; managing partner & nbsp ; de Ged Capital ha e N Llev & aacute ; bamos tiempo queriendo e N nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar what con nosotros e N de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing ["Q-087 Who tiempo queriendo expandir nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo ["Q-088 Who en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Llevábamos ["Q-089 ]
en startups ibéricas ["Q-090 & nbsp ; Por su parte Isaac de la Pe & ntilde ; a & nbsp ; partner & nbsp ; de Conexo Ventures ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; de what fundamental para que las startups en las que invirtamos accedan al Mercado & iacute ; a r & aacute ; pida ?"] "
rápida ["Q-091 & nbsp ; what N de la Pe & ntilde ; a & nbsp ; partner & nbsp ; de Conexo Ventures ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track  , al mercado de Estados Unidos por la vía rápida " ["Q-093 & nbsp ; Por su parte Isaac de la Pe & ntilde ; a & nbsp ; partner & nbsp ; de Conexo Ventures ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; what fundamental para que las startups e F invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ["Q-094 Who ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups ["Q-095 Who en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , entre otras cosas para obtener mayores " ["Q-097 Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalizaci & o N ; n servir & aacute ; what o o N N M & uacute ; ltiplos a la inversi & oacute ; n mediante salidas en mercados m & aacute ; s avanzados ?"] "
y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la vía rápida. Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalización servirá entre otras cosas para obtener mayores múltiplos a la inversión mediante salidas en mercados más avanzados. Una prue , Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos de año " ["Q-099 Una prueba de nuestro excelente criterio de selecci & oacute ; n y acompa & ntilde ; amiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos & ntilde ; o ?"] "
ya han ["Q-0100 Una prueba de nuestro excelente criterio de selecci & oacute ; n y acompa & ntilde ; amiento de empresas es que dos de las what N en menos de a & ntilde ; o ?"] "
Una ["Q-0101 Who y acompa & ntilde ; amiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos de a & ntilde ; o ?"] "
y cinco ["Q-0102 Who en menos de a & ntilde ; o ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables
fondo que tiene ["Q-01 Who por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-02 Who y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-03 Who preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
de alta ["Q-04 Who finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansi& , Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansión internacional. Además tendrán
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. , fondo que tiene compromisos de inversión por cerca de 20 millones de euros " ["Q-08 How much n N puente ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros ["Q-09 How much n N puente ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-10 Who n N a ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. , Las startups participadas " ["Q-12 Who por Conexo Ventures contar & aacute ; n con un soporte legal de recursos humanos y ventas para su expansi & oacute ; n internacional ?"] "
Las startups participadas por Conexo Ventures ["Q-13 Who y ventas para su expansi & oacute ; n internacional ?"] "
Joaquim Hierro Lopes managing ["Q-14 Who tiempo queriendo expandir nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo ["Q-15 Who en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ["Q-16 Who ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups ["Q-17 Who en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Una ["Q-18 Who y acompa & ntilde ; amiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos de a & ntilde ; o ?"] "
y cinco ["Q-19 Who en menos de a & ntilde ; o ?"] "
GED ["Q-01 Ged Capital invierte Bnext Buguroo Y Kushki a trav\u00e9s de Conexo Ventures La Gestora ib & eacute ; de what Ged Capital lanza su primer fondo ?"] "
fondo de ["Q-02 Ged Capital you N Bnext Buguroo Y Kushki a trav\u00e9s de Conexo Ventures La gestora you N & eacute ; what N de venture capital Conexo Ventures ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , Esta nueva actividad de GED " ["Q-04 De what nueva Esta actividad en el segmento del & nbsp ; venture capital & nbsp ; se suma a las estrategias ya existentes en la gestora de inversi & oacute ; n en & nbsp ; private equity & nbsp ; e infraestructuras ?"] "
ya existentes ["Q-05 Esta nueva actividad de Ged Capital en el segmento del & nbsp ; venture capital & nbsp ; what existentes en la gestora de inversi & oacute ; n en & nbsp ; private equity & nbsp ; e infraestructuras ?"] "
GED Capital invierte BNext Buguroo y Kushki ["Q-06 ]
Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos ["Q-07 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos financieros aseguradores y relacionados con viajes & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; n del fraude bancario Mediante & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; rica Latina con inteligencia artificial ) ?"] "
Buguroo (prevención ["Q-08 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos what financieros aseguradores y N De Espa & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; n del fraude bancario Mediante & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; rica Latina con inteligencia artificial ) ?"] "
Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos hecho ya han ["Q-09 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos financieros aseguradores y relacionados con viajes de Espa & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; what N & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; rica Latina con inteligencia artificial ) ?"] "
Una ["Q-010 A trav & eacute ; s de la misma han invertido en Bnext & nbsp ; ( el primer marketplace de productos financieros aseguradores y relacionados c N viajes de Espa & ntilde ; a ) Buguroo & nbsp ; ( prevenci & oacute ; n del fraude bancario Mediante & nbsp ; deep learning ) y Kushki & nbsp ; ( plataforma de pago online para Am & eacute ; what N ) ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas " ["Q-012 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; de what n por cerca de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y"
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-013 & nbsp ; what N de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospe
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-014 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; what n p N de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-015 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; what N disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y ho
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma ["Q-016 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio what escalables y N preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-017 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y what defendibles p N sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "passag
Buguroo (prevención ["Q-018 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta what demanda como ciberseguridad pagos y marketplaces f N & oacute ; n y viajes y hospedaje ?"] "
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-019 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; n por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal what y y N N administra
fondo que tiene ["Q-020 Who por cerca de 20 millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-021 Who y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
fondo que tiene ["Q-022 Who preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
de alta demanda como ciberseguridad pagos y marketplaces ["Q-023 Who finanzas y seguros legal y administraci & oacute ; n y viajes y hospedaje ?"] "
pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de re , Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas " ["Q-025 & nbsp ; El fondo que tiene compromisos de inversi & oacute ; de how much n por cerca millones de euros busca oportunidades en & nbsp ; startups & nbsp ; ib & eacute ; ricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administraci & oac
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que " ["Q-027 Su foco se centra en la inversi & oacute ; n en Series A En aquellas & nbsp ; startups & nbsp ; que tengan en what y generen ingresos tras haber demostrado su aceptaci & oacute ; n & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que ["Q-028 Su foco se centra en la inversi & oacute ; what n e J & nbsp ; startups & nbsp ; que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptaci & oacute ; n en el mercado con m & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"]
en startups ibéricas ["Q-029 Su foco se centra en la inversi & oacute ; n en Series A En aquellas & nbsp ; startups & nbsp ; what J relevantes tras haber demostrado su aceptaci & oacute ; n en el mercado con m & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"] "
ya han ["Q-030 Su foco se centra en la inversi & oacute ; n en Series A En aquellas & nbsp ; startups & nbsp ; que tengan productos desarrollados y generen ingresos what r r N N N & oacute ; n en el mercado con m & eacute ; tricas que sustenten la tesis de inversi & oacute ; n ?"] "
Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track para las compañías más innovadoras de España y Portugal que deseen crecer en Norteamérica.Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansión internacional. Además tendrán , Los partners de Conexo Ventures tendrán una participación activa en la estrategia de las compañías y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la vía rápida. Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalización servirá
y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la vía rápida. Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalización servirá entre otras cosas para obtener mayores múltiplos a la inversión mediante salidas en mercados más avanzados. Una prue , Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí " ["Q-034 Conexo Ventures buscar & aacute ; apoyar a e N de emprendedores formados que sean what e e N N N & iacute ; lograr las siguientes rondas de financiaci & oacute ; n ( series B Y C ) y finalmente los & nbsp ; exit ?"] "
Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación ["Q-035 Conexo Ventures buscar & aacute ; apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos Y ah & iacute ; lograr what l l N N N rondas de financiaci & oacute ; n ( series B Y C ) y finalmente los & nbsp ; exit ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , . " ["Q-037 ]
fondo que tiene compromisos de inversión por cerca de 20 millones de euros ["Q-038 How much n N puente ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros ["Q-039 How much n N puente ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-040 Este puente a & eacute ; Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-041 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; compa & ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-042 Este puente a & eacute ; Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-043 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; compa & ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-044 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; compa & n N ; & iacute ; & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-045 Este p p N N N & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-046 Este puente a & e N ; N & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-047 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n n N N N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-048 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para l l N N N & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-049 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & n n N N N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-050 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & whose ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-051 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & whose ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas ["Q-052 Who n N a ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco ["Q-053 Who n N a ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Una prueba de nuestro excelente ["Q-054 Este puente a & eacute ; n how much Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-055 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; n how much compa & ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-056 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & how much n n N N N ; para las compa & n N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
en startups ibéricas ["Q-057 Este puente a & eacute ; reo entre Espa & ntilde ; a y Estados Unidos servir & aacute ; de & nbsp ; fast track & n N ; para las compa & how much n n N N N ; & iacute ; as m & aacute ; s innovadoras de Espa & ntilde ; a y Portugal que deseen crecer en Norteam & eacute ; rica ?"] "
Llevábamos ["Q-058 ]
Las startups participadas ["Q-059 Las & nbsp ; startups & nbsp ; what participadas p N & aacute ; n con un soporte legal de recursos humanos y ventas para su expansi & oacute ; n internacional ?"] "
Las startups participadas ["Q-060 Las & nbsp ; startups & nbsp ; participadas por Conexo Ventures contar & aacute ; n con un soporte legal de recursos what humanos y N para su expansi & oacute ; n internacional ?"] "
Las startups participadas por Conexo Ventures contarán con un soporte legal de recursos humanos y ventas para su expansión ["Q-061 Las & nbsp ; startups & nbsp ; participadas por Conexo Ventures contar & aacute ; n con un soporte legal de recursos humanos y ventas p N & oacute ; n internacional ?"] "
Las startups participadas ["Q-062 Who por Conexo Ventures contar & aacute ; n con un soporte legal de recursos humanos y ventas para su expansi & oacute ; n internacional ?"] "
Las startups participadas por Conexo Ventures ["Q-063 Who y ventas para su expansi & oacute ; n internacional ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , privado " ["Q-065 Adem & aacute ; s tendr & aacute ; n el apoyo del equipo gestor para La Sindicaci & oacute ; n de futuras rondas de financiaci & oacute ; de what fondos ?"] "
Además tendrán el apoyo del equipo gestor para la sindicación ["Q-066 Adem & aacute ; s tendr & aacute ; what n e J & oacute ; n de futuras rondas de financiaci & oacute ; n con fondos de capital privado norteamericanos ?"] "
Además ["Q-067 Adem & aacute ; s tendr & aacute ; n el apoyo del equipo gestor para La Sindicaci & oacute ; n de futuras rondas de financiaci & oacute ; what n c N de capital privado norteamericanos ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , compuesto por tres partners con " ["Q-069 El C s & eacute ; nior ejecutivo de Conexo Ventures & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-070 El C s & eacute ; nior ejecutivo de Conexo Ventures & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-071 El e C C s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; en what en el mundo del emprendimiento y la inversi & oacute ; n de la Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-072 El e C C s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; de what en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-073 El e e N N N s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-074 El e C C s & e N ; nior ejecutivo de Conexo Ventures e N & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-075 El e C C s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; N & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-076 El whose s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-077 El e C S & eacute ; nior ejecutivo de Conexo Ventures whose & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-078 El e how much C s & eacute ; nior ejecutivo de Conexo Ventures & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-079 El how much e e N N N s & eacute ; nior ejecutivo de Conexo Ventures E J & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
compuesto por tres partners con ["Q-080 El e C C s & e N ; nior ejecutivo de how much Conexo Ventures e N & aacute ; compuesto por tres & nbsp ; partners & nbsp ; con experiencia en el mundo del emprendimiento y la inversi & oacute ; n en venture Joaquim Hierro Isaac de La Pe & ntilde ; a y Damien Balsan ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables
Llevábamos ["Q-083 En este sentido Joaquim Hierro Lopes & nbsp ; managing partner & nbsp ; de Ged Capital ha expresado Llev & aacute ; de what bamos tiempo queriendo expandir nuestra actividad al venture capital Y cuando conocimos al equipo ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí , Los partners de Conexo Ventures tendrán una participación activa en la estrategia de las compañías y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED " ["Q-085 En este sentido Joaquim Hierro Lopes & nbsp ; managing partner & nbsp ; de Ged Capital ha expresado Llev & aacute ; what J nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Los partners de Conexo Ventures tendrán una participación activa en la estrategia de las compañías y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED ["Q-086 En e N sentido Joaquim Hierro Lopes & nbsp ; managing partner & nbsp ; de Ged Capital ha e N Llev & aacute ; bamos tiempo queriendo e N nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar what con nosotros e N de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing ["Q-087 Who tiempo queriendo expandir nuestra actividad al venture capital Y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo ["Q-088 Who en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora ?"] "
Llevábamos ["Q-089 ]
en startups ibéricas ["Q-090 & nbsp ; Por su parte Isaac de la Pe & ntilde ; a & nbsp ; partner & nbsp ; de Conexo Ventures ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; de what fundamental para que las startups en las que invirtamos accedan al Mercado & iacute ; a r & aacute ; pida ?"] "
rápida ["Q-091 & nbsp ; what N de la Pe & ntilde ; a & nbsp ; partner & nbsp ; de Conexo Ventures ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables y defendibles preferentemente utilizando Inteligencia Artificial para sectores de alta demanda como ciberseguridad pagos y marketplaces finanzas y seguros legal y administración y viajes y hospedaje. Su foco se centra en la inversión en Series A en aquellas startups que tengan productos desarrollados y generen ingresos relevantes tras haber demostrado su aceptación en el mercado con métricas que sustenten la tesis de inversión.Conexo Ventures buscará apoyar a equipos de emprendedores formados que sean exportables a Estados Unidos y ahí lograr las siguientes rondas de financiación (series B y C) y finalmente los exit. El equipo gestor de Conexo Ventures tiene una presencia activa en Boston y Silicon Valley. Este puente aéreo entre España y Estados Unidos servirá de fast track  , al mercado de Estados Unidos por la vía rápida " ["Q-093 & nbsp ; Por su parte Isaac de la Pe & ntilde ; a & nbsp ; partner & nbsp ; de Conexo Ventures ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; what fundamental para que las startups e F invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ["Q-094 Who ha a & ntilde ; adido & nbsp ; El apoyo de nuestro fondo ser & aacute ; fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups ["Q-095 Who en las que invirtamos accedan al mercado de Estados Unidos por la V & iacute ; a r & aacute ; pida ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , entre otras cosas para obtener mayores " ["Q-097 Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalizaci & o N ; n servir & aacute ; what o o N N M & uacute ; ltiplos a la inversi & oacute ; n mediante salidas en mercados m & aacute ; s avanzados ?"] "
y se involucrarán en la operativa junto a los fundadores de las startups.En este sentido Joaquim Hierro Lopes managing partner de GED Capital ha expresado Llevábamos tiempo queriendo expandir nuestra actividad al venture capital y cuando conocimos al equipo de Conexo no tuvimos ninguna duda de que eran las personas indicadas para trabajar con nosotros en esta nueva estrategia de capital privado que desarrollaremos desde nuestra gestora. Por su parte Isaac de la Peña partner de Conexo Ventures ha añadido El apoyo de nuestro fondo será fundamental para que las startups en las que invirtamos accedan al mercado de Estados Unidos por la vía rápida. Aprovechando las eficiencias de capital del Sur de Europa nuestra estrategia de internacionalización servirá entre otras cosas para obtener mayores múltiplos a la inversión mediante salidas en mercados más avanzados. Una prue , Una prueba de nuestro excelente criterio de selección y acompañamiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos de año " ["Q-099 Una prueba de nuestro excelente criterio de selecci & oacute ; n y acompa & ntilde ; amiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos & ntilde ; o ?"] "
ya han ["Q-0100 Una prueba de nuestro excelente criterio de selecci & oacute ; n y acompa & ntilde ; amiento de empresas es que dos de las what N en menos de a & ntilde ; o ?"] "
Una ["Q-0101 Who y acompa & ntilde ; amiento de empresas es que dos de las operaciones que hemos hecho ya han multiplicado su valor por cuatro y cinco veces en menos de a & ntilde ; o ?"] "
y cinco ["Q-0102 Who en menos de a & ntilde ; o ?"] "
GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables , GED Capital invierte BNext Buguroo y Kushki a trav\u00e9s de Conexo Ventures La gestora ibérica independiente GED Capital lanza su primer fondo de venture capital Conexo Ventures. Esta nueva actividad de GED Capital en el segmento del venture capital se suma a las estrategias ya existentes en la gestora de inversión en private equity e infraestructuras. A través de la misma han invertido en BNext (el primer marketplace de productos financieros aseguradores y relacionados con viajes de España) Buguroo (prevención del fraude bancario mediante deep learning) y Kushki (plataforma de pago online para América Latina con inteligencia artificial). El fondo que tiene compromisos de inversión por cerca de 20 millones de euros busca oportunidades en startups ibéricas que desarrollen software disruptivo con modelos de negocio escalables
"Many ["Q-01 Whom are Intel and Cray taking taking off the cliff ? Click here to view original web page at veryangrybird ?"] "
34;Many ["Q-02 What Are Intel and Cray taking taking us off the cliff ? Click here to v N at veryangrybird ?"] "
Intel and Cray ["Q-03 Who taking us off the cliff ? Click here to view original web page at veryangrybird ?"] "
Click here to view original web page at veryangrybird.blogspot.com "Many changes ["Q-04 Who are coming in the decade of the 2020s ?"] "
TECH WARNING ["Q-05 Whose Brave New World is right around the corner ?"] "
Brave New World ["Q-06 Who is right around the corner ?"] "
TECH WARNING ["Q-07 What might this get tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-08 Who might get a bit tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-09 Who are the times you live in ?"] "
TECH WARNING ["Q-10 Who live in ?"] "
TECH WARNING ["Q-11 What is this that Elon Musk Glenn Beck and others have been warning us about ?"] "
TECH WARNING ["Q-12 Who is something that Elon Musk Glenn Beck and others have been warning us about ?"] "
Elon Musk Glenn Beck ["Q-13 Who have been warning us about ?"] "
exaflops deep learning chatbots ["Q-14 What does it has to do with things ( terms ) called and turing tests ?"] "
Elon Musk Glenn Beck ["Q-15 Who has to do with things ( terms ) called exaflops deep learning chatbots and turing tests ?"] "
Elon Musk Glenn Beck ["Q-16 Who deep learning do with t N tests ?"] "
Did I ["Q-17 Who lose everybody as of yet ? these terms are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-18 Who are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Intel and Cray ["Q-19 Who are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-20 Who making the Big Leap into true Ai ?"] "
us to AI ["Q-21 Whom did the super highway needed to get to Ai is the super computer ?"] "
The super highway ["Q-22 Who needed to get us to Ai is the super computer ?"] "
AI ["Q-23 Who is the super computer ?"] "
2021 ["Q-24 When are and Intel and Cray about to unleash a doozie ?"] "
The super highway needed to get us to AI is the super computer ["Q-25 What are and Intel and Cray about to u N in 2021 ?"] "
Intel and Cray ["Q-26 Who are about to unleash a doozie in 2021 ?"] "
Intel and Cray ["Q-27 Who would help before you continue [ & # 8230 ; ] ?"] "
Intel and Cray ["Q-28 Who continue [ & # 8230 ; ] ?"] "
cliff ["Q-01 Off what Are Intel and Cray taking taking us ? Click here to view original web page at veryangrybird ?"] "
veryangrybird.blogspot.com ["Q-02 At what Are Intel and Cray taking taking us off the cliff ? Click here to view original web page ?"] "
"Many ["Q-03 Whom are Intel and Cray taking taking off the cliff ? Click here to view original web page at veryangrybird ?"] "
34;Many ["Q-04 What Are Intel and Cray taking taking us off the cliff ? Click here to v N at veryangrybird ?"] "
Intel and Cray ["Q-05 Who taking us off the cliff ? Click here to view original web page at veryangrybird ?"] "
Intel ["Q-06 ]
Intel ["Q-07 ]
Intel and Cray ["Q-08 Com & # 34 ; in what are many changes coming of the 2020s ?"] "
2020s ["Q-09 Com & # 34 ; of what are many changes coming in the decade ?"] "
34;Many ["Q-010 Com & # 34 ; what are many changes coming in the decade of the 2020s ?"] "
Click here to view original web page at veryangrybird.blogspot.com "Many changes ["Q-011 Who are coming in the decade of the 2020s ?"] "
Intel ["Q-012 ]
tech world ["Q-013 Despite the bitter and on what acrimonious fighting in Washington life fighting ?"] "
TECH WARNING ["Q-014 Despite the bitter and what acrimonious fighting in Washington life fighting on in the tech world ?"] "
#34;Many ["Q-015 ]
corner." ["Q-016 Around what is your Brave New World right ?"] "
TECH WARNING ["Q-017 Whose Brave New World is right around the corner ?"] "
Our Brave New World ["Q-018 Who is right around the corner ?"] "
34;Many ["Q-019 ]
34;Many ["Q-020 ]
TECH WARNING ["Q-021 What might this get tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-022 This might get a bit what are tech deep but these live in ?"] "
TECH WARNING ["Q-023 Who might get a bit tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-024 Who are the times you live in ?"] "
TECH WARNING ["Q-025 Who live in ?"] "
#34;Many ["Q-026 ]
TECH WARNING ["Q-027 What is this that Elon Musk Glenn Beck and others have been warning us about ?"] "
exaflops deep learning chatbots and turing tests ["Q-028 This is something that what have Elon Musk Glenn Beck and others been warning about ?"] "
TECH WARNING ["Q-029 Who is something that Elon Musk Glenn Beck and others have been warning us about ?"] "
Elon Musk Glenn Beck ["Q-030 Who have been warning us about ?"] "
#34;Many ["Q-031 ]
things ["Q-032 With what does it has to do ( terms ) called exaflops deep learning chatbots and turing tests ?"] "
exaflops deep learning chatbots ["Q-033 What does it has to do with things ( terms ) called and turing tests ?"] "
exaflops deep learning ["Q-034 It has to do with things ( terms ) called what chatbots and turing turing ?"] "
Elon Musk Glenn Beck ["Q-035 Who has to do with things ( terms ) called exaflops deep learning chatbots and turing tests ?"] "
exaflops ["Q-036 Who deep learning do with t N tests ?"] "
I continue [… ["Q-037 ]
we ["Q-038 Hello ? Did you lose everybody as of yet ? as whom are these terms important are on the cusp of making the Big Leap into true Ai ?"] "
the cusp ["Q-039 Hello ? Did you lose everybody as of yet ? these terms are on what are important as you of making the Big Leap into true Ai ?"] "
BIG LEAP ["Q-040 Hello ? Did you lose everybody as of yet ? these terms are of what are important as you on the cusp into true Ai ?"] "
true AI ["Q-041 Hello ? Did you lose everybody as of yet ? these terms are important as you are into what on the cusp of making making the Big Leap ?"] "
everybody ["Q-042 Hello ? what do Did you lose as of yet ? these terms are important as you are on the cusp of making the Big Leap into true Ai ?"] "
BIG LEAP ["Q-043 Hello ? Did you lose everybody as of yet ? these terms are important as you are what on the cusp of making making into true Ai ?"] "
Hello? Did I ["Q-044 Who lose everybody as of yet ? these terms are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-045 Who are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Intel and Cray ["Q-046 Who are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-047 Who making the Big Leap into true Ai ?"] "
I continue [… ["Q-048 ]
AI ["Q-049 To what did the super highway needed to get us is the super computer ?"] "
us to AI ["Q-050 Whom did the super highway needed to get to Ai is the super computer ?"] "
AI ["Q-051 The super highway needed to get us to what is Ai ?"] "
The super highway ["Q-052 Who needed to get us to Ai is the super computer ?"] "
AI ["Q-053 Who is the super computer ?"] "
I continue [… ["Q-054 ]
2021 ["Q-055 When are and Intel and Cray about to unleash a doozie ?"] "
The super highway needed to get us to AI is the super computer ["Q-056 What are and Intel and Cray about to u N in 2021 ?"] "
Intel and Cray ["Q-057 Who are about to unleash a doozie in 2021 ?"] "
2021 ["Q-058 In how much are and Intel and Cray about to unleash a doozie ?"] "
I continue [… ["Q-059 ]
Intel and Cray ["Q-060 Maybe before whom would some definitions help continue [ & # 8230 ; ] ?"] "
Intel and Cray ["Q-061 Maybe some definitions would help what before you c N & # 8230 ; ] ?"] "
Intel and Cray ["Q-062 Who would help before you continue [ & # 8230 ; ] ?"] "
Intel and Cray ["Q-063 Who continue [ & # 8230 ; ] ?"] "
I continue [… ["Q-064 ]
"Many ["Q-01 Whom are Intel and Cray taking taking off the cliff ? Click here to view original web page at veryangrybird ?"] "
34;Many ["Q-02 What Are Intel and Cray taking taking us off the cliff ? Click here to v N at veryangrybird ?"] "
Intel and Cray ["Q-03 Who taking us off the cliff ? Click here to view original web page at veryangrybird ?"] "
Click here to view original web page at veryangrybird.blogspot.com "Many changes ["Q-04 Who are coming in the decade of the 2020s ?"] "
TECH WARNING ["Q-05 Whose Brave New World is right around the corner ?"] "
Brave New World ["Q-06 Who is right around the corner ?"] "
TECH WARNING ["Q-07 What might this get tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-08 Who might get a bit tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-09 Who are the times you live in ?"] "
TECH WARNING ["Q-10 Who live in ?"] "
TECH WARNING ["Q-11 What is this that Elon Musk Glenn Beck and others have been warning us about ?"] "
TECH WARNING ["Q-12 Who is something that Elon Musk Glenn Beck and others have been warning us about ?"] "
Elon Musk Glenn Beck ["Q-13 Who have been warning us about ?"] "
exaflops deep learning chatbots ["Q-14 What does it has to do with things ( terms ) called and turing tests ?"] "
Elon Musk Glenn Beck ["Q-15 Who has to do with things ( terms ) called exaflops deep learning chatbots and turing tests ?"] "
Elon Musk Glenn Beck ["Q-16 Who deep learning do with t N tests ?"] "
Did I ["Q-17 Who lose everybody as of yet ? these terms are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-18 Who are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Intel and Cray ["Q-19 Who are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-20 Who making the Big Leap into true Ai ?"] "
us to AI ["Q-21 Whom did the super highway needed to get to Ai is the super computer ?"] "
The super highway ["Q-22 Who needed to get us to Ai is the super computer ?"] "
AI ["Q-23 Who is the super computer ?"] "
2021 ["Q-24 When are and Intel and Cray about to unleash a doozie ?"] "
The super highway needed to get us to AI is the super computer ["Q-25 What are and Intel and Cray about to u N in 2021 ?"] "
Intel and Cray ["Q-26 Who are about to unleash a doozie in 2021 ?"] "
Intel and Cray ["Q-27 Who would help before you continue [ & # 8230 ; ] ?"] "
Intel and Cray ["Q-28 Who continue [ & # 8230 ; ] ?"] "
cliff ["Q-01 Off what Are Intel and Cray taking taking us ? Click here to view original web page at veryangrybird ?"] "
veryangrybird.blogspot.com ["Q-02 At what Are Intel and Cray taking taking us off the cliff ? Click here to view original web page ?"] "
"Many ["Q-03 Whom are Intel and Cray taking taking off the cliff ? Click here to view original web page at veryangrybird ?"] "
34;Many ["Q-04 What Are Intel and Cray taking taking us off the cliff ? Click here to v N at veryangrybird ?"] "
Intel and Cray ["Q-05 Who taking us off the cliff ? Click here to view original web page at veryangrybird ?"] "
Intel ["Q-06 ]
Intel ["Q-07 ]
Intel and Cray ["Q-08 Com & # 34 ; in what are many changes coming of the 2020s ?"] "
2020s ["Q-09 Com & # 34 ; of what are many changes coming in the decade ?"] "
34;Many ["Q-010 Com & # 34 ; what are many changes coming in the decade of the 2020s ?"] "
Click here to view original web page at veryangrybird.blogspot.com "Many changes ["Q-011 Who are coming in the decade of the 2020s ?"] "
Intel ["Q-012 ]
tech world ["Q-013 Despite the bitter and on what acrimonious fighting in Washington life fighting ?"] "
TECH WARNING ["Q-014 Despite the bitter and what acrimonious fighting in Washington life fighting on in the tech world ?"] "
#34;Many ["Q-015 ]
corner." ["Q-016 Around what is your Brave New World right ?"] "
TECH WARNING ["Q-017 Whose Brave New World is right around the corner ?"] "
Our Brave New World ["Q-018 Who is right around the corner ?"] "
34;Many ["Q-019 ]
34;Many ["Q-020 ]
TECH WARNING ["Q-021 What might this get tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-022 This might get a bit what are tech deep but these live in ?"] "
TECH WARNING ["Q-023 Who might get a bit tech deep but these are the times you live in ?"] "
TECH WARNING ["Q-024 Who are the times you live in ?"] "
TECH WARNING ["Q-025 Who live in ?"] "
#34;Many ["Q-026 ]
TECH WARNING ["Q-027 What is this that Elon Musk Glenn Beck and others have been warning us about ?"] "
exaflops deep learning chatbots and turing tests ["Q-028 This is something that what have Elon Musk Glenn Beck and others been warning about ?"] "
TECH WARNING ["Q-029 Who is something that Elon Musk Glenn Beck and others have been warning us about ?"] "
Elon Musk Glenn Beck ["Q-030 Who have been warning us about ?"] "
#34;Many ["Q-031 ]
things ["Q-032 With what does it has to do ( terms ) called exaflops deep learning chatbots and turing tests ?"] "
exaflops deep learning chatbots ["Q-033 What does it has to do with things ( terms ) called and turing tests ?"] "
exaflops deep learning ["Q-034 It has to do with things ( terms ) called what chatbots and turing turing ?"] "
Elon Musk Glenn Beck ["Q-035 Who has to do with things ( terms ) called exaflops deep learning chatbots and turing tests ?"] "
exaflops ["Q-036 Who deep learning do with t N tests ?"] "
I continue [… ["Q-037 ]
we ["Q-038 Hello ? Did you lose everybody as of yet ? as whom are these terms important are on the cusp of making the Big Leap into true Ai ?"] "
the cusp ["Q-039 Hello ? Did you lose everybody as of yet ? these terms are on what are important as you of making the Big Leap into true Ai ?"] "
BIG LEAP ["Q-040 Hello ? Did you lose everybody as of yet ? these terms are of what are important as you on the cusp into true Ai ?"] "
true AI ["Q-041 Hello ? Did you lose everybody as of yet ? these terms are important as you are into what on the cusp of making making the Big Leap ?"] "
everybody ["Q-042 Hello ? what do Did you lose as of yet ? these terms are important as you are on the cusp of making the Big Leap into true Ai ?"] "
BIG LEAP ["Q-043 Hello ? Did you lose everybody as of yet ? these terms are important as you are what on the cusp of making making into true Ai ?"] "
Hello? Did I ["Q-044 Who lose everybody as of yet ? these terms are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-045 Who are important as you are on the cusp of making the Big Leap into true Ai ?"] "
Intel and Cray ["Q-046 Who are on the cusp of making the Big Leap into true Ai ?"] "
Hello ["Q-047 Who making the Big Leap into true Ai ?"] "
I continue [… ["Q-048 ]
AI ["Q-049 To what did the super highway needed to get us is the super computer ?"] "
us to AI ["Q-050 Whom did the super highway needed to get to Ai is the super computer ?"] "
AI ["Q-051 The super highway needed to get us to what is Ai ?"] "
The super highway ["Q-052 Who needed to get us to Ai is the super computer ?"] "
AI ["Q-053 Who is the super computer ?"] "
I continue [… ["Q-054 ]
2021 ["Q-055 When are and Intel and Cray about to unleash a doozie ?"] "
The super highway needed to get us to AI is the super computer ["Q-056 What are and Intel and Cray about to u N in 2021 ?"] "
Intel and Cray ["Q-057 Who are about to unleash a doozie in 2021 ?"] "
2021 ["Q-058 In how much are and Intel and Cray about to unleash a doozie ?"] "
I continue [… ["Q-059 ]
Intel and Cray ["Q-060 Maybe before whom would some definitions help continue [ & # 8230 ; ] ?"] "
Intel and Cray ["Q-061 Maybe some definitions would help what before you c N & # 8230 ; ] ?"] "
Intel and Cray ["Q-062 Who would help before you continue [ & # 8230 ; ] ?"] "
Intel and Cray ["Q-063 Who continue [ & # 8230 ; ] ?"] "
I continue [… ["Q-064 ]
Bird\u2019s-AI ["Q-01 Who make the trek south each fall migrating in pursuit of warmer winter temperatures ?"] "
How Deep Learning Helps Ornithologists Track Migration Patterns ["Q-02 Who appeared first on the Official Nvidia Blog ?"] "
the trek south ["Q-01 Bird \u2019 s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make in what each fall migrating of warmer winter temperatures ?"] "
trek south ["Q-02 Bird \u2019 s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make of what each fall migrating in pursuit ?"] "
Bird\u2019s-AI ["Q-03 Bird \u2019 what do s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make south each fall migrating in pursuit of warmer winter temperatures ?"] "
Bird\u2019s-AI ["Q-04 Bird \u2019 what do s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek s R in pursuit of warmer winter temperatures ?"] "
Bird\u2019s-AI ["Q-05 Who make the trek south each fall migrating in pursuit of warmer winter temperatures ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter of them don\u2019t make it back to northern breeding grounds in the spring falling victim to predators weather or man-made hazards like oil pits and cell towers. Many of these migratory Read article >The ["Q-06 ]
northern breeding grounds ["Q-07 But at least a quarter of them don \u2019 t make to what it back in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
spring falling victim ["Q-08 But at least a quarter of them don in what do \u2019 t make it back to northern breeding grounds to predators weather or man - made hazards like oil pits and cell towers ?"] "
oil pits ["Q-09 But at least a quarter of them don \u2019 t make it back to like what northern breeding grounds in the spring falling breeding victim to predators weather or man - made hazards and cell towers ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter ["Q-010 But at least a quarter of them d n make it back to northern breeding grounds in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
Bird\u2019s-AI ["Q-011 But at least a quarter of them don whom do \u2019 t make back to northern breeding grounds in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
grounds ["Q-012 But at least a quarter of them don what do \u2019 t make it back to northern breeding in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
victim ["Q-013 But at least a quarter of them don \u2019 t make it back to what northern breeding grounds in the spring falling breeding to predators weather or man - made hazards like oil pits and cell towers ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter of them don\u2019t make it back to northern breeding grounds in the spring falling victim to predators weather ["Q-014 But at least a quarter of them don \u2019 t make it back to what northern breeding grounds in the spring falling breeding victim to p N or man - made hazards like oil pits and cell towers ?"] "
62;The ["Q-015 ]
The Official NVIDIA Blog ["Q-016 Many of these migratory Read article & # 62 ; the post Bird \u2019 on what did s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns appeared first ?"] "
Deep Learning Helps Ornithologists Track Migration Patterns ["Q-017 Who appeared first on the Official Nvidia Blog ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter of them don\u2019t make it back to northern breeding grounds in the spring falling victim to predators weather or man-made hazards like oil pits and cell towers. Many of these migratory Read article >The ["Q-018 ]
62;The post Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns appeared first on The Official NVIDIA Blog. ["Q-019 ]
Bird\u2019s-AI ["Q-01 Who make the trek south each fall migrating in pursuit of warmer winter temperatures ?"] "
How Deep Learning Helps Ornithologists Track Migration Patterns ["Q-02 Who appeared first on the Official Nvidia Blog ?"] "
the trek south ["Q-01 Bird \u2019 s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make in what each fall migrating of warmer winter temperatures ?"] "
trek south ["Q-02 Bird \u2019 s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make of what each fall migrating in pursuit ?"] "
Bird\u2019s-AI ["Q-03 Bird \u2019 what do s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make south each fall migrating in pursuit of warmer winter temperatures ?"] "
Bird\u2019s-AI ["Q-04 Bird \u2019 what do s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek s R in pursuit of warmer winter temperatures ?"] "
Bird\u2019s-AI ["Q-05 Who make the trek south each fall migrating in pursuit of warmer winter temperatures ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter of them don\u2019t make it back to northern breeding grounds in the spring falling victim to predators weather or man-made hazards like oil pits and cell towers. Many of these migratory Read article >The ["Q-06 ]
northern breeding grounds ["Q-07 But at least a quarter of them don \u2019 t make to what it back in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
spring falling victim ["Q-08 But at least a quarter of them don in what do \u2019 t make it back to northern breeding grounds to predators weather or man - made hazards like oil pits and cell towers ?"] "
oil pits ["Q-09 But at least a quarter of them don \u2019 t make it back to like what northern breeding grounds in the spring falling breeding victim to predators weather or man - made hazards and cell towers ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter ["Q-010 But at least a quarter of them d n make it back to northern breeding grounds in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
Bird\u2019s-AI ["Q-011 But at least a quarter of them don whom do \u2019 t make back to northern breeding grounds in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
grounds ["Q-012 But at least a quarter of them don what do \u2019 t make it back to northern breeding in the spring falling victim to predators weather or man - made hazards like oil pits and cell towers ?"] "
victim ["Q-013 But at least a quarter of them don \u2019 t make it back to what northern breeding grounds in the spring falling breeding to predators weather or man - made hazards like oil pits and cell towers ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter of them don\u2019t make it back to northern breeding grounds in the spring falling victim to predators weather ["Q-014 But at least a quarter of them don \u2019 t make it back to what northern breeding grounds in the spring falling breeding victim to p N or man - made hazards like oil pits and cell towers ?"] "
62;The ["Q-015 ]
The Official NVIDIA Blog ["Q-016 Many of these migratory Read article & # 62 ; the post Bird \u2019 on what did s - ai View How Deep Learning Helps Ornithologists Track Migration Patterns appeared first ?"] "
Deep Learning Helps Ornithologists Track Migration Patterns ["Q-017 Who appeared first on the Official Nvidia Blog ?"] "
Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns Billions of birds in North America make the trek south each fall migrating in pursuit of warmer winter temperatures. But at least a quarter of them don\u2019t make it back to northern breeding grounds in the spring falling victim to predators weather or man-made hazards like oil pits and cell towers. Many of these migratory Read article >The ["Q-018 ]
62;The post Bird\u2019s-AI View How Deep Learning Helps Ornithologists Track Migration Patterns appeared first on The Official NVIDIA Blog. ["Q-019 ]
UND ["Q-01 Where new cluster to create a unified environment that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-02 What N to create a unified environment with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
Bright Cluster Manager for HPC... UND ["Q-03 What new cluster to create with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-04 What new cluster to create a unified environment with Bright automation software that d N to the cloud and deep learning resources ?"] "
prweb16629857.htm ["Q-01 ]
prweb16629857.htm ["Q-02 ]
prweb16629857.htm ["Q-03 ]
versatility access to the cloud ["Q-04 Und designs new cluster to create to what versatility access and deep learning resources ?"] "
UND ["Q-05 Where new cluster to create a unified environment that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-06 What N to create a unified environment with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-07 What new cluster to create with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-08 What new cluster to create a unified environment with Bright automation software that d N to the cloud and deep learning resources ?"] "
prweb16629857.htm ["Q-09 ]
prweb16629857.htm ["Q-010 ]
prweb16629857.htm ["Q-011 ]
prweb16629857.htm ["Q-012 ]
prweb16629857.htm ["Q-013 ]
UND ["Q-01 Where new cluster to create a unified environment that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-02 What N to create a unified environment with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
Bright Cluster Manager for HPC... UND ["Q-03 What new cluster to create with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-04 What new cluster to create a unified environment with Bright automation software that d N to the cloud and deep learning resources ?"] "
prweb16629857.htm ["Q-01 ]
prweb16629857.htm ["Q-02 ]
prweb16629857.htm ["Q-03 ]
versatility access to the cloud ["Q-04 Und designs new cluster to create to what versatility access and deep learning resources ?"] "
UND ["Q-05 Where new cluster to create a unified environment that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-06 What N to create a unified environment with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-07 What new cluster to create with Bright automation software that delivers versatility access to the cloud and deep learning resources ?"] "
UND ["Q-08 What new cluster to create a unified environment with Bright automation software that d N to the cloud and deep learning resources ?"] "
prweb16629857.htm ["Q-09 ]
prweb16629857.htm ["Q-010 ]
prweb16629857.htm ["Q-011 ]
prweb16629857.htm ["Q-012 ]
prweb16629857.htm ["Q-013 ]
Artificial Intelligence (AI) and\u00a0deep learning image recognition ["Q-01 Who has become a reality ?"] "
SAS Blogs ["Q-02 Where did the post Computer vision Past present and future appeared first ?"] "
The post Computer vision Past present and future ["Q-03 Who appeared first on Sas Blogs ?"] "
reality ["Q-01 Computer vision Past present and future thanks to recent advances in artificial Intelligence ( Ai ) and what has deep learning image recognition become ?"] "
Artificial Intelligence (AI) and\u00a0deep learning image recognition ["Q-02 Who has become a reality ?"] "
. ["Q-03 ]
SAS Blogs ["Q-04 Where did the post Computer vision Past present and future appeared first ?"] "
The post Computer vision Past present and future ["Q-05 Who appeared first on Sas Blogs ?"] "
. ["Q-06 ]
. ["Q-07 ]
Artificial Intelligence (AI) and\u00a0deep learning image recognition ["Q-01 Who has become a reality ?"] "
SAS Blogs ["Q-02 Where did the post Computer vision Past present and future appeared first ?"] "
The post Computer vision Past present and future ["Q-03 Who appeared first on Sas Blogs ?"] "
reality ["Q-01 Computer vision Past present and future thanks to recent advances in artificial Intelligence ( Ai ) and what has deep learning image recognition become ?"] "
Artificial Intelligence (AI) and\u00a0deep learning image recognition ["Q-02 Who has become a reality ?"] "
. ["Q-03 ]
SAS Blogs ["Q-04 Where did the post Computer vision Past present and future appeared first ?"] "
The post Computer vision Past present and future ["Q-05 Who appeared first on Sas Blogs ?"] "
. ["Q-06 ]
. ["Q-07 ]
secure your property with cameras ["Q-01 Who are considering doing so there is a new product coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-02 Who coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-03 Who may interest i and later this month Chris will have a video review of it out as well ?"] "
Chris ["Q-04 Who will have a video review of it out as well ?"] "
Press Release ["Q-05 Who out as well ?"] "
smart camera hub ["Q-06 What is camect that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-07 What is Camect a smart camera hub that is bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect Smart Camera Hub Coming Soon For those of you who secure your property with cameras or are considering doing so there is a new product coming soon that may interest you and later this month Chris will have a video review of it out as well. Camect ["Q-08 Who is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-09 Who is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
all footage local ["Q-10 Who can enable cloud backup if me wish ?"] "
Press Release ["Q-11 Who wish ?"] "
Captured ["Q-12 What captured video can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-13 Who can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-14 Who is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
worldwide access ["Q-15 Who is free ?"] "
If your security system ["Q-16 Who uses additional cameras and i want to view more than two of them remotely then there is a year subscription fee ?"] "
cameras ["Q-17 Who want to view more than two of them remotely then there is a year subscription fee ?"] "
twelve 1080p ["Q-18 While the average home security system will have five about what is cameras it able to handle of average scene complexity so i should have some room to expand my system if me wish ?"] "
average scene complexity ["Q-19 While the average home security system will have five of what is cameras it able to handle about twelve 1080p cameras so i should have some room to expand my system if me wish ?"] "
if you wish ["Q-20 While the average home security system will have five so whom is cameras it able to handle about twelve 1080p cameras of average scene complexity should have some room to expand my system if me wish ?"] "
if you wish ["Q-21 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of if whom should average scene complexity so i have some room to expand my system wish ?"] "
five cameras ["Q-22 While what will the average home security system have is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
some room ["Q-23 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have to expand my system if me wish ?"] "
your system ["Q-24 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have some room to expand if me wish ?"] "
average home security system ["Q-25 Who will have five cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
five cameras ["Q-26 Who is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
home security system ["Q-27 Who should have some room to expand my system if me wish ?"] "
Press Release ["Q-28 Who wish ?"] "
five ["Q-29 While how much will the average home security system have cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
expand your system if you wish ["Q-30 What are the feeds from these cameras with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
expand your system if you wish ["Q-31 What are the feeds from these cameras also analyzed with a deep learning algorithm to identify captured and depending on what it is i will be alerted ?"] "
cameras ["Q-32 Who are also analyzed with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
the activity ["Q-33 Who captured and depending on what it is i will be alerted ?"] "
the activity captured ["Q-34 Who depending on what it is i will be alerted ?"] "
Press Release ["Q-35 Who is i will be alerted ?"] "
the activity captured and depending on what it is you will be alerted. By providing feedback to the device on these notifications it can improve its model and become more accurate so it will let you know when a package is being delivered but not when a squirrel runs by. By providing the system public camera live streams found on YouTube the company has created a demonstration of these alerts that you can find here Camect Alerts Demo.Presently there is an IndieGoGo page for Camect where you can pre-order a unit for $299 down from the usual $399 price or $549 with lifetime service that would normally cost $1149. They are expected to ship in January 2020.Source Press Release ["Q-36 Who will be alerted ?"] "
feedback ["Q-37 What by providing providing to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
alerted ["Q-38 Who providing feedback to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
providing feedback to the device on these notifications ["Q-39 Who can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
By providing feedback to the device on these notifications it can improve its model ["Q-40 Who become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
more accurate ["Q-41 Who will let i know when a package is being delivered but not when a squirrel runs by ?"] "
become more accurate ["Q-42 Who know when a package is being delivered but not when a squirrel runs by ?"] "
a package ["Q-43 Who is being delivered but not when a squirrel runs by ?"] "
a squirrel ["Q-44 What by providing providing public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
a squirrel ["Q-45 Who providing the system public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
public camera live streams ["Q-46 Who found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube the company ["Q-47 Who has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
Press Release ["Q-48 Who can find here Camect Alerts Demo ?"] "
$1149 ["Q-49 Who can pre - order a unit for down from the usual price or with lifetime service that would normally cost ?"] "
Press Release ["Q-50 What are they expected to ship in January 2020 ?"] "
Press Release ["Q-51 Who are expected to ship in January 2020 ?"] "
$399 price or $549 ["Q-52 How much are they expected to s N ?"] "
Camect Smart Camera Hub Coming Soon For those of you who secure your property with cameras or are considering ["Q-01 Camect Smart Camera Hub Coming Soon for those of me who secure my property with cameras or are considering doing so there is a new product coming soon that may interest i and later of whom will this month Chris have a video review out as well ?"] "
your property ["Q-02 Camect Smart Camera Hub Coming Soon for those of me who secure what are my property with cameras or considering doing so there is a new product coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
your property ["Q-03 Camect Smart Camera Hub Coming Soon for those of me who secure what are my property with cameras or considering doing so there is soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
interest you ["Q-04 Camect Smart Camera Hub Coming Soon for those of me who secure my property with cameras or are considering doing so there is a new product coming soon what that may and later this month Chris will have a video review of it out as well ?"] "
a video review ["Q-05 Camect Smart Camera Hub Coming Soon for those of me who secure my property with cameras or are considering doing so there is a new product coming soon that may interest i and later what will this month Chris have of it out as well ?"] "
secure your property with cameras ["Q-06 Who are considering doing so there is a new product coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-07 Who coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-08 Who may interest i and later this month Chris will have a video review of it out as well ?"] "
Chris ["Q-09 Who will have a video review of it out as well ?"] "
Press Release ["Q-010 Who out as well ?"] "
Alerts Demo ["Q-011 ]
proprietary camera systems ["Q-012 Camect is a smart camera hub that is a bit different from to what is other security camera systems as it not tied applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
other security camera systems ["Q-013 From what is Camect a smart camera hub that is a bit different as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-014 As whom is Camect a smart camera hub that is a bit different from other security camera systems is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
objects ["Q-015 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect though whom all footage local can enable cloud backup if me wish ?"] "
all footage local ["Q-016 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps if whom can local though me enable cloud backup wish ?"] "
Camect is a smart camera hub ["Q-017 What is camect that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-018 What is Camect a smart camera hub that is bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
not tied ["Q-019 Camect is a smart camera hub that is a bit different from what is other security camera systems as it to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect Smart Camera Hub Coming Soon For those of you who secure your property with cameras or are considering doing so there is a new product coming soon that may interest you and later this month Chris will have a video review of it out as well. Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies AI ["Q-020 Camect is a smart camera hub that is a bit different from what is other security camera systems as it not tied to proprietary camera systems a N to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
proprietary camera systems ["Q-021 Camect is a smart camera hub that is a bit d J from other security camera systems as it is not tied to what Ai to d J and keeps all footage local though me can enable cloud backup if me wish ?"] "
keeps all footage local ["Q-022 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and what k k N N N footage local though me can enable cloud backup if me wish ?"] "
cloud backup ["Q-023 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps what can local though me enable if me wish ?"] "
Camect ["Q-024 Who is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-025 Who is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
all footage local ["Q-026 Who can enable cloud backup if me wish ?"] "
Press Release ["Q-027 Who wish ?"] "
Press Release ["Q-028 ]
Internet ["Q-029 Over what Captured video can still be accessed even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
backup ["Q-030 Without what Captured video can still be accessed over the Internet even but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
your control ["Q-031 Captured video can still be accessed over the Internet even outside what is without the backup but it not uploaded to remote servers and for two cameras this worldwide access is free ?"] "
two cameras ["Q-032 Captured video can still be accessed over the Internet even for what is without the backup but it not uploaded to remote servers outside my control and worldwide access is free ?"] "
Captured ["Q-033 What captured video can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
remote servers ["Q-034 Captured video can still be accessed over the Internet even what is without the backup but it not uploaded to r N outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-035 Who can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-036 Who is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
worldwide access ["Q-037 Who is free ?"] "
two ["Q-038 Captured video can still be accessed over the Internet even for how much is without the backup but it not uploaded to remote servers outside my control and cameras this worldwide access is free ?"] "
Press Release ["Q-039 ]
two ["Q-040 If my security system uses than what additional cameras and i want to view more of them remotely then there is a year subscription fee ?"] "
$60 ["Q-041 If my security system uses of whom additional cameras and i want to view more than two remotely then there is a year subscription fee ?"] "
$60 a year subscription fee ["Q-042 If my security system uses what additional cameras and i want to view more than two of them remotely then there is ?"] "
$60 ["Q-043 If whose security system uses additional cameras and i want to view more than two of them remotely then there is a year subscription fee ?"] "
your security system ["Q-044 Who uses additional cameras and i want to view more than two of them remotely then there is a year subscription fee ?"] "
cameras ["Q-045 Who want to view more than two of them remotely then there is a year subscription fee ?"] "
$60 ["Q-046 If my security system uses than how much additional cameras and i want to view more of them remotely then there is a year subscription fee ?"] "
Press Release ["Q-047 ]
those feeds onto its 1 TB of expandable storage ["Q-048 The Camect works by first searching for video feeds from security cameras on my network and then aggregating of what those feeds onto its 1 tb ?"] "
first ["Q-049 The Camect works by what searching for video feeds from security cameras on my network and then searching onto its 1 tb of expandable storage ?"] "
1 TB ["Q-050 The Camect works by first searching for video feeds from security cameras on my network and then aggregating what those feeds o you of expandable storage ?"] "
1 ["Q-051 The Camect works by first searching for video feeds from security cameras on my network and then aggregating how much those feeds o you Tb of expandable storage ?"] "
Press Release ["Q-052 ]
twelve 1080p ["Q-053 While the average home security system will have five about what is cameras it able to handle of average scene complexity so i should have some room to expand my system if me wish ?"] "
average scene complexity ["Q-054 While the average home security system will have five of what is cameras it able to handle about twelve 1080p cameras so i should have some room to expand my system if me wish ?"] "
if you wish ["Q-055 While the average home security system will have five so whom is cameras it able to handle about twelve 1080p cameras of average scene complexity should have some room to expand my system if me wish ?"] "
if you wish ["Q-056 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of if whom should average scene complexity so i have some room to expand my system wish ?"] "
five cameras ["Q-057 While what will the average home security system have is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
average scene complexity so you should have some room ["Q-058 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have to expand my system if me wish ?"] "
your system ["Q-059 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have some room to expand if me wish ?"] "
average home security system ["Q-060 Who will have five cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
five cameras ["Q-061 Who is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
home security system will have five cameras ["Q-062 Who should have some room to expand my system if me wish ?"] "
Press Release ["Q-063 Who wish ?"] "
five ["Q-064 While how much will the average home security system have cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
twelve 1080p ["Q-065 While the average home security system will have five how much is cameras it able to h N cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
Press Release ["Q-066 ]
deep learning algorithm ["Q-067 With what are the feeds from these cameras also analyzed to identify the activity captured and depending on what it is i will be alerted ?"] "
expand your system if you wish ["Q-068 What are the feeds from these cameras with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
expand your system if you wish ["Q-069 What are the feeds from these cameras also analyzed with a deep learning algorithm to identify captured and depending on what it is i will be alerted ?"] "
security cameras on your network ["Q-070 The feeds from these cameras are also analyzed with a deep learning algorithm to identify the activity captured and depending on what whom is it will be alerted ?"] "
expand your system if you wish ["Q-071 The feeds from these cameras are also analyzed with a deep learning algorithm to identify the activity captured and depending on what it is what will i be alerted ?"] "
cameras ["Q-072 Who are also analyzed with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
the activity ["Q-073 Who captured and depending on what it is i will be alerted ?"] "
the activity captured ["Q-074 Who depending on what it is i will be alerted ?"] "
Press Release ["Q-075 Who is i will be alerted ?"] "
Press Release ["Q-076 Who will be alerted ?"] "
Press Release ["Q-077 ]
public camera live streams found on YouTube ["Q-078 To what by providing providing feedback on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
public camera live streams found on YouTube ["Q-079 On what by providing providing feedback to the device can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
its model ["Q-080 By providing feedback to the device on these notifications it can improve so whom its model and become more accurate will let i know when a package is being delivered but not when a squirrel runs by ?"] "
feedback ["Q-081 What by providing providing to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
its model ["Q-082 By providing feedback to what can the device on these notifications it improve and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
more accurate ["Q-083 By providing feedback to the device on these notifications it can improve its model and become what will accurate so it let know when a package is being delivered but not when a squirrel runs by ?"] "
a package ["Q-084 By providing feedback to the device on these notifications it can improve its model and become more accurate so it will let i know when what is a package being delivered but not when a squirrel runs by ?"] "
alerted ["Q-085 Who providing feedback to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
providing feedback to the device on these notifications ["Q-086 Who can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
By providing feedback to the device on these notifications it can improve its model ["Q-087 Who become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
more accurate ["Q-088 Who will let i know when a package is being delivered but not when a squirrel runs by ?"] "
become more accurate ["Q-089 Who know when a package is being delivered but not when a squirrel runs by ?"] "
a package ["Q-090 Who is being delivered but not when a squirrel runs by ?"] "
Press Release ["Q-091 ]
YouTube the company ["Q-092 By providing the system public camera on what live streams found has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube the company ["Q-093 By providing the system public camera live streams found of what has the company created a demonstration that me can find here Camect Alerts Demo ?"] "
YouTube ["Q-094 By providing the system public camera live streams found that whom has the company created a demonstration of these alerts can find here Camect Alerts Demo ?"] "
a squirrel ["Q-095 What by providing providing public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube ["Q-096 By providing the system public camera live streams found what has the company created of these alerts that me can find here Camect Alerts Demo ?"] "
Camect Alerts Demo ["Q-097 By providing the system public camera live streams found on youtube the company has created what can a demonstration of these alerts that me find ?"] "
a squirrel ["Q-098 Who providing the system public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
public camera live streams ["Q-099 Who found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube the company ["Q-0100 Who has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
Press Release ["Q-0101 Who can find here Camect Alerts Demo ?"] "
Press Release ["Q-0102 ]
$299 ["Q-0103 Presently there is an Indiegogo page for Camect where i can pre - order from what a unit for down or with lifetime service that would normally cost ?"] "
lifetime service ["Q-0104 Presently there is an Indiegogo page for Camect where with what can i pre - order a unit for down from the usual price or that would normally cost ?"] "
a unit for $299 ["Q-0105 Presently there is an Indiegogo page for Camect where what can i pre - order for down from the usual price or with lifetime service that would normally cost ?"] "
$1149 ["Q-0106 Who can pre - order a unit for down from the usual price or with lifetime service that would normally cost ?"] "
Press Release ["Q-0107 ]
Press Release ["Q-0108 In what are they expected to ship ?"] "
Press Release ["Q-0109 What are they expected to ship in January 2020 ?"] "
Press Release ["Q-0110 Who are expected to ship in January 2020 ?"] "
$399 price or $549 ["Q-0111 How much are they expected to s N ?"] "
Press Release ["Q-0112 ]
Press Release ["Q-0113 ]
secure your property with cameras ["Q-01 Who are considering doing so there is a new product coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-02 Who coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-03 Who may interest i and later this month Chris will have a video review of it out as well ?"] "
Chris ["Q-04 Who will have a video review of it out as well ?"] "
Press Release ["Q-05 Who out as well ?"] "
smart camera hub ["Q-06 What is camect that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-07 What is Camect a smart camera hub that is bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect Smart Camera Hub Coming Soon For those of you who secure your property with cameras or are considering doing so there is a new product coming soon that may interest you and later this month Chris will have a video review of it out as well. Camect ["Q-08 Who is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-09 Who is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
all footage local ["Q-10 Who can enable cloud backup if me wish ?"] "
Press Release ["Q-11 Who wish ?"] "
Captured ["Q-12 What captured video can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-13 Who can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-14 Who is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
worldwide access ["Q-15 Who is free ?"] "
If your security system ["Q-16 Who uses additional cameras and i want to view more than two of them remotely then there is a year subscription fee ?"] "
cameras ["Q-17 Who want to view more than two of them remotely then there is a year subscription fee ?"] "
twelve 1080p ["Q-18 While the average home security system will have five about what is cameras it able to handle of average scene complexity so i should have some room to expand my system if me wish ?"] "
average scene complexity ["Q-19 While the average home security system will have five of what is cameras it able to handle about twelve 1080p cameras so i should have some room to expand my system if me wish ?"] "
if you wish ["Q-20 While the average home security system will have five so whom is cameras it able to handle about twelve 1080p cameras of average scene complexity should have some room to expand my system if me wish ?"] "
if you wish ["Q-21 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of if whom should average scene complexity so i have some room to expand my system wish ?"] "
five cameras ["Q-22 While what will the average home security system have is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
some room ["Q-23 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have to expand my system if me wish ?"] "
your system ["Q-24 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have some room to expand if me wish ?"] "
average home security system ["Q-25 Who will have five cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
five cameras ["Q-26 Who is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
home security system ["Q-27 Who should have some room to expand my system if me wish ?"] "
Press Release ["Q-28 Who wish ?"] "
five ["Q-29 While how much will the average home security system have cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
expand your system if you wish ["Q-30 What are the feeds from these cameras with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
expand your system if you wish ["Q-31 What are the feeds from these cameras also analyzed with a deep learning algorithm to identify captured and depending on what it is i will be alerted ?"] "
cameras ["Q-32 Who are also analyzed with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
the activity ["Q-33 Who captured and depending on what it is i will be alerted ?"] "
the activity captured ["Q-34 Who depending on what it is i will be alerted ?"] "
Press Release ["Q-35 Who is i will be alerted ?"] "
the activity captured and depending on what it is you will be alerted. By providing feedback to the device on these notifications it can improve its model and become more accurate so it will let you know when a package is being delivered but not when a squirrel runs by. By providing the system public camera live streams found on YouTube the company has created a demonstration of these alerts that you can find here Camect Alerts Demo.Presently there is an IndieGoGo page for Camect where you can pre-order a unit for $299 down from the usual $399 price or $549 with lifetime service that would normally cost $1149. They are expected to ship in January 2020.Source Press Release ["Q-36 Who will be alerted ?"] "
feedback ["Q-37 What by providing providing to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
alerted ["Q-38 Who providing feedback to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
providing feedback to the device on these notifications ["Q-39 Who can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
By providing feedback to the device on these notifications it can improve its model ["Q-40 Who become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
more accurate ["Q-41 Who will let i know when a package is being delivered but not when a squirrel runs by ?"] "
become more accurate ["Q-42 Who know when a package is being delivered but not when a squirrel runs by ?"] "
a package ["Q-43 Who is being delivered but not when a squirrel runs by ?"] "
a squirrel ["Q-44 What by providing providing public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
a squirrel ["Q-45 Who providing the system public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
public camera live streams ["Q-46 Who found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube the company ["Q-47 Who has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
Press Release ["Q-48 Who can find here Camect Alerts Demo ?"] "
$1149 ["Q-49 Who can pre - order a unit for down from the usual price or with lifetime service that would normally cost ?"] "
Press Release ["Q-50 What are they expected to ship in January 2020 ?"] "
Press Release ["Q-51 Who are expected to ship in January 2020 ?"] "
$399 price or $549 ["Q-52 How much are they expected to s N ?"] "
Camect Smart Camera Hub Coming Soon For those of you who secure your property with cameras or are considering ["Q-01 Camect Smart Camera Hub Coming Soon for those of me who secure my property with cameras or are considering doing so there is a new product coming soon that may interest i and later of whom will this month Chris have a video review out as well ?"] "
your property ["Q-02 Camect Smart Camera Hub Coming Soon for those of me who secure what are my property with cameras or considering doing so there is a new product coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
your property ["Q-03 Camect Smart Camera Hub Coming Soon for those of me who secure what are my property with cameras or considering doing so there is soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
interest you ["Q-04 Camect Smart Camera Hub Coming Soon for those of me who secure my property with cameras or are considering doing so there is a new product coming soon what that may and later this month Chris will have a video review of it out as well ?"] "
a video review ["Q-05 Camect Smart Camera Hub Coming Soon for those of me who secure my property with cameras or are considering doing so there is a new product coming soon that may interest i and later what will this month Chris have of it out as well ?"] "
secure your property with cameras ["Q-06 Who are considering doing so there is a new product coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-07 Who coming soon that may interest i and later this month Chris will have a video review of it out as well ?"] "
Camect Smart Camera Hub Coming ["Q-08 Who may interest i and later this month Chris will have a video review of it out as well ?"] "
Chris ["Q-09 Who will have a video review of it out as well ?"] "
Press Release ["Q-010 Who out as well ?"] "
Alerts Demo ["Q-011 ]
proprietary camera systems ["Q-012 Camect is a smart camera hub that is a bit different from to what is other security camera systems as it not tied applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
other security camera systems ["Q-013 From what is Camect a smart camera hub that is a bit different as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-014 As whom is Camect a smart camera hub that is a bit different from other security camera systems is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
objects ["Q-015 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect though whom all footage local can enable cloud backup if me wish ?"] "
all footage local ["Q-016 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps if whom can local though me enable cloud backup wish ?"] "
Camect is a smart camera hub ["Q-017 What is camect that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-018 What is Camect a smart camera hub that is bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
not tied ["Q-019 Camect is a smart camera hub that is a bit different from what is other security camera systems as it to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect Smart Camera Hub Coming Soon For those of you who secure your property with cameras or are considering doing so there is a new product coming soon that may interest you and later this month Chris will have a video review of it out as well. Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies AI ["Q-020 Camect is a smart camera hub that is a bit different from what is other security camera systems as it not tied to proprietary camera systems a N to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
proprietary camera systems ["Q-021 Camect is a smart camera hub that is a bit d J from other security camera systems as it is not tied to what Ai to d J and keeps all footage local though me can enable cloud backup if me wish ?"] "
keeps all footage local ["Q-022 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and what k k N N N footage local though me can enable cloud backup if me wish ?"] "
cloud backup ["Q-023 Camect is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps what can local though me enable if me wish ?"] "
Camect ["Q-024 Who is a smart camera hub that is a bit different from other security camera systems as it is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
Camect ["Q-025 Who is not tied to proprietary camera systems applies Ai to detect objects and keeps all footage local though me can enable cloud backup if me wish ?"] "
all footage local ["Q-026 Who can enable cloud backup if me wish ?"] "
Press Release ["Q-027 Who wish ?"] "
Press Release ["Q-028 ]
Internet ["Q-029 Over what Captured video can still be accessed even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
backup ["Q-030 Without what Captured video can still be accessed over the Internet even but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
your control ["Q-031 Captured video can still be accessed over the Internet even outside what is without the backup but it not uploaded to remote servers and for two cameras this worldwide access is free ?"] "
two cameras ["Q-032 Captured video can still be accessed over the Internet even for what is without the backup but it not uploaded to remote servers outside my control and worldwide access is free ?"] "
Captured ["Q-033 What captured video can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
remote servers ["Q-034 Captured video can still be accessed over the Internet even what is without the backup but it not uploaded to r N outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-035 Who can still be accessed over the Internet even without the backup but it is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
Captured video ["Q-036 Who is not uploaded to remote servers outside my control and for two cameras this worldwide access is free ?"] "
worldwide access ["Q-037 Who is free ?"] "
two ["Q-038 Captured video can still be accessed over the Internet even for how much is without the backup but it not uploaded to remote servers outside my control and cameras this worldwide access is free ?"] "
Press Release ["Q-039 ]
two ["Q-040 If my security system uses than what additional cameras and i want to view more of them remotely then there is a year subscription fee ?"] "
$60 ["Q-041 If my security system uses of whom additional cameras and i want to view more than two remotely then there is a year subscription fee ?"] "
$60 a year subscription fee ["Q-042 If my security system uses what additional cameras and i want to view more than two of them remotely then there is ?"] "
$60 ["Q-043 If whose security system uses additional cameras and i want to view more than two of them remotely then there is a year subscription fee ?"] "
your security system ["Q-044 Who uses additional cameras and i want to view more than two of them remotely then there is a year subscription fee ?"] "
cameras ["Q-045 Who want to view more than two of them remotely then there is a year subscription fee ?"] "
$60 ["Q-046 If my security system uses than how much additional cameras and i want to view more of them remotely then there is a year subscription fee ?"] "
Press Release ["Q-047 ]
those feeds onto its 1 TB of expandable storage ["Q-048 The Camect works by first searching for video feeds from security cameras on my network and then aggregating of what those feeds onto its 1 tb ?"] "
first ["Q-049 The Camect works by what searching for video feeds from security cameras on my network and then searching onto its 1 tb of expandable storage ?"] "
1 TB ["Q-050 The Camect works by first searching for video feeds from security cameras on my network and then aggregating what those feeds o you of expandable storage ?"] "
1 ["Q-051 The Camect works by first searching for video feeds from security cameras on my network and then aggregating how much those feeds o you Tb of expandable storage ?"] "
Press Release ["Q-052 ]
twelve 1080p ["Q-053 While the average home security system will have five about what is cameras it able to handle of average scene complexity so i should have some room to expand my system if me wish ?"] "
average scene complexity ["Q-054 While the average home security system will have five of what is cameras it able to handle about twelve 1080p cameras so i should have some room to expand my system if me wish ?"] "
if you wish ["Q-055 While the average home security system will have five so whom is cameras it able to handle about twelve 1080p cameras of average scene complexity should have some room to expand my system if me wish ?"] "
if you wish ["Q-056 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of if whom should average scene complexity so i have some room to expand my system wish ?"] "
five cameras ["Q-057 While what will the average home security system have is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
average scene complexity so you should have some room ["Q-058 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have to expand my system if me wish ?"] "
your system ["Q-059 While the average home security system will have five cameras it is able to handle about twelve 1080p cameras of what should average scene complexity so i have some room to expand if me wish ?"] "
average home security system ["Q-060 Who will have five cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
five cameras ["Q-061 Who is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
home security system will have five cameras ["Q-062 Who should have some room to expand my system if me wish ?"] "
Press Release ["Q-063 Who wish ?"] "
five ["Q-064 While how much will the average home security system have cameras it is able to handle about twelve 1080p cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
twelve 1080p ["Q-065 While the average home security system will have five how much is cameras it able to h N cameras of average scene complexity so i should have some room to expand my system if me wish ?"] "
Press Release ["Q-066 ]
deep learning algorithm ["Q-067 With what are the feeds from these cameras also analyzed to identify the activity captured and depending on what it is i will be alerted ?"] "
expand your system if you wish ["Q-068 What are the feeds from these cameras with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
expand your system if you wish ["Q-069 What are the feeds from these cameras also analyzed with a deep learning algorithm to identify captured and depending on what it is i will be alerted ?"] "
security cameras on your network ["Q-070 The feeds from these cameras are also analyzed with a deep learning algorithm to identify the activity captured and depending on what whom is it will be alerted ?"] "
expand your system if you wish ["Q-071 The feeds from these cameras are also analyzed with a deep learning algorithm to identify the activity captured and depending on what it is what will i be alerted ?"] "
cameras ["Q-072 Who are also analyzed with a deep learning algorithm to identify the activity captured and depending on what it is i will be alerted ?"] "
the activity ["Q-073 Who captured and depending on what it is i will be alerted ?"] "
the activity captured ["Q-074 Who depending on what it is i will be alerted ?"] "
Press Release ["Q-075 Who is i will be alerted ?"] "
Press Release ["Q-076 Who will be alerted ?"] "
Press Release ["Q-077 ]
public camera live streams found on YouTube ["Q-078 To what by providing providing feedback on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
public camera live streams found on YouTube ["Q-079 On what by providing providing feedback to the device can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
its model ["Q-080 By providing feedback to the device on these notifications it can improve so whom its model and become more accurate will let i know when a package is being delivered but not when a squirrel runs by ?"] "
feedback ["Q-081 What by providing providing to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
its model ["Q-082 By providing feedback to what can the device on these notifications it improve and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
more accurate ["Q-083 By providing feedback to the device on these notifications it can improve its model and become what will accurate so it let know when a package is being delivered but not when a squirrel runs by ?"] "
a package ["Q-084 By providing feedback to the device on these notifications it can improve its model and become more accurate so it will let i know when what is a package being delivered but not when a squirrel runs by ?"] "
alerted ["Q-085 Who providing feedback to the device on these notifications it can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
providing feedback to the device on these notifications ["Q-086 Who can improve its model and become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
By providing feedback to the device on these notifications it can improve its model ["Q-087 Who become more accurate so it will let i know when a package is being delivered but not when a squirrel runs by ?"] "
more accurate ["Q-088 Who will let i know when a package is being delivered but not when a squirrel runs by ?"] "
become more accurate ["Q-089 Who know when a package is being delivered but not when a squirrel runs by ?"] "
a package ["Q-090 Who is being delivered but not when a squirrel runs by ?"] "
Press Release ["Q-091 ]
YouTube the company ["Q-092 By providing the system public camera on what live streams found has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube the company ["Q-093 By providing the system public camera live streams found of what has the company created a demonstration that me can find here Camect Alerts Demo ?"] "
YouTube ["Q-094 By providing the system public camera live streams found that whom has the company created a demonstration of these alerts can find here Camect Alerts Demo ?"] "
a squirrel ["Q-095 What by providing providing public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube ["Q-096 By providing the system public camera live streams found what has the company created of these alerts that me can find here Camect Alerts Demo ?"] "
Camect Alerts Demo ["Q-097 By providing the system public camera live streams found on youtube the company has created what can a demonstration of these alerts that me find ?"] "
a squirrel ["Q-098 Who providing the system public camera live streams found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
public camera live streams ["Q-099 Who found on youtube the company has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
YouTube the company ["Q-0100 Who has created a demonstration of these alerts that me can find here Camect Alerts Demo ?"] "
Press Release ["Q-0101 Who can find here Camect Alerts Demo ?"] "
Press Release ["Q-0102 ]
$299 ["Q-0103 Presently there is an Indiegogo page for Camect where i can pre - order from what a unit for down or with lifetime service that would normally cost ?"] "
lifetime service ["Q-0104 Presently there is an Indiegogo page for Camect where with what can i pre - order a unit for down from the usual price or that would normally cost ?"] "
a unit for $299 ["Q-0105 Presently there is an Indiegogo page for Camect where what can i pre - order for down from the usual price or with lifetime service that would normally cost ?"] "
$1149 ["Q-0106 Who can pre - order a unit for down from the usual price or with lifetime service that would normally cost ?"] "
Press Release ["Q-0107 ]
Press Release ["Q-0108 In what are they expected to ship ?"] "
Press Release ["Q-0109 What are they expected to ship in January 2020 ?"] "
Press Release ["Q-0110 Who are expected to ship in January 2020 ?"] "
$399 price or $549 ["Q-0111 How much are they expected to s N ?"] "
Press Release ["Q-0112 ]
Press Release ["Q-0113 ]
Roger Titcombe OfSTED ["Q-01 Who are right about this ?"] "
Starting GCSEs in Y9 is common. It is a form of gaming performance tables in terms of GCSE Grade 4/5 It is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and STEM A LevelsHowever unless OfSTED penalises schools much more rigorously there will be little change ["Q-02 What is it of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
performance tables ["Q-03 What is it a form of gaming in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
OfSTED penalises schools much more rigorously there will be little change ["Q-04 Who is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming performance tables ["Q-05 Who is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
this ["Q-01 Comment on ofsted criticises 3-year Gcses and low Ebacc entry in about what are new inspection report by Roger Titcombe Ofsted right ?"] "
Roger Titcombe OfSTED ["Q-02 Who are right about this ?"] "
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-03 ]
3-year ["Q-04 ]
students ["Q-05 It is a form of gaming performance tables in terms of Gcse Grade 4/5 to what is it massively damaging in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
post 16 progression especially to Academic ["Q-06 It is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development to what 16 progression especially and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming performance tables ["Q-07 Of what is it a form in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming ["Q-08 It is in what performance tables of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming ["Q-09 It is of what performance tables in terms is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
Starting GCSEs in Y9 ["Q-010 It is a form of gaming performance tables in terms of Gcse Grade 4/5 in what is it massively damaging to students of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
4/5 ["Q-011 It is a form of gaming performance tables in terms of Gcse Grade 4/5 of what is it massively damaging to students in terms deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
OfSTED penalises schools much more rigorously there will be little change ["Q-012 It is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development where 16 progression especially to Academic and Stem A Levelshowever penalises schools much more rigorously there will be little change ?"] "
Starting GCSEs in Y9 is common. It is a form of gaming performance tables in terms of GCSE Grade 4/5 It is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and STEM A LevelsHowever unless OfSTED penalises schools much more rigorously there will be little change ["Q-013 What is it of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
performance tables ["Q-014 What is it a form of gaming in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
16 progression ["Q-015 It is a form of gaming p N tables in terms of Gcse Grade 4/5 what is it massively damaging to students in terms of cognitive development deep learning and ultimately p N especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
OfSTED penalises schools ["Q-016 It is a form of gaming p N tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 p N especially to Academic and Stem A Levelshowever unless Ofsted what p p N N N much more rigorously there will be little change ?"] "
Academic and STEM A LevelsHowever ["Q-017 It is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to what schools much more rigorously there will be ?"] "
OfSTED penalises schools much more rigorously there will be little change ["Q-018 Who is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming performance tables ["Q-019 Who is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
16 ["Q-020 It is a form of gaming p N tables in terms of Gcse Grade 4/5 how much is it massively damaging to students in terms of cognitive development deep learning and ultimately p N progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-021 ]
3-year GCSEs and low EBacc ["Q-022 ]
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-023 ]
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-024 ]
Roger Titcombe OfSTED ["Q-01 Who are right about this ?"] "
Starting GCSEs in Y9 is common. It is a form of gaming performance tables in terms of GCSE Grade 4/5 It is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and STEM A LevelsHowever unless OfSTED penalises schools much more rigorously there will be little change ["Q-02 What is it of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
performance tables ["Q-03 What is it a form of gaming in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
OfSTED penalises schools much more rigorously there will be little change ["Q-04 Who is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming performance tables ["Q-05 Who is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
this ["Q-01 Comment on ofsted criticises 3-year Gcses and low Ebacc entry in about what are new inspection report by Roger Titcombe Ofsted right ?"] "
Roger Titcombe OfSTED ["Q-02 Who are right about this ?"] "
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-03 ]
3-year ["Q-04 ]
students ["Q-05 It is a form of gaming performance tables in terms of Gcse Grade 4/5 to what is it massively damaging in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
post 16 progression especially to Academic ["Q-06 It is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development to what 16 progression especially and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming performance tables ["Q-07 Of what is it a form in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming ["Q-08 It is in what performance tables of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming ["Q-09 It is of what performance tables in terms is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
Starting GCSEs in Y9 ["Q-010 It is a form of gaming performance tables in terms of Gcse Grade 4/5 in what is it massively damaging to students of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
4/5 ["Q-011 It is a form of gaming performance tables in terms of Gcse Grade 4/5 of what is it massively damaging to students in terms deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
OfSTED penalises schools much more rigorously there will be little change ["Q-012 It is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development where 16 progression especially to Academic and Stem A Levelshowever penalises schools much more rigorously there will be little change ?"] "
Starting GCSEs in Y9 is common. It is a form of gaming performance tables in terms of GCSE Grade 4/5 It is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and STEM A LevelsHowever unless OfSTED penalises schools much more rigorously there will be little change ["Q-013 What is it of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
performance tables ["Q-014 What is it a form of gaming in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
16 progression ["Q-015 It is a form of gaming p N tables in terms of Gcse Grade 4/5 what is it massively damaging to students in terms of cognitive development deep learning and ultimately p N especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
OfSTED penalises schools ["Q-016 It is a form of gaming p N tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 p N especially to Academic and Stem A Levelshowever unless Ofsted what p p N N N much more rigorously there will be little change ?"] "
Academic and STEM A LevelsHowever ["Q-017 It is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to what schools much more rigorously there will be ?"] "
OfSTED penalises schools much more rigorously there will be little change ["Q-018 Who is a form of gaming performance tables in terms of Gcse Grade 4/5 it is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
gaming performance tables ["Q-019 Who is massively damaging to students in terms of cognitive development deep learning and ultimately post 16 progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
16 ["Q-020 It is a form of gaming p N tables in terms of Gcse Grade 4/5 how much is it massively damaging to students in terms of cognitive development deep learning and ultimately p N progression especially to Academic and Stem A Levelshowever unless Ofsted penalises schools much more rigorously there will be little change ?"] "
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-021 ]
3-year GCSEs and low EBacc ["Q-022 ]
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-023 ]
Seehttps//rogertitcombelearningmatters.wordpress.com/2015/12/20/the-unintended-consequences-of-the-school-testing-regime-by-professor-alastair-sharp/ ["Q-024 ]
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage ["Q-01 What J technologies \u00bb hat eine Deep - learning - plattform entwickelt die Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
Deep-Learning-Plattform entwickelt ["Q-01 Ein Baukasten f\u00fcr Deep Learning Das Eth - spin - off \u00ab Mirage technologies \u00bb hat eine und what Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln ?"] "
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage ["Q-02 What J technologies \u00bb hat eine Deep - learning - plattform entwickelt die Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage Technologies\u00bb hat eine Deep-Learning-Plattform entwickelt ["Q-03 Deep Learning Das Eth - spin - off \u00ab Mirage technologies \u00bb hat e J die Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage Technologies\u00bb hat eine Deep-Learning-Plattform entwickelt ["Q-04 Deep Learning Das Eth - spin - off \u00ab Mirage technologies \u00bb hat eine Deep - learning - plattform entwickelt d J und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
zu optimieren ["Q-05 ]
zu optimieren ["Q-06 ]
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage ["Q-01 What J technologies \u00bb hat eine Deep - learning - plattform entwickelt die Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
Deep-Learning-Plattform entwickelt ["Q-01 Ein Baukasten f\u00fcr Deep Learning Das Eth - spin - off \u00ab Mirage technologies \u00bb hat eine und what Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln ?"] "
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage ["Q-02 What J technologies \u00bb hat eine Deep - learning - plattform entwickelt die Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage Technologies\u00bb hat eine Deep-Learning-Plattform entwickelt ["Q-03 Deep Learning Das Eth - spin - off \u00ab Mirage technologies \u00bb hat e J die Start - ups und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
Ein Baukasten f\u00fcr Deep Learning Das ETH-Spin-off \u00abMirage Technologies\u00bb hat eine Deep-Learning-Plattform entwickelt ["Q-04 Deep Learning Das Eth - spin - off \u00ab Mirage technologies \u00bb hat eine Deep - learning - plattform entwickelt d J und Unternehmen helfen soll ihre Produkte schneller zu entwickeln und zu optimieren ?"] "
zu optimieren ["Q-05 ]
zu optimieren ["Q-06 ]
Machine Learning Kalifornien ["Q-01 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-02 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Deep Learning KI ["Q-03 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
einem Porno und Obama der Trump beleidigt Kalifornien ["Q-01 In what will machine Learning Kalifornien gegen Deepfake - pornografie vorgehen Gal Gadot will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Gal Gadot ["Q-02 Will Machine Learning Kalifornien gegen in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-03 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-04 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gegen mit Hilfe Von Ki g J ?"] "
Machine Learning Kalifornien ["Q-05 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-06 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-07 ]
Gal Gadot ["Q-08 ]
Deep Learning KI ["Q-09 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-010 ]
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-011 ]
Machine Learning Kalifornien ["Q-01 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-02 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Deep Learning KI ["Q-03 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
einem Porno und Obama der Trump beleidigt Kalifornien ["Q-01 In what will machine Learning Kalifornien gegen Deepfake - pornografie vorgehen Gal Gadot will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Gal Gadot ["Q-02 Will Machine Learning Kalifornien gegen in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-03 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-04 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gegen mit Hilfe Von Ki g J ?"] "
Machine Learning Kalifornien ["Q-05 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-06 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-07 ]
Gal Gadot ["Q-08 ]
Deep Learning KI ["Q-09 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-010 ]
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-011 ]
new W-2200 Cascade Lake-X Xeon chips ["Q-01 What did Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro Intel ["Q-02 Who launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-03 Who should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-04 Who be planning to refresh the machine in the near future ?"] "
Intel Xeon-W chips ["Q-05 Who could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
18 AVX 512 ["Q-06 How much enabled cores in the new w-2200 chips along with up to 48 Pcie lanes Turbo Boost Max 3 ?"] "
Intel vPro ["Q-07 Where are the chips similar to Intels x - series chips but for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
The chips ["Q-08 Who are similar to Intels x - series chips but with Intel vpro for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
Intel ["Q-09 Who offer 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-10 Who rendering 97 % faster 4k video editing and 2 ?"] "
Intel Deep Learning Boost ["Q-11 What is Intel introducing new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel ["Q-12 Who is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel is introducing a new more affordable pricing structure for the updated chips ["Q-13 Who dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
50 percent ["Q-14 Who compared to prior - generation Xeon chips ?"] "
cost ["Q-15 What could the pricing cuts drive of future imac Pro models down should Apple pass those savings along to consumers ?"] "
The pricing cuts ["Q-16 Who could drive the cost of future imac Pro models down should Apple pass those savings along to consumers ?"] "
iMac Pro models ["Q-17 Who down should Apple pass those savings along to consumers ?"] "
2017 ["Q-18 When did Apple released the imac Pro and has nt updated it since then so its due for a refresh ?"] "
the iMac Pro ["Q-19 What did Apple released in 2017 and has nt updated it since then so its due for a refresh ?"] "
Apple ["Q-20 Who released the imac Pro in 2017 and has nt updated it since then so its due for a refresh ?"] "
iMac Pro ["Q-21 Who updated it since then so its due for a refresh ?"] "
no rumors that an updated model ["Q-22 Who is in the works but you often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
no rumors ["Q-23 Who often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
other hardware ["Q-24 Who could still come in a 2019 update ?"] "
W-2200 chips ["Q-25 What does Intel says will be available starting in November ?"] "
Intel ["Q-26 Who says the new Xeon W-2200 chips will be available starting in November ?"] "
Intel says the new Xeon W-2200 chips ["Q-27 Who will be available starting in November ?"] "
iMac Pro ["Q-01 For what did Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable should Apple be planning to refresh the machine in the near future ?"] "
Apple be planning to refresh the machine in the near future ["Q-02 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should in what be Apple planning to refresh the machine ?"] "
new W-2200 Cascade Lake-X Xeon chips ["Q-03 What did Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-04 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for what should a new imac Pro Apple be planning to refresh the machine in the near future ?"] "
Apple ["Q-05 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should what be Apple planning to refresh the machine in the near future ?"] "
machine ["Q-06 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should what be Apple planning to refresh in the near future ?"] "
Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro Intel ["Q-07 Who launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-08 Who should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro should Apple ["Q-09 Who be planning to refresh the machine in the near future ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-010 ]
Apple ["Q-011 Right now for what custom Intel Xeon - w chips imac Pro models but could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
iMac Pro models ["Q-012 Right now Apple uses custom Intel Xeon - w chips for its of what could imac Pro models but use a stock version or a custom version ?"] "
Intel Xeon-W chips ["Q-013 Right now Apple what N for its imac Pro models but could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
iMac Pro models ["Q-014 Right now Apple uses custom Intel Xeon - w chips for its what could imac Pro models but use of the W-2200 Xeon chips or a custom version ?"] "
Intel Xeon-W chips ["Q-015 Who could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-016 ]
18 AVX 512 ["Q-017 How much enabled cores in the new w-2200 chips along with up to 48 Pcie lanes Turbo Boost Max 3 ?"] "
chips will be available starting in November.Tag IntelThis article "Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro" ["Q-018 ]
Chips Appropriate for an Updated iMac Pro" ["Q-019 ]
Intels X-Series chips ["Q-020 To what are the chips similar but with Intel vpro for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
1TB ECC RAM VROC ["Q-021 To what are the chips similar to Intels x - series chips but with Intel vpro for support for up and Ras ( reliability availability and serviceability ) features ?"] "
Intel vPro ["Q-022 Where are the chips similar to Intels x - series chips but for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
support ["Q-023 For what are the chips similar to Intels x - series chips but with Intel vpro for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
The chips ["Q-024 Who are similar to Intels x - series chips but with Intel vpro for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
chips will be available starting in November.Tag IntelThis article "Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro" ["Q-025 ]
Intels X-Series chips ["Q-026 According to Intel its what new chips o N faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
97% ["Q-027 According to Intel its new chips offer 2x faster 3d what architecture rendering rendering faster 4k video editing and 2 ?"] "
Intel ["Q-028 According to whose 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-029 Who offer 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-030 Who rendering 97 % faster 4k video editing and 2 ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-031 ]
Chips Appropriate for an Updated iMac Pro" ["Q-032 ]
almost 50 percent ["Q-033 Intel is introducing a new more affordable pricing structure for to what the updated chips dropping dropping prices by up to prior - generation Xeon chips ?"] "
50 percent ["Q-034 Intel is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 did percent compared compared ?"] "
updated chips dropping prices ["Q-035 For what is Intel introducing a new more affordable pricing structure by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel Deep Learning Boost) for visual effects motion graphics 3D rendering and more. The chips are similar to Intels X-Series chips but with Intel vPro for support for up to 1TB ECC RAM VROC and RAS (reliability availability and serviceability) features.According to Intel its new chips offer 2x faster 3D architecture rendering 97% faster 4K video editing and 2.1x faster video game compile times.Intel is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent ["Q-036 What is Intel introducing new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
the updated chips dropping prices ["Q-037 Intel is introducing a new more affordable pricing structure for what the updated chips dropping dropping by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel ["Q-038 Who is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel is introducing a new more affordable pricing structure for the updated chips ["Q-039 Who dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
50 percent ["Q-040 Who compared to prior - generation Xeon chips ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-041 ]
Apple pass ["Q-042 The pricing cuts could drive the cost of future imac Pro models down should to what those savings along ?"] "
iMac Pro models down ["Q-043 Of what could the pricing cuts drive the cost down should Apple pass those savings along to consumers ?"] "
cost ["Q-044 What could the pricing cuts drive of future imac Pro models down should Apple pass those savings along to consumers ?"] "
Apple ["Q-045 The pricing cuts could drive the cost of what R pass those savings along to consumers ?"] "
pass those savings ["Q-046 The pricing cuts could drive the cost of future imac Pro models down should apple what p p N N N along to consumers ?"] "
pricing cuts ["Q-047 Who could drive the cost of future imac Pro models down should Apple pass those savings along to consumers ?"] "
iMac Pro models ["Q-048 Who down should Apple pass those savings along to consumers ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-049 ]
2017 ["Q-050 When did Apple released the imac Pro and has nt updated it since then so its due for a refresh ?"] "
iMac Pro models down ["Q-051 Apple released the imac Pro in 2017 so what did and has nt updated it since then due for a refresh ?"] "
a refresh ["Q-052 Apple released the imac Pro in 2017 for what did and has nt updated it since then so its due ?"] "
the iMac Pro ["Q-053 What did Apple released in 2017 and has nt updated it since then so its due for a refresh ?"] "
nt ["Q-054 Apple released the imac Pro in 2017 whom updated since then so its due for a refresh ?"] "
Apple ["Q-055 Who released the imac Pro in 2017 and has nt updated it since then so its due for a refresh ?"] "
iMac Pro ["Q-056 Who updated it since then so its due for a refresh ?"] "
2017 ["Q-057 In how much did Apple released the imac Pro and has nt updated it since then so its due for a refresh ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-058 ]
an updated model is in the works ["Q-059 There are no rumors that in what is an updated model but you often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
minor Mac refreshes ["Q-060 There are no rumors that an updated model is where in the works but you often do nt hear much so upgraded processors and other hardware could still come in a 2019 update ?"] "
2019 update ["Q-061 There are no rumors that an updated model is in the works but you often do nt hear much about minor Mac refreshes so upgraded processors and in what other hardware could still come ?"] "
no rumors that an updated model ["Q-062 Who is in the works but you often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
no rumors ["Q-063 Who often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
upgraded processors and other hardware ["Q-064 Who could still come in a 2019 update ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-065 ]
November ["Q-066 Intel says when will the new Xeon W-2200 chips be available starting ?"] "
new Xeon W-2200 chips ["Q-067 What does Intel says will be available starting in November ?"] "
available starting ["Q-068 Intel says what will the new Xeon W-2200 chips be in November ?"] "
Intel ["Q-069 Who says the new Xeon W-2200 chips will be available starting in November ?"] "
Intel says the new Xeon W-2200 chips ["Q-070 Who will be available starting in November ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-071 ]
Chips Appropriate for an Updated iMac Pro" ["Q-072 ]
Chips Appropriate for an Updated iMac Pro" ["Q-073 ]
new W-2200 Cascade Lake-X Xeon chips ["Q-01 What did Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro Intel ["Q-02 Who launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-03 Who should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-04 Who be planning to refresh the machine in the near future ?"] "
Intel Xeon-W chips ["Q-05 Who could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
18 AVX 512 ["Q-06 How much enabled cores in the new w-2200 chips along with up to 48 Pcie lanes Turbo Boost Max 3 ?"] "
Intel vPro ["Q-07 Where are the chips similar to Intels x - series chips but for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
The chips ["Q-08 Who are similar to Intels x - series chips but with Intel vpro for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
Intel ["Q-09 Who offer 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-10 Who rendering 97 % faster 4k video editing and 2 ?"] "
Intel Deep Learning Boost ["Q-11 What is Intel introducing new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel ["Q-12 Who is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel is introducing a new more affordable pricing structure for the updated chips ["Q-13 Who dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
50 percent ["Q-14 Who compared to prior - generation Xeon chips ?"] "
cost ["Q-15 What could the pricing cuts drive of future imac Pro models down should Apple pass those savings along to consumers ?"] "
The pricing cuts ["Q-16 Who could drive the cost of future imac Pro models down should Apple pass those savings along to consumers ?"] "
iMac Pro models ["Q-17 Who down should Apple pass those savings along to consumers ?"] "
2017 ["Q-18 When did Apple released the imac Pro and has nt updated it since then so its due for a refresh ?"] "
the iMac Pro ["Q-19 What did Apple released in 2017 and has nt updated it since then so its due for a refresh ?"] "
Apple ["Q-20 Who released the imac Pro in 2017 and has nt updated it since then so its due for a refresh ?"] "
iMac Pro ["Q-21 Who updated it since then so its due for a refresh ?"] "
no rumors that an updated model ["Q-22 Who is in the works but you often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
no rumors ["Q-23 Who often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
other hardware ["Q-24 Who could still come in a 2019 update ?"] "
W-2200 chips ["Q-25 What does Intel says will be available starting in November ?"] "
Intel ["Q-26 Who says the new Xeon W-2200 chips will be available starting in November ?"] "
Intel says the new Xeon W-2200 chips ["Q-27 Who will be available starting in November ?"] "
iMac Pro ["Q-01 For what did Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable should Apple be planning to refresh the machine in the near future ?"] "
Apple be planning to refresh the machine in the near future ["Q-02 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should in what be Apple planning to refresh the machine ?"] "
new W-2200 Cascade Lake-X Xeon chips ["Q-03 What did Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-04 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for what should a new imac Pro Apple be planning to refresh the machine in the near future ?"] "
Apple ["Q-05 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should what be Apple planning to refresh the machine in the near future ?"] "
machine ["Q-06 Intel Launches New W-2200 Xeon Chips Appropriate for an Updated imac Pro Intel today launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should what be Apple planning to refresh in the near future ?"] "
Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro Intel ["Q-07 Who launched new W-2200 Cascade Lake - x Xeon chips that are potentially suitable for a new imac Pro should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro ["Q-08 Who should Apple be planning to refresh the machine in the near future ?"] "
iMac Pro should Apple ["Q-09 Who be planning to refresh the machine in the near future ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-010 ]
Apple ["Q-011 Right now for what custom Intel Xeon - w chips imac Pro models but could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
iMac Pro models ["Q-012 Right now Apple uses custom Intel Xeon - w chips for its of what could imac Pro models but use a stock version or a custom version ?"] "
Intel Xeon-W chips ["Q-013 Right now Apple what N for its imac Pro models but could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
iMac Pro models ["Q-014 Right now Apple uses custom Intel Xeon - w chips for its what could imac Pro models but use of the W-2200 Xeon chips or a custom version ?"] "
Intel Xeon-W chips ["Q-015 Who could use a stock version of the W-2200 Xeon chips or a custom version ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-016 ]
18 AVX 512 ["Q-017 How much enabled cores in the new w-2200 chips along with up to 48 Pcie lanes Turbo Boost Max 3 ?"] "
chips will be available starting in November.Tag IntelThis article "Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro" ["Q-018 ]
Chips Appropriate for an Updated iMac Pro" ["Q-019 ]
Intels X-Series chips ["Q-020 To what are the chips similar but with Intel vpro for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
1TB ECC RAM VROC ["Q-021 To what are the chips similar to Intels x - series chips but with Intel vpro for support for up and Ras ( reliability availability and serviceability ) features ?"] "
Intel vPro ["Q-022 Where are the chips similar to Intels x - series chips but for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
support ["Q-023 For what are the chips similar to Intels x - series chips but with Intel vpro for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
The chips ["Q-024 Who are similar to Intels x - series chips but with Intel vpro for support for up to 1 tb Ecc Ram Vroc and Ras ( reliability availability and serviceability ) features ?"] "
chips will be available starting in November.Tag IntelThis article "Intel Launches New W-2200 Xeon Chips Appropriate for an Updated iMac Pro" ["Q-025 ]
Intels X-Series chips ["Q-026 According to Intel its what new chips o N faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
97% ["Q-027 According to Intel its new chips offer 2x faster 3d what architecture rendering rendering faster 4k video editing and 2 ?"] "
Intel ["Q-028 According to whose 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-029 Who offer 2x faster 3d architecture rendering 97 % faster 4k video editing and 2 ?"] "
Intel ["Q-030 Who rendering 97 % faster 4k video editing and 2 ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-031 ]
Chips Appropriate for an Updated iMac Pro" ["Q-032 ]
almost 50 percent ["Q-033 Intel is introducing a new more affordable pricing structure for to what the updated chips dropping dropping prices by up to prior - generation Xeon chips ?"] "
50 percent ["Q-034 Intel is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 did percent compared compared ?"] "
updated chips dropping prices ["Q-035 For what is Intel introducing a new more affordable pricing structure by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel Deep Learning Boost) for visual effects motion graphics 3D rendering and more. The chips are similar to Intels X-Series chips but with Intel vPro for support for up to 1TB ECC RAM VROC and RAS (reliability availability and serviceability) features.According to Intel its new chips offer 2x faster 3D architecture rendering 97% faster 4K video editing and 2.1x faster video game compile times.Intel is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent ["Q-036 What is Intel introducing new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
the updated chips dropping prices ["Q-037 Intel is introducing a new more affordable pricing structure for what the updated chips dropping dropping by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel ["Q-038 Who is introducing a new more affordable pricing structure for the updated chips dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
Intel is introducing a new more affordable pricing structure for the updated chips ["Q-039 Who dropping prices by up to almost 50 percent compared to prior - generation Xeon chips ?"] "
50 percent ["Q-040 Who compared to prior - generation Xeon chips ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-041 ]
Apple pass ["Q-042 The pricing cuts could drive the cost of future imac Pro models down should to what those savings along ?"] "
iMac Pro models down ["Q-043 Of what could the pricing cuts drive the cost down should Apple pass those savings along to consumers ?"] "
cost ["Q-044 What could the pricing cuts drive of future imac Pro models down should Apple pass those savings along to consumers ?"] "
Apple ["Q-045 The pricing cuts could drive the cost of what R pass those savings along to consumers ?"] "
pass those savings ["Q-046 The pricing cuts could drive the cost of future imac Pro models down should apple what p p N N N along to consumers ?"] "
pricing cuts ["Q-047 Who could drive the cost of future imac Pro models down should Apple pass those savings along to consumers ?"] "
iMac Pro models ["Q-048 Who down should Apple pass those savings along to consumers ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-049 ]
2017 ["Q-050 When did Apple released the imac Pro and has nt updated it since then so its due for a refresh ?"] "
iMac Pro models down ["Q-051 Apple released the imac Pro in 2017 so what did and has nt updated it since then due for a refresh ?"] "
a refresh ["Q-052 Apple released the imac Pro in 2017 for what did and has nt updated it since then so its due ?"] "
the iMac Pro ["Q-053 What did Apple released in 2017 and has nt updated it since then so its due for a refresh ?"] "
nt ["Q-054 Apple released the imac Pro in 2017 whom updated since then so its due for a refresh ?"] "
Apple ["Q-055 Who released the imac Pro in 2017 and has nt updated it since then so its due for a refresh ?"] "
iMac Pro ["Q-056 Who updated it since then so its due for a refresh ?"] "
2017 ["Q-057 In how much did Apple released the imac Pro and has nt updated it since then so its due for a refresh ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-058 ]
an updated model is in the works ["Q-059 There are no rumors that in what is an updated model but you often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
minor Mac refreshes ["Q-060 There are no rumors that an updated model is where in the works but you often do nt hear much so upgraded processors and other hardware could still come in a 2019 update ?"] "
2019 update ["Q-061 There are no rumors that an updated model is in the works but you often do nt hear much about minor Mac refreshes so upgraded processors and in what other hardware could still come ?"] "
no rumors that an updated model ["Q-062 Who is in the works but you often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
no rumors ["Q-063 Who often do nt hear much about minor Mac refreshes so upgraded processors and other hardware could still come in a 2019 update ?"] "
upgraded processors and other hardware ["Q-064 Who could still come in a 2019 update ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-065 ]
November ["Q-066 Intel says when will the new Xeon W-2200 chips be available starting ?"] "
new Xeon W-2200 chips ["Q-067 What does Intel says will be available starting in November ?"] "
available starting ["Q-068 Intel says what will the new Xeon W-2200 chips be in November ?"] "
Intel ["Q-069 Who says the new Xeon W-2200 chips will be available starting in November ?"] "
Intel says the new Xeon W-2200 chips ["Q-070 Who will be available starting in November ?"] "
Chips Appropriate for an Updated iMac Pro" ["Q-071 ]
Chips Appropriate for an Updated iMac Pro" ["Q-072 ]
Chips Appropriate for an Updated iMac Pro" ["Q-073 ]
Machine Learning Kalifornien ["Q-01 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-02 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Deep Learning KI ["Q-03 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
einem Porno und Obama der Trump beleidigt Kalifornien ["Q-01 In what will machine Learning Kalifornien gegen Deepfake - pornografie vorgehen Gal Gadot will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Gal Gadot ["Q-02 Will Machine Learning Kalifornien gegen in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-03 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-04 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gegen mit Hilfe Von Ki g J ?"] "
Machine Learning Kalifornien ["Q-05 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-06 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-07 ]
Gal Gadot ["Q-08 ]
Deep Learning KI ["Q-09 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-010 ]
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-011 ]
Machine Learning Kalifornien ["Q-01 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-02 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Deep Learning KI ["Q-03 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
einem Porno und Obama der Trump beleidigt Kalifornien ["Q-01 In what will machine Learning Kalifornien gegen Deepfake - pornografie vorgehen Gal Gadot will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Gal Gadot ["Q-02 Will Machine Learning Kalifornien gegen in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-03 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gef\u00e4lschten Videos vorgehen ?"] "
einem Porno ["Q-04 Machine Learning Kalifornien will gegen Deepfake - pornografie Vorgehen Gal Gadot in what will einem Porno und Obama der Trump beleidigt Kalifornien st\u00e4rker gegen mit Hilfe Von Ki g J ?"] "
Machine Learning Kalifornien ["Q-05 Who will gegen Deepfake - pornografie Vorgehen Gal Gadot in einem Porno und Obama der Trump beleidigt Kalifornien will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien ["Q-06 Who will st\u00e4rker gegen mit Hilfe Von Ki gef\u00e4lschten Videos vorgehen ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-07 ]
Gal Gadot ["Q-08 ]
Deep Learning KI ["Q-09 What N auch eine Einschr\u00e4nkung der Meinungs\u00e4u\u00dferung meinen B\u00fcrgerrechtler ?"] "
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-010 ]
Machine Learning Kalifornien will gegen Deepfake-Pornografie vorgehen Gal Gadot ["Q-011 ]
Material Microstructures ["Q-01 What a conditional Generative Model for predicting predicting from processing methods ?"] "
modelsthe processing-structure relationship ["Q-02 What a conditional Generative Model for predicting Material Microstructures from processing predicting ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-03 Who linking Biswadip Dey A N to the material property - which is the primaryinterest in engineering applications ?"] "
Wei Chen Amit ChakrabortyMicrostructures of a material form the bridge linking processing conditions -which can be controlled to the material property - which is the primaryinterest in engineering applications. Thus a critical task in material designis ["Q-04 Who establishing the processing - structure relationship which requires domainexpertise and techniques that can model the high - dimensional materialmicrostructure ?"] "
high-dimensional materialmicrostructure ["Q-05 What this work proposes that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-06 Who proposes a deep learning based approach that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ["Q-07 Who based as a conditional processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-08 Who develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
ACWGAN-GP ["Q-09 Who given processingcondition ?"] "
GAN ["Q-10 Who is free of feature engineering requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
free of feature engineering ["Q-11 Who requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
GAN ["Q-12 Who is applicable to a wide range of material systems ?"] "
ACWGAN-GP ["Q-13 What you d N ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
GAN ["Q-14 Who demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
GAN ["Q-15 Who using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
Wei Chen Amit ChakrabortyMicrostructures of a material form the bridge linking processing conditions -which can be controlled to the material property - which is the primaryinterest in engineering applications. Thus a critical task in material designis establishing the processing-structure relationship which requires domainexpertise and techniques that can model the high-dimensional materialmicrostructure. This work proposes a deep learning based approach that modelsthe processing-structure relationship as a conditional image synthesis problem.In particular we develop an auxiliary classifier Wasserstein GAN with gradientpenalty (ACWGAN-GP) to synthesize microstructures under a given processingcondition. This approach is free of feature engineering requires modest domainknowledge and is applicable to a wide range of material systems. We demonstratethis approach using the ultra high carbon steel ["Q-16 Who is annotated with a label descr
Wei Chen Amit ["Q-17 Who describing high carbon steel ( U N to ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-18 Whose results show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
Wei Chen Amit ["Q-19 Who show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-20 Who can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-21 Who given cooling method ?"] "
Processing Methods ["Q-01 From what A Conditional Generative Model for predicting predicting Material Microstructures ?"] "
Material Microstructures ["Q-02 What a conditional Generative Model for predicting predicting from processing methods ?"] "
eess ["Q-03 What a conditional Generative Model for predicting Material Microstructures from processing predicting ?"] "
Conditional Generative Model ["Q-04 ]
Conditional Generative Model ["Q-05 ]
Wei Chen Amit ChakrabortyMicrostructures ["Q-06 ]
property ["Q-07 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of to what a material form the bridge linking processing conditions linking - which is the primaryinterest in engineering applications ?"] "
engineering applications ["Q-08 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of in what a material form the bridge linking processing conditions linking to the material property - which is the primaryinterest ?"] "
a material form the bridge linking processing conditions -which ["Q-09 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of what a material form the bridge linking linking -which can be controlled to the material property - which is the primaryinterest in engineering applications ?"] "
Conditional Generative Model ["Q-010 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of what a material form the bridge linking linking processing conditions - N to the material property - which is the primaryinterest in engineering applications ?"] "
Conditional Generative Model ["Q-011 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of what a material form the bridge linking processing conditions linking to the material property - which is in engineering applications ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-012 Who linking Biswadip Dey A N to the material property - which is the primaryinterest in engineering applications ?"] "
A Conditional Generative Model for Predicting Material Microstructures from Processing Methods ["Q-013 ]
processing-structure relationship ["Q-014 Thus a critical task in material designis establishing establishing which requires domainexpertise and techniques that can model the high - dimensional materialmicrostructure ?"] "
domainexpertise ["Q-015 Thus what a critical task in material designis establishing establishing the processing - structure relationship which requires and techniques that can model the high - dimensional materialmicrostructure ?"] "
high-dimensional materialmicrostructure ["Q-016 Thus what a critical task in material designis establishing establishing the processing - structure relationship which requires domainexpertise and techniques that can model ?"] "
critical task in material designis ["Q-017 Who establishing the processing - structure relationship which requires domainexpertise and techniques that can model the high - dimensional materialmicrostructure ?"] "
Conditional Generative Model ["Q-018 ]
a conditional image synthesis problem ["Q-019 This work proposes as what did a deep learning based based processing - structure relationship ?"] "
high-dimensional materialmicrostructure ["Q-020 What this work proposes that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
modelsthe processing-structure relationship ["Q-021 This work proposes did a deep learning based based approach that m J as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-022 Who proposes a deep learning based approach that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-023 Who based as a conditional processing - structure relationship as a conditional image synthesis problem ?"] "
Conditional Generative Model ["Q-024 ]
gradientpenalty ["Q-025 In with what do particular you develop an auxiliary classifier Wasserstein Gan ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
a given processingcondition ["Q-026 In under what do particular you develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize microstructures ?"] "
processing-structure relationship ["Q-027 In what do particular you develop with gradientpenalty ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
processing-structure relationship ["Q-028 In what do particular you develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to s N under a given processingcondition ?"] "
microstructures ["Q-029 In particular you develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize what did microstructures under a given given ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-030 Who develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
ACWGAN-GP ["Q-031 Who given processingcondition ?"] "
A Conditional Generative Model ["Q-032 ]
a wide range ["Q-033 This approach is free of feature engineering requires to what is modest domainknowledge and applicable of material systems ?"] "
feature engineering ["Q-034 Of what is this approach free requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
material systems ["Q-035 This approach is free of feature engineering requires of what is modest domainknowledge and applicable to a wide range ?"] "
modest domainknowledge ["Q-036 This approach is what does free of feature engineering requires and is applicable to a wide range of material systems ?"] "
GAN ["Q-037 Who is free of feature engineering requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
free of feature engineering ["Q-038 Who requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
Wasserstein GAN ["Q-039 Who is applicable to a wide range of material systems ?"] "
Conditional Generative Model ["Q-040 ]
a label describing the cooling method ["Q-041 We demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where with what is eachmicrostructure annotated wassubjected to ?"] "
ACWGAN-GP ["Q-042 What you d N ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
eachmicrostructure ["Q-043 We demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where what is eachmicrostructure annotated with a label describing the cooling method it wassubjected to ?"] "
cooling method ["Q-044 We demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where what is eachmicrostructure annotated with a label describing wassubjected to ?"] "
GAN ["Q-045 Who demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
GAN ["Q-046 Who using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
UHCS) ["Q-047 Who is annotated with a label describing the cooling method it wassubjected to ?"] "
ultra ["Q-048 Who describing high carbon steel ( U N to ?"] "
arXiv1910.02133v1 ["Q-049 ]
ACWGAN-GP ["Q-050 Our results show can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
cooling method ["Q-051 Our results show for what can that acwgan - gp synthesize high - qualitymultiphase microstructures ?"] "
high-qualitymultiphase microstructures ["Q-052 Our results show what can that Acwgan - gp synthesize for a given cooling method ?"] "
high-qualitymultiphase ["Q-053 Our results show that Acwgan - gp can synthesize what did high - qualitymultiphase microstructures for a given given cooling ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-054 Whose results show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
Wei Chen Amit ChakrabortyMicrostructures of a material form the bridge linking processing conditions -which can be controlled to the material property - which is the primaryinterest in engineering applications. Thus a critical task in material designis establishing the processing-structure relationship which requires domainexpertise and techniques that can model the high-dimensional materialmicrostructure. This work proposes a deep learning based approach that modelsthe processing-structure relationship as a conditional image synthesis problem.In particular we develop an auxiliary classifier Wasserstein GAN ["Q-055 Who show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-056 Who can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-057 Who given cooling method ?"] "
Conditional Generative Model ["Q-058 ]
arXiv1910.02133v1 ["Q-059 ]
Material Microstructures ["Q-01 What a conditional Generative Model for predicting predicting from processing methods ?"] "
modelsthe processing-structure relationship ["Q-02 What a conditional Generative Model for predicting Material Microstructures from processing predicting ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-03 Who linking Biswadip Dey A N to the material property - which is the primaryinterest in engineering applications ?"] "
Wei Chen Amit ChakrabortyMicrostructures of a material form the bridge linking processing conditions -which can be controlled to the material property - which is the primaryinterest in engineering applications. Thus a critical task in material designis ["Q-04 Who establishing the processing - structure relationship which requires domainexpertise and techniques that can model the high - dimensional materialmicrostructure ?"] "
high-dimensional materialmicrostructure ["Q-05 What this work proposes that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-06 Who proposes a deep learning based approach that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ["Q-07 Who based as a conditional processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-08 Who develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
ACWGAN-GP ["Q-09 Who given processingcondition ?"] "
GAN ["Q-10 Who is free of feature engineering requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
free of feature engineering ["Q-11 Who requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
GAN ["Q-12 Who is applicable to a wide range of material systems ?"] "
ACWGAN-GP ["Q-13 What you d N ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
GAN ["Q-14 Who demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
GAN ["Q-15 Who using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
Wei Chen Amit ChakrabortyMicrostructures of a material form the bridge linking processing conditions -which can be controlled to the material property - which is the primaryinterest in engineering applications. Thus a critical task in material designis establishing the processing-structure relationship which requires domainexpertise and techniques that can model the high-dimensional materialmicrostructure. This work proposes a deep learning based approach that modelsthe processing-structure relationship as a conditional image synthesis problem.In particular we develop an auxiliary classifier Wasserstein GAN with gradientpenalty (ACWGAN-GP) to synthesize microstructures under a given processingcondition. This approach is free of feature engineering requires modest domainknowledge and is applicable to a wide range of material systems. We demonstratethis approach using the ultra high carbon steel ["Q-16 Who is annotated with a label descr
Wei Chen Amit ["Q-17 Who describing high carbon steel ( U N to ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-18 Whose results show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
Wei Chen Amit ["Q-19 Who show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-20 Who can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-21 Who given cooling method ?"] "
Processing Methods ["Q-01 From what A Conditional Generative Model for predicting predicting Material Microstructures ?"] "
Material Microstructures ["Q-02 What a conditional Generative Model for predicting predicting from processing methods ?"] "
eess ["Q-03 What a conditional Generative Model for predicting Material Microstructures from processing predicting ?"] "
Conditional Generative Model ["Q-04 ]
Conditional Generative Model ["Q-05 ]
Wei Chen Amit ChakrabortyMicrostructures ["Q-06 ]
property ["Q-07 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of to what a material form the bridge linking processing conditions linking - which is the primaryinterest in engineering applications ?"] "
engineering applications ["Q-08 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of in what a material form the bridge linking processing conditions linking to the material property - which is the primaryinterest ?"] "
a material form the bridge linking processing conditions -which ["Q-09 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of what a material form the bridge linking linking -which can be controlled to the material property - which is the primaryinterest in engineering applications ?"] "
Conditional Generative Model ["Q-010 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of what a material form the bridge linking linking processing conditions - N to the material property - which is the primaryinterest in engineering applications ?"] "
Conditional Generative Model ["Q-011 Iv ] ) authors Akshay Iyer Biswadip Dey Arindam Dasgupta Wei Chen Amit Chakrabortymicrostructures of what a material form the bridge linking processing conditions linking to the material property - which is in engineering applications ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-012 Who linking Biswadip Dey A N to the material property - which is the primaryinterest in engineering applications ?"] "
A Conditional Generative Model for Predicting Material Microstructures from Processing Methods ["Q-013 ]
processing-structure relationship ["Q-014 Thus a critical task in material designis establishing establishing which requires domainexpertise and techniques that can model the high - dimensional materialmicrostructure ?"] "
domainexpertise ["Q-015 Thus what a critical task in material designis establishing establishing the processing - structure relationship which requires and techniques that can model the high - dimensional materialmicrostructure ?"] "
high-dimensional materialmicrostructure ["Q-016 Thus what a critical task in material designis establishing establishing the processing - structure relationship which requires domainexpertise and techniques that can model ?"] "
critical task in material designis ["Q-017 Who establishing the processing - structure relationship which requires domainexpertise and techniques that can model the high - dimensional materialmicrostructure ?"] "
Conditional Generative Model ["Q-018 ]
a conditional image synthesis problem ["Q-019 This work proposes as what did a deep learning based based processing - structure relationship ?"] "
high-dimensional materialmicrostructure ["Q-020 What this work proposes that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
modelsthe processing-structure relationship ["Q-021 This work proposes did a deep learning based based approach that m J as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-022 Who proposes a deep learning based approach that modelsthe processing - structure relationship as a conditional image synthesis problem ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-023 Who based as a conditional processing - structure relationship as a conditional image synthesis problem ?"] "
Conditional Generative Model ["Q-024 ]
gradientpenalty ["Q-025 In with what do particular you develop an auxiliary classifier Wasserstein Gan ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
a given processingcondition ["Q-026 In under what do particular you develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize microstructures ?"] "
processing-structure relationship ["Q-027 In what do particular you develop with gradientpenalty ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
processing-structure relationship ["Q-028 In what do particular you develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to s N under a given processingcondition ?"] "
microstructures ["Q-029 In particular you develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize what did microstructures under a given given ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-030 Who develop an auxiliary classifier Wasserstein Gan with gradientpenalty ( Acwgan - gp ) to synthesize microstructures under a given processingcondition ?"] "
ACWGAN-GP ["Q-031 Who given processingcondition ?"] "
A Conditional Generative Model ["Q-032 ]
a wide range ["Q-033 This approach is free of feature engineering requires to what is modest domainknowledge and applicable of material systems ?"] "
feature engineering ["Q-034 Of what is this approach free requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
material systems ["Q-035 This approach is free of feature engineering requires of what is modest domainknowledge and applicable to a wide range ?"] "
modest domainknowledge ["Q-036 This approach is what does free of feature engineering requires and is applicable to a wide range of material systems ?"] "
GAN ["Q-037 Who is free of feature engineering requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
free of feature engineering ["Q-038 Who requires modest domainknowledge and is applicable to a wide range of material systems ?"] "
Wasserstein GAN ["Q-039 Who is applicable to a wide range of material systems ?"] "
Conditional Generative Model ["Q-040 ]
a label describing the cooling method ["Q-041 We demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where with what is eachmicrostructure annotated wassubjected to ?"] "
ACWGAN-GP ["Q-042 What you d N ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
eachmicrostructure ["Q-043 We demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where what is eachmicrostructure annotated with a label describing the cooling method it wassubjected to ?"] "
cooling method ["Q-044 We demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where what is eachmicrostructure annotated with a label describing wassubjected to ?"] "
GAN ["Q-045 Who demonstratethis approach using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
GAN ["Q-046 Who using the ultra high carbon steel ( Uhcs ) database where eachmicrostructure is annotated with a label describing the cooling method it wassubjected to ?"] "
UHCS) ["Q-047 Who is annotated with a label describing the cooling method it wassubjected to ?"] "
ultra ["Q-048 Who describing high carbon steel ( U N to ?"] "
arXiv1910.02133v1 ["Q-049 ]
ACWGAN-GP ["Q-050 Our results show can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
cooling method ["Q-051 Our results show for what can that acwgan - gp synthesize high - qualitymultiphase microstructures ?"] "
high-qualitymultiphase microstructures ["Q-052 Our results show what can that Acwgan - gp synthesize for a given cooling method ?"] "
high-qualitymultiphase ["Q-053 Our results show that Acwgan - gp can synthesize what did high - qualitymultiphase microstructures for a given given cooling ?"] "
Wei Chen Amit ChakrabortyMicrostructures ["Q-054 Whose results show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
Wei Chen Amit ChakrabortyMicrostructures of a material form the bridge linking processing conditions -which can be controlled to the material property - which is the primaryinterest in engineering applications. Thus a critical task in material designis establishing the processing-structure relationship which requires domainexpertise and techniques that can model the high-dimensional materialmicrostructure. This work proposes a deep learning based approach that modelsthe processing-structure relationship as a conditional image synthesis problem.In particular we develop an auxiliary classifier Wasserstein GAN ["Q-055 Who show that Acwgan - gp can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-056 Who can synthesize high - qualitymultiphase microstructures for a given cooling method ?"] "
ACWGAN-GP ["Q-057 Who given cooling method ?"] "
Conditional Generative Model ["Q-058 ]
arXiv1910.02133v1 ["Q-059 ]
Nguyen Vo Kyumin LeeIn ["Q-01 Who fighting against fake news many fact - checking systems comprised ofhuman - based fact - checking sites ( e ?"] "
Nguyen Vo Kyumin LeeIn ["Q-02 Who comprised ofhuman - based fact - checking sites ( e ?"] "
andautomatic detection systems ["Q-03 Who have been developed in recent years ?"] "
fake news ["Q-04 What keep howeveronline users still sharing even when it has been debunked ?"] "
it has been debunked ["Q-05 Howeveronline users still keep sharing fake news even when what has it been debunked ?"] "
Howeveronline users ["Q-06 Who still keep sharing fake news even when it has been debunked ?"] "
Howeveronline users ["Q-07 Who has been debunked ?"] "
early fake news detection ["Q-08 Who may be insufficient and you need anothercomplementary approach to mitigate the spread of misinformation ?"] "
early fake news detection ["Q-09 Who need anothercomplementary approach to mitigate the spread of misinformation ?"] "
Nguyen Vo Kyumin LeeIn ["Q-10 Who combating fake news ?"] "
leverage online users ["Q-11 Who named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online users ["Q-12 Who build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
torefute misinformation ["Q-13 What your analysis reveals that the fact - checkers tend and use formal language ( e ?"] "
fact-checkers ["Q-14 Who tend torefute misinformation and use formal language ( e ?"] "
Our framework ["Q-15 Whose framework successfully generates relevant responses andoutperforms competing models by achieving up to 30 % improvements ?"] "
Fact-checking Language ["Q-01 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-02 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-03 ]
fake news ["Q-04 Cl ] ) authors against what Nguyen Vo Kyumin Leein fighting fighting many fact - checking systems comprised ofhuman - based fact - checking sites ( e ?"] "
ofhuman-based ["Q-05 Cl ] ) authors Nguyen Vo Kyumin Leein fighting against fake news what did many fact - checking systems comprised ( e ?"] "
Nguyen Vo Kyumin LeeIn ["Q-06 Who fighting against fake news many fact - checking systems comprised ofhuman - based fact - checking sites ( e ?"] "
Nguyen Vo Kyumin LeeIn ["Q-07 Who comprised ofhuman - based fact - checking sites ( e ?"] "
Fact-checking Language ["Q-08 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-09 ]
Fact-checking Language ["Q-010 ]
Fact-checking Language ["Q-011 ]
fact-checking sites ["Q-012 Com ) in what have andautomatic detection systems been developed ?"] "
snopes.com and politifact.com ["Q-013 Com ) what have andautomatic detection systems been developed in recent years ?"] "
andautomatic detection systems ["Q-014 Who have been developed in recent years ?"] "
Fact-checking Language ["Q-015 ]
fake news ["Q-016 What keep howeveronline users still sharing even when it has been debunked ?"] "
it has been debunked ["Q-017 Howeveronline users still keep sharing fake news even when what has it been debunked ?"] "
Howeveronline users ["Q-018 Who still keep sharing fake news even when it has been debunked ?"] "
Howeveronline users ["Q-019 Who has been debunked ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-020 ]
misinformation ["Q-021 Itmeans that early fake news detection may be of what insufficient and you need anothercomplementary approach to mitigate the spread ?"] "
we need anothercomplementary approach ["Q-022 Itmeans that early fake news detection may be what insufficient and you n N to mitigate the spread of misinformation ?"] "
insufficient ["Q-023 Itmeans that early fake news detection may be what insufficient and you need anothercomplementary approach to mitigate of misinformation ?"] "
early fake news detection ["Q-024 Who may be insufficient and you need anothercomplementary approach to mitigate the spread of misinformation ?"] "
early fake news detection ["Q-025 Who need anothercomplementary approach to mitigate the spread of misinformation ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-026 ]
text generation ["Q-027 Of what a novel application for combating fake news ?"] "
combating fake news ["Q-028 For what a novel application of text generation fake news ?"] "
fake news ["Q-029 In this paperwe introduce a novel application of what text generation for combating combating ?"] "
Nguyen Vo Kyumin LeeIn ["Q-030 Who combating fake news ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-031 ]
online ["Q-032 Inparticular you ( 1 ) leverage to what did online users named emph { fact - checkers } who citefact - checking sites as credible evidences in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
credible evidences ["Q-033 Inparticular you ( 1 ) leverage as what did online users named emph { fact - checkers } who citefact - checking sites to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online ["Q-034 Inparticular you ( 1 ) leverage in what did online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online ["Q-035 Inparticular you ( 1 ) leverage of what did online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online ["Q-036 Inparticular you ( 1 ) leverage what did online users named emph { fact - checkers } who c N as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
a deep learning framework ["Q-037 Inparticular you ( 1 ) leverage online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) what propose and build to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
and(3 ["Q-038 Inparticular you ( 1 ) leverage online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) what propose and build a deep learning framework to g N withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
emph{fact-checkers} ["Q-039 Inparticular you ( 1 ) leverage online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase ?"] "
leverage online users ["Q-040 Who named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online users ["Q-041 Who build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-042 ]
torefute misinformation ["Q-043 What your analysis reveals that the fact - checkers tend and use formal language ( e ?"] "
fact-checkers ["Q-044 Who tend torefute misinformation and use formal language ( e ?"] "
arXiv1910.02202v1 ["Q-045 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-046 ]
cs ["Q-047 ]
30% improvements ["Q-048 Our framework successfully generates to what relevant responses andoutperforms competing models by achieving competing ?"] "
relevant responses andoutperforms competing models by achieving up to 30% improvements ["Q-049 Our framework successfully generates by what relevant responses andoutperforms competing competing models up to 30 % improvements ?"] "
Our framework ["Q-050 Whose framework successfully generates relevant responses andoutperforms competing models by achieving up to 30 % improvements ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-051 ]
superiority of our ["Q-052 That what Ourqualitative study also confirms of your generated responsescompared with responses generated from the existing models ?"] "
Nguyen Vo Kyumin LeeIn fighting against fake news many fact-checking systems comprised ofhuman-based fact-checking sites (e.g. snopes.com and politifact.com) andautomatic detection systems have been developed in recent years. Howeveronline users still keep sharing fake news even when it has been debunked. Itmeans that early fake news detection may be insufficient and we need anothercomplementary approach to mitigate the spread of misinformation. In this paperwe introduce a novel application of text generation for combating fake news. Inparticular we (1) leverage online users named emph{fact-checkers} who citefact-checking sites as credible evidences to fact-check information in publicdiscourse; (2) analyze linguistic characteristics of fact-checking tweets; and(3) propose and build a deep learning framework to generate responses withfact-checking intention to increase the fact-checkers engagement infact-checking activities. Our analysis reveals that the fact-checkers tend torefute , responses " ["Q-054 Ourqualitative study also confirms with what generated that the superiority of your generated responsescompared from the existing models ?"] "
existing models ["Q-055 Ourqualitative study also confirms from what generated that the superiority of your generated responsescompared with responses responsescompared ?"] "
superiority of our ["Q-056 Ourqualitative study also confirms what generated that the superiority of your generated responsescompared with responses generated from the existing models ?"] "
Ourqualitative study also confirms that the superiority of our ["Q-057 Ourqualitative study also confirms what generated that the superiority of your generated responsescompared with responses generated from the existing responsescompared ?"] "
our ["Q-058 Ourqualitative study also confirms that the superiority of whose generated responsescompared with responses generated from the existing models ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-059 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-060 ]
Nguyen Vo Kyumin LeeIn ["Q-01 Who fighting against fake news many fact - checking systems comprised ofhuman - based fact - checking sites ( e ?"] "
Nguyen Vo Kyumin LeeIn ["Q-02 Who comprised ofhuman - based fact - checking sites ( e ?"] "
andautomatic detection systems ["Q-03 Who have been developed in recent years ?"] "
fake news ["Q-04 What keep howeveronline users still sharing even when it has been debunked ?"] "
it has been debunked ["Q-05 Howeveronline users still keep sharing fake news even when what has it been debunked ?"] "
Howeveronline users ["Q-06 Who still keep sharing fake news even when it has been debunked ?"] "
Howeveronline users ["Q-07 Who has been debunked ?"] "
early fake news detection ["Q-08 Who may be insufficient and you need anothercomplementary approach to mitigate the spread of misinformation ?"] "
early fake news detection ["Q-09 Who need anothercomplementary approach to mitigate the spread of misinformation ?"] "
Nguyen Vo Kyumin LeeIn ["Q-10 Who combating fake news ?"] "
leverage online users ["Q-11 Who named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online users ["Q-12 Who build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
torefute misinformation ["Q-13 What your analysis reveals that the fact - checkers tend and use formal language ( e ?"] "
fact-checkers ["Q-14 Who tend torefute misinformation and use formal language ( e ?"] "
Our framework ["Q-15 Whose framework successfully generates relevant responses andoutperforms competing models by achieving up to 30 % improvements ?"] "
Fact-checking Language ["Q-01 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-02 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-03 ]
fake news ["Q-04 Cl ] ) authors against what Nguyen Vo Kyumin Leein fighting fighting many fact - checking systems comprised ofhuman - based fact - checking sites ( e ?"] "
ofhuman-based ["Q-05 Cl ] ) authors Nguyen Vo Kyumin Leein fighting against fake news what did many fact - checking systems comprised ( e ?"] "
Nguyen Vo Kyumin LeeIn ["Q-06 Who fighting against fake news many fact - checking systems comprised ofhuman - based fact - checking sites ( e ?"] "
Nguyen Vo Kyumin LeeIn ["Q-07 Who comprised ofhuman - based fact - checking sites ( e ?"] "
Fact-checking Language ["Q-08 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-09 ]
Fact-checking Language ["Q-010 ]
Fact-checking Language ["Q-011 ]
fact-checking sites ["Q-012 Com ) in what have andautomatic detection systems been developed ?"] "
snopes.com and politifact.com ["Q-013 Com ) what have andautomatic detection systems been developed in recent years ?"] "
andautomatic detection systems ["Q-014 Who have been developed in recent years ?"] "
Fact-checking Language ["Q-015 ]
fake news ["Q-016 What keep howeveronline users still sharing even when it has been debunked ?"] "
it has been debunked ["Q-017 Howeveronline users still keep sharing fake news even when what has it been debunked ?"] "
Howeveronline users ["Q-018 Who still keep sharing fake news even when it has been debunked ?"] "
Howeveronline users ["Q-019 Who has been debunked ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-020 ]
misinformation ["Q-021 Itmeans that early fake news detection may be of what insufficient and you need anothercomplementary approach to mitigate the spread ?"] "
we need anothercomplementary approach ["Q-022 Itmeans that early fake news detection may be what insufficient and you n N to mitigate the spread of misinformation ?"] "
insufficient ["Q-023 Itmeans that early fake news detection may be what insufficient and you need anothercomplementary approach to mitigate of misinformation ?"] "
early fake news detection ["Q-024 Who may be insufficient and you need anothercomplementary approach to mitigate the spread of misinformation ?"] "
early fake news detection ["Q-025 Who need anothercomplementary approach to mitigate the spread of misinformation ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-026 ]
text generation ["Q-027 Of what a novel application for combating fake news ?"] "
combating fake news ["Q-028 For what a novel application of text generation fake news ?"] "
fake news ["Q-029 In this paperwe introduce a novel application of what text generation for combating combating ?"] "
Nguyen Vo Kyumin LeeIn ["Q-030 Who combating fake news ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-031 ]
online ["Q-032 Inparticular you ( 1 ) leverage to what did online users named emph { fact - checkers } who citefact - checking sites as credible evidences in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
credible evidences ["Q-033 Inparticular you ( 1 ) leverage as what did online users named emph { fact - checkers } who citefact - checking sites to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online ["Q-034 Inparticular you ( 1 ) leverage in what did online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online ["Q-035 Inparticular you ( 1 ) leverage of what did online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online ["Q-036 Inparticular you ( 1 ) leverage what did online users named emph { fact - checkers } who c N as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
a deep learning framework ["Q-037 Inparticular you ( 1 ) leverage online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) what propose and build to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
and(3 ["Q-038 Inparticular you ( 1 ) leverage online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) what propose and build a deep learning framework to g N withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
emph{fact-checkers} ["Q-039 Inparticular you ( 1 ) leverage online users named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase ?"] "
leverage online users ["Q-040 Who named emph { fact - checkers } who citefact - checking sites as credible evidences to fact - check information in publicdiscourse ; ( 2 ) analyze linguistic characteristics of fact - checking tweets ; and ( 3 ) propose and build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
online users ["Q-041 Who build a deep learning framework to generate responses withfact - checking intention to increase the fact - checkers engagement infact - checking activities ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-042 ]
torefute misinformation ["Q-043 What your analysis reveals that the fact - checkers tend and use formal language ( e ?"] "
fact-checkers ["Q-044 Who tend torefute misinformation and use formal language ( e ?"] "
arXiv1910.02202v1 ["Q-045 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-046 ]
cs ["Q-047 ]
30% improvements ["Q-048 Our framework successfully generates to what relevant responses andoutperforms competing models by achieving competing ?"] "
relevant responses andoutperforms competing models by achieving up to 30% improvements ["Q-049 Our framework successfully generates by what relevant responses andoutperforms competing competing models up to 30 % improvements ?"] "
Our framework ["Q-050 Whose framework successfully generates relevant responses andoutperforms competing models by achieving up to 30 % improvements ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-051 ]
superiority of our ["Q-052 That what Ourqualitative study also confirms of your generated responsescompared with responses generated from the existing models ?"] "
Nguyen Vo Kyumin LeeIn fighting against fake news many fact-checking systems comprised ofhuman-based fact-checking sites (e.g. snopes.com and politifact.com) andautomatic detection systems have been developed in recent years. Howeveronline users still keep sharing fake news even when it has been debunked. Itmeans that early fake news detection may be insufficient and we need anothercomplementary approach to mitigate the spread of misinformation. In this paperwe introduce a novel application of text generation for combating fake news. Inparticular we (1) leverage online users named emph{fact-checkers} who citefact-checking sites as credible evidences to fact-check information in publicdiscourse; (2) analyze linguistic characteristics of fact-checking tweets; and(3) propose and build a deep learning framework to generate responses withfact-checking intention to increase the fact-checkers engagement infact-checking activities. Our analysis reveals that the fact-checkers tend torefute , responses " ["Q-054 Ourqualitative study also confirms with what generated that the superiority of your generated responsescompared from the existing models ?"] "
existing models ["Q-055 Ourqualitative study also confirms from what generated that the superiority of your generated responsescompared with responses responsescompared ?"] "
superiority of our ["Q-056 Ourqualitative study also confirms what generated that the superiority of your generated responsescompared with responses generated from the existing models ?"] "
Ourqualitative study also confirms that the superiority of our ["Q-057 Ourqualitative study also confirms what generated that the superiority of your generated responsescompared with responses generated from the existing responsescompared ?"] "
our ["Q-058 Ourqualitative study also confirms that the superiority of whose generated responsescompared with responses generated from the existing models ?"] "
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-059 ]
Learning from Fact-checkers Analysis and Generation of Fact-checking Language ["Q-060 ]
A Case Study ["Q-01 What has fernandez Shouhuai Xudeep Learning been very successful in many application domains ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning ["Q-02 Who has been very successful in many application domains ?"] "
not beensystematically investigated ["Q-03 What does Howeverits usefulness in the context of network intrusion detection has ?"] "
network intrusion detection ["Q-04 Who has not beensystematically investigated ?"] "
Howeverits usefulness ["Q-05 What in this paper you r N on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Gabriel C. ["Q-06 Who report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Deep Neural Networks (DNNs) canoutperform other machine learning based intrusion detection systems whilebeing robust ["Q-07 How much p N show of dynamic Ip addresses ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning has been very successful in many application domains. Howeverits usefulness in the context of network intrusion detection has not beensystematically investigated. In this paper we report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection. We show that Deep Neural Networks (DNNs) canoutperform other machine learning based intrusion detection systems whilebeing robust in the presence of dynamic IP addresses. We also show thatAutoencoders ["Q-08 Who show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D p N of dynamic Ip addresses ?"] "
intrusion detection systems ["Q-09 Who learning based neural Networks ( D N robust in t D p N of dynamic Ip addresses ?"] "
Deep Neural Networks ["Q-10 Who p N that of dynamic Ip addresses ?"] "
Deep Neural Networks ["Q-11 What you also s N can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-12 Who also show thatautoencoders can be effective for network anomaly detection ?"] "
thatAutoencoders ["Q-13 Who can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-01 ]
arXiv1910.02203v1 ["Q-02 ]
Deep Neural Networks ["Q-03 ]
Deep Neural Networks ["Q-04 ]
application domains ["Q-05 In what has fernandez Shouhuai Xudeep Learning been very successful ?"] "
A Case Study ["Q-06 What has fernandez Shouhuai Xudeep Learning been very successful in many application domains ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning ["Q-07 Who has been very successful in many application domains ?"] "
Deep Neural Networks ["Q-08 ]
not beensystematically investigated ["Q-09 What does Howeverits usefulness in the context of network intrusion detection has ?"] "
network intrusion detection ["Q-010 Who has not beensystematically investigated ?"] "
Deep Neural Networks ["Q-011 ]
usingdeep learning ["Q-012 On what in this paper you report a case study for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
supervised network intrusion detection ["Q-013 For what in this paper you report a case study on usingdeep learning and unsupervisednetwork anomaly detection ?"] "
Howeverits ["Q-014 What in this paper you r N on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Gabriel C. ["Q-015 Who report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Deep Neural Networks ["Q-016 ]
whilebeing robust ["Q-017 How much p N show of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-018 We show that Deep Neural Networks ( Dnns ) canoutperform learning other machine learning based intrusion detection systems whilebeing based robust in p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-019 We show that Deep Neural Networks ( Dnns ) canoutperform learning other machine learning based intrusion detection systems whilebeing based robust in t D of dynamic Ip addresses ?"] "
Deep Neural Networks ["Q-020 That what you show ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in the presence of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-021 We show that Deep Neural Networks ( Dnns ) canoutperform in what learning other machine learning based intrusion detection systems whilebeing based robust of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-022 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D of what p p N N ?"] "
intrusion detection systems whilebeing ["Q-023 We show that Deep Neural Networks ( Dnns ) canoutperform what did other machine learning based based in t D p N of dynamic Ip addresses ?"] "
We also show thatAutoencoders ["Q-024 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t t N N N p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-025 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D p p N N N of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-026 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in whose p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-027 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D whose of dynamic Ip addresses ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning has been very successful in many application domains. Howeverits usefulness in the context of network intrusion detection has not beensystematically investigated. In this paper we report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection. We show that Deep Neural Networks (DNNs) canoutperform other machine learning based intrusion detection systems whilebeing robust in the presence of dynamic IP addresses. We also show thatAutoencoders ["Q-028 Who show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D p N of dynamic Ip addresses ?"] "
intrusion detection systems ["Q-029 Who learning based neural Networks ( D N robust in t D p N of dynamic Ip addresses ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning has been very successful in many application domains. Howeverits usefulness in the context of network intrusion detection has not beensystematically investigated. In this paper we report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection. We show that Deep Neural Networks (DNNs ["Q-030 Who p N that of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-031 We show that Deep Neural Networks ( Dnns ) canoutperform t how much learning other machine learning based intrusion detection systems whilebeing based robust in p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-032 We show that Deep Neural Networks ( Dnns ) canoutperform p how much learning other machine learning based intrusion detection systems whilebeing based robust in t D of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-033 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in how much t t N N N p N of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-034 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D how much p p N N N of dynamic Ip addresses ?"] "
A Case Study on Using Deep Learning for Network Intrusion Detection ["Q-035 ]
network anomaly detection ["Q-036 We also show for what can thatautoencoders be effective ?"] "
thatAutoencoders ["Q-037 What you also s N can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-038 Who also show thatautoencoders can be effective for network anomaly detection ?"] "
thatAutoencoders ["Q-039 Who can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-040 ]
Deep Neural Networks ["Q-041 ]
A Case Study ["Q-01 What has fernandez Shouhuai Xudeep Learning been very successful in many application domains ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning ["Q-02 Who has been very successful in many application domains ?"] "
not beensystematically investigated ["Q-03 What does Howeverits usefulness in the context of network intrusion detection has ?"] "
network intrusion detection ["Q-04 Who has not beensystematically investigated ?"] "
Howeverits usefulness ["Q-05 What in this paper you r N on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Gabriel C. ["Q-06 Who report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Deep Neural Networks (DNNs) canoutperform other machine learning based intrusion detection systems whilebeing robust ["Q-07 How much p N show of dynamic Ip addresses ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning has been very successful in many application domains. Howeverits usefulness in the context of network intrusion detection has not beensystematically investigated. In this paper we report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection. We show that Deep Neural Networks (DNNs) canoutperform other machine learning based intrusion detection systems whilebeing robust in the presence of dynamic IP addresses. We also show thatAutoencoders ["Q-08 Who show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D p N of dynamic Ip addresses ?"] "
intrusion detection systems ["Q-09 Who learning based neural Networks ( D N robust in t D p N of dynamic Ip addresses ?"] "
Deep Neural Networks ["Q-10 Who p N that of dynamic Ip addresses ?"] "
Deep Neural Networks ["Q-11 What you also s N can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-12 Who also show thatautoencoders can be effective for network anomaly detection ?"] "
thatAutoencoders ["Q-13 Who can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-01 ]
arXiv1910.02203v1 ["Q-02 ]
Deep Neural Networks ["Q-03 ]
Deep Neural Networks ["Q-04 ]
application domains ["Q-05 In what has fernandez Shouhuai Xudeep Learning been very successful ?"] "
A Case Study ["Q-06 What has fernandez Shouhuai Xudeep Learning been very successful in many application domains ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning ["Q-07 Who has been very successful in many application domains ?"] "
Deep Neural Networks ["Q-08 ]
not beensystematically investigated ["Q-09 What does Howeverits usefulness in the context of network intrusion detection has ?"] "
network intrusion detection ["Q-010 Who has not beensystematically investigated ?"] "
Deep Neural Networks ["Q-011 ]
usingdeep learning ["Q-012 On what in this paper you report a case study for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
supervised network intrusion detection ["Q-013 For what in this paper you report a case study on usingdeep learning and unsupervisednetwork anomaly detection ?"] "
Howeverits ["Q-014 What in this paper you r N on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Gabriel C. ["Q-015 Who report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection ?"] "
Deep Neural Networks ["Q-016 ]
whilebeing robust ["Q-017 How much p N show of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-018 We show that Deep Neural Networks ( Dnns ) canoutperform learning other machine learning based intrusion detection systems whilebeing based robust in p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-019 We show that Deep Neural Networks ( Dnns ) canoutperform learning other machine learning based intrusion detection systems whilebeing based robust in t D of dynamic Ip addresses ?"] "
Deep Neural Networks ["Q-020 That what you show ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in the presence of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-021 We show that Deep Neural Networks ( Dnns ) canoutperform in what learning other machine learning based intrusion detection systems whilebeing based robust of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-022 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D of what p p N N ?"] "
intrusion detection systems whilebeing ["Q-023 We show that Deep Neural Networks ( Dnns ) canoutperform what did other machine learning based based in t D p N of dynamic Ip addresses ?"] "
We also show thatAutoencoders ["Q-024 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t t N N N p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-025 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D p p N N N of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-026 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in whose p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-027 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D whose of dynamic Ip addresses ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning has been very successful in many application domains. Howeverits usefulness in the context of network intrusion detection has not beensystematically investigated. In this paper we report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection. We show that Deep Neural Networks (DNNs) canoutperform other machine learning based intrusion detection systems whilebeing robust in the presence of dynamic IP addresses. We also show thatAutoencoders ["Q-028 Who show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D p N of dynamic Ip addresses ?"] "
intrusion detection systems ["Q-029 Who learning based neural Networks ( D N robust in t D p N of dynamic Ip addresses ?"] "
Gabriel C. Fernandez Shouhuai XuDeep Learning has been very successful in many application domains. Howeverits usefulness in the context of network intrusion detection has not beensystematically investigated. In this paper we report a case study on usingdeep learning for both supervised network intrusion detection and unsupervisednetwork anomaly detection. We show that Deep Neural Networks (DNNs ["Q-030 Who p N that of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-031 We show that Deep Neural Networks ( Dnns ) canoutperform t how much learning other machine learning based intrusion detection systems whilebeing based robust in p N of dynamic Ip addresses ?"] "
thatAutoencoders ["Q-032 We show that Deep Neural Networks ( Dnns ) canoutperform p how much learning other machine learning based intrusion detection systems whilebeing based robust in t D of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-033 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in how much t t N N N p N of dynamic Ip addresses ?"] "
dynamic IP addresses ["Q-034 We show that Deep Neural Networks ( Dnns ) canoutperform other machine learning based intrusion detection systems whilebeing robust in t D how much p p N N N of dynamic Ip addresses ?"] "
A Case Study on Using Deep Learning for Network Intrusion Detection ["Q-035 ]
network anomaly detection ["Q-036 We also show for what can thatautoencoders be effective ?"] "
thatAutoencoders ["Q-037 What you also s N can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-038 Who also show thatautoencoders can be effective for network anomaly detection ?"] "
thatAutoencoders ["Q-039 Who can be effective for network anomaly detection ?"] "
Deep Neural Networks ["Q-040 ]
Deep Neural Networks ["Q-041 ]
useful information ["Q-01 What can Ebertreal - time tweets provide on evolving events andsituations ?"] "
Ray Chen David S. ["Q-02 Who can provide useful information on evolving events andsituations ?"] "
Ray Chen David S. EbertReal ["Q-03 Who evolving events andsituations ?"] "
Geotagged tweets ["Q-04 Who geotagged especially useful as they indicate especially useful as they indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-05 Who indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-06 Who provide geographic context ?"] "
situational awareness ["Q-07 However only for what are a smallportion of tweets geotagged limiting their use ?"] "
Geotagged ["Q-08 However only what are a smallportion of tweets geotagged limiting for situational awareness ?"] "
Ray Chen David S. EbertReal-time tweets can provide useful information on evolving events andsituations. Geotagged tweets are especially useful as they indicate thelocation of origin and provide geographic context. However only a smallportion of tweets ["Q-09 Who are geotagged limiting their use for situational awareness ?"] "
Luke S. Snyder Morteza ["Q-10 Who adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
Luke S. Snyder ["Q-11 Who evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
a visualanalytics system ["Q-12 Who tailored for real - time situational awareness ?"] "
Tweets for Real-time Visual Analytics ["Q-01 ]
City-level Geolocation of Tweets for Real-time Visual Analytics ["Q-02 ]
Tweets for Real-time Visual Analytics ["Q-03 ]
Tweets for Real-time Visual Analytics ["Q-04 ]
Tweets for Real-time Visual Analytics ["Q-05 ]
evolving events andsituations ["Q-06 On what can Ebertreal - time tweets provide useful information ?"] "
useful information ["Q-07 What can Ebertreal - time tweets provide on evolving events andsituations ?"] "
geographic context ["Q-08 Ebertreal - time tweets can provide what useful information on evolving evolving ?"] "
Ray Chen David S. EbertReal ["Q-09 Who can provide useful information on evolving events andsituations ?"] "
Ray Chen David S. EbertReal ["Q-010 Who evolving events andsituations ?"] "
Tweets for Real-time Visual Analytics ["Q-011 ]
Luke S. Snyder ["Q-012 As whom did Geotagged tweets Geotagged especially useful indicate thelocation of origin and provide geographic context ?"] "
origin ["Q-013 Geotagged tweets are especially of what useful as they indicate thelocation and provide geographic context ?"] "
situational awareness ["Q-014 Geotagged tweets are especially what you useful as they J of origin and provide geographic context ?"] "
geographic context ["Q-015 Geotagged tweets are especially useful as they indicate what thelocation of origin and provide ?"] "
Geotagged tweets ["Q-016 Who geotagged especially useful as they indicate especially useful as they indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-017 Who indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-018 Who provide geographic context ?"] "
Tweets for Real-time Visual Analytics ["Q-019 ]
situational awareness ["Q-020 However only for what are a smallportion of tweets geotagged limiting their use ?"] "
Geotagged ["Q-021 However only what are a smallportion of tweets geotagged limiting for situational awareness ?"] "
Ray Chen David S. EbertReal-time tweets can provide useful information on evolving events andsituations. Geotagged tweets are especially useful as they indicate thelocation of origin and provide geographic context. However only a smallportion of tweets ["Q-022 Who are geotagged limiting their use for situational awareness ?"] "
Tweets for Real-time Visual Analytics ["Q-023 ]
city-level geolocation prediction ["Q-024 In this paper you adapt improve for what and evaluate a state - of - the - art deep learningmodel and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
a visualanalytics system ["Q-025 In this paper you adapt improve and evaluate a state - of - the - art deep learningmodel for with what it for real - time situational awareness ?"] "
real-time situational awareness ["Q-026 In this paper you adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate for what did it with a visualanalytics system tailored ?"] "
a state-of-the-art deep learningmodel ["Q-027 In this paper you adapt improve what and evaluate for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
visualanalytics system ["Q-028 In this paper you adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and whom you you N N N with a visualanalytics system tailored for real - time situational awareness ?"] "
Luke S. Snyder Morteza Karimzadeh ["Q-029 Who adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
Luke S. Snyder ["Q-030 Who evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
a visualanalytics system ["Q-031 Who tailored for real - time situational awareness ?"] "
Tweets for Real-time Visual Analytics ["Q-032 ]
City-level Geolocation of Tweets for Real-time Visual Analytics ["Q-033 ]
City-level Geolocation of Tweets for Real-time Visual Analytics ["Q-034 ]
useful information ["Q-01 What can Ebertreal - time tweets provide on evolving events andsituations ?"] "
Ray Chen David S. ["Q-02 Who can provide useful information on evolving events andsituations ?"] "
Ray Chen David S. EbertReal ["Q-03 Who evolving events andsituations ?"] "
Geotagged tweets ["Q-04 Who geotagged especially useful as they indicate especially useful as they indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-05 Who indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-06 Who provide geographic context ?"] "
situational awareness ["Q-07 However only for what are a smallportion of tweets geotagged limiting their use ?"] "
Geotagged ["Q-08 However only what are a smallportion of tweets geotagged limiting for situational awareness ?"] "
Ray Chen David S. EbertReal-time tweets can provide useful information on evolving events andsituations. Geotagged tweets are especially useful as they indicate thelocation of origin and provide geographic context. However only a smallportion of tweets ["Q-09 Who are geotagged limiting their use for situational awareness ?"] "
Luke S. Snyder Morteza ["Q-10 Who adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
Luke S. Snyder ["Q-11 Who evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
a visualanalytics system ["Q-12 Who tailored for real - time situational awareness ?"] "
Tweets for Real-time Visual Analytics ["Q-01 ]
City-level Geolocation of Tweets for Real-time Visual Analytics ["Q-02 ]
Tweets for Real-time Visual Analytics ["Q-03 ]
Tweets for Real-time Visual Analytics ["Q-04 ]
Tweets for Real-time Visual Analytics ["Q-05 ]
evolving events andsituations ["Q-06 On what can Ebertreal - time tweets provide useful information ?"] "
useful information ["Q-07 What can Ebertreal - time tweets provide on evolving events andsituations ?"] "
geographic context ["Q-08 Ebertreal - time tweets can provide what useful information on evolving evolving ?"] "
Ray Chen David S. EbertReal ["Q-09 Who can provide useful information on evolving events andsituations ?"] "
Ray Chen David S. EbertReal ["Q-010 Who evolving events andsituations ?"] "
Tweets for Real-time Visual Analytics ["Q-011 ]
Luke S. Snyder ["Q-012 As whom did Geotagged tweets Geotagged especially useful indicate thelocation of origin and provide geographic context ?"] "
origin ["Q-013 Geotagged tweets are especially of what useful as they indicate thelocation and provide geographic context ?"] "
situational awareness ["Q-014 Geotagged tweets are especially what you useful as they J of origin and provide geographic context ?"] "
geographic context ["Q-015 Geotagged tweets are especially useful as they indicate what thelocation of origin and provide ?"] "
Geotagged tweets ["Q-016 Who geotagged especially useful as they indicate especially useful as they indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-017 Who indicate thelocation of origin and provide geographic context ?"] "
Geotagged tweets ["Q-018 Who provide geographic context ?"] "
Tweets for Real-time Visual Analytics ["Q-019 ]
situational awareness ["Q-020 However only for what are a smallportion of tweets geotagged limiting their use ?"] "
Geotagged ["Q-021 However only what are a smallportion of tweets geotagged limiting for situational awareness ?"] "
Ray Chen David S. EbertReal-time tweets can provide useful information on evolving events andsituations. Geotagged tweets are especially useful as they indicate thelocation of origin and provide geographic context. However only a smallportion of tweets ["Q-022 Who are geotagged limiting their use for situational awareness ?"] "
Tweets for Real-time Visual Analytics ["Q-023 ]
city-level geolocation prediction ["Q-024 In this paper you adapt improve for what and evaluate a state - of - the - art deep learningmodel and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
a visualanalytics system ["Q-025 In this paper you adapt improve and evaluate a state - of - the - art deep learningmodel for with what it for real - time situational awareness ?"] "
real-time situational awareness ["Q-026 In this paper you adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate for what did it with a visualanalytics system tailored ?"] "
a state-of-the-art deep learningmodel ["Q-027 In this paper you adapt improve what and evaluate for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
visualanalytics system ["Q-028 In this paper you adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and whom you you N N N with a visualanalytics system tailored for real - time situational awareness ?"] "
Luke S. Snyder Morteza Karimzadeh ["Q-029 Who adapt improve and evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
Luke S. Snyder ["Q-030 Who evaluate a state - of - the - art deep learningmodel for city - level geolocation prediction and integrate it with a visualanalytics system tailored for real - time situational awareness ?"] "
a visualanalytics system ["Q-031 Who tailored for real - time situational awareness ?"] "
Tweets for Real-time Visual Analytics ["Q-032 ]
City-level Geolocation of Tweets for Real-time Visual Analytics ["Q-033 ]
City-level Geolocation of Tweets for Real-time Visual Analytics ["Q-034 ]
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-01 Who based method for colored transparentobject matting from a single image ?"] "
multiple images ["Q-02 What existing approaches for transparent objectmatting Existing N and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
their applications ["Q-03 What existing approaches for transparent objectmatting often existing multiple images and long processing times which greatlyhinder on real - world transparent objects ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-04 Who existing multiple images and l J p N multiple images and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
a matte ["Q-05 What can the recentlyproposed Tom - net produce for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
TOM-Net ["Q-06 Who can produce a matte for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
extendTOM-Net ["Q-07 What you formulate of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-08 Who formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
coloredtransparent object matting ["Q-09 Who simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
Kenneth WongThis paper proposes a deep learning based method for colored transparentobject matting from a single image. Existing approaches for transparent objectmatting often require multiple images and long processing times which greatlyhinder their applications on real-world transparent objects. The recentlyproposed TOM-Net can produce a matte for a colorless transparent object from asingle image in a single fast feed-forward pass. In this paper we extendTOM-Net to handle colored transparent object by modeling the intrinsic color ofa transparent object with a color filter. We formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework ["Q-10 Who learning this task ?"] "
a large-scale syntheticdataset ["Q-11 What you create for training your network ?"] "
our network ["Q-12 What you create a large - scale syntheticdataset for training ?"] "
TOM-Net ["Q-13 Who create a large - scale syntheticdataset for training your network ?"] "
Colored Transparent Object Matting ["Q-14 What you also c N ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-15 Who also capture a real dataset forevaluation ?"] "
real datasets ["Q-16 Who show promisingresults which demonstrate the effectiveness of your method ?"] "
Colored Transparent Object Matting ["Q-01 ]
Colored Transparent Object Matting ["Q-02 ]
Colored Transparent Object Matting ["Q-03 ]
colored transparentobject matting ["Q-04 Cv ] ) authors Jamal Ahmed Rahim Kwan - yee Kenneth Wongthis paper proposes for what did a deep learning based based method from a single image ?"] "
a single image ["Q-05 Cv ] ) authors Jamal Ahmed Rahim Kwan - yee Kenneth Wongthis paper proposes from what did a deep learning based based method for colored transparentobject matting ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-06 Who based method for colored transparentobject matting from a single image ?"] "
Colored Transparent Object Matting ["Q-07 ]
real-world ["Q-08 On what Existing approaches for transparent objectmatting often existing multiple images and long processing times which greatlyhinder their applications ?"] "
multiple images ["Q-09 What existing approaches for transparent objectmatting Existing N and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
their applications ["Q-010 What existing approaches for transparent objectmatting often existing multiple images and long processing times which greatlyhinder on real - world transparent objects ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-011 Who existing multiple images and l J p N multiple images and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
Colored Transparent Object Matting ["Q-012 ]
a colorless transparent object ["Q-013 For what can the recentlyproposed Tom - net produce a matte from asingle image in a single fast feed - forward pass ?"] "
asingle image ["Q-014 From what can the recentlyproposed Tom - net produce a matte for a colorless transparent object in a single fast feed - forward pass ?"] "
a single fast feed-forward pass ["Q-015 In what can the recentlyproposed Tom - net produce a matte for a colorless transparent object from asingle image ?"] "
a matte ["Q-016 What can the recentlyproposed Tom - net produce for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
TOM-Net ["Q-017 Who can produce a matte for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
Colored Transparent Object Matting ["Q-018 ]
modeling ["Q-019 By what in this paper you extendtom - net to handle colored transparent object intrinsic color ofa transparent object with a color filter ?"] "
colored ["Q-020 In this paper you extendtom - net to handle with what transparent object by modeling modeling the intrinsic color ofa transparent object ?"] "
extendTOM-Net ["Q-021 What in this paper you extendtom - net to h N by modeling the intrinsic color ofa transparent object with a color filter ?"] "
colored ["Q-022 In this paper you extendtom - net to handle what transparent object by modeling modeling with a color filter ?"] "
Colored Transparent Object Matting ["Q-023 ]
extendTOM-Net ["Q-024 Of what you formulate the problem as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
extendTOM-Net ["Q-025 As what you formulate the problem of coloredtransparent object matting object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
a single image ["Q-026 We formulate from what the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field and present a deeplearning framework for learning this task ?"] "
learning this task ["Q-027 We formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from for what a deeplearning framework ?"] "
extendTOM-Net ["Q-028 What you formulate of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
an object mask ["Q-029 We formulate what the problem of coloredtransparent object matting as simultaneously estimating and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
a deeplearning framework ["Q-030 We formulate what the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present for learning this task ?"] "
extendTOM-Net ["Q-031 We formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present what a deeplearning framework for learning learning ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-032 Who formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
coloredtransparent object matting ["Q-033 Who simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
deeplearning framework ["Q-034 Who learning this task ?"] "
Colored Transparent Object Matting ["Q-035 ]
training our network ["Q-036 For what you create a large - scale syntheticdataset ?"] "
a large-scale syntheticdataset ["Q-037 What you create for training your network ?"] "
our network ["Q-038 What you create a large - scale syntheticdataset for training ?"] "
TOM-Net ["Q-039 Who create a large - scale syntheticdataset for training your network ?"] "
Colored Transparent Object Matting ["Q-040 ]
Colored Transparent Object Matting ["Q-041 What you also c N ?"] "
Kenneth WongThis ["Q-042 Who also capture a real dataset forevaluation ?"] "
Colored Transparent Object Matting ["Q-043 ]
our method ["Q-044 Experiments on both synthetic and of what real datasets show promisingresults which demonstrate the effectiveness ?"] "
show promisingresults ["Q-045 Experiments on both synthetic and what real datasets s N which demonstrate the effectiveness of your method ?"] "
effectiveness ["Q-046 Experiments on both synthetic and what real datasets show promisingresults which demonstrate of your method ?"] "
real datasets ["Q-047 Who show promisingresults which demonstrate the effectiveness of your method ?"] "
Colored Transparent Object Matting ["Q-048 ]
Colored Transparent Object Matting ["Q-049 ]
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-01 Who based method for colored transparentobject matting from a single image ?"] "
multiple images ["Q-02 What existing approaches for transparent objectmatting Existing N and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
their applications ["Q-03 What existing approaches for transparent objectmatting often existing multiple images and long processing times which greatlyhinder on real - world transparent objects ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-04 Who existing multiple images and l J p N multiple images and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
a matte ["Q-05 What can the recentlyproposed Tom - net produce for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
TOM-Net ["Q-06 Who can produce a matte for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
extendTOM-Net ["Q-07 What you formulate of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-08 Who formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
coloredtransparent object matting ["Q-09 Who simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
Kenneth WongThis paper proposes a deep learning based method for colored transparentobject matting from a single image. Existing approaches for transparent objectmatting often require multiple images and long processing times which greatlyhinder their applications on real-world transparent objects. The recentlyproposed TOM-Net can produce a matte for a colorless transparent object from asingle image in a single fast feed-forward pass. In this paper we extendTOM-Net to handle colored transparent object by modeling the intrinsic color ofa transparent object with a color filter. We formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework ["Q-10 Who learning this task ?"] "
a large-scale syntheticdataset ["Q-11 What you create for training your network ?"] "
our network ["Q-12 What you create a large - scale syntheticdataset for training ?"] "
TOM-Net ["Q-13 Who create a large - scale syntheticdataset for training your network ?"] "
Colored Transparent Object Matting ["Q-14 What you also c N ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-15 Who also capture a real dataset forevaluation ?"] "
real datasets ["Q-16 Who show promisingresults which demonstrate the effectiveness of your method ?"] "
Colored Transparent Object Matting ["Q-01 ]
Colored Transparent Object Matting ["Q-02 ]
Colored Transparent Object Matting ["Q-03 ]
colored transparentobject matting ["Q-04 Cv ] ) authors Jamal Ahmed Rahim Kwan - yee Kenneth Wongthis paper proposes for what did a deep learning based based method from a single image ?"] "
a single image ["Q-05 Cv ] ) authors Jamal Ahmed Rahim Kwan - yee Kenneth Wongthis paper proposes from what did a deep learning based based method for colored transparentobject matting ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-06 Who based method for colored transparentobject matting from a single image ?"] "
Colored Transparent Object Matting ["Q-07 ]
real-world ["Q-08 On what Existing approaches for transparent objectmatting often existing multiple images and long processing times which greatlyhinder their applications ?"] "
multiple images ["Q-09 What existing approaches for transparent objectmatting Existing N and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
their applications ["Q-010 What existing approaches for transparent objectmatting often existing multiple images and long processing times which greatlyhinder on real - world transparent objects ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-011 Who existing multiple images and l J p N multiple images and long processing times which greatlyhinder their applications on real - world transparent objects ?"] "
Colored Transparent Object Matting ["Q-012 ]
a colorless transparent object ["Q-013 For what can the recentlyproposed Tom - net produce a matte from asingle image in a single fast feed - forward pass ?"] "
asingle image ["Q-014 From what can the recentlyproposed Tom - net produce a matte for a colorless transparent object in a single fast feed - forward pass ?"] "
a single fast feed-forward pass ["Q-015 In what can the recentlyproposed Tom - net produce a matte for a colorless transparent object from asingle image ?"] "
a matte ["Q-016 What can the recentlyproposed Tom - net produce for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
TOM-Net ["Q-017 Who can produce a matte for a colorless transparent object from asingle image in a single fast feed - forward pass ?"] "
Colored Transparent Object Matting ["Q-018 ]
modeling ["Q-019 By what in this paper you extendtom - net to handle colored transparent object intrinsic color ofa transparent object with a color filter ?"] "
colored ["Q-020 In this paper you extendtom - net to handle with what transparent object by modeling modeling the intrinsic color ofa transparent object ?"] "
extendTOM-Net ["Q-021 What in this paper you extendtom - net to h N by modeling the intrinsic color ofa transparent object with a color filter ?"] "
colored ["Q-022 In this paper you extendtom - net to handle what transparent object by modeling modeling with a color filter ?"] "
Colored Transparent Object Matting ["Q-023 ]
extendTOM-Net ["Q-024 Of what you formulate the problem as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
extendTOM-Net ["Q-025 As what you formulate the problem of coloredtransparent object matting object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
a single image ["Q-026 We formulate from what the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field and present a deeplearning framework for learning this task ?"] "
learning this task ["Q-027 We formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from for what a deeplearning framework ?"] "
extendTOM-Net ["Q-028 What you formulate of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
an object mask ["Q-029 We formulate what the problem of coloredtransparent object matting as simultaneously estimating and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
a deeplearning framework ["Q-030 We formulate what the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present for learning this task ?"] "
extendTOM-Net ["Q-031 We formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present what a deeplearning framework for learning learning ?"] "
Jamal Ahmed Rahim Kwan-Yee Kenneth WongThis ["Q-032 Who formulate the problem of coloredtransparent object matting as simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
coloredtransparent object matting ["Q-033 Who simultaneously estimating an object mask a colorfilter and a refractive flow field from a single image and present a deeplearning framework for learning this task ?"] "
deeplearning framework ["Q-034 Who learning this task ?"] "
Colored Transparent Object Matting ["Q-035 ]
training our network ["Q-036 For what you create a large - scale syntheticdataset ?"] "
a large-scale syntheticdataset ["Q-037 What you create for training your network ?"] "
our network ["Q-038 What you create a large - scale syntheticdataset for training ?"] "
TOM-Net ["Q-039 Who create a large - scale syntheticdataset for training your network ?"] "
Colored Transparent Object Matting ["Q-040 ]
Colored Transparent Object Matting ["Q-041 What you also c N ?"] "
Kenneth WongThis ["Q-042 Who also capture a real dataset forevaluation ?"] "
Colored Transparent Object Matting ["Q-043 ]
our method ["Q-044 Experiments on both synthetic and of what real datasets show promisingresults which demonstrate the effectiveness ?"] "
show promisingresults ["Q-045 Experiments on both synthetic and what real datasets s N which demonstrate the effectiveness of your method ?"] "
effectiveness ["Q-046 Experiments on both synthetic and what real datasets show promisingresults which demonstrate of your method ?"] "
real datasets ["Q-047 Who show promisingresults which demonstrate the effectiveness of your method ?"] "
Colored Transparent Object Matting ["Q-048 ]
Colored Transparent Object Matting ["Q-049 ]
Self-supervised Feature Learning for 3D Medical Images ["Q-01 Who playing a Rubiks Cube ?"] "
annotated 3D ["Q-02 However as the annotations of 3d of what are medical data difficult to acquire Thenumber medical images is often not enough to well train thedeep learning networks ?"] "
thenumber ["Q-03 However as the annotations of 3d what are medical data difficult to acquire of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
thedeep learning networks ["Q-04 However as the annotations of 3d medical data are difficult to acquire thenumber of annotated 3d what is medical images often not enough to w R ?"] "
the annotations of 3D medical data ["Q-05 Who are difficult to acquire thenumber of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
3D medical images ["Q-06 Who is often not enough to well train thedeep learning networks ?"] "
theinformation ["Q-07 What the self - supervised learning deeply exploiting exploiting of raw data is one of the potential solutions to loose therequirement of training data ?"] "
The self-supervised learning ["Q-08 Who exploiting theinformation of raw data is one of the potential solutions to loose therequirement of training data ?"] "
raw data ["Q-09 Who is one of the potential solutions to loose therequirement of training data ?"] "
a self-supervisedlearning framework ["Q-10 What in this paper you propose for the volumetric medical images ?"] "
Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-11 Who propose a self - supervisedlearning framework for the volumetric medical images ?"] "
A novel proxy task i.e ["Q-12 What is Rubiks cube recovery formulated to pre - train 3d neural networks ?"] "
pre-train 3D neural networks ["Q-13 What is Rubiks cube recovery formulated to p N neural networks ?"] "
Rubiks cube recovery ["Q-14 Who is formulated to pre - train 3d neural networks ?"] "
pre-train 3D neural networks ["Q-15 How much is Rubiks cube recovery formulated to p N neural networks ?"] "
3D neural networks ["Q-16 Who involves two operations you ?"] "
Authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-17 Who you ?"] "
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ["Q-18 Who fromraw 3d data ?"] "
Hu Kai Ma Yujiu Yang Yefeng ["Q-19 Who e ?"] "
brain tumor segmentation ["Q-20 What you show that ourself - supervised learning can substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ["Q-21 Who is the first work focusing on theself - supervised learning of 3d neural networks ?"] "
Rubiks Cube ["Q-01 Self - supervised Feature Learning for 3d what Medical Images by playing playing ?"] "
Self-supervised Feature Learning for 3D Medical Images ["Q-02 Who playing a Rubiks Cube ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-03 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-04 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-05 ]
deep learning ["Q-06 Cv ] ) authors of what did Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of studies tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
studies tryto ["Q-07 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of of what deep learning increasing increasing number tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
3D volumetric medical data ["Q-08 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of deep learning increasing number of studies tryto for what did computer aided diagnosis systems volumetric medical data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube. (arXiv1910.02241v1 ["Q-09 Cv ] ) authors what did Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed of deep learning increasing number of studies tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
Self-supervised Feature Learning ["Q-010 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of what deep learning increasing increasing of studies tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
Self-supervised Feature Learning ["Q-011 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of what learning deep learning increasing number of studies increasing N aided diagnosis systems for 3d volumetric medical data ?"] "
Self-supervised Feature Learning ["Q-012 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of what learning deep learning increasing number of studies increasing computer a J for 3d volumetric medical data ?"] "
3D volumetric ["Q-013 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of deep learning increasing number of studies tryto for how much did computer aided diagnosis systems volumetric medical data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-014 ]
annotated 3D ["Q-015 However as the annotations of 3d of what are medical data difficult to acquire Thenumber medical images is often not enough to well train thedeep learning networks ?"] "
thenumber ["Q-016 However as the annotations of 3d what are medical data difficult to acquire of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
thedeep learning networks ["Q-017 However as the annotations of 3d medical data are difficult to acquire thenumber of annotated 3d what is medical images often not enough to w R ?"] "
the annotations of 3D medical data ["Q-018 Who are difficult to acquire thenumber of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
3D medical images ["Q-019 Who is often not enough to well train thedeep learning networks ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-020 ]
raw data ["Q-021 Of what the self - supervised learning deeply exploiting exploiting theinformation is one of the potential solutions to loose therequirement of training data ?"] "
potential solutions ["Q-022 The self - supervised learning deeply exploiting theinformation of of what is raw data one to loose therequirement of training data ?"] "
training data ["Q-023 The self - supervised learning deeply exploiting theinformation of of what is raw data one of the potential solutions to loose therequirement ?"] "
theinformation ["Q-024 What the self - supervised learning deeply exploiting exploiting of raw data is one of the potential solutions to loose therequirement of training data ?"] "
annotated 3D medical images ["Q-025 The self - supervised learning deeply exploiting theinformation of what is raw data of the potential solutions to loose therequirement of training data ?"] "
annotated 3D medical images ["Q-026 The self - supervised learning deeply exploiting theinformation of what is raw data one of the potential solutions to l J of training data ?"] "
The self-supervised learning ["Q-027 Who exploiting theinformation of raw data is one of the potential solutions to loose therequirement of training data ?"] "
raw data ["Q-028 Who is one of the potential solutions to loose therequirement of training data ?"] "
one ["Q-029 The self - supervised learning deeply exploiting theinformation of how much is raw data of the potential solutions to loose therequirement of training data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-030 ]
the volumetric medical images ["Q-031 For what in this paper you propose a self - supervisedlearning framework ?"] "
a self-supervisedlearning framework ["Q-032 What in this paper you propose for the volumetric medical images ?"] "
Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-033 Who propose a self - supervisedlearning framework for the volumetric medical images ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-034 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-035 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-036 ]
A novel proxy task i.e ["Q-037 What is Rubiks cube recovery formulated to pre - train 3d neural networks ?"] "
pre-train 3D ["Q-038 What is Rubiks cube recovery formulated to p N neural networks ?"] "
Rubiks cube recovery ["Q-039 Who is formulated to pre - train 3d neural networks ?"] "
pre-train 3D neural networks ["Q-040 How much is Rubiks cube recovery formulated to p N neural networks ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-041 ]
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-042 The proxytask what you you N N N you ?"] "
3D neural networks ["Q-043 Who involves two operations you ?"] "
Authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-044 Who you ?"] "
arXiv1910.02241v1 ["Q-045 The proxytask how much you you N N N operations you ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-046 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-047 ]
3D data ["Q-048 Cube rearrangement and cube rotation whichenforce networks to learn translational and what rotational invariant features f J ?"] "
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ["Q-049 Who fromraw 3d data ?"] "
two operations ["Q-050 Cube rearrangement and cube rotation whichenforce networks to learn translational and how much rotational invariant features f J data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-051 ]
thepre-trained network ["Q-052 Compared to the train - from - scratch strategy fine - tuning from on what to a better accuracy e ?"] "
Hu Kai Ma Yujiu Yang Yefeng ["Q-053 Who e ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-054 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-055 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-056 ]
ourself-supervised learning approach ["Q-057 That what you show can substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
3Ddeep learning networks ["Q-058 We show that of what ourself - supervised learning approach learning substantially boost the accuracies on the volumetric medical datasets without using extradata ?"] "
volumetric medical datasets ["Q-059 We show that on what ourself - supervised learning approach learning substantially boost the accuracies of 3ddeep learning networks without using extradata ?"] "
using extradata ["Q-060 We show that without what ourself - supervised learning approach learning substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets ?"] "
brain tumor segmentation ["Q-061 What you show that ourself - supervised learning can substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
3Ddeep ["Q-062 We show that what ourself - supervised learning approach learning substantially boost of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
3Ddeep learning networks ["Q-063 We show that what ourself - supervised learning approach learning substantially boost the accuracies of 3ddeep learning on the volumetric medical datasets without using extradata ?"] "
extradata ["Q-064 We show that ourself - supervised learning approach can substantially boost the accuracies of 3ddeep learning networks on what the volumetric medical datasets without using using ?"] "
ourself-supervised learning approach can substantially boost the accuracies of 3Ddeep ["Q-065 We show that of how much ourself - supervised learning approach learning substantially boost the accuracies learning networks on the volumetric medical datasets without using extradata ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-066 ]
theself-supervised learning ["Q-067 To your on what is best knowledge this the first work focusing of 3d neural networks ?"] "
first work focusing ["Q-068 To your best knowledge this is of what on theself - supervised learning neural networks ?"] "
first work focusing ["Q-069 To your what is best knowledge this on theself - supervised learning of 3d neural networks ?"] "
Hu Kai Ma Yujiu Yang Yefeng ["Q-070 Who is the first work focusing on theself - supervised learning of 3d neural networks ?"] "
first work focusing ["Q-071 To your best knowledge this is of how much on theself - supervised learning neural networks ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-072 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-073 ]
Self-supervised Feature Learning for 3D Medical Images ["Q-01 Who playing a Rubiks Cube ?"] "
annotated 3D ["Q-02 However as the annotations of 3d of what are medical data difficult to acquire Thenumber medical images is often not enough to well train thedeep learning networks ?"] "
thenumber ["Q-03 However as the annotations of 3d what are medical data difficult to acquire of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
thedeep learning networks ["Q-04 However as the annotations of 3d medical data are difficult to acquire thenumber of annotated 3d what is medical images often not enough to w R ?"] "
the annotations of 3D medical data ["Q-05 Who are difficult to acquire thenumber of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
3D medical images ["Q-06 Who is often not enough to well train thedeep learning networks ?"] "
theinformation ["Q-07 What the self - supervised learning deeply exploiting exploiting of raw data is one of the potential solutions to loose therequirement of training data ?"] "
The self-supervised learning ["Q-08 Who exploiting theinformation of raw data is one of the potential solutions to loose therequirement of training data ?"] "
raw data ["Q-09 Who is one of the potential solutions to loose therequirement of training data ?"] "
a self-supervisedlearning framework ["Q-10 What in this paper you propose for the volumetric medical images ?"] "
Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-11 Who propose a self - supervisedlearning framework for the volumetric medical images ?"] "
A novel proxy task i.e ["Q-12 What is Rubiks cube recovery formulated to pre - train 3d neural networks ?"] "
pre-train 3D neural networks ["Q-13 What is Rubiks cube recovery formulated to p N neural networks ?"] "
Rubiks cube recovery ["Q-14 Who is formulated to pre - train 3d neural networks ?"] "
pre-train 3D neural networks ["Q-15 How much is Rubiks cube recovery formulated to p N neural networks ?"] "
3D neural networks ["Q-16 Who involves two operations you ?"] "
Authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-17 Who you ?"] "
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ["Q-18 Who fromraw 3d data ?"] "
Hu Kai Ma Yujiu Yang Yefeng ["Q-19 Who e ?"] "
brain tumor segmentation ["Q-20 What you show that ourself - supervised learning can substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ["Q-21 Who is the first work focusing on theself - supervised learning of 3d neural networks ?"] "
Rubiks Cube ["Q-01 Self - supervised Feature Learning for 3d what Medical Images by playing playing ?"] "
Self-supervised Feature Learning for 3D Medical Images ["Q-02 Who playing a Rubiks Cube ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-03 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-04 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-05 ]
deep learning ["Q-06 Cv ] ) authors of what did Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of studies tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
studies tryto ["Q-07 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of of what deep learning increasing increasing number tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
3D volumetric medical data ["Q-08 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of deep learning increasing number of studies tryto for what did computer aided diagnosis systems volumetric medical data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube. (arXiv1910.02241v1 ["Q-09 Cv ] ) authors what did Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed of deep learning increasing number of studies tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
Self-supervised Feature Learning ["Q-010 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of what deep learning increasing increasing of studies tryto build computer aided diagnosis systems for 3d volumetric medical data ?"] "
Self-supervised Feature Learning ["Q-011 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of what learning deep learning increasing number of studies increasing N aided diagnosis systems for 3d volumetric medical data ?"] "
Self-supervised Feature Learning ["Q-012 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of what learning deep learning increasing number of studies increasing computer a J for 3d volumetric medical data ?"] "
3D volumetric ["Q-013 Cv ] ) authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng zhengwitnessed the development of deep learning increasing number of studies tryto for how much did computer aided diagnosis systems volumetric medical data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-014 ]
annotated 3D ["Q-015 However as the annotations of 3d of what are medical data difficult to acquire Thenumber medical images is often not enough to well train thedeep learning networks ?"] "
thenumber ["Q-016 However as the annotations of 3d what are medical data difficult to acquire of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
thedeep learning networks ["Q-017 However as the annotations of 3d medical data are difficult to acquire thenumber of annotated 3d what is medical images often not enough to w R ?"] "
the annotations of 3D medical data ["Q-018 Who are difficult to acquire thenumber of annotated 3d medical images is often not enough to well train thedeep learning networks ?"] "
3D medical images ["Q-019 Who is often not enough to well train thedeep learning networks ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-020 ]
raw data ["Q-021 Of what the self - supervised learning deeply exploiting exploiting theinformation is one of the potential solutions to loose therequirement of training data ?"] "
potential solutions ["Q-022 The self - supervised learning deeply exploiting theinformation of of what is raw data one to loose therequirement of training data ?"] "
training data ["Q-023 The self - supervised learning deeply exploiting theinformation of of what is raw data one of the potential solutions to loose therequirement ?"] "
theinformation ["Q-024 What the self - supervised learning deeply exploiting exploiting of raw data is one of the potential solutions to loose therequirement of training data ?"] "
annotated 3D medical images ["Q-025 The self - supervised learning deeply exploiting theinformation of what is raw data of the potential solutions to loose therequirement of training data ?"] "
annotated 3D medical images ["Q-026 The self - supervised learning deeply exploiting theinformation of what is raw data one of the potential solutions to l J of training data ?"] "
The self-supervised learning ["Q-027 Who exploiting theinformation of raw data is one of the potential solutions to loose therequirement of training data ?"] "
raw data ["Q-028 Who is one of the potential solutions to loose therequirement of training data ?"] "
one ["Q-029 The self - supervised learning deeply exploiting theinformation of how much is raw data of the potential solutions to loose therequirement of training data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-030 ]
the volumetric medical images ["Q-031 For what in this paper you propose a self - supervisedlearning framework ?"] "
a self-supervisedlearning framework ["Q-032 What in this paper you propose for the volumetric medical images ?"] "
Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-033 Who propose a self - supervisedlearning framework for the volumetric medical images ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-034 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-035 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-036 ]
A novel proxy task i.e ["Q-037 What is Rubiks cube recovery formulated to pre - train 3d neural networks ?"] "
pre-train 3D ["Q-038 What is Rubiks cube recovery formulated to p N neural networks ?"] "
Rubiks cube recovery ["Q-039 Who is formulated to pre - train 3d neural networks ?"] "
pre-train 3D neural networks ["Q-040 How much is Rubiks cube recovery formulated to p N neural networks ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-041 ]
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-042 The proxytask what you you N N N you ?"] "
3D neural networks ["Q-043 Who involves two operations you ?"] "
Authors Xinrui Zhuang Yuexiang Li Yifan Hu Kai Ma Yujiu Yang Yefeng ZhengWitnessed ["Q-044 Who you ?"] "
arXiv1910.02241v1 ["Q-045 The proxytask how much you you N N N operations you ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-046 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-047 ]
3D data ["Q-048 Cube rearrangement and cube rotation whichenforce networks to learn translational and what rotational invariant features f J ?"] "
Li Yifan Hu Kai Ma Yujiu Yang Yefeng ["Q-049 Who fromraw 3d data ?"] "
two operations ["Q-050 Cube rearrangement and cube rotation whichenforce networks to learn translational and how much rotational invariant features f J data ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-051 ]
thepre-trained network ["Q-052 Compared to the train - from - scratch strategy fine - tuning from on what to a better accuracy e ?"] "
Hu Kai Ma Yujiu Yang Yefeng ["Q-053 Who e ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-054 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-055 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-056 ]
ourself-supervised learning approach ["Q-057 That what you show can substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
3Ddeep learning networks ["Q-058 We show that of what ourself - supervised learning approach learning substantially boost the accuracies on the volumetric medical datasets without using extradata ?"] "
volumetric medical datasets ["Q-059 We show that on what ourself - supervised learning approach learning substantially boost the accuracies of 3ddeep learning networks without using extradata ?"] "
using extradata ["Q-060 We show that without what ourself - supervised learning approach learning substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets ?"] "
brain tumor segmentation ["Q-061 What you show that ourself - supervised learning can substantially boost the accuracies of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
3Ddeep ["Q-062 We show that what ourself - supervised learning approach learning substantially boost of 3ddeep learning networks on the volumetric medical datasets without using extradata ?"] "
3Ddeep learning networks ["Q-063 We show that what ourself - supervised learning approach learning substantially boost the accuracies of 3ddeep learning on the volumetric medical datasets without using extradata ?"] "
extradata ["Q-064 We show that ourself - supervised learning approach can substantially boost the accuracies of 3ddeep learning networks on what the volumetric medical datasets without using using ?"] "
ourself-supervised learning approach can substantially boost the accuracies of 3Ddeep ["Q-065 We show that of how much ourself - supervised learning approach learning substantially boost the accuracies learning networks on the volumetric medical datasets without using extradata ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-066 ]
theself-supervised learning ["Q-067 To your on what is best knowledge this the first work focusing of 3d neural networks ?"] "
first work focusing ["Q-068 To your best knowledge this is of what on theself - supervised learning neural networks ?"] "
first work focusing ["Q-069 To your what is best knowledge this on theself - supervised learning of 3d neural networks ?"] "
Hu Kai Ma Yujiu Yang Yefeng ["Q-070 Who is the first work focusing on theself - supervised learning of 3d neural networks ?"] "
first work focusing ["Q-071 To your best knowledge this is of how much on theself - supervised learning neural networks ?"] "
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-072 ]
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubiks Cube ["Q-073 ]
Zhang Jun ZhouBayesian ["Q-01 Who is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
SGLD ["Q-02 Where do previous theoretical studies have shownvarious appealing properties from the convergence propertiesto the generalization bounds ?"] "
appealing properties ["Q-03 What do previous theoretical studies have of Sgld ranging from the convergence propertiesto the generalization bounds ?"] "
preventing themembership attack ["Q-04 What in this paper you study of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-05 Who study the properties of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-06 Who is used for training a given Dnn model has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-07 Who training attack w W aims to d V as a commonthreat against deep learning algorithms ?"] "
Zhang Jun ZhouBayesian ["Q-08 Who build a theoreticalframework to analyze the information leakage ( w ?"] "
amodel ["Q-09 Who trained using Sgld ?"] "
SGLD ["Q-10 Where did based on this framework you based canprevent the information leakage of the training dataset to a certain extent ?"] "
theoretical analysis ["Q-11 Who can be naturally extended to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
different datasets and models ["Q-12 Who verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults on different datasets and models verify our theoretical findings ["Q-13 Who andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
SGLD algorithm ["Q-14 Who can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
leakage butalso ["Q-15 Who improve the generalization ability of the Dnn models in real - worldapplications ?"] "
StochasticGradient Langevin Dynamics~(SGLD) is an effective method to enable Bayesiandeep learning on large-scale datasets. Previous theoretical studies have shownvarious appealing properties of SGLD ranging from the convergence propertiesto the generalization bounds. In this paper we study the properties of SGLDfrom a novel perspective of membership privacy protection (i.e. preventing themembership attack). The membership attack which aims to determine whether aspecific sample is used for training a given DNN model has emerged as a commonthreat against deep learning algorithms. To this end we build a theoreticalframework to analyze the information leakage (w.r.t. the training dataset) of amodel trained using SGLD. Based on this framework we demonstrate that SGLD canprevent the information leakage of the training dataset to a certain extent.Moreover our theoretical analysis can be naturally extended to other types ofStochastic Gradient Markov Chain Monte Carlo
StochasticGradient Langevin Dynamics~(SGLD ["Q-02 ]
StochasticGradient Langevin Dynamics~(SGLD ["Q-03 ]
intrinsic ["Q-04 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian as what is deep learning recently regarded tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. (arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-05 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian tocharacterize what is deep learning recently regarded as an intrinsic way of deep neural networks~ ( Dnns ) ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics ["Q-06 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian is deep learning recently regarded as an intrinsic way tocharacterize the weight uncertainty ( Dnns ) ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics ["Q-07 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian what is deep learning as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
Zhang Jun ZhouBayesian ["Q-08 Who is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-09 ]
effective method ["Q-010 Stochasticgradient Langevin Dynamics~ ( Sgld ) is an what method to e J on large - scale datasets ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-011 ]
SGLD ["Q-012 Where do previous theoretical studies have shownvarious appealing properties from the convergence propertiesto the generalization bounds ?"] "
convergence ["Q-013 Previous theoretical studies have from what shownvarious appealing properties of Sgld ranging appealing propertiesto the generalization bounds ?"] "
appealing properties ["Q-014 What do previous theoretical studies have of Sgld ranging from the convergence propertiesto the generalization bounds ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-015 Previous theoretical studies have what shownvarious appealing properties of Sgld ranging appealing from the convergence p you ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-016 ]
preventing themembership attack ["Q-017 Of what in this paper you study the properties novel perspective of membership privacy protection ( you ?"] "
membership privacy protection ["Q-018 Of what in this paper you study the properties of Sgldfrom a novel perspective ( you ?"] "
preventing themembership attack ["Q-019 What in this paper you study of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-020 Who study the properties of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-021 ]
StochasticGradient Langevin Dynamics~(SGLD ["Q-022 ]
deep neural networks~(DNNs ["Q-023 ]
training a given DNN model ["Q-024 The membership attack which aims to determine whether for what is aspecific sample used has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-025 The membership attack which aims to determine whether aspecific sample is used as what for training a given Dnn model training against deep learning algorithms ?"] "
deep learning algorithms ["Q-026 The membership attack which aims to determine whether aspecific sample is used against what for training a given Dnn model training as a commonthreat ?"] "
aspecific sample is used for training a given DNN model ["Q-027 The membership attack which aims to determine whether what is aspecific sample used for training a given Dnn model has emerged as a commonthreat against deep learning algorithms ?"] "
a given DNN model ["Q-028 The membership attack which aims to determine whether what is aspecific sample used for training has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-029 The membership attack which aims to determine whether aspecific sample is used what for training a given Dnn model training as a commonthreat against deep learning algorithms ?"] "
Zhang Jun ZhouBayesian ["Q-030 Who is used for training a given Dnn model has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-031 Who training attack w W aims to d V as a commonthreat against deep learning algorithms ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-032 ]
a theoreticalframework ["Q-033 To what this end you build to analyze the information leakage ( w ?"] "
leakage ["Q-034 To what this end you build a theoreticalframework to a you ( w ?"] "
SGLD ["Q-035 Who build a theoreticalframework to analyze the information leakage ( w ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-036 ]
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. (arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-037 ]
StochasticGradient Langevin Dynamics~(SGLD ["Q-038 ]
SGLD ["Q-039 The training dataset ) what trained of amodel trained using using ?"] "
amodel ["Q-040 Who trained using Sgld ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-041 ]
SGLD canprevent ["Q-042 Based on this framework you demonstrate to what the information leakage of the training dataset ?"] "
SGLD ["Q-043 Where did based on this framework you based canprevent the information leakage of the training dataset to a certain extent ?"] "
training dataset ["Q-044 Based on this framework you demonstrate of what the information leakage to a certain extent ?"] "
leakage ["Q-045 Based on this framework you demonstrate what N of the training dataset to a certain extent ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-046 ]
other types ofStochastic ["Q-047 Moreover your to what can theoretical analysis be naturally extended ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
leakage of the training dataset to a certain extent.Moreover our theoretical analysis can be naturally extended ["Q-048 Moreover your what can theoretical analysis be to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
SGLD ["Q-049 Moreover whose theoretical analysis can be naturally extended to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
theoretical analysis ["Q-050 Who can be naturally extended to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-051 ]
SGLD algorithm ["Q-052 Empiricalresults on different datasets and models verify your where theoretical findings andsuggest can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults ["Q-053 Empiricalresults on different datasets and models verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce where do the information leakage butalso improve the generalization ability in real - worldapplications ?"] "
reduce ["Q-054 Empiricalresults on different datasets and models verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce do the information leakage butalso improve the generalization ability of the Dnn models ?"] "
different ["Q-055 Empiricalresults on what different datasets and models verify theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
leakage butalso ["Q-056 Empiricalresults on different datasets and models verify your theoretical findings andsuggest what that the Sgld algorithm can not only reduce improve the generalization ability of the Dnn models in real - worldapplications ?"] "
generalization ability ["Q-057 Empiricalresults on different datasets and models verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce what do the information leakage butalso improve of the Dnn models in real - worldapplications ?"] "
Empiricalresults ["Q-058 Empiricalresults on different datasets and models verify whose theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults ["Q-059 Who verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults on different datasets and models verify our theoretical findings ["Q-060 Who andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
SGLD algorithm ["Q-061 Who can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
leakage butalso ["Q-062 Who improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. (arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-063 ]
arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-064 ]
Zhang Jun ZhouBayesian ["Q-01 Who is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
SGLD ["Q-02 Where do previous theoretical studies have shownvarious appealing properties from the convergence propertiesto the generalization bounds ?"] "
appealing properties ["Q-03 What do previous theoretical studies have of Sgld ranging from the convergence propertiesto the generalization bounds ?"] "
preventing themembership attack ["Q-04 What in this paper you study of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-05 Who study the properties of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-06 Who is used for training a given Dnn model has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-07 Who training attack w W aims to d V as a commonthreat against deep learning algorithms ?"] "
Zhang Jun ZhouBayesian ["Q-08 Who build a theoreticalframework to analyze the information leakage ( w ?"] "
amodel ["Q-09 Who trained using Sgld ?"] "
SGLD ["Q-10 Where did based on this framework you based canprevent the information leakage of the training dataset to a certain extent ?"] "
theoretical analysis ["Q-11 Who can be naturally extended to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
different datasets and models ["Q-12 Who verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults on different datasets and models verify our theoretical findings ["Q-13 Who andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
SGLD algorithm ["Q-14 Who can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
leakage butalso ["Q-15 Who improve the generalization ability of the Dnn models in real - worldapplications ?"] "
StochasticGradient Langevin Dynamics~(SGLD) is an effective method to enable Bayesiandeep learning on large-scale datasets. Previous theoretical studies have shownvarious appealing properties of SGLD ranging from the convergence propertiesto the generalization bounds. In this paper we study the properties of SGLDfrom a novel perspective of membership privacy protection (i.e. preventing themembership attack). The membership attack which aims to determine whether aspecific sample is used for training a given DNN model has emerged as a commonthreat against deep learning algorithms. To this end we build a theoreticalframework to analyze the information leakage (w.r.t. the training dataset) of amodel trained using SGLD. Based on this framework we demonstrate that SGLD canprevent the information leakage of the training dataset to a certain extent.Moreover our theoretical analysis can be naturally extended to other types ofStochastic Gradient Markov Chain Monte Carlo
StochasticGradient Langevin Dynamics~(SGLD ["Q-02 ]
StochasticGradient Langevin Dynamics~(SGLD ["Q-03 ]
intrinsic ["Q-04 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian as what is deep learning recently regarded tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. (arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-05 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian tocharacterize what is deep learning recently regarded as an intrinsic way of deep neural networks~ ( Dnns ) ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics ["Q-06 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian is deep learning recently regarded as an intrinsic way tocharacterize the weight uncertainty ( Dnns ) ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics ["Q-07 Lg ] ) authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun Zhoubayesian what is deep learning as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
Zhang Jun ZhouBayesian ["Q-08 Who is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~ ( Dnns ) ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-09 ]
effective method ["Q-010 Stochasticgradient Langevin Dynamics~ ( Sgld ) is an what method to e J on large - scale datasets ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-011 ]
SGLD ["Q-012 Where do previous theoretical studies have shownvarious appealing properties from the convergence propertiesto the generalization bounds ?"] "
convergence ["Q-013 Previous theoretical studies have from what shownvarious appealing properties of Sgld ranging appealing propertiesto the generalization bounds ?"] "
appealing properties ["Q-014 What do previous theoretical studies have of Sgld ranging from the convergence propertiesto the generalization bounds ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-015 Previous theoretical studies have what shownvarious appealing properties of Sgld ranging appealing from the convergence p you ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-016 ]
preventing themembership attack ["Q-017 Of what in this paper you study the properties novel perspective of membership privacy protection ( you ?"] "
membership privacy protection ["Q-018 Of what in this paper you study the properties of Sgldfrom a novel perspective ( you ?"] "
preventing themembership attack ["Q-019 What in this paper you study of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian ["Q-020 Who study the properties of Sgldfrom a novel perspective of membership privacy protection ( you ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-021 ]
StochasticGradient Langevin Dynamics~(SGLD ["Q-022 ]
deep neural networks~(DNNs ["Q-023 ]
training a given DNN model ["Q-024 The membership attack which aims to determine whether for what is aspecific sample used has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-025 The membership attack which aims to determine whether aspecific sample is used as what for training a given Dnn model training against deep learning algorithms ?"] "
deep learning algorithms ["Q-026 The membership attack which aims to determine whether aspecific sample is used against what for training a given Dnn model training as a commonthreat ?"] "
aspecific sample is used for training a given DNN model ["Q-027 The membership attack which aims to determine whether what is aspecific sample used for training a given Dnn model has emerged as a commonthreat against deep learning algorithms ?"] "
a given DNN model ["Q-028 The membership attack which aims to determine whether what is aspecific sample used for training has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-029 The membership attack which aims to determine whether aspecific sample is used what for training a given Dnn model training as a commonthreat against deep learning algorithms ?"] "
Zhang Jun ZhouBayesian ["Q-030 Who is used for training a given Dnn model has emerged as a commonthreat against deep learning algorithms ?"] "
DNN model ["Q-031 Who training attack w W aims to d V as a commonthreat against deep learning algorithms ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-032 ]
a theoreticalframework ["Q-033 To what this end you build to analyze the information leakage ( w ?"] "
leakage ["Q-034 To what this end you build a theoreticalframework to a you ( w ?"] "
SGLD ["Q-035 Who build a theoreticalframework to analyze the information leakage ( w ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-036 ]
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. (arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-037 ]
StochasticGradient Langevin Dynamics~(SGLD ["Q-038 ]
SGLD ["Q-039 The training dataset ) what trained of amodel trained using using ?"] "
amodel ["Q-040 Who trained using Sgld ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-041 ]
SGLD canprevent ["Q-042 Based on this framework you demonstrate to what the information leakage of the training dataset ?"] "
SGLD ["Q-043 Where did based on this framework you based canprevent the information leakage of the training dataset to a certain extent ?"] "
training dataset ["Q-044 Based on this framework you demonstrate of what the information leakage to a certain extent ?"] "
leakage ["Q-045 Based on this framework you demonstrate what N of the training dataset to a certain extent ?"] "
StochasticGradient Langevin Dynamics~(SGLD ["Q-046 ]
other types ofStochastic ["Q-047 Moreover your to what can theoretical analysis be naturally extended ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
leakage of the training dataset to a certain extent.Moreover our theoretical analysis can be naturally extended ["Q-048 Moreover your what can theoretical analysis be to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
SGLD ["Q-049 Moreover whose theoretical analysis can be naturally extended to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
theoretical analysis ["Q-050 Who can be naturally extended to other types ofstochastic Gradient Markov Chain Monte Carlo ( Sg - mcmc ) methods ?"] "
arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-051 ]
SGLD algorithm ["Q-052 Empiricalresults on different datasets and models verify your where theoretical findings andsuggest can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults ["Q-053 Empiricalresults on different datasets and models verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce where do the information leakage butalso improve the generalization ability in real - worldapplications ?"] "
reduce ["Q-054 Empiricalresults on different datasets and models verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce do the information leakage butalso improve the generalization ability of the Dnn models ?"] "
different ["Q-055 Empiricalresults on what different datasets and models verify theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
leakage butalso ["Q-056 Empiricalresults on different datasets and models verify your theoretical findings andsuggest what that the Sgld algorithm can not only reduce improve the generalization ability of the Dnn models in real - worldapplications ?"] "
generalization ability ["Q-057 Empiricalresults on different datasets and models verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce what do the information leakage butalso improve of the Dnn models in real - worldapplications ?"] "
Empiricalresults ["Q-058 Empiricalresults on different datasets and models verify whose theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults ["Q-059 Who verify your theoretical findings andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Empiricalresults on different datasets and models verify our theoretical findings ["Q-060 Who andsuggest that the Sgld algorithm can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
SGLD algorithm ["Q-061 Who can not only reduce the information leakage butalso improve the generalization ability of the Dnn models in real - worldapplications ?"] "
leakage butalso ["Q-062 Who improve the generalization ability of the Dnn models in real - worldapplications ?"] "
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. (arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-063 ]
arXiv1910.02249v1 [cs.LG]) Authors Bingzhe Wu Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun Li Wang Xiaolu Zhang Jun ZhouBayesian deep learning is recently regarded as an intrinsic way tocharacterize the weight uncertainty of deep neural networks~(DNNs ["Q-064 ]
Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining ["Q-01 Who is a challenging taskthat requires enormous compute power especially if no pre - trained models existto initialize the process ?"] "
Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models ["Q-02 Who existto initialize the process ?"] "
a novel tournament method ["Q-03 What you present to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
Brian Van Essen ["Q-04 Who present a novel tournament method to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
generative adversarial networks ["Q-05 Who built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ascalable deep learning framework ["Q-06 Who optimized for Hpc systems ?"] "
our framework ["Q-07 What you demonstrate by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
LBANN ["Q-08 Who demonstrate your framework by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
We demonstrate our framework ["Q-09 Who creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework by creating a complex predictivemodel ["Q-10 Who based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens"
Sam Ade Jacobs ["Q-11 Whose approach combines an Hpc workflow a C extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
a scalableneural network architecture ["Q-12 Who using a coral - class supercomputer ?"] "
70.2 ["Q-13 What Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve of 70 ?"] "
Experimentalresults ["Q-14 Who show that 64 trainers ( 1024 Gpus ) achieve a speedup of 70 ?"] "
J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework by creating a complex predictivemodel based on multi-variate data from high-energy-density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion.Our approach combines an HPC workflow and extends LBANN with optimized dataingestion and the new tournament-style training algorithm to produce a , asingle trainer " ["Q-02 ]
asingle trainer ["Q-03 ]
asingle trainer ["Q-04 ]
no pre-trained models ["Q-05 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on large scientific data is if what taskthat requires enormous compute power especially existto initialize the process ?"] "
large scientific data ["Q-06 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on what is large scientific data taskthat requires enormous compute power especially if no pre - trained models existto initialize the process ?"] "
compute power ["Q-07 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on large scientific data is what taskthat requires especially if no pre - trained models existto initialize the process ?"] "
Parallelizing Training of Deep Generative Models ["Q-08 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power e R if what no pre - trained models e R ?"] "
Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining ["Q-09 Who is a challenging taskthat requires enormous compute power especially if no pre - trained models existto initialize the process ?"] "
pre-trained models ["Q-010 Who existto initialize the process ?"] "
asingle trainer ["Q-011 ]
generative adversarial networks ["Q-012 As what you present a novel tournament method to traintraditional as well on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ["Q-013 We present a novel tournament method to traintraditional as well as where generative adversarial networks built built ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ["Q-014 We present a novel tournament method to traintraditional as well as generative adversarial networks built on Lbann where did ascalable deep learning framework optimized ?"] "
a novel tournament method ["Q-015 What you present to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
Brian Van Essen ["Q-016 Who present a novel tournament method to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
generative adversarial networks ["Q-017 Who built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ascalable deep learning framework ["Q-018 Who optimized for Hpc systems ?"] "
arXiv1910.02270v1 [cs.DC]) Authors Sam Ade Jacobs Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework by creating a complex predictivemodel based on multi-variate data from high-energy-density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion.Our approach combi , asingle trainer " ["Q-020 Of what some ?"] "
exploits ["Q-021 Lbann combinesmultiple levels of parallelism and what e e N N N of the worlds largestsupercomputers ?"] "
asingle trainer ["Q-022 ]
LBANN ["Q-023 By what you demonstrate your framework complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
multi-variate data ["Q-024 We demonstrate your framework by creating on what did a complex predictivemodel based based from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-025 We demonstrate your framework by creating did a complex predictivemodel based based on multi - variate data of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-026 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-027 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-028 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-029 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions from tens of millions of simulations of inertial confinement fusion ?"] "
multi-variate ["Q-030 We demonstrate your framework by creating a complex predictivemodel based on from what did multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-031 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-032 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of inertial confinement fusion ?"] "
inertial confinement fusion ["Q-033 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations ?"] "
our framework ["Q-034 What you demonstrate by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
our framework ["Q-035 We demonstrate what your framework by creating creating on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Brian Van Essen ["Q-036 Who demonstrate your framework by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Sam Ade Jacobs Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework ["Q-037 Who creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar value
Brian Van Essen ["Q-038 Who based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets ["Q-039 ]
LBANN ["Q-040 An Hpc workflow extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-041 Our approach combines Lbann with optimized dataingestion the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-042 An Hpc workflow extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-043 Our approach combines with what Lbann a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-044 Our approach combines Lbann with optimized dataingestion the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-045 Our approach what c c N N N a C extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-046 Our approach combines a D Hpc workflow a a D D D extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-047 Our approach combines an Hpc workflow a C what e e N N N with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-048 Our approach combines an Hpc workflow a C extends Lbann with optimized dataingestion a a D D D the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-049 Our approach combines what Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce Coral - class supercomputer ?"] "
Sam Ade Jacobs ["Q-050 Whose approach combines an Hpc workflow a C extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-051 Our approach combines an Hpc workflow whose extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-052 Our approach combines an Hpc workflow a C extends Lbann with optimized dataingestion whose the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
a scalableneural network architecture ["Q-053 Who using a coral - class supercomputer ?"] "
LBANN ["Q-054 A how much an Hpc workflow extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-055 Our approach combines a how much Lbann with optimized dataingestion the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-056 Our approach combines a D Hpc workflow how much a a D D D extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-057 Our approach combines an Hpc workflow a C extends Lbann with optimized dataingestion how much a a D D D the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
asingle trainer ["Q-058 ]
64 trainers ["Q-059 That what Experimentalresults show ( 1024 Gpus ) achieve a speedup of 70 ?"] "
LBANN ["Q-060 Of what Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve a speedup ?"] "
LBANN ["Q-061 What Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve of 70 ?"] "
Experimentalresults ["Q-062 Who show that 64 trainers ( 1024 Gpus ) achieve a speedup of 70 ?"] "
64 ["Q-063 That how much Experimentalresults show trainers ( 1024 Gpus ) achieve a speedup of 70 ?"] "
70.2 ["Q-064 Of how much Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve a speedup ?"] "
asingle trainer ["Q-065 ]
asingle trainer ["Q-066 ]
asingle trainer ["Q-067 ]
Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining ["Q-01 Who is a challenging taskthat requires enormous compute power especially if no pre - trained models existto initialize the process ?"] "
Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models ["Q-02 Who existto initialize the process ?"] "
a novel tournament method ["Q-03 What you present to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
Brian Van Essen ["Q-04 Who present a novel tournament method to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
generative adversarial networks ["Q-05 Who built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ascalable deep learning framework ["Q-06 Who optimized for Hpc systems ?"] "
our framework ["Q-07 What you demonstrate by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
LBANN ["Q-08 Who demonstrate your framework by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
We demonstrate our framework ["Q-09 Who creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework by creating a complex predictivemodel ["Q-10 Who based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens"
Sam Ade Jacobs ["Q-11 Whose approach combines an Hpc workflow a C extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
a scalableneural network architecture ["Q-12 Who using a coral - class supercomputer ?"] "
70.2 ["Q-13 What Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve of 70 ?"] "
Experimentalresults ["Q-14 Who show that 64 trainers ( 1024 Gpus ) achieve a speedup of 70 ?"] "
J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework by creating a complex predictivemodel based on multi-variate data from high-energy-density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion.Our approach combines an HPC workflow and extends LBANN with optimized dataingestion and the new tournament-style training algorithm to produce a , asingle trainer " ["Q-02 ]
asingle trainer ["Q-03 ]
asingle trainer ["Q-04 ]
no pre-trained models ["Q-05 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on large scientific data is if what taskthat requires enormous compute power especially existto initialize the process ?"] "
large scientific data ["Q-06 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on what is large scientific data taskthat requires enormous compute power especially if no pre - trained models existto initialize the process ?"] "
compute power ["Q-07 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on large scientific data is what taskthat requires especially if no pre - trained models existto initialize the process ?"] "
Parallelizing Training of Deep Generative Models ["Q-08 Thiagaranjan Shusen Liu Peer - timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian Spearstraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power e R if what no pre - trained models e R ?"] "
Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining ["Q-09 Who is a challenging taskthat requires enormous compute power especially if no pre - trained models existto initialize the process ?"] "
pre-trained models ["Q-010 Who existto initialize the process ?"] "
asingle trainer ["Q-011 ]
generative adversarial networks ["Q-012 As what you present a novel tournament method to traintraditional as well on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ["Q-013 We present a novel tournament method to traintraditional as well as where generative adversarial networks built built ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ["Q-014 We present a novel tournament method to traintraditional as well as generative adversarial networks built on Lbann where did ascalable deep learning framework optimized ?"] "
a novel tournament method ["Q-015 What you present to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
Brian Van Essen ["Q-016 Who present a novel tournament method to traintraditional as well as generative adversarial networks built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
generative adversarial networks ["Q-017 Who built on Lbann ascalable deep learning framework optimized for Hpc systems ?"] "
LBANN ascalable deep learning framework ["Q-018 Who optimized for Hpc systems ?"] "
arXiv1910.02270v1 [cs.DC]) Authors Sam Ade Jacobs Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework by creating a complex predictivemodel based on multi-variate data from high-energy-density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion.Our approach combi , asingle trainer " ["Q-020 Of what some ?"] "
exploits ["Q-021 Lbann combinesmultiple levels of parallelism and what e e N N N of the worlds largestsupercomputers ?"] "
asingle trainer ["Q-022 ]
LBANN ["Q-023 By what you demonstrate your framework complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
multi-variate data ["Q-024 We demonstrate your framework by creating on what did a complex predictivemodel based based from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-025 We demonstrate your framework by creating did a complex predictivemodel based based on multi - variate data of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-026 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-027 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-028 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-029 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions from tens of millions of simulations of inertial confinement fusion ?"] "
multi-variate ["Q-030 We demonstrate your framework by creating a complex predictivemodel based on from what did multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived of millions of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-031 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of simulations of inertial confinement fusion ?"] "
a complex predictivemodel ["Q-032 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of inertial confinement fusion ?"] "
inertial confinement fusion ["Q-033 We demonstrate your framework by creating of what did a complex predictivemodel based based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations ?"] "
our framework ["Q-034 What you demonstrate by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
our framework ["Q-035 We demonstrate what your framework by creating creating on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Brian Van Essen ["Q-036 Who demonstrate your framework by creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Sam Ade Jacobs Brian Van Essen David Hysom Jae-Seung Yeom Tim Moon Rushil Anirudh Jayaraman J. Thiagaranjan Shusen Liu Peer-Timo Bremer Jim Gaffney Tom Benson Peter Robinson Luc Peterson Brian SpearsTraining deep neural networks on large scientific data is a challenging taskthat requires enormous compute power especially if no pre-trained models existto initialize the process. We present a novel tournament method to traintraditional as well as generative adversarial networks built on LBANN ascalable deep learning framework optimized for HPC systems. LBANN combinesmultiple levels of parallelism and exploits some of the worlds largestsupercomputers. We demonstrate our framework ["Q-037 Who creating a complex predictivemodel based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar value
Brian Van Essen ["Q-038 Who based on multi - variate data from high - energy - density physics containinghundreds of millions of images and hundreds of millions of scalar valuesderived from tens of millions of simulations of inertial confinement fusion ?"] "
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets ["Q-039 ]
LBANN ["Q-040 An Hpc workflow extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-041 Our approach combines Lbann with optimized dataingestion the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-042 An Hpc workflow extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-043 Our approach combines with what Lbann a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-044 Our approach combines Lbann with optimized dataingestion the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-045 Our approach what c c N N N a C extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-046 Our approach combines a D Hpc workflow a a D D D extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-047 Our approach combines an Hpc workflow a C what e e N N N with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-048 Our approach combines an Hpc workflow a C extends Lbann with optimized dataingestion a a D D D the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-049 Our approach combines what Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce Coral - class supercomputer ?"] "
Sam Ade Jacobs ["Q-050 Whose approach combines an Hpc workflow a C extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-051 Our approach combines an Hpc workflow whose extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-052 Our approach combines an Hpc workflow a C extends Lbann with optimized dataingestion whose the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
a scalableneural network architecture ["Q-053 Who using a coral - class supercomputer ?"] "
LBANN ["Q-054 A how much an Hpc workflow extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-055 Our approach combines a how much Lbann with optimized dataingestion the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-056 Our approach combines a D Hpc workflow how much a a D D D extends Lbann with optimized dataingestion a C the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
LBANN ["Q-057 Our approach combines an Hpc workflow a C extends Lbann with optimized dataingestion how much a a D D D the new tournament - style training algorithm to produce a scalableneural network architecture using a coral - class supercomputer ?"] "
asingle trainer ["Q-058 ]
64 trainers ["Q-059 That what Experimentalresults show ( 1024 Gpus ) achieve a speedup of 70 ?"] "
LBANN ["Q-060 Of what Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve a speedup ?"] "
LBANN ["Q-061 What Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve of 70 ?"] "
Experimentalresults ["Q-062 Who show that 64 trainers ( 1024 Gpus ) achieve a speedup of 70 ?"] "
64 ["Q-063 That how much Experimentalresults show trainers ( 1024 Gpus ) achieve a speedup of 70 ?"] "
70.2 ["Q-064 Of how much Experimentalresults show that 64 trainers ( 1024 Gpus ) achieve a speedup ?"] "
asingle trainer ["Q-065 ]
asingle trainer ["Q-066 ]
asingle trainer ["Q-067 ]
arXiv1910.02285v1 ["Q-01 How much a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-02 Who a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Deep Learning System ["Q-03 Who diagnosing Pulmonary Tuberculosis ?"] "
arXiv1910.02285v1 ["Q-04 How much a A D D D Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-05 Who developed a deep learning model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
CT imaging datasets from 223 patients with activePTB ["Q-06 Who were collected and another 501 cases from a healthy population served asnegative samples ?"] "
professional radiologists ["Q-07 Who served asnegative samples ?"] "
samples.2884 lesions of PTB ["Q-08 Who were carefully labeled and classifiedmanually by professional radiologists ?"] "
Three state-of-the-art 3D convolutionneural network (CNN) models ["Q-09 Who were trained and evaluated in the inspection of Ptbct images ?"] "
Three state-of-the-art 3D convolutionneural network ["Q-10 Who evaluated in the inspection of Ptbct images ?"] "
Transfer ["Q-11 Who learning utilized d you also utilized during this process ?"] "
Thebest model ["Q-12 What was Thebest model selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
spatial location ["Q-13 What was Thebest model selected to annotate of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Thebest model ["Q-14 Who was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
lesions andclassify ["Q-15 Who andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Noisy-Or Bayesian function ["Q-16 Who was used to generatean overall infection probability ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-17 Who wasexported ?"] "
85.9% and 89.2%respectively ["Q-18 Where did the results showed that the recall and precision rates from theperspective of a single lesion region were 85 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-19 Who showed that the recall and precision rates from theperspective of a single lesion region of Ptb were 85 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-20 Who were 85 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-21 Who were 98 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-22 Who was 90 ?"] "
asan effective reference ["Q-23 What might the new method serve for decision making by clinical doctors ?"] "
the PTB lesion type classification was 90.9%.The new method ["Q-24 Who might serve asan effective reference for decision making by clinical doctors ?"] "
arXiv1910.02285v1 ["Q-01 How much a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-02 Who a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Deep Learning System ["Q-03 Who diagnosing Pulmonary Tuberculosis ?"] "
arXiv1910.02285v1 ["Q-04 How much a A D D D Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Xu Lanjuan LiWe developed a deep learning model-based system to automatically generate aquantitative Computed Tomography (CT) diagnostic report for PulmonaryTuberculosis (PTB) cases.501 CT imaging datasets from 223 patients with activePTB were collected and another 501 cases from a healthy population served asnegative samples.2884 lesions of PTB were carefully labeled and classifiedmanually by professional radiologists.Three state-of-the-art 3D convolutionneural network (CNN) models were trained and evaluated in the inspection of PTBCT images. Transfer learning method was also utilized during this process. Thebest model was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously.Then the Noisy-Or Bayesian function was used to generatean overall infection probability.Finally a quantitative diagnostic report wasexported.The results showed that the recall and precision rates from theperspectiv , Xu Lanjuan LiWe developed a deep learning model-based system to automatically generate aquantitative Computed Tomography (CT) diagnostic report for PulmonaryTuberculosis " ["Q-06 ]
85.9% and 89.2%respectively ["Q-07 ]
PulmonaryTuberculosis ["Q-08 Iv ] ) authors where Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan Liwe developed a deep learning model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report ( Ptb ) cases ?"] "
A Deep Learning System That Generates Quantitative CT Reports for Diagnosing Pulmonary Tuberculosis. (arXiv1910.02285v1 [eess.IV]) Authors Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe developed a deep learning ["Q-09 Iv ] ) authors what Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan Liwe developed model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
Computed Tomography ["Q-010 Iv ] ) authors what Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan Liwe developed a deep learning model - based system to automatically g N ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-011 Who developed a deep learning model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
89.2%respectively ["Q-012 ]
CT imaging ["Q-013 501 from what datasets with activeptb were collected and another 501 cases from a healthy population served asnegative samples ?"] "
CT imaging datasets from 223 patients with activePTB were collected and another 501 cases from a healthy population served asnegative samples.2884 ["Q-014 501 where datasets from 223 patients were collected and another 501 cases from a healthy population served asnegative samples ?"] "
a healthy population ["Q-015 501 Ct imaging datasets from 223 from what were patients with activeptb collected and another 501 cases served asnegative samples ?"] "
carefully labeled and classifiedmanually by professional radiologists ["Q-016 501 Ct imaging datasets from 223 what were patients with activeptb collected and another 501 cases from a healthy population served asnegative samples ?"] "
asnegative samples.2884 ["Q-017 501 Ct imaging datasets from 223 patients with activeptb were collected and another 501 cases from what did a healthy population served ?"] "
activePTB ["Q-018 Who were collected and another 501 cases from a healthy population served asnegative samples ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-019 Who served asnegative samples ?"] "
223 ["Q-020 501 from how much datasets patients with activeptb were collected and another 501 cases from a healthy population served asnegative samples ?"] "
89.2%respectively ["Q-021 ]
professional radiologists ["Q-022 2884 by what were lesions of Ptb carefully labeled and classifiedmanually ?"] "
samples.2884 ["Q-023 2884 what were lesions of Ptb and classifiedmanually by professional radiologists ?"] "
PTB ["Q-024 Who were carefully labeled and classifiedmanually by professional radiologists ?"] "
89.2%respectively ["Q-025 ]
inspection ["Q-026 Three state - of - the - art 3d convolutionneural network ( Cnn ) models were trained in what did and evaluated of Ptbct images ?"] "
PTBCT images ["Q-027 Three state - of - the - art 3d convolutionneural network ( Cnn ) models were trained where did and evaluated in the inspection ?"] "
professional radiologists.Three state-of-the-art 3D convolutionneural network (CNN) models were trained and evaluated in the inspection of PTBCT images ["Q-028 Three state - of - the - art 3d convolutionneural network ( Cnn ) what were models trained and evaluated in the inspection of Ptbct images ?"] "
Three state-of-the-art 3D convolutionneural network (CNN) models ["Q-029 Who were trained and evaluated in the inspection of Ptbct images ?"] "
Three state-of-the-art 3D convolutionneural network ["Q-030 Who evaluated in the inspection of Ptbct images ?"] "
85.9% and 89.2%respectively ["Q-031 ]
this process ["Q-032 During what Transfer learning method learning also utilized ?"] "
Transfer ["Q-033 Who learning utilized d you also utilized during this process ?"] "
89.2%respectively ["Q-034 ]
lesions andclassify ["Q-035 Of what was Thebest model selected to annotate the spatial location andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
miliary infiltrative ["Q-036 Thebest model was selected to annotate into what the spatial location of lesions andclassify them and cavitarytypes simultaneously ?"] "
Thebest model ["Q-037 What was Thebest model selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
spatial location ["Q-038 What was Thebest model selected to annotate of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Thebest model ["Q-039 Thebest model was selected to annotate whom the spatial location of lesions andclassify into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Thebest model ["Q-040 Who was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
lesions andclassify ["Q-041 Who andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
89.2%respectively ["Q-042 ]
Noisy-Or Bayesian ["Q-043 Then what was the noisy - or bayesian function used to generatean overall infection probability ?"] "
overall infection probability ["Q-044 Then what was the noisy - or bayesian function used to g J ?"] "
Noisy-Or Bayesian function ["Q-045 Who was used to generatean overall infection probability ?"] "
89.2%respectively ["Q-046 ]
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-047 Who wasexported ?"] "
85.9% and 89.2%respectively ["Q-048 ]
85.9% and 89.2%respectively ["Q-049 That what did the results showed and precision rates from theperspective of a single lesion region of Ptb were 85 ?"] "
85.9% and 89.2%respectively ["Q-050 From what did the results showed that the recall and precision rates of a single lesion region of Ptb were 85 ?"] "
85.9% and 89.2%respectively ["Q-051 Of what did the results showed that the recall and precision rates from theperspective of Ptb were 85 ?"] "
85.9% and 89.2%respectively ["Q-052 Where did the results showed that the recall and precision rates from theperspective of a single lesion region were 85 ?"] "
85.9% and 89.2%respectively ["Q-053 The results showed that the recall and precision rates from theperspective of what were a single lesion region of Ptb ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe developed a deep learning model-based system to automatically generate aquantitative Computed Tomography (CT) diagnostic report for PulmonaryTuberculosis (PTB) cases.501 CT imaging datasets from 223 patients with activePTB were collected and another 501 cases from a healthy population served asnegative samples.2884 lesions of PTB were carefully labeled and classifiedmanually by professional radiologists.Three state-of-the-art 3D convolutionneural network (CNN) models were trained and evaluated in the inspection of PTBCT images. Transfer learning method was also utilized during this process. Thebest model was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously.Then the Noisy-Or Bayesian function was used to generatean overall infection probability.Finally a quantitative diagnostic report wasexported.The results showed that the recall , Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe " ["Q-055 Who were 85 ?"] "
85.9% and 89.2%respectively ["Q-056 The results showed that the recall and precision rates from theperspective of how much were a single lesion region of Ptb ?"] "
89.2%respectively ["Q-057 ]
89.2%respectively ["Q-058 ]
89.2%respectively ["Q-059 ]
98.7% and 93.7% respectively ["Q-060 The overall recall and precision ratesfrom what were the perspective ofone Ptb case ?"] "
Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-061 Who were 98 ?"] "
98.7% and 93.7% respectively ["Q-062 The overall recall and precision ratesfrom how much were the perspective ofone Ptb case ?"] "
89.2%respectively ["Q-063 ]
85.9% and 89.2%respectively ["Q-064 ]
89.2%respectively ["Q-065 ]
90.9%.The ["Q-066 Moreover the precision rateof what did the Ptb lesion type classification was ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-067 Who was 90 ?"] "
90.9%.The ["Q-068 Moreover the precision rateof how much did the Ptb lesion type classification was ?"] "
89.2%respectively ["Q-069 ]
85.9% and 89.2%respectively ["Q-070 ]
decision ["Q-071 For what might the new method serve asan effective reference by clinical doctors ?"] "
clinical doctors ["Q-072 By what might the new method serve asan effective reference for decision making ?"] "
asan effective reference ["Q-073 What might the new method serve for decision making by clinical doctors ?"] "
the PTB lesion type classification was 90.9%.The new method ["Q-074 Who might serve asan effective reference for decision making by clinical doctors ?"] "
85.9% and 89.2%respectively ["Q-075 ]
85.9% and 89.2%respectively ["Q-076 ]
arXiv1910.02285v1 ["Q-01 How much a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-02 Who a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Deep Learning System ["Q-03 Who diagnosing Pulmonary Tuberculosis ?"] "
arXiv1910.02285v1 ["Q-04 How much a A D D D Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-05 Who developed a deep learning model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
CT imaging datasets from 223 patients with activePTB ["Q-06 Who were collected and another 501 cases from a healthy population served asnegative samples ?"] "
professional radiologists ["Q-07 Who served asnegative samples ?"] "
samples.2884 lesions of PTB ["Q-08 Who were carefully labeled and classifiedmanually by professional radiologists ?"] "
Three state-of-the-art 3D convolutionneural network (CNN) models ["Q-09 Who were trained and evaluated in the inspection of Ptbct images ?"] "
Three state-of-the-art 3D convolutionneural network ["Q-10 Who evaluated in the inspection of Ptbct images ?"] "
Transfer ["Q-11 Who learning utilized d you also utilized during this process ?"] "
Thebest model ["Q-12 What was Thebest model selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
spatial location ["Q-13 What was Thebest model selected to annotate of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Thebest model ["Q-14 Who was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
lesions andclassify ["Q-15 Who andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Noisy-Or Bayesian function ["Q-16 Who was used to generatean overall infection probability ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-17 Who wasexported ?"] "
85.9% and 89.2%respectively ["Q-18 Where did the results showed that the recall and precision rates from theperspective of a single lesion region were 85 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-19 Who showed that the recall and precision rates from theperspective of a single lesion region of Ptb were 85 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-20 Who were 85 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-21 Who were 98 ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-22 Who was 90 ?"] "
asan effective reference ["Q-23 What might the new method serve for decision making by clinical doctors ?"] "
the PTB lesion type classification was 90.9%.The new method ["Q-24 Who might serve asan effective reference for decision making by clinical doctors ?"] "
arXiv1910.02285v1 ["Q-01 How much a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-02 Who a D Deep Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Deep Learning System ["Q-03 Who diagnosing Pulmonary Tuberculosis ?"] "
arXiv1910.02285v1 ["Q-04 How much a A D D D Deep Learning System that generates quantitative Ct Reports for diagnosing Pulmonary Tuberculosis ?"] "
Xu Lanjuan LiWe developed a deep learning model-based system to automatically generate aquantitative Computed Tomography (CT) diagnostic report for PulmonaryTuberculosis (PTB) cases.501 CT imaging datasets from 223 patients with activePTB were collected and another 501 cases from a healthy population served asnegative samples.2884 lesions of PTB were carefully labeled and classifiedmanually by professional radiologists.Three state-of-the-art 3D convolutionneural network (CNN) models were trained and evaluated in the inspection of PTBCT images. Transfer learning method was also utilized during this process. Thebest model was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously.Then the Noisy-Or Bayesian function was used to generatean overall infection probability.Finally a quantitative diagnostic report wasexported.The results showed that the recall and precision rates from theperspectiv , Xu Lanjuan LiWe developed a deep learning model-based system to automatically generate aquantitative Computed Tomography (CT) diagnostic report for PulmonaryTuberculosis " ["Q-06 ]
85.9% and 89.2%respectively ["Q-07 ]
PulmonaryTuberculosis ["Q-08 Iv ] ) authors where Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan Liwe developed a deep learning model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report ( Ptb ) cases ?"] "
A Deep Learning System That Generates Quantitative CT Reports for Diagnosing Pulmonary Tuberculosis. (arXiv1910.02285v1 [eess.IV]) Authors Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe developed a deep learning ["Q-09 Iv ] ) authors what Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan Liwe developed model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
Computed Tomography ["Q-010 Iv ] ) authors what Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan Liwe developed a deep learning model - based system to automatically g N ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-011 Who developed a deep learning model - based system to automatically generate aquantitative Computed Tomography ( Ct ) diagnostic report for Pulmonarytuberculosis ( Ptb ) cases ?"] "
89.2%respectively ["Q-012 ]
CT imaging ["Q-013 501 from what datasets with activeptb were collected and another 501 cases from a healthy population served asnegative samples ?"] "
CT imaging datasets from 223 patients with activePTB were collected and another 501 cases from a healthy population served asnegative samples.2884 ["Q-014 501 where datasets from 223 patients were collected and another 501 cases from a healthy population served asnegative samples ?"] "
a healthy population ["Q-015 501 Ct imaging datasets from 223 from what were patients with activeptb collected and another 501 cases served asnegative samples ?"] "
carefully labeled and classifiedmanually by professional radiologists ["Q-016 501 Ct imaging datasets from 223 what were patients with activeptb collected and another 501 cases from a healthy population served asnegative samples ?"] "
asnegative samples.2884 ["Q-017 501 Ct imaging datasets from 223 patients with activeptb were collected and another 501 cases from what did a healthy population served ?"] "
activePTB ["Q-018 Who were collected and another 501 cases from a healthy population served asnegative samples ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-019 Who served asnegative samples ?"] "
223 ["Q-020 501 from how much datasets patients with activeptb were collected and another 501 cases from a healthy population served asnegative samples ?"] "
89.2%respectively ["Q-021 ]
professional radiologists ["Q-022 2884 by what were lesions of Ptb carefully labeled and classifiedmanually ?"] "
samples.2884 ["Q-023 2884 what were lesions of Ptb and classifiedmanually by professional radiologists ?"] "
PTB ["Q-024 Who were carefully labeled and classifiedmanually by professional radiologists ?"] "
89.2%respectively ["Q-025 ]
inspection ["Q-026 Three state - of - the - art 3d convolutionneural network ( Cnn ) models were trained in what did and evaluated of Ptbct images ?"] "
PTBCT images ["Q-027 Three state - of - the - art 3d convolutionneural network ( Cnn ) models were trained where did and evaluated in the inspection ?"] "
professional radiologists.Three state-of-the-art 3D convolutionneural network (CNN) models were trained and evaluated in the inspection of PTBCT images ["Q-028 Three state - of - the - art 3d convolutionneural network ( Cnn ) what were models trained and evaluated in the inspection of Ptbct images ?"] "
Three state-of-the-art 3D convolutionneural network (CNN) models ["Q-029 Who were trained and evaluated in the inspection of Ptbct images ?"] "
Three state-of-the-art 3D convolutionneural network ["Q-030 Who evaluated in the inspection of Ptbct images ?"] "
85.9% and 89.2%respectively ["Q-031 ]
this process ["Q-032 During what Transfer learning method learning also utilized ?"] "
Transfer ["Q-033 Who learning utilized d you also utilized during this process ?"] "
89.2%respectively ["Q-034 ]
lesions andclassify ["Q-035 Of what was Thebest model selected to annotate the spatial location andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
miliary infiltrative ["Q-036 Thebest model was selected to annotate into what the spatial location of lesions andclassify them and cavitarytypes simultaneously ?"] "
Thebest model ["Q-037 What was Thebest model selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
spatial location ["Q-038 What was Thebest model selected to annotate of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Thebest model ["Q-039 Thebest model was selected to annotate whom the spatial location of lesions andclassify into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
Thebest model ["Q-040 Who was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
lesions andclassify ["Q-041 Who andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously ?"] "
89.2%respectively ["Q-042 ]
Noisy-Or Bayesian ["Q-043 Then what was the noisy - or bayesian function used to generatean overall infection probability ?"] "
overall infection probability ["Q-044 Then what was the noisy - or bayesian function used to g J ?"] "
Noisy-Or Bayesian function ["Q-045 Who was used to generatean overall infection probability ?"] "
89.2%respectively ["Q-046 ]
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-047 Who wasexported ?"] "
85.9% and 89.2%respectively ["Q-048 ]
85.9% and 89.2%respectively ["Q-049 That what did the results showed and precision rates from theperspective of a single lesion region of Ptb were 85 ?"] "
85.9% and 89.2%respectively ["Q-050 From what did the results showed that the recall and precision rates of a single lesion region of Ptb were 85 ?"] "
85.9% and 89.2%respectively ["Q-051 Of what did the results showed that the recall and precision rates from theperspective of Ptb were 85 ?"] "
85.9% and 89.2%respectively ["Q-052 Where did the results showed that the recall and precision rates from theperspective of a single lesion region were 85 ?"] "
85.9% and 89.2%respectively ["Q-053 The results showed that the recall and precision rates from theperspective of what were a single lesion region of Ptb ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe developed a deep learning model-based system to automatically generate aquantitative Computed Tomography (CT) diagnostic report for PulmonaryTuberculosis (PTB) cases.501 CT imaging datasets from 223 patients with activePTB were collected and another 501 cases from a healthy population served asnegative samples.2884 lesions of PTB were carefully labeled and classifiedmanually by professional radiologists.Three state-of-the-art 3D convolutionneural network (CNN) models were trained and evaluated in the inspection of PTBCT images. Transfer learning method was also utilized during this process. Thebest model was selected to annotate the spatial location of lesions andclassify them into miliary infiltrative caseous tuberculoma and cavitarytypes simultaneously.Then the Noisy-Or Bayesian function was used to generatean overall infection probability.Finally a quantitative diagnostic report wasexported.The results showed that the recall , Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe " ["Q-055 Who were 85 ?"] "
85.9% and 89.2%respectively ["Q-056 The results showed that the recall and precision rates from theperspective of how much were a single lesion region of Ptb ?"] "
89.2%respectively ["Q-057 ]
89.2%respectively ["Q-058 ]
89.2%respectively ["Q-059 ]
98.7% and 93.7% respectively ["Q-060 The overall recall and precision ratesfrom what were the perspective ofone Ptb case ?"] "
Wei Wu Xukun Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-061 Who were 98 ?"] "
98.7% and 93.7% respectively ["Q-062 The overall recall and precision ratesfrom how much were the perspective ofone Ptb case ?"] "
89.2%respectively ["Q-063 ]
85.9% and 89.2%respectively ["Q-064 ]
89.2%respectively ["Q-065 ]
90.9%.The ["Q-066 Moreover the precision rateof what did the Ptb lesion type classification was ?"] "
Li Peng Du Guanjing Lang Min Xu Kaijin Xu Lanjuan LiWe ["Q-067 Who was 90 ?"] "
90.9%.The ["Q-068 Moreover the precision rateof how much did the Ptb lesion type classification was ?"] "
89.2%respectively ["Q-069 ]
85.9% and 89.2%respectively ["Q-070 ]
decision ["Q-071 For what might the new method serve asan effective reference by clinical doctors ?"] "
clinical doctors ["Q-072 By what might the new method serve asan effective reference for decision making ?"] "
asan effective reference ["Q-073 What might the new method serve for decision making by clinical doctors ?"] "
the PTB lesion type classification was 90.9%.The new method ["Q-074 Who might serve asan effective reference for decision making by clinical doctors ?"] "
85.9% and 89.2%respectively ["Q-075 ]
85.9% and 89.2%respectively ["Q-076 ]
Ali-akbar Agha-mohammadi Evangelos A. TheodorouDeep ["Q-01 What has theodoroudeep learning enjoyed and applying state - of - the - artmodel learning methods to controls is an exciting prospect ?"] "
David D. Fan Jennifer Nguyen Rohan Thakker Nikhilesh Alatur Ali-akbar Agha-mohammadi Evangelos A. TheodorouDeep learning ["Q-02 Who has enjoyed much recent success and applying state - of - the - artmodel learning methods to controls is an exciting prospect ?"] "
David D. Fan ["Q-03 Who applying state - of - the - artmodel learning methods to controls is an exciting prospect ?"] "
Evangelos A. TheodorouDeep ["Q-04 Who is an exciting prospect ?"] "
safety stability ["Q-05 While what you propose aframework which satisfies these constraints of deepneural networks for learning model uncertainties ?"] "
safety stability and real-time performance ["Q-06 What you propose aframework which s N while allowing the use of deepneural networks for learning model uncertainties ?"] "
David D. Fan ["Q-07 Who propose aframework which satisfies these constraints while allowing the use of deepneural networks for learning model uncertainties ?"] "
David D. Fan ["Q-08 Who allowing the use of deepneural networks for learning model uncertainties ?"] "
deepneural networks ["Q-09 Who learning model uncertainties ?"] "
David D. Fan Jennifer Nguyen Rohan Thakker Nikhilesh Alatur Ali-akbar ["Q-10 Who is theuse of bayesian model learning which provides an avenue for maintainingappropriate degrees of caution in the face of the unknown ?"] "
Bayesian model ["Q-11 Who learning which provides an avenue for maintainingappropriate degrees of caution in the face of the unknown ?"] "
leveraging the theory ["Q-12 What do in the proposedapproach you develop ofstochastic Clfs ( Control Lypunov Functions ) and stochastic Cbfs ( Controlbarrier Functions ) along with tractable bayesian model learning via Gaussianprocesses or bayesian neural networks ?"] "
David D. Fan ["Q-13 Who develop an adaptive control framework leveraging the theory ofstochastic Clfs ( Control Lypunov Functions ) and stochastic Cbfs ( Controlbarrier Functions ) along with tractable bayesian model learning via Gaussianprocesses or bayesian neural networks ?"] "
adaptive control framework ["Q-14 Who leveraging the theory ofstochastic Clfs ( Control Lypunov Functions ) and stochastic Cbfs ( Controlbarrier Functions ) along with tractable bayesian model learning via Gaussianprocesses or bayesian neural networks ?"] "
tractable Bayesian model ["Q-15 Who learning via Gaussianprocesses or bayesian neural networks ?"] "
David D. Fan ["Q-16 Who adapting to unknown dynamics withprobability 1 ?"] "
dynamics withprobability 1. We demonstrate this architecture ["Q-17 What you d N for high - speed terrestrialmobility targeting potential applications in safety - critical high - speed Marsrover missions ?"] "
David D. Fan ["Q-18 Who demonstrate this architecture for high - speed terrestrialmobility targeting potential applications in safety - critical high - speed Marsrover missions ?"] "
high-speed terrestrialmobility ["Q-19 Who targeting potential applications in safety - critical high - speed Marsrover missions ?"] "
stochastic CBFs ["Q-01 ]
Control Lypunov Functions ["Q-02 ]
Bayesian Learning-Based Adaptive Control for Safety Critical Systems ["Q-03 ]
Control Lypunov Functions ["Q-04 ]
Control Lypunov Functions ["Q-05 ]
Ali-akbar Agha-mohammadi Evangelos A. TheodorouDeep learning ["Q-06 Theodoroudeep learning has enjoyed to what much recent success and applying applying state - of - the - artmodel learning methods is an exciting prospect ?"] "
Ali-akbar Agha-mohammadi Evangelos A. TheodorouDeep learning has enjoyed much recent success ["Q-07 What has theodoroudeep learning enjoyed and applying state - of - the - artmodel learning methods to controls is an exciting prospect ?"] "
Ali-akbar Agha-mohammadi ["Q-08 Theodoroudeep learning has enjoyed what much recent success and applying applying to controls is an exciting prospect ?"] "
controls is an exciting prospect ["Q-09 Theodoroudeep learning has enjoyed much recent success and applying state - of - the - artmodel learning methods to what is controls ?"] "
David D. Fan ["Q-010 Who has enjoyed much recent success and applying state - of - the - artmodel learning methods to controls is an exciting prospect ?"] "
David D. Fan ["Q-011 Who applying state - of - the - artmodel learning methods to controls is an exciting prospect ?"] "
Evangelos A. TheodorouDeep ["Q-012 Who is an exciting prospect ?"] "
Bayesian Learning-Based Adaptive Control for Safety Critical Systems ["Q-013 ]
arXiv1910.02325v1 ["Q-014 ]
safety stability ["Q-015 While what you propose aframework which satisfies these constraints of deepneural networks for learning model uncertainties ?"] "
deepneural networks ["Q-016 We propose aframework which satisfies of what these constraints while allowing allowing the use for learning model uncertainties ?"] "
learning model uncertainties ["Q-017 We propose aframework which satisfies for what these constraints while allowing allowing the use of deepneural networks ?"] "
safety stability and real-time performance ["Q-018 What you propose aframework which s N while allowing the use of deepneural networks for learning model uncertainties ?"] "
safety stability and real-time performance ["Q-019 We propose aframework which satisfies what these constraints while allowing allowing of deepneural networks for learning model uncertainties ?"] "
deepneural ["Q-020 We propose aframework which satisfies these constraints while allowing the use of what deepneural networks for learning learning ?"] "
David D. Fan ["Q-021 Who propose aframework which satisfies these constraints while allowing the use of deepneural networks for learning model uncertainties ?"] "
David D. Fan ["Q-022 Who allowing the use of deepneural networks for learning model uncertainties ?"] "
deepneural networks ["Q-023 Who learning model uncertainties ?"] "
Bayesian Learning-Based Adaptive Control for Safety Critical Systems. (arXiv1910.02325v1 [eess ["Q-024 ]
Bayesian model learning ["Q-025 Central to theuse what is your method which provides an avenue for maintainingappropriate degrees of caution in the face of the unknown ?"] "
Bayesian ["Q-026 Central to your method is theuse of for what Bayesian model learning learning which provides an avenue of caution in the face of the unknown ?"] "
Bayesian ["Q-027 Central to your method is theuse of of what Bayesian model learning learning which provides an avenue for maintainingappropriate degrees in the face of the unknown ?"] "
Bayesian ["Q-028 Central to your method is theuse of in what bayesian model learning learning which provides an avenue for maintainingappropriate degrees of caution of the unknown ?"] "
Bayesian ["Q-029 Central to your method is theuse of of what Bayesian model learning learning which provides an avenue for maintainingappropriate degrees of caution in the face unknown ?"] "
Evangelos A. TheodorouDeep learning has enjoyed much recent success and applying state-of-the-artmodel learning methods to controls is an exciting prospect. However there is astrong reluctance to use these methods on safety-critical systems which haveconstraints on safety stability and real-time performance. We propose aframework which satisfies these constraints while allowing the use of deepneural networks for learning model uncertainties. Central to our method is theuse of Bayesian model learning which provides an avenue ["Q-030 Central to your method is theuse of what Bayesian model learning learning which provides for maintainingappropriate degrees of caution in the face of the unknown ?"] "
our ["Q-031 Central to whose method is theuse of bayesian model learning which provides an avenue for maintainingappropriate degrees of caution in the face of the unknown ?"] "
David D. Fan Jennifer Nguyen Rohan Thakker Nikhilesh Alatur Ali-akbar Agha-mohammadi Evangelos A. TheodorouDeep ["Q-032 Who is theuse of bayesian model learning which provides an avenue for maintainingappropriate degrees of caution in the face of the unknown ?"] "
Bayesian model ["Q-033 Who learning which provides an avenue for maintainingappropriate degrees of caution in the face of the unknown ?"] "
Bayesian Learning-Based Adaptive Control for Safety Critical Systems ["Q-034 ]
tractable Bayesian model learning ["Q-035 In the proposedapproach you develop along what an adaptive control framework leveraging leveraging the theory ofstochastic Clfs ( Control Lypunov Functions ) and stochastic Cbfs ( Controlbarrier Functions ) via Gaussianprocesses or bayesian neural networks ?"] "
GaussianProcesses ["Q-036 In the proposedapproach you develop an adaptive control framework leveraging the theory ofstochastic Clfs ( Control Lypunov Functions ) and stochastic Cbfs ( Controlbarrier Functions ) along with where tractable bayesian model learning learning or bayesian neural networks ?"] "
adaptive control framework ["Q-037 What do in the proposedapproach you develop ofstochastic Clfs ( Control Lypunov Functions ) and stochastic Cbfs ( Controlbarrier Functions ) along with tractable bayesian model learning via Gaussianprocesses or bayesian neural networks ?"] "
David D. Fan ["Q-038 Who develop an adaptiv