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Firefox ออกส่วนขยายใหม่ชื่อว่า Advance สำหรับการแนะนำเว็บไซต์และบทความโดยขึ้นกับสิ่งที่ผู้ใช้กำลังอ่านอยู่ รวมถึงประวัติการเข้าชมเว็บไซต์บนเบราว์เซอร์

Advance จะมีสองส่วนคือ Read Next ซึ่งจะแนะนำบทความที่เหมาะสมขึ้นกับแท็บที่ผู้ใช้กำลังใช้งานอยู่ และอีกส่วนคือ For You ที่จะแนะนำตามตามประวัติการเข้าชมเว็บไซต์ของผู้ใช้งาน

ฟีเจอร์แนะนำทั้งหมดนี้จะถูกสร้างขึ้นแสดงให้ผู้ใช้แต่ละคนดูตามข้อมูลของผู้ใช้คนนั้น ๆ โดยใช้เทคโนโลยี machine learning จากสตาร์ทอัพ Laserlike โดย Mozilla จะให้ผู้ใช้ควบคุมได้ว่าเมื่อไรที่จะให้ Advance ทำงาน, ตรวจสอบได้ว่า Laserlike จะเห็นประวัติการเข้าชมอะไรบ้าง และสามารถสั่งลบข้อมูลได้เมื่อต้องการ

ปัจจุบัน Advance ยังอยู่ในขั้นทดสอบโครงการ Test Pilot ของ Firefox ผู้ใช้ที่สนใจสามารถดูรายละเอียดได้ที่ Firefox Test Pilot

ที่มา - Mozilla, The Verge

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          Economist - Forecasting - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience with machine learning applications. We are breaking fresh ground, pioneering in a program that is crucial for future Amazon growth, and our business...
From Amazon.com - Wed, 27 Jun 2018 07:21:23 GMT - View all Seattle, WA jobs
          Sales Engineer - Hitachi Vantara - New York, NY      Cache   Translate Page   Web Page Cache   
Account Managers, internal specialists and customers. Understanding of Data Science and Machine Learning....
From Hitachi Vantara - Sat, 04 Aug 2018 04:47:47 GMT - View all New York, NY jobs
          Oracle Unveils Autonomous Database Cloud Service; Larry Ellison Comments      Cache   Translate Page   Web Page Cache   
Oracle has introduced a cloud-based database service offering intended to help public and private sector customers process, report and analyze transactions. The Autonomous Transaction Processing system uses machine learning algorithms for users to automate existing databases and is designed to run on government, financial, retail and manufacturing applications, Oracle said Tuesday. The company released the offering to complement the firm’s […]
          Associate Architect, AI Innovation, Chief Technology Office, Enterprise - Microsoft - Redmond, WA      Cache   Translate Page   Web Page Cache   
Artificial Intelligence, Quantum Computing, Serverless Computing, Machine Learning, Micro-services solution design, and hybrid cloud-based solutions....
From Microsoft - Wed, 01 Aug 2018 08:29:27 GMT - View all Redmond, WA jobs
          Solution Architect - Data & Analytics - Neudesic LLC - Seattle, WA      Cache   Translate Page   Web Page Cache   
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Mon, 02 Jul 2018 10:04:49 GMT - View all Seattle, WA jobs
          Technical Support Engineer II - NAS/ Storage - Pure Storage - Lehi, UT      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Wed, 01 Aug 2018 06:20:10 GMT - View all Lehi, UT jobs
          Pure Support Escalation Engineer - Pure Storage - Lehi, UT      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Fri, 08 Jun 2018 18:26:33 GMT - View all Lehi, UT jobs
          Technical Support Engineer II/III - Pure Storage - Lehi, UT      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Fri, 08 Jun 2018 06:19:02 GMT - View all Lehi, UT jobs
          Sr. BI Engineer - Republic Finance - Plano, TX      Cache   Translate Page   Web Page Cache   
Continuously explore and recommend new BI technology, including those powered by machine learning, A.I., and natural language processing, to improve the value...
From Republic Finance - Wed, 25 Apr 2018 16:14:02 GMT - View all Plano, TX jobs
          Solution Architect - Data & Analytics - Neudesic LLC - New York, NY      Cache   Translate Page   Web Page Cache   
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Sat, 16 Jun 2018 09:58:39 GMT - View all New York, NY jobs
          MSP Sales Development Manager - Pure Storage - Chicago, IL      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Tue, 24 Jul 2018 04:27:07 GMT - View all Chicago, IL jobs
          Research Scientist, Quantum Computing Applications - LOCKHEED MARTIN CORPORATION - Louisville, CO      Cache   Translate Page   Web Page Cache   
Experience in design and development of algorithms and applications for machine learning using quantum and/or classical computing....
From Lockheed Martin Corporation - Mon, 02 Jul 2018 04:09:30 GMT - View all Louisville, CO jobs
          Playground Global - Investment Associate (Venture Capital Team) - playground.global - Palo Alto, CA      Cache   Translate Page   Web Page Cache   
Artificial intelligence, robotics, sensors, new compute platforms, quantum technologies, next generation manufacturing, machine learning, space technologies,...
From Playground.global - Fri, 18 May 2018 18:05:13 GMT - View all Palo Alto, CA jobs
          Hardware Technical Marketing Engineer - Pure Storage - Mountain View, CA      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Wed, 08 Aug 2018 00:35:30 GMT - View all Mountain View, CA jobs
          SSD Qualification Test Engineer - Pure Storage - Mountain View, CA      Cache   Translate Page   Web Page Cache   
Ability to operate in a fast paced changing business environment. The world is experiencing a technological revolution driven by AI, machine learning, virtual...
From Pure Storage - Mon, 06 Aug 2018 16:34:06 GMT - View all Mountain View, CA jobs
          Software Engineer, Core Products - Pure Storage - Mountain View, CA      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Sun, 05 Aug 2018 06:17:33 GMT - View all Mountain View, CA jobs
          Machine Learning Engineer - Technica Corporation - Dulles, VA      Cache   Translate Page   Web Page Cache   
Technica Corporation is seeking a Machine Learning Engineer to support our internal Innovation, Research and Development (IRD) team....
From Technica Corporation - Wed, 11 Jul 2018 06:07:15 GMT - View all Dulles, VA jobs
          How is machine learning transforming the finance industry?      Cache   Translate Page   Web Page Cache   

The influence of machine learning, a strand of artificial intelligence (AI), is spreading through various industries. Over three-quarters of businesses are now pouring money into "big data", setting the stage for machine learning to grow much further in reach over the next few years.

The post How is machine learning transforming the finance industry? appeared first on The London Economic.


          QA of Machine Learning Models with PDCA Cycle      Cache   Translate Page   Web Page Cache   

The primary goal of establishing and implementing Quality Assurance (QA) practices for machine learning/data science projects or, projects using machine learning models is to achieve consistent and sustained improvements in business processes making use of underlying ML predictions. This is where the idea of PDCA cycle (Plan-Do-Check-Act) is applied to establish a repeatable process ensuring that high-quality machine learning [...]

The post QA of Machine Learning Models with PDCA Cycle appeared first on Reskilling IT.


          Sr Software Engineer ( Big Data, NoSQL, distributed systems ) - Stride Search - Los Altos, CA      Cache   Translate Page   Web Page Cache   
Experience with text search platforms, machine learning platforms. Mastery over Linux system internals, ability to troubleshoot performance problems using tools...
From Stride Search - Tue, 03 Jul 2018 06:48:29 GMT - View all Los Altos, CA jobs
          Business Strategy, Sr. Manager - Hortonworks - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Dallas, TX jobs
          Business Strategy, Sr. Manager - Hortonworks - Atlanta, GA      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Atlanta, GA jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page   Web Page Cache   
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Mon, 14 May 2018 23:57:10 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Portland, OR      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:10 GMT - View all Portland, OR jobs
          AWS Architect - Insight Enterprises, Inc. - Chicago, IL      Cache   Translate Page   Web Page Cache   
Database architecture, Big Data, Machine Learning, Business Intelligence, Advanced Analytics, Data Mining, ETL. Internal teammate application guidelines:....
From Insight - Thu, 12 Jul 2018 01:56:10 GMT - View all Chicago, IL jobs
          Data Scientist / Operations Research Engineer - Advanced Micro Devices, Inc. - Austin, TX      Cache   Translate Page   Web Page Cache   
Work closely with the business units to identify Machine Learning applications, define the strategic and tactical needs and drive the appropriate business...
From Advanced Micro Devices, Inc. - Thu, 12 Jul 2018 07:32:54 GMT - View all Austin, TX jobs
          ISV Technology Director - AI and ML - 67511 - Advanced Micro Devices, Inc. - Austin, TX      Cache   Translate Page   Web Page Cache   
AMD’s Machine Learning team work on many high-impact projects that serve AMD’s various lines of business. What you do at AMD changes everything....
From Advanced Micro Devices, Inc. - Sat, 07 Jul 2018 01:32:18 GMT - View all Austin, TX jobs
          ISV Technology Director - AI and ML - 67453 - Advanced Micro Devices, Inc. - Santa Clara, CA      Cache   Translate Page   Web Page Cache   
AMD’s Machine Learning team work on many high-impact projects that serve AMD’s various lines of business. What you do at AMD changes everything....
From Advanced Micro Devices, Inc. - Sat, 07 Jul 2018 01:32:16 GMT - View all Santa Clara, CA jobs
          Data Science Analyst - Strategic Data Solutions - Apple - Austin, TX      Cache   Translate Page   Web Page Cache   
We apply data science and machine learning to drive strategic impact across multiple lines of business at Apple....
From Apple - Fri, 06 Jul 2018 13:47:35 GMT - View all Austin, TX jobs
          Sr Software Engineer - Applied Machine Learning - Apple - Austin, TX      Cache   Translate Page   Web Page Cache   
We work on many high-impact projects that serve various Apple lines of business. Understanding of machine learning, statistics....
From Apple - Fri, 15 Jun 2018 01:48:26 GMT - View all Austin, TX jobs
          Director, Customer Service Product and Tools - Kabam - Austin, TX      Cache   Translate Page   Web Page Cache   
Enthusiastic about the latest mobile trends and emerging technologies (IE Machine Learning, AI). Providing leadership and supporting for the technology...
From Kabam - Thu, 24 May 2018 02:31:26 GMT - View all Austin, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:15 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Austin, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all Austin, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Houston, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:13 GMT - View all Houston, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - San Antonio, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all San Antonio, TX jobs
          Desenvolvedor Java para projetos de IA e Machine Learning - Hop - Belo Horizonte, MG      Cache   Translate Page   Web Page Cache   
Nós somos a Hop, uma empresa que nasceu para dar vida às ideias inovadoras! Unimos metodologias de Design com Inteligência Artificial e Computação Cognitiva...
De Hop - Tue, 24 Jul 2018 13:51:19 GMT - Visualizar todas as empregos: Belo Horizonte, MG
          A machine learning system trained on scholarly journals could correct Wikipedia's gendered under-representation problem      Cache   Translate Page   Web Page Cache   

Quicksilver is a machine-learning tool from AI startup Primer: it used 30,000 Wikipedia entries to create a model that allowed it to identify the characteristics that make a scientist noteworthy enough for encyclopedic inclusion; then it mined the academic search-engine Semantic Scholar to identify the 200,000 scholars in a variety of fields; now it is systematically composing draft Wikipedia entries for scholars on its list who are missing from the encyclopedia. (more…)


          GPU Accelerated SQL queries with PostgreSQL & PG-Strom in OpenShift-3.10      Cache   Translate Page   Web Page Cache   

Openshift is integrated with Cloud Infrastructure Server Cluster. Contact us to find out our latest offers! Introduction In the OpenShift 3.9 GPU blog, we leveraged machine learning frameworks on OpenShift for image recognition. And in the How To Use GPUs with DevicePlugin in OpenShift 3.10 blog, we installed and configured Continue Reading

The post GPU Accelerated SQL queries with PostgreSQL & PG-Strom in OpenShift-3.10 appeared first on ReadySpace Singapore.


          Principal Market Validation Specialist - PTC - Needham, MA      Cache   Translate Page   Web Page Cache   
Advance knowledge and experience with Machine Learning / Data Science / Analytics. Customer Satisfaction focus, both internal and external, with strong...
From PTC - Wed, 16 May 2018 14:29:21 GMT - View all Needham, MA jobs
          A machine learning system trained on scholarly journals could correct Wikipedia's gendered under-representation problem      Cache   Translate Page   Web Page Cache   

Quicksilver is a machine-learning tool from AI startup Primer: it used 30,000 Wikipedia entries to create a model that allowed it to identify the characteristics that make a scientist noteworthy enough for encyclopedic inclusion; then it mined the academic search-engine Semantic Scholar to identify the 200,000 scholars in a variety of fields; now it is systematically composing draft Wikipedia entries for scholars on its list who are missing from the encyclopedia. (more…)


          There's something eerie about bots that teach themselves to cheat      Cache   Translate Page   Web Page Cache   

One of the holy grails of computer science is unsupervised machine learning, where you tell an algorithm what goal you want it to attain, and give it some data to practice on, and the algorithm uses statistics to invent surprising ways of solving your problem. (more…)


          Cloud Engineer – High Performance Computing Specialist - EagleView Technologies - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Leveraging 17 years of the most advanced aerial imaging technology in the world, along with the most recent advances in machine learning and AI, EagleView is...
From Indeed - Thu, 28 Jun 2018 22:33:10 GMT - View all Bellevue, WA jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:15 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Austin, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all Austin, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Houston, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:13 GMT - View all Houston, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - San Antonio, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all San Antonio, TX jobs
          Improving Machine Learning with Continuous Learning Models-P2P      Cache   Translate Page   Web Page Cache   
Machine learning models are exposed to a variety of different tasks and are required to perform well on these tasks over time. However, what if the datasets change dramatically over time? For example, in an image classification system, the machine learning model was trained on one distribution yet over time, new images arrive which force [...]
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:15 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Austin, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all Austin, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Houston, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:13 GMT - View all Houston, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - San Antonio, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all San Antonio, TX jobs
          Bell Labs - Integrated Photonics Researcher - NOKIA - Holmdel, NJ      Cache   Translate Page   Web Page Cache   
Nokia is a global leader in the technologies that connect people and things. Investigate and implement machine learning based optimization to control large...
From Nokia - Mon, 18 Jun 2018 15:55:57 GMT - View all Holmdel, NJ jobs
          AA Chief SW Architect - NOKIA - San Jose, CA      Cache   Translate Page   Web Page Cache   
Analytics, AI, and machine learning. Presenting to customers, industry forums, analysts and internal audiences....
From Nokia - Mon, 18 Jun 2018 15:51:40 GMT - View all San Jose, CA jobs
          Projekt-Nr. 51816 - Test Manager (m/f) Python      Cache   Translate Page   Web Page Cache   
Currently we are looking for a Test Manager (m/f) Python for our customer in Nuremberg.

The following tasks should be done:
+ coordinate test activities in a python apllication Developement
+ manage defined standards on test quality
+ manage test data
+ coach Python application developers how to set uo and perform testing in a cloud environment
+ participate actively in testing
+ close co-operation with DevOps engineers.

Anforderungen:
Must-Haves:
+ long standing experience in how to structure, organize and perform application testing
+ practical experience in python application development
+ profound knowledge of cloud environments (AWS)
+ Experience in testing application with integrated machine learning components strongly preferred
+ solid knowledge in Docker, Mongo DB

Zusätzliche Informationen:
Konnten wir Ihr Interesse wecken? Dann freuen wir uns auf die Zusendung Ihres aussagekräftigen Qualifikationsprofils unter Angabe Ihrer Stundensatzvorstellung.

Projekt-Nr.:
51816

Stellentyp:
freiberuflich

Einsatzort:
D9

Start:
asap

Dauer:
5 monhts ++
          Business Strategy, Sr. Manager - Hortonworks - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Dallas, TX jobs
          Business Strategy, Sr. Manager - Hortonworks - Atlanta, GA      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Atlanta, GA jobs
           Advance is a Firefox extension that recommends sites based on your browsing habits       Cache   Translate Page   Web Page Cache   
It uses machine learning and your browsing history and habits to recommend new sites to you.
          Bentley Systems Announces Finalists in the Year in Infrastructure 2018 Awards Program      Cache   Translate Page   Web Page Cache   

Winners to be selected and announced at Bentley’s
Year in Infrastructure 2018 Conference, October 15-18 in London

EXTON, Pa. – August 7, 2018 – Bentley Systems, Incorporated, a leading global provider of comprehensive software solutions for advancing infrastructure, today announced the finalists in the Year in Infrastructure 2018 Awards program. The annual awards program honors the extraordinary work of Bentley users advancing infrastructure design, construction, and operations throughout the world. Twelve independent jury panels of distinguished industry experts selected the 57 finalists from 420 nominations submitted by more than 340 user organizations around the world.

The finalists for Year in Infrastructure 2018 awards for going digital advancements in infrastructure are:

Bridges
• GS E&C Corporation – Jungkun~Jinjeong Bypass Road (Sueo-chon Bridge) – Gwangyang,
  Jeolla-Namdo, South Korea
• Indian Railways – Reality modeling facilitates efficient planning, construction and monitoring of
  Chenab Bridge – Reasi District, Jammu & Kashmir, India
• PT. WIJAYA KARYA (Persero) Tbk – Design and Build of Road Bridge at Teluk Lamong Port Project – Gresik-Surabaya, East Java, Indonesia

Buildings and Campuses
• Anil Verma Associates, Inc. – Regional Connector Transit Corridor (RCTC) – Los Angeles,
  California, United States
• Shalom Baranes Associates – Cannon House Office Building Renewal – Washington,
  District of Columbia, United States
• Voyants Solutions Private Limited – Station Development plan for Gwalior Railway Station –
  Gwalior, Madhya Pradesh, India

Communications Networks
• iForte Solusi Infotek – iForte Fiber Management System – Jakarta, Indonesia
• PT. Linknet – Linknet Operation Center – Jakarta, Indonesia
• SiteSee – Advancing Telecommunications – Brisbane, Queensland, Australia

Construction
• AAEngineering Group, LLP – Phase II of Pustynnoe Gold Plant: modernization and capacity
  increase – Balkhash, Karaganda region, Kazakhstan
• Lendlease Engineering – New bridge over the Richmond River at Broadwater – Ballina, New South
  Wales, Australia
• Tianjin Tianhe-Cloud Building Engineering Technology Co., Ltd. and China State Construction
   Bridge Co., Ltd. – Main Channel Road Project of Ningbo-Zhoushan Port (Zhoudai Bridge)
  – Zhoushan, Zhejiang, China

Digital Cities
• Avineon India Pvt. Ltd. – Digital 3D Building Model of Rotterdam – Rotterdam, Netherlands
• CCCC Water Transportation Consultants Co., Ltd. – BIM Technology Application in the
  Municipal Infrastructure Phase I Project of Zhong-Guan-Cun Science and Technology
  Town – Baodi District, Tianjin City, China
• Yunnan Yunling Engineering Cost Consultation Co., Ltd. – New Municipal Road Construction PPP
   Project of the Municipal Public Facility Construction Project of Guandu Culture New City –
   Kunming, Yunnan, China

Environmental Engineering
• China Water Resources Pearl River Planning Surveying & Designing Co., Ltd. –
  Jiangxi Xinjiang Bazizui Navigation-Power Junction Project – Shangrao, Jiangxi, China
• PT. WIJAYA KARYA (Persero) Tbk – Landslide Disaster Protection Project on the National Road
  Network – Cianjur, West Java, Indonesia
• Setec-Terrasol – Extension L11 – Adaptation of the Mairie des Lilas Station – Paris, France

Manufacturing
• Brownfield Engineering Sdn. Bhd. – Propose 48MW Large Scale Solar (LSS) Project –
   Kudat, Sabah, Malaysia
• Digital Engineering (BIM) Center of Shenyang Aluminum & Magnesium Engineering & Research
   Institute Co., Ltd. – Alumina Refinery Project Cooperated between CHALCO and Indonesia –
   Bukit Batu, West Kalimantan, Indonesia
• Toshiba Transmission and Distribution Systems Asia Sdn. Bhd. – Integration of SCADA System
   with Electrical Panels for Brunei National Control Center – Brunei Darussalam

Mining and Offshore Engineering
• CADDS Group Pty Ltd – Rio Tinto Iron Ore Sentry Guarding Project – Dampier,
   Western Australia, Australia
• Northern Engineering & Technology Incorporation, MCC – SINO Iron Ore Mine – Perth,
  Western Australia, Australia
• POWERCHINA Huadong Engineering Corporation Limited – Jiangsu Offshore Wind Farm –
  Jiangsu Province, China

Power Generation
• JSC ATOMPROEKT – Hanhikivi 1 Nuclear Power Plant – Northern Ostrobothnia Region, Finland
• Northwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group –
  Huaneng Ningxia Dam Power Plant Stage Ⅳ project – Qingtongxia, Ningxia Hui autonomous
  region, China
• Sacyr Somague – Hydroelectric use of the Foz Tua Dam – Foz Tua, Alijó- Vila Real, Portugal

Project Delivery
• AECOM – Gaining New Perspective through ProjectWise Insights – United Kingdom
• Arup – Arup Australasia Project Systems Team – Brisbane, Queensland, Australia
• Dragados SA & Transport for London – Bank Station Capacity Upgrade – London, United Kingdom

Rail and Transit
• China Railway Engineering Consulting Group Co., Ltd. – BIM Project for the Beijing-Zhangjiakou
   High-speed Railway – Beijing, China
• Italferr S.p.A. – Naples-Bari Route, Apice-Orsara Double Railway Line, Hirpinia-Orsara Operational
  Lot – Provinces of Avellino and Foggia, Italy
• Skanska Costain Strabag Joint Venture (SCS) – Hs2 Main Works Lots S1 and S2 – London,
   United Kingdom

Reality Modeling
• Hong Kong Science & Technology Parks Corporation & Chain Technology Development Co. Limited
  – Smart Campus of the Hong Kong Science Park – Hong Kong, China
• Skand Pty Ltd – Building Envelope Inspection Powered by Machine Learning and Reality Modeling
  for RMIT University Brunswick Campus – Victoria, Australia
• Transport for London - Major Projects Directorate – Deep Tube Upgrade Programme -
   Piccadilly Line Upgrade – London, United Kingdom

Road and Rail Asset Performance
• CSX Transportation – Annual Patch Rail Capital Planning – Jacksonville, Florida, United States
• Illinois Department of Transportation – Oversize-Overweight Truck Permitting System –
  Springfield, Illinois, United States
• Maharashtra Metro Rail Corporation Ltd. – Nagpur Metro Asset Information Management System – Nagpur, Maharashtra, India

Roads and Highways
• Alabama Department of Transportation – Birmingham, AL I-59/I-20 Corridor Project –
  Birmingham, Alabama, United States
• Henan Provincial Communications Planning & Design Institute Co., Ltd. – BIM-based Further
  Design and Digital Construction of the Yaoshan-Luanchuan Section Project in the
  Zhengzhou-Xixia Expressway – Luoyang, Henan, China
• Lebuhraya Borneo Utara – Pan Borneo Highway Sarawak – Sarawak, Malaysia

Structural Engineering
• Arab Engineering Bureau – Burj Alfardan – Lusail, Qatar
• Shilp Consulting Engineers – Alambagh Bus Terminal – Lucknow, Uttar Pradesh, India
• VYOM Consultants – K10 Grand Commercial High Rise – Vadodara, Gujarat, India

Utilities and Industrial Asset Performance
• Oman Gas Company S.A.O.C. – Asset Performance Solution for Reliability Management –
   Al-Khuwair, Muscat, Oman
• Vedanta Limited - Cairn Oil and Gas – Well Integrity and Flow Assurance Management –
   States of Rajasthan, Andhra Pradesh, and Gujarat, India
• Volgogradnefteproekt LLC – Object Modeling and Life Cycle Management: Project Implementation
   and Commissioning – Volgograd region, Russia

Utilities Transmission and Distribution
• Northeast Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group –
  New project of a 750 kV substation in the Bortala Mongol Autonomous Prefecture – Bortala
  Mongol, Xinjiang Uyghur, China
• Pestech International Berhad – Substation Design & Automation for Olak Lempit
  Substation Project – Banting, Selangor, Malaysia
• POWERCHINA Hubei Electric Engineering Corporation Limited – Cha'anling-Xiaojiazhou
  220 kV Electric Transmission Line Project – Xianning, Hubei, China

Water and Wastewater Treatment Plants
• MCC Capital Engineering & Research Incorporation Limited – 400,000 ton/day Water Supply
  Project of Wenjiang District, Chengdu City – Chengdu, Sichuan, China
• Shanghai Civil Engineering Co., Ltd of CREC – Civil engineering of the Beihu sewage treatment
  plant and auxiliary project – Wuhan, Hubei, China
• Suez Water Technologies & Solutions – Ultra Pure Water Project 1 GW Manufacturing Solar Silicon
   PV Cells & Modules – Kutch, Gujarat, India

Water, Wastewater, and Stormwater Networks
• Beijing Institute of Water – Beijing South-to-North Water Diversion Auxiliary Project: Hexi
  Branch Project – Beijing, China
• DTK Hydronet Solutions – Conceptioneering and Master Planning of Bankura Multi Village
  Bulk Water Supply Scheme – Bankura, West Bengal, India
• NJS Engineers India P Limited – JICA Assisted Agra Water Supply Project – Agra,
  Uttar Pradesh, India

The finalists will present their innovative projects to their peers, the jurors, industry thought leaders, and more than 130 members of the media as part of related infrastructure forums at Bentley’s Year in Infrastructure 2018 Conference, to be held later this year, October 15 through 18, in London at the Hilton London Metropole.

Chris Barron, Bentley Systems’ chief communications officer, said, “The Year in Infrastructure Conference is an ideal opportunity for infrastructure leaders from around the world to network with their peers, and learn about technologies and best practices to accelerate their organizations’ digital advancement. As part of the conference, we are pleased to congratulate and acknowledge the awards program finalists for their excellent work, and to provide conference attendees with the chance to meet the finalists and watch their project presentations, which represent this year’s most outstanding going digital advancements in infrastructure.”

This year’s conference will include:
• thought-provoking keynotes by industry leaders including Chair of National Infrastructure
  Commission for the UK, Sir John Armitt, and Chief Strategy Officer for Siemens AG,
  Dr. Horst J. Kayser
Digital Advancement Academies—interactive half-day learning sessions led by subject matter
  experts in their areas of expertise including BIM advancement, construction, constructioneering,
  digital advancement research, process industries, and reality modeling
• live technology presentations and panel discussions from Bentley’s strategic partners – Microsoft,
  Siemens, and Topcon
• opportunities for attendees to meet for one-on-one discussions with awards finalists
• informative industry forums and panel discussions
• Year in Infrastructure Awards finalists’ presentations on October 16 and 17
• evening ceremony and gala featuring announcement of the Year in Infrastructure Awards winners
  on October 18

View the Year in Infrastructure 2018 Conference agenda.

To view a searchable collection of innovative infrastructure projects from the annual Year in Infrastructure Awards program, access Bentley’s Infrastructure Yearbooks.
 

 


          Naive Bayes Tutorial: Naive Bayes Classifier in Python      Cache   Translate Page   Web Page Cache   

Classification and prediction are two the most important aspects of Machine Learning and Naive Bayes is a simple but surprisingly powerful algorithm for predictive modeling. So guys, in this Naive Bayes tutorial, I'll be covering the following topics:

  • What is Naive Bayes?
  • What is Bayes' Theorem?
  • Game Prediction using Bayes’ Theorem
  • Naive Bayes in the Industry
  • Step By Step Implementation of Naive Bayes
  • Naive Bayes with SKLEARN

What Is Naive Bayes?

Naive Bayes is among one of the simplest, but most powerful algorithms for classification based on Bayes' Theorem with an assumption of independence among predictors. The Naive Bayes model is easy to build and particularly useful for very large data sets. There are two parts to this algorithm:


          How to Use AI to Become an Authority in Population Health Management      Cache   Translate Page   Web Page Cache   

We are all aware of the sudden wave of Artificial Intelligence and Machine Learning that is redefining healthcare goals for the future.

We have been asking several questions on population health. What will population health look like in the next five years? Will health data impact the overall disease research? How can we get there?


          Digitize Handwriting With Intelligent Character Recognition      Cache   Translate Page   Web Page Cache   

A lot of people use the terms "Machine Learning" and "Artificial Intelligence" interchangeably, and while they are closely related, this perspective is acknowledging just one small part of a much larger story.

Machine Learning is actually a very particular subset of AI in which statistical techniques are employed to give computers the ability to "learn" on their own. Essentially, the more data you feed a computer related to the task you're trying to get it to perform, the better it's able to do just that — all without being literally programmed to do so.


          Cognitive Image Analysis: Azure and Google Come Out Winners!      Cache   Translate Page   Web Page Cache   

Image analysis is defined in Wikipedia as "...the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques."

With the advent of machine learning, image analysis is being offered as a Cognitive API offering by many AI/ML providers like AWS Recognition, Azure Computer Vision, and Google CloudVision.


          Samsung Heavy Industries picks AWS to develop autonomous shipping      Cache   Translate Page   Web Page Cache   
Samsung Heavy Industries selected AWS as its preferred cloud provider.

Samsung Heavy Industries is developing an autonomous smart shipping system to enable the self-piloting of large container ships, LNG carriers, and floating production systems. The company will use the breadth of AWS’s services, including machine learning, augmented reality and virtual reality, analytics, databases, compute, and storage to develop this platform. This includes Amazon Elastic Compute Cloud (Amazon EC2), Amazon Relational Database Service (Amazon RDS), Amazon Simple Storage Solution (Amazon S3), AWS Key Management Service (KMS), and AWS CloudTrail to create integrated systems for all vessel-related data collected from land to sea.

“We’re digitizing our shipping fleet by using the most advanced technologies in the world to enhance our approaches to shipbuilding, operations, and delivery, and chose AWS as our preferred cloud provider to help us quickly transform Samsung Heavy Industries’ into a cloud-first maritime business,” said Dongyeon Lee, Director of Ship & Offshore Performance Research Center at Samsung Heavy Industries. “By leveraging AWS, we’ve successfully released several smart shipping systems so that our customers can manage their ships and fleets more efficiently, and we continue to test new capabilities for ocean-bound vessel navigation and automation. AWS delivers a highly flexible environment, with the broadest and deepest portfolio of cloud services, that is ideal for accelerating research and development across the company, and it has enabled our developers and data scientists to bring new ideas to market at an unprecedented pace.”
          Solutions Architect - NVIDIA - Washington State      Cache   Translate Page   Web Page Cache   
Assist field business development in through the enablement process for GPU Computing products, technical relationship and assisting machine learning/deep...
From NVIDIA - Fri, 20 Apr 2018 08:02:03 GMT - View all Washington State jobs
          Embedded ML Developer - Erwin Hymer Group North America - Virginia Beach, VA      Cache   Translate Page   Web Page Cache   
NVIDIA VisionWorks, OpenCV. Game Development, Accelerated Computing, Machine Learning/Deep Learning, Virtual Reality, Professional Visualization, Autonomous...
From Indeed - Fri, 22 Jun 2018 17:57:58 GMT - View all Virginia Beach, VA jobs
          US Federal CTO - Solution Architect - NVIDIA - Virginia      Cache   Translate Page   Web Page Cache   
Build and cultivate internal understanding of Federal customer data analytics and machine learning requirements among the NVIDIA technical community including...
From NVIDIA - Tue, 07 Aug 2018 01:54:32 GMT - View all Virginia jobs
          Solutions Architect - NVIDIA - Virginia      Cache   Translate Page   Web Page Cache   
Build and cultivate internal understanding of data analytics and machine learning among the NVIDIA technical community....
From NVIDIA - Sun, 03 Jun 2018 08:00:36 GMT - View all Virginia jobs
          Software Engineer | Python Backend (New York) - BenevolentAI - New York, NY      Cache   Translate Page   Web Page Cache   
Machine Learning Squads. All employment is decided on the basis of qualifications, merit, and business need. Fun internal events (boat parties, karting, Oktober...
From BenevolentAI - Thu, 28 Jun 2018 21:30:28 GMT - View all New York, NY jobs
          Taking the pulse of machine learning adoption      Cache   Translate Page   Web Page Cache   
Despite the hype, ML really is in its infancy according to a just-published survey from O'Reilly. The good news is that those who are furthest along with ML are getting quite cognizant of moral and regulatory hazards, like bias and privacy. The survey results drop hints of drastic changes in store as adoption grows more broad-based.
          Senior Solution Architect - Cyber Security - NVIDIA - Maryland      Cache   Translate Page   Web Page Cache   
You will also be an internal champion for Cyber Security and Machine Learning among the NVIDIA technical community....
From NVIDIA - Wed, 01 Aug 2018 07:57:49 GMT - View all Maryland jobs
          Solutions Architect - NVIDIA - Maryland      Cache   Translate Page   Web Page Cache   
You will also be an internal champion for Data Analytics and Machine Learning among the NVIDIA technical community....
From NVIDIA - Sun, 08 Jul 2018 07:55:18 GMT - View all Maryland jobs
          Solutions Architect, Accelerated Computing - NVIDIA - Santa Clara, CA      Cache   Translate Page   Web Page Cache   
Assist field business development in through the enablement process for GPU Computing products, technical relationship and assisting machine learning/deep...
From NVIDIA - Tue, 24 Jul 2018 07:56:24 GMT - View all Santa Clara, CA jobs
          Associate Architect, AI Innovation, Chief Technology Office, Enterprise - Microsoft - Redmond, WA      Cache   Translate Page   Web Page Cache   
Artificial Intelligence, Quantum Computing, Serverless Computing, Machine Learning, Micro-services solution design, and hybrid cloud-based solutions....
From Microsoft - Wed, 01 Aug 2018 08:29:27 GMT - View all Redmond, WA jobs
          Solution Architect - Data & Analytics - Neudesic LLC - Seattle, WA      Cache   Translate Page   Web Page Cache   
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Mon, 02 Jul 2018 10:04:49 GMT - View all Seattle, WA jobs
          Machine Learning & Distributed Ledger Sr. Engineer - Mainstreet Technologies, Inc - McLean, VA      Cache   Translate Page   Web Page Cache   
Machine Learning & Distributed Ledger Sr. Engineer Job Description • Responsible for delivery in the areas of: data science/machine learning & Distributed...
From Mainstreet Technologies, Inc - Thu, 02 Aug 2018 00:52:33 GMT - View all McLean, VA jobs
          Technical Support Engineer II - NAS/ Storage - Pure Storage - Lehi, UT      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Wed, 01 Aug 2018 06:20:10 GMT - View all Lehi, UT jobs
          Pure Support Escalation Engineer - Pure Storage - Lehi, UT      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Fri, 08 Jun 2018 18:26:33 GMT - View all Lehi, UT jobs
          Technical Support Engineer II/III - Pure Storage - Lehi, UT      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Fri, 08 Jun 2018 06:19:02 GMT - View all Lehi, UT jobs
          Solution Architect - Data & Analytics - Neudesic LLC - New York, NY      Cache   Translate Page   Web Page Cache   
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Sat, 16 Jun 2018 09:58:39 GMT - View all New York, NY jobs
          MSP Sales Development Manager - Pure Storage - Chicago, IL      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Tue, 24 Jul 2018 04:27:07 GMT - View all Chicago, IL jobs
          Research Scientist, Quantum Computing Applications - LOCKHEED MARTIN CORPORATION - Louisville, CO      Cache   Translate Page   Web Page Cache   
Experience in design and development of algorithms and applications for machine learning using quantum and/or classical computing....
From Lockheed Martin Corporation - Mon, 02 Jul 2018 04:09:30 GMT - View all Louisville, CO jobs
          Sr. BI Engineer - Republic Finance - Plano, TX      Cache   Translate Page   Web Page Cache   
Continuously explore and recommend new BI technology, including those powered by machine learning, A.I., and natural language processing, to improve the value...
From Republic Finance - Wed, 25 Apr 2018 16:14:02 GMT - View all Plano, TX jobs
          Playground Global - Investment Associate (Venture Capital Team) - playground.global - Palo Alto, CA      Cache   Translate Page   Web Page Cache   
Artificial intelligence, robotics, sensors, new compute platforms, quantum technologies, next generation manufacturing, machine learning, space technologies,...
From Playground.global - Fri, 18 May 2018 18:05:13 GMT - View all Palo Alto, CA jobs
          Hardware Technical Marketing Engineer - Pure Storage - Mountain View, CA      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Wed, 08 Aug 2018 00:35:30 GMT - View all Mountain View, CA jobs
          SSD Qualification Test Engineer - Pure Storage - Mountain View, CA      Cache   Translate Page   Web Page Cache   
Ability to operate in a fast paced changing business environment. The world is experiencing a technological revolution driven by AI, machine learning, virtual...
From Pure Storage - Mon, 06 Aug 2018 16:34:06 GMT - View all Mountain View, CA jobs
          Software Engineer, Core Products - Pure Storage - Mountain View, CA      Cache   Translate Page   Web Page Cache   
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Sun, 05 Aug 2018 06:17:33 GMT - View all Mountain View, CA jobs
          Machine Learning Developer - Kinaxis - Ottawa, ON      Cache   Translate Page   Web Page Cache   
Kinaxis® is a leading edge software company located in Ottawa, Canada. Our RapidResponse® on demand software enables manufacturers and brand owners to drive...
From Kinaxis - Wed, 08 Aug 2018 20:38:15 GMT - View all Ottawa, ON jobs
          Platform Developer, Machine Learning - Kinaxis - Ottawa, ON      Cache   Translate Page   Web Page Cache   
Kinaxis® is revolutionizing the supply chain planning industry by breaking down functional silos of data, people, and processes. Our unique leading edge cloud...
From Kinaxis - Wed, 08 Aug 2018 20:38:15 GMT - View all Ottawa, ON jobs
          The Newest Digital Trend In Oil & Gas      Cache   Translate Page   Web Page Cache   
Artificial intelligence, or rather things like machine learning and automation, which are often wrongly called artificial intelligence, is a big thing in oil and gas right now. The hype around AI spreads a lot further than the oil and gas industry, but in it, the technology is making the first splashes and it looks like they are fast multiplying. While “AI”—or more accurately predictive and analytic algorithms, and automation—in the upstream segment of the industry has garnered some attention already, there is a somewhat…
          CCNT “Soul in Silico & Filter Dysmorphia” - 08.08.2018      Cache   Translate Page   Web Page Cache   

This week on Canary Cry NewsTalk, Forbes publishes pro-transhumanist and anti-god propaganda; plastic surgeons are noticing Snapchat dysmorphia; an update on Flippy’s growing family, and Bezos could do so much better. If you want MORE, Become a Patron, join the exclusive community, and receive Extended Reports of CCNT every week!

AGG for the WEEK OF July 31-Aug 7

YOU HEARD IT HERE FIRST FOLKS! (Updates on stories)

Ancestry and 23andMe Agree to New Rules to Make You Feel Safer Handing Over Your DNA

Tesla suspends shares after Elon Musk tweets he wants to take the carmaker private

 

TECHNOLOGY/AI

AI Vs. God: Who Stays And Who Leaves?

The future of artificial intelligence is the toaster

New Artificial Intelligence Device Identifies Objects at the Speed of Light

Particle physicists team up with AI to solve toughest science problems

World class AI experts share what their favorite algorithm is

Video Friday: Professor Ishiguro’s New Robot Child, and More - IEEE Spectrum

Lip-reading artificial intelligence could help the deaf—or spies | Science | AAAS

ai: The beginning of a wave: AI tiptoes into the workplace - The Economic Times

Ethics and the pursuit of artificial intelligence | South China Morning Post

Artificial intelligence: Scary predictions for AI

20 terrifying uses of artificial intelligence - TechRepublic

BBC - Future - 12 new tech terms you need to understand the future

 

BIOMEDICAL/GENETICS/TRANSHUMANISM

Shivom is creating a genomic data hub to elongate human life with AI | VentureBeat

Captain America on Mars - Scientific American Blog Network

Genetics technology could lead to more crops, fresher food

 

CRYPTOCURRENCY/B-B-B-BLOCKCHAIN

Weed's Biggest Wedding Announcement Just Happened And Cryptocurrency Is The Bride

 

CONSPIRACY THEORIES AND SOMETIMES FACTS!

Freemasons Reportedly Ready to Welcome Transgender Women - Sputnik International

Are you being recorded while placed on hold? - abcactionnews.com WFTS-TV

Alex Jones' Infowars Still Not Banned On App Stores, Instagram And Twitter

#QAnon, the pro-Trump conspiracy theory, explained - Vox

Why the GOP is so easily infiltrated by bonkers conspiracy theorists - The Washington Post

 

SPACE/ALIEN/ETs/UFOs

A Mysterious, Powerful Force is Flinging Radio Waves at Us From Deep Space

NASA space telescope TESS starts search for Earth-like planets

Top Scientists Explain to Senators Why We Must Look for Aliens

Is Humanity About To Accidentally Declare Interstellar War On Alien Civilizations?

Should the Moon Be Quarantined? - Scientific American

 

STORIES THAT DOVETAIL OTHER RESEARCHER’S WORK

Stonehenge mystery solved, says breakthrough scientific study | Fox News

Ancient Roman Library Discovered Beneath German City

 

SOCIAL MEDIA/GOOGLE/AMAZON

Plastic surgeons say more patients coming in with 'Snapchat dysmorphia' | TheHill

Social media is making children regress to mentality of three-year-olds, says top brain scientist

Facebook: Hey Can We Pretty Please Maybe Have Lots of Your Banking Information Too?

Facebook Dating offerings can be seen in leaked pre-launch screenshots | Fox News

Without Sergey Brin, Google has lost its fear of authoritarian China — Quartz

Senators Demand Answers About Google’s Censored Chinese Search Engine | Fortune

Employees at Google, Amazon and Microsoft Have Threatened to Walk Off the Job Over the Use of AI



“THE FOUR HORSEMEN of the TECHNOCALYPSE!”

Amazon’s Jeff Bezos would need to spend $28 million a day to avoid getting richer - MarketWatch

Elon Musk says Tesla is making a mini-car that can fit an adult - Business Insider

Elon Musk: I know more about nuking Mars than scientists

Is Mark Zuckerberg Wet or Dry?

 

BASIL’S CAREER ADVICE

Upwork: Blockchain the Fastest Growing Skill in US Freelance Job Market

7 Job Skills Of The Future (That AIs And Robots Can't Do Better Than Humans)

How to Get Started in Machine Learning and Robotics

DeepMind Cofounder Gives Teenage AI Fan 5 Pieces Of Advice

 

THE DOORS OF PERCEPTION AND OTHER NEAT THINGS ABOUT THE BRAIN

10-Year-Old Boy Recovers Impressively After One-Sixth of His Brain Is Removed

Past experiences shape what we see more than what we are looking at now

The DolphinView headset lets you ‘see’ like your favorite sea creature - The Verge

Telepathic communication just 'a matter of time' as twins reveal blueprint for brain interface

Can you hear these silent GIFs? You may have a new form of synesthesia. - Vox

 

OTHER INTERESTING STORIES THAT POINT TOWARDS THE END TIMES

USPS: Carriers to wear flea repellent for deliveries in Sacramento County neighborhood

Donald Trump's star voted off Hollywood Walk of Fame

 

ICKY NEWS UPDATE

Catherine Oxenberg feels 'horrendous guilt' after bringing daughter into alleged sex cult | Fox News

Nikki Goldstein visits sex robots with artificial intelligence | Daily Mail Online

German Couple Convicted Of Selling Child On The Darknet : NPR

 


          Harvard & University of Toronto Researchers Apply Deep Generative Models to Inverse Molecular Design      Cache   Translate Page   Web Page Cache   
Benjamin Sanchez-Lengeling from Harvard University and Alán Aspuru-Guzik from the University of Toronto have successfully applied machine learning models to speed up the materials discovery process. Their paper Inverse molecular design using machine learning: Generative models for matter engineering was published July 27 in Science Vol. 361.
          Cloudera recognised in Gartner Peer Insights Customers' Choice      Cache   Translate Page   Web Page Cache   
Cloudera (http://www.cloudera.com/) (NYSE: CLDR), the modern platform for machine learning and analytics optimised for the cloud, announced it was recognised...
          CSIS RIST Relativity Project Coordinator - CSIS Lead Investigator - Citi - Tampa, FL      Cache   Translate Page   Web Page Cache   
Diversity is a key business imperative and a source of strength at Citi. Degree in Computer Science, Machine Learning, Information Retrieval or related field,...
From Citi - Sun, 05 Aug 2018 06:14:57 GMT - View all Tampa, FL jobs
          Comment on A Gentle Introduction to Statistical Power and Power Analysis in Python by Phil Clark      Cache   Translate Page   Web Page Cache   
Great article, thanks for the attacking this important, often neglected topic, from a machine learning perspective. One question though; in this sentence, "the statistical power can be increased in a test by increasing the significance level", did you mean power can be increased by decreasing the significance level (as in, decreasing alpha)? Maybe the use of the phrase significance level is misleading.
          Comment on How To Prepare Your Data For Machine Learning in Python with Scikit-Learn by Jason Brownlee      Cache   Translate Page   Web Page Cache   
Normalizer is normalizing the vector length I believe. Use the MinMax scaler instead.
          Comment on Overfitting and Underfitting With Machine Learning Algorithms by Jason Brownlee      Cache   Translate Page   Web Page Cache   
I don't have much material on augmentation sorry.
          Comment on Find Your Machine Learning Tribe by Jason Brownlee      Cache   Translate Page   Web Page Cache   
Thanks!
          Comment on Your First Machine Learning Project in Python Step-By-Step by Jason Brownlee      Cache   Translate Page   Web Page Cache   
Well done!
          Principal Market Validation Specialist - PTC - Needham, MA      Cache   Translate Page   Web Page Cache   
Advance knowledge and experience with Machine Learning / Data Science / Analytics. Customer Satisfaction focus, both internal and external, with strong...
From PTC - Wed, 16 May 2018 14:29:21 GMT - View all Needham, MA jobs
          Facebook Wants to Teach Machine Learning      Cache   Translate Page   Web Page Cache   

When you think of technical education about machine learning, Facebook might not be the company that pops into your head. However, the company uses machine learning, and they’ve rolled out a six-part video series that they say “shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems.”

The videos correspond to what they say are the six aspects of machine learning development:

  1. Problem definition
  2. Data
  3. Evaluation
  4. Features
  5. Model
  6. Experimentation

None of the videos are longer than 10 minutes, so you’ll invest less than an hour. The videos focus less on a specific product …read more


          Principal Data & AI Developer - Lightspeed - Montréal, QC      Cache   Translate Page   Web Page Cache   
Furthermore, we will apply our advanced data analytics, artificial intelligence/machine learning knowledge and experience in combination with our business...
From LightSpeed - Thu, 12 Jul 2018 14:31:24 GMT - View all Montréal, QC jobs
          Director, Data & AI - Lightspeed - Montréal, QC      Cache   Translate Page   Web Page Cache   
Furthermore, we will apply our advanced data analytics, artificial intelligence/machine learning knowledge and experience in combination with our business...
From LightSpeed - Thu, 12 Jul 2018 14:31:24 GMT - View all Montréal, QC jobs
          Senior Principal Data & AI Developer - Lightspeed - Montréal, QC      Cache   Translate Page   Web Page Cache   
Furthermore, we will apply our advanced data analytics, artificial intelligence/machine learning knowledge and experience in combination with our business...
From LightSpeed - Thu, 12 Jul 2018 14:31:23 GMT - View all Montréal, QC jobs
          Samsung Heavy Industries bets on AWS as it builds out its autonomous ship platform      Cache   Translate Page   Web Page Cache   
Samsung Heavy Industries will use a variety of AWS services notably for machine learning and augmented reality.

          Machine Learning for Marketing: Essential Training      Cache   Translate Page   Web Page Cache   
Machine Learning for Marketing: Essential Training
Machine Learning for Marketing: Essential Training
MP4 | Video: 720p | Duration: 55:54 | English | Subtitles: VTT | 220.6 MB

          Samsung Heavy Industries bets on AWS as it builds out its autonomous ship platform      Cache   Translate Page   Web Page Cache   
Samsung Heavy Industries will use a variety of AWS services notably for machine learning and augmented reality.
          Red Team (Web App) - Cylance, Inc. - Texas      Cache   Translate Page   Web Page Cache   
Internal / External / Wireless - Penetration Testing (3+ years REQUIRED). By successfully applying artificial intelligence and machine learning to crack the DNA...
From Cylance, Inc. - Fri, 27 Jul 2018 01:27:57 GMT - View all Texas jobs
          Red Team Senior Consultant (Plano, TX) - Cylance, Inc. - Texas      Cache   Translate Page   Web Page Cache   
Internal / External / Wireless - Penetration Testing (3+ years REQUIRED). By successfully applying artificial intelligence and machine learning to crack the DNA...
From Cylance, Inc. - Fri, 27 Jul 2018 01:27:54 GMT - View all Texas jobs
          Director, Security Research - DigitalShield - White Plains, NY      Cache   Translate Page   Web Page Cache   
By successfully applying machine learning and artificial. Redefined the threat intelligence market, garnered acclaim from industry....
From DigitalShield - Fri, 13 Jul 2018 03:43:59 GMT - View all White Plains, NY jobs
          Consultant - DigitalShield - White Plains, NY      Cache   Translate Page   Web Page Cache   
By successfully applying machine learning and artificial. Detailing technical issues identified and their associated business....
From DigitalShield - Fri, 13 Jul 2018 03:43:58 GMT - View all White Plains, NY jobs
          Principal Consultant, Red Team - Cylance, Inc. - New York, NY      Cache   Translate Page   Web Page Cache   
By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has redefined the endpoint protection market,...
From Cylance, Inc. - Fri, 20 Jul 2018 01:27:36 GMT - View all New York, NY jobs
          Red Team Senior Consultant (Remote) - Cylance, Inc. - Colorado      Cache   Translate Page   Web Page Cache   
By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has redefined the endpoint protection market,...
From Cylance, Inc. - Wed, 25 Jul 2018 19:27:59 GMT - View all Colorado jobs
          Technical Account Manager - Cylance, Inc. - Irvine, CA      Cache   Translate Page   Web Page Cache   
By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has redefined the endpoint protection market,...
From Cylance, Inc. - Fri, 27 Jul 2018 19:28:10 GMT - View all Irvine, CA jobs
          Senior DevOps Engineer - Cylance, Inc. - Irvine, CA      Cache   Translate Page   Web Page Cache   
By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has redefined the endpoint protection market,...
From Cylance, Inc. - Sun, 08 Jul 2018 19:27:56 GMT - View all Irvine, CA jobs
          Senior Operations Analyst - Cylance, Inc. - Irvine, CA      Cache   Translate Page   Web Page Cache   
By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has redefined the endpoint protection market,...
From Cylance, Inc. - Fri, 06 Jul 2018 01:27:27 GMT - View all Irvine, CA jobs
          Global Alliances Solution Architect - Cylance, Inc. - Irvine, CA      Cache   Translate Page   Web Page Cache   
By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has redefined the endpoint protection market,...
From Cylance, Inc. - Fri, 22 Jun 2018 19:27:32 GMT - View all Irvine, CA jobs
          QA Engineering Manager - Cylance, Inc. - Irvine, CA      Cache   Translate Page   Web Page Cache   
Windows, macOS, or Linux internals knowledge. By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has...
From Cylance, Inc. - Tue, 24 Apr 2018 19:28:37 GMT - View all Irvine, CA jobs
          Financial Reporting Director - Cylance, Inc. - Irvine, CA      Cache   Translate Page   Web Page Cache   
By successfully applying artificial intelligence and machine learning to crack the DNA of malware, Cylance has redefined the endpoint protection market,...
From Cylance, Inc. - Sat, 14 Apr 2018 13:27:47 GMT - View all Irvine, CA jobs
          Sr Director, Growth Marketing Technology - eBay Inc. - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Further, the Marketing Tech Leader will apply the latest data analysis and machine learning technologies to innovate applications in both BI analysis and...
From eBay Inc. - Fri, 01 Jun 2018 08:04:49 GMT - View all Bellevue, WA jobs
          Software Engineer - Machine Learning - Convoy - Seattle, WA      Cache   Translate Page   Web Page Cache   
Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes....
From Convoy - Sat, 19 May 2018 10:13:22 GMT - View all Seattle, WA jobs
          Production ML for Data Scientists: What You Can Do and How to Make It Easy, August 22 Webinar      Cache   Translate Page   Web Page Cache   
Learn about MLOps –machine learning operationalization that breaks down the silos between data science and IT; Streamlines deployment and orchestration, and adds advanced functionality.
          Principal Program Manager - Microsoft - Redmond, WA      Cache   Translate Page   Web Page Cache   
Our internal customers use machine learning models to analyze multi-exabyte datasets. The Big Data team builds solutions that enable customers to tackle...
From Microsoft - Sat, 28 Jul 2018 02:13:20 GMT - View all Redmond, WA jobs
          Senior Software Engineer - Microsoft - Redmond, WA      Cache   Translate Page   Web Page Cache   
Experience with leveraging machine learning and AI for Analytics. The Big Data Fundamentals team focuses on Engineering systems, Advanced data Analytics /...
From Microsoft - Fri, 27 Apr 2018 19:10:03 GMT - View all Redmond, WA jobs
          Software Development Manager - Core Video Delivery Technologies, Prime Video - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Strong business and technical vision. Experience in machine learning technologies and big data is a plus. We leverage Amazon Web Services (AWS) technologies...
From Amazon.com - Thu, 02 Aug 2018 19:21:25 GMT - View all Seattle, WA jobs
          Solutions Architect - Amazon Web Services - Amazon.com - San Francisco, CA      Cache   Translate Page   Web Page Cache   
DevOps, Big Data, Machine Learning, Serverless computing etc. High level of comfort communicating effectively across internal and external organizations....
From Amazon.com - Thu, 26 Jul 2018 08:17:05 GMT - View all San Francisco, CA jobs
          Data Scientist & Machine Learning Engineer - Telenor Microfinance Bank Limited - Islamabad      Cache   Translate Page   Web Page Cache   
Position / Title: Data Scientist & Machine Learning Engineer Job Type: Permanent Department: Digital Business Location: Islamabad Qualification & Experience...
From jobssection.com - Fri, 03 Aug 2018 03:16:55 GMT - View all Islamabad jobs
          Data Science Analyst - Strategic Data Solutions - Apple - Austin, TX      Cache   Translate Page   Web Page Cache   
We apply data science and machine learning to drive strategic impact across multiple lines of business at Apple....
From Apple - Fri, 06 Jul 2018 13:47:35 GMT - View all Austin, TX jobs
          Sr Software Engineer - Applied Machine Learning - Apple - Austin, TX      Cache   Translate Page   Web Page Cache   
We work on many high-impact projects that serve various Apple lines of business. Understanding of machine learning, statistics....
From Apple - Fri, 15 Jun 2018 01:48:26 GMT - View all Austin, TX jobs
          Director, Customer Service Product and Tools - Kabam - Austin, TX      Cache   Translate Page   Web Page Cache   
Enthusiastic about the latest mobile trends and emerging technologies (IE Machine Learning, AI). Providing leadership and supporting for the technology...
From Kabam - Thu, 24 May 2018 02:31:26 GMT - View all Austin, TX jobs
          8/9/2018: Career Mail: Jobs in data analysis will more than double this year      Cache   Translate Page   Web Page Cache   

EMPLOYERS are collecting huge amounts of data, so people with data science and analytics skills are in demand. Data scientists use algorithms and machine learning to turn data into business information. ‘We expect to see advertised roles in data...
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page   Web Page Cache   
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Mon, 14 May 2018 23:57:10 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Portland, OR      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:10 GMT - View all Portland, OR jobs
          AWS Architect - Insight Enterprises, Inc. - Chicago, IL      Cache   Translate Page   Web Page Cache   
Database architecture, Big Data, Machine Learning, Business Intelligence, Advanced Analytics, Data Mining, ETL. Internal teammate application guidelines:....
From Insight - Thu, 12 Jul 2018 01:56:10 GMT - View all Chicago, IL jobs
          Facebook Wants to Teach Machine Learning      Cache   Translate Page   Web Page Cache   

When you think of technical education about machine learning, Facebook might not be the company that pops into your head. However, the company uses machine learning, and they’ve rolled out a six-part video series that they say “shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems.”

The videos correspond to what they say are the six aspects of machine learning development:

  1. Problem definition
  2. Data
  3. Evaluation
  4. Features
  5. Model
  6. Experimentation

None of the videos are longer than 10 minutes, so you’ll invest less than an hour. The videos focus less on a specific product …read more


          On Prem Python Engineer      Cache   Translate Page   Web Page Cache   
NC-Raleigh, ON PREM PYTHON ENGINEER - PERM - RALEIGH, NC On Prem Python Engineer Responsibilities: * Work with product stakeholders to identify new product opportunities, new features on existing products, and improve existing features in data driven product focused ways. * Help build, train, and maintain machine learning and statistical models and corpuses at the heart of our business. * Quickly assess the p
          EPYC wins in the server room for AMD      Cache   Translate Page   Web Page Cache   

AMD is continuing to see success in the server room, grabbing a bit more market share from Intel this quarter.  The estimated revenue was $57.66m in the Q2 2018 whereas Q1 was $36m, as far as actual market share, AMD has increased their slice of the pie by 1.3% versus an increase of 0.5% this time last year.  AMD is hopeful they can reach 5% by the end of the year; The Register notes that 2.1% or so would be more in line with the current trend.  Regardless this is great news for AMD and indicates the attractiveness of EPYC for those companies looking for server upgrades.

amd_server_cpu_revnue_share_2q2018.jpg

"Aaron Rakers, senior analyst at Wells Fargo, has seen the second 2018 quarter numbers. He told The Register: "Intel's server CPU share is estimated to have dec lined to 98.7 per cent vs 99 per cent in the prior period and 99.5 per cent a year ago."

Here is some more Tech News from around the web:

Tech Talk

 

read more


          Sr. Product Marketing Manager - Automation Anywhere - San Jose, CA      Cache   Translate Page   Web Page Cache   
Experience in artificial intelligence, analytics, machine learning or business process management software especially in the enterprise space is a big plus but...
From Automation Anywhere - Sat, 16 Jun 2018 05:57:32 GMT - View all San Jose, CA jobs
          Director, Product Marketing - Security - Automation Anywhere - San Jose, CA      Cache   Translate Page   Web Page Cache   
Experience in artificial intelligence, analytics, machine learning or business process management software especially in the enterprise space is a big plus but...
From Automation Anywhere - Sat, 16 Jun 2018 05:57:32 GMT - View all San Jose, CA jobs
          Director, Product Marketing - Enterprise - Automation Anywhere - San Jose, CA      Cache   Translate Page   Web Page Cache   
Experience in artificial intelligence, analytics, machine learning or business process management software especially in the enterprise space is a big plus but...
From Automation Anywhere - Sat, 16 Jun 2018 05:57:32 GMT - View all San Jose, CA jobs
          Desenvolvedor Java para projetos de IA e Machine Learning - Hop - Belo Horizonte, MG      Cache   Translate Page   Web Page Cache   
Nós somos a Hop, uma empresa que nasceu para dar vida às ideias inovadoras! Unimos metodologias de Design com Inteligência Artificial e Computação Cognitiva...
De Hop - Tue, 24 Jul 2018 13:51:19 GMT - Visualizar todas as empregos: Belo Horizonte, MG
          Machine learning could predict medication response in patients with complex mood disorders      Cache   Translate Page   Web Page Cache   
(Lawson Health Research Institute) In a collaborative study by Lawson Health Research Institute, The Mind Research Network and Brainnetome Center, researchers have developed an artificial intelligence (AI) algorithm that analyzes brain scans to better classify illness in patients with a complex mood disorder and help predict their response to medication. (Source: EurekAlert! - Medicine and Health)

MedWorm Message: Have you tried our new medical search engine? More powerful than before. Log on with your social media account. 100% free.


          Business Strategy, Sr. Manager - Hortonworks - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Dallas, TX jobs
          Business Strategy, Sr. Manager - Hortonworks - Atlanta, GA      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Atlanta, GA jobs
          Senior Data & Applied Scientist - Microsoft - Redmond, WA      Cache   Translate Page   Web Page Cache   
Experience developing and applying statistical modeling, machine learning models or data mining algorithms to solve real world problems....
From Microsoft - Wed, 25 Apr 2018 07:13:50 GMT - View all Redmond, WA jobs
          Director, Financial Services - Data Scientist - KPMG - Seattle, WA      Cache   Translate Page   Web Page Cache   
Statistics, data mining, machine learning, statistics, operations research, econometrics, natural language processing, and/or information retrieval....
From KPMG LLP - Thu, 17 May 2018 08:18:36 GMT - View all Seattle, WA jobs
          Database Administrator - Radiant Solutions - Springfield, VA      Cache   Translate Page   Web Page Cache   
Machine learning, data mining, and knowledge discovery. Work is non-routine and very complex, involving the application of advanced technical and business...
From Radiant Solutions - Wed, 04 Jul 2018 01:36:29 GMT - View all Springfield, VA jobs
          Immuta Introduces Open Interface for External Data Catalogs and Global Policy Enforcement for Scalable AI Governance      Cache   Translate Page   Web Page Cache   
On July 25, Immuta unveiled new features to its data management platform, including Global Policies, external Data Catalog Integration, and Curated Tag support for faster data access and policy authoring for scalable AI and machine learning operations. The post Immuta Introduces Open Interface for External Data Catalogs and Global Policy Enforcement for Scalable AI Governance appeared first on Legal Reader.
          Sr.SDE - Amazon.com - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Build Products for amazon external facing and internal facing systems. The team uses various content classification and machine learning algorithms for solving...
From Amazon.com - Wed, 18 Jul 2018 19:20:37 GMT - View all Bellevue, WA jobs
          Software Development Engineer: Machine Learning Service - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Build, operate and optimize critical AWS services enabling machine learning capabilities for internal use and by AWS customers....
From Amazon.com - Wed, 08 Aug 2018 01:22:33 GMT - View all Seattle, WA jobs
          Software Development Engineer - Prime Video Customer Growth - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience building machine learning enabled services. Amazon is an Equal Opportunity-Affirmative Action Employer - Minority/Female/Disability/Vet....
From Amazon.com - Sat, 04 Aug 2018 01:28:01 GMT - View all Seattle, WA jobs
          Principal Product Manager, Amazon Process Automation - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience implementing machine learning based solutions. You will be working closely with businesses and understanding the requirements, working actively with...
From Amazon.com - Thu, 02 Aug 2018 19:20:59 GMT - View all Seattle, WA jobs
          Product Manager - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
You will be working closely with businesses and understanding the requirements, working actively with Technology, Machine learning and Operations teams, making...
From Amazon.com - Thu, 02 Aug 2018 19:20:51 GMT - View all Seattle, WA jobs
          Sr. Risk Manager, Product Quality - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience working with Data Scientists and Economists to develop and improve Machine Learning models. Author and edit risk assessments and program updates for...
From Amazon.com - Wed, 01 Aug 2018 08:07:28 GMT - View all Seattle, WA jobs
          In case you missed it: July 2018 roundup      Cache   Translate Page   Web Page Cache   
In case you missed them, here are some articles from July of particular interest to R users. A program to validate quality and security for R packages: the Linux Foundation's CII Best Practices Badge Program. R scripts to generate images in the style of famous artworks, like Mondrian's. A 6-minute video tour of the AI and Machine Learning services in Azure, including R. The July roundup of AI, Machine Learning and Data Science news. An R package for tiling hexagon-shaped images, used to create a striking banner of hex stickers for useR!2018. Highlights and links to videos from the useR!2018...
          iOS Developer - PGS SOFTWARE - Rzeszów, podkarpackie      Cache   Translate Page   Web Page Cache   
Augmented Reality, Machine Learning, iBeacons, Top Level Security. Elastyczne godziny pracy....
Od PGS SOFTWARE - Wed, 08 Aug 2018 14:51:19 GMT - Pokaż wszystkie Rzeszów, podkarpackie oferty pracy
          How to teach a machine to think like a human      Cache   Translate Page   Web Page Cache   
Machine learning is the branch of computer science that makes artificial intelligence possible.
          AI Filters Down to Qualcomm’s Snapdragon 600 Series Chips      Cache   Translate Page   Web Page Cache   

Qualcomm today announced the Snapdragon 670, an update to the 660. The 670 is based on Qualcomm's Kryo 360 CPU with eight cores: two 2.0 GHz cores target high-power tasks and six 1.7 GHz cores target low-power tasks. The 670 is pared with the Adreno 615 GPU. Together, these contribute to a 15% boost in overall performance and a 25% boost in gaming performance. Similar to the Snapdragon 845 and 710, the Snapdragon 670 brings artificial intelligence / machine learning to mid-range phones and their cameras via the Hexagon 685 DSP. Qualcomm claims the 670 delivers platform-wide AI optimizations with the power to handle advanced operations such as automatic scene recognition and voice recognition. The Spectra 250 image signal processor allows 670-powered cameras to support real-time noise reduction, video noise reduction, and image stabilization. The chip supports Qualcomm's Aqstic, aptX, and aptX HD, as well as displays up to full HD+. On the connectivity front, the 670 includes Qualcomm's X12 modem with LAA, 3-channel carrier aggregation, and 256 QAM for max download speeds of 600 Mbps. The chip also packs Bluetooth 5 and tri-band wifi. Other features include support for Qualcomm QuickCharge 4.0 and the Unity/Unreal gaming engines. Qualcomm says devices with the Snapdragon 670 will debut during the third quarter of the year. The 670 now stands at the top of the 600 series chips. It will find its way into devices that fall in the $300 to $500 range.


          Instructor (Data Science, Artificial Intelligence, Machine Learning) - Cortechma Inc. - Thornhill, ON      Cache   Translate Page   Web Page Cache   
Cortechma Academy team is looking for professors, instructors and engineers with both academically and professionally strong background specializing in one of...
From Indeed - Wed, 01 Aug 2018 16:56:17 GMT - View all Thornhill, ON jobs
           Looking forward with Google Play      Cache   Translate Page   Web Page Cache   

Posted by Purnima Kochikar, Director, Google Play, Apps & Games

On Monday we released Android 9 Pie. As we continue to push the Android platform forward, we're always looking to provide new ways to distribute your apps efficiently, help people discover and engage with your work, and improve the overall security of our ecosystem. Google Play has had a busy year so far with some big milestones around helping you reach more users, including:

  • Shrinking download size: Android App Bundle & Dynamic Delivery has helped reduce app sizes by up to 65%, leading to increased downloads and fewer uninstalls.
  • Helpling improve quality: New tools in the Play Console have helped you reduce crash rates by up to 70%.
  • Improving discovery: Improvements to the discovery experience has increased Google Play Store visits by 30% over the last 12 months.
  • Keeping users safe: Google Play Protect scans more than 50 billion apps a day and Android API level 26 adoption requirements improve app security and performance.

Google Play is dedicated to helping you build and grow quality app businesses, reach the more than 2 billion Android devices globally and provide your users with better experiences. Here are some of the important areas we're prioritizing this year:

Innovative Distribution

We've added more testing tools to the popular Play Console to help developers de-risk app launches with internal and external test tracks and staged rollouts to get valuable early feedback. This year we've expanded the Start on Android program globally that provides developers new to Android additional guidance to optimize their apps before launch. Google Play Instant remains a huge bet to transform app discovery and improve conversions by letting users engage without the friction of installing. We're seeing great results from early adopters and are working on new places to surface instant experience, including ads, and making them easier to build throughout the year.

Improving App Quality

Google Play plays an important role helping developers understand and fix quality and performance issues. At I/O, we showcased how we expanded the battery, stability and rendering of Android vitals reporting to include app start time & permission denials, enabling developers to cut application not responding errors by up to 95%. We also expanded the functionality of automated device testing with the pre-launch report to enable games testing. Recently, we increased the importance of app quality in our search and discovery recommendations that has resulted in higher engagement and satisfaction with downloaded games.

Richer Discovery

Over the last year we've rolled out more editorial content and improved our machine learning to deliver personalized recommendations for apps and games that engage users. Since most game downloads come from browsing (as opposed to searching or deep linking into) the store, we've put particular focus on games discovery, with a new games home page, special sections for premium and new games, immersive video trailers and screenshots, and the ability to try games instantly. We've also introduced new programs to help drive app downloads through richer discovery. For example, since launching our app pre-registration program in 2016, we've seen nearly 250 million app pre-registrations. Going forward, we'll be expanding on these programs and others like LiveOps cards to help developers engage more deeply with their audience.

Expanding Commerce Platform

Google Play now collects payments in 150 markets via credit card, direct carrier billing (DCB), Paypal, and gift cards. Direct carrier billing is now enabled across 167 carriers in 64 markets. In 2018, we have focused on expanding our footprint in Africa and Latam with launches in Ghana, Kenya, Tanzania, Nigeria, Peru & Colombia. And users can now buy Google Play credit via gift cards or other means in more 800,000 retail locations around the world. This year, we also launched seller support in 18 new markets bringing the total markets with seller support to 98. Our subscription offering continues to improve with ML-powered fraud detection and even more control for subscribers and developers. Google Play's risk modeling automatically helps detect fraudulent transactions and purchase APIs help you better analyze your refund data to identify suspicious activity.

Maintaining a Safe & Secure Ecosystem

Google Play Protect and our other systems scan and analyze more than 50 billion apps a day to keep our ecosystem safe for users and developers. In fact, people who only download apps from Google Play are nine times less likely to download a potentially harmful app than those who download from other sources. We've made significant improvements in our ability to detect abuse—such as impersonation, inappropriate content, fraud, or malware—through new machine learning models and techniques. The result is that 99% of apps with abusive content are identified and rejected before anyone can install them. We're also continuing to run the Google Play Security Rewards Program through a collaboration with Hacker One to discover other vulnerabilities.

We are continually inspired by what developers build—check out #IMakeApps for incredible examples—and want every developer to have the tools needed to succeed. We can't wait to see what you do next!


          Instructor (Data Science, Artificial Intelligence, Machine Learning) - Cortechma Inc. - Thornhill, ON      Cache   Translate Page   Web Page Cache   
Cortechma Academy team is looking for professors, instructors and engineers with both academically and professionally strong background specializing in one of...
From Indeed - Wed, 01 Aug 2018 16:56:17 GMT - View all Thornhill, ON jobs
          A machine learning system trained on scholarly journals could correct Wikipedia's gendered under-representation problem      Cache   Translate Page   Web Page Cache   

Quicksilver is a machine-learning tool from AI startup Primer: it used 30,000 Wikipedia entries to create a model that allowed it to identify the characteristics that make a scientist noteworthy enough for encyclopedic inclusion; then it mined the academic search-engine Semantic Scholar to identify the 200,000 scholars in a variety of fields; now it is systematically composing draft Wikipedia entries for scholars on its list who are missing from the encyclopedia. (more…)


          There's something eerie about bots that teach themselves to cheat      Cache   Translate Page   Web Page Cache   

One of the holy grails of computer science is unsupervised machine learning, where you tell an algorithm what goal you want it to attain, and give it some data to practice on, and the algorithm uses statistics to invent surprising ways of solving your problem. (more…)


          Business Strategy, Sr. Manager - Hortonworks - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Dallas, TX jobs
          Business Strategy, Sr. Manager - Hortonworks - Atlanta, GA      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Atlanta, GA jobs
          MACHINE LEARNING ENGINEER FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Engineer for Speech related Applications (6 months contract)....
From Huawei Canada - Mon, 18 Jun 2018 23:46:16 GMT - View all Montréal, QC jobs
          MACHINE LEARNING INTERN FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Intern for Speech related Applications....
From Huawei Canada - Mon, 18 Jun 2018 17:50:57 GMT - View all Montréal, QC jobs
          MACHINE LEARNING HARDWARE RESEARCHER OR DEVELOPER - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Hardware Researcher or Developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:32 GMT - View all Montréal, QC jobs
          Machine Learning Software Developer - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. ML Software developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:31 GMT - View all Montréal, QC jobs
          Associate Engineer : Machine Learning - Web Spiders - Kolkata, West Bengal      Cache   Translate Page   Web Page Cache   
We offer free tax consulting through our Chartered Accountants. Want a dynamic, challenging career?...
From Web Spiders - Fri, 27 Jul 2018 09:34:41 GMT - View all Kolkata, West Bengal jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page   Web Page Cache   
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Mon, 14 May 2018 23:57:10 GMT - View all Dallas, TX jobs
          Senior Manager, Software Engineering - DELL - Austin, TX      Cache   Translate Page   Web Page Cache   
Experience with machine learning and artificial intelligence. Learn more about Diversity and Inclusion at Dell here....
From Dell - Wed, 18 Jul 2018 11:23:18 GMT - View all Austin, TX jobs
          Director, Software Engineering - DELL - Austin, TX      Cache   Translate Page   Web Page Cache   
Experience with machine learning and artificial intelligence. Learn more about Diversity and Inclusion at Dell here....
From Dell - Sat, 07 Jul 2018 11:22:08 GMT - View all Austin, TX jobs
          Cloud Solution Architect - Microsoft - Philadelphia, PA      Cache   Translate Page   Web Page Cache   
Machine Learning (SAS, R, Python). Problem-solving mentality leveraging internal and/or external resources....
From Microsoft - Tue, 17 Apr 2018 18:34:17 GMT - View all Philadelphia, PA jobs
          Sizing Hot-Warm Architectures for Logging and Metrics in the Elasticsearch Service on Elastic Cloud      Cache   Translate Page   Web Page Cache   

These are exciting times! Elasticsearch Service on Elastic Cloud recently added support for a wide range of hardware choices and deployment templates, which makes it perfectly suited for efficient handling of logging and metrics related workloads. With all this new flexibility comes a lot of choices to be made. Picking the most appropriate architecture for your use-case and estimating the required cluster size be can be tricky. Don’t worry — we are here to help!

This blog post will teach you about the different architectures that are commonly used for logging and metrics use cases and when to use them. It will also provide guidance on how to size and manage your cluster(s) so you get the most out of them.

What architectures are available for my logging cluster?

In the simplest of all Elasticsearch clusters, all data nodes have the same specification and handle all roles. As this type of cluster grows, nodes for specific tasks are often added, e.g. dedicated master, ingest and machine learning nodes. This takes load off the data nodes and allows them to operate more efficiently. In this type of cluster all data nodes share the indexing and query load evenly, and as they all have the same specification, we often refer to this as a homogenous or uniform cluster architecture.

uniform_cluster.png

Another architecture that is very popular, especially when working with time-based data like logs and metrics, is what we refer to as the hot-warm architecture. This relies on the principle that data generally is immutable and can be indexed into time-based indices. Each index thus contains data covering a specific time period, which makes it possible to manage retention and life cycle of data by deleting full indices. This architecture has two different types of data nodes with different hardware profiles: ‘hot’ and ‘warm’ data nodes.

hot-warm_cluster.png

Hot data nodes hold all the most recent indices and therefore handle all indexing load in the cluster. As the most recent data also typically is the most frequently queried, these nodes tend to get very busy. Indexing into Elasticsearch can be very CPU and I/O intensive, and the additional query load means that these nodes need to be powerful and have very fast storage. This generally means local, attached SSDs.

Warm nodes on the other hand are optimized to handle long-term storage of read-only indices in the cluster in a cost efficient way. They are generally equipped with good amounts of RAM and CPU but often uses local attached spinning disks or SAN instead of SSDs. Once indices on the hot nodes exceed the retention period for those nodes and are no longer indexed into, they get relocated to the warm nodes.

It is important to note that moving data from hot to warm nodes does not necessarily mean that it will be slower to query. As these nodes do not handle any resource intensive indexing at all, they are often able to efficiently serve queries against older data at low latencies without having to utilize SSD based storage.

As data nodes in this architecture are very specialized and can be under high load, it is recommended to use dedicated master, ingest, machine learning and coordinating-only nodes.

Which architecture should I pick?

For a lot of use-cases either of these architectures will work well, and which one to pick is not always clear. There are however certain conditions and constraints that may make one of the architectures more suitable than the other.

The type(s) of storage available to the cluster is an important factor to consider. As a hot/warm architecture requires very fast storage for the hot nodes, this architecture is not suitable if the cluster is limited to the use of slower storage. In this case it is better to use a uniform architecture and spread out indexing and querying across as many nodes as possible.

Uniform clusters are often supported by local spinning disks or SAN attached as block storage, even though SSDs are getting more and more common. Slower storage may not be able to support very high indexing rates, especially when there is also concurrent querying, so it can take a long time to fill up the available disk space. Holding large data volumes per node may therefore only be possible if you have a reasonably long retention period.

If the use-case stipulates a very short retention period, e.g. less than 10 days, data will not sit idle on disk for long once indexed. This requires performant storage. A hot/warm architecture may work, but a uniform cluster with just hot data nodes may be better and easier to manage.

How much storage do I need?

One of the main drivers when sizing a cluster for a logging and/or metrics use case is the amount of storage. The ratio between the volume of raw data and how much space this will take up on disk once indexed and replicated in Elasticsearch will depend a lot on the type of data and how this is indexed. The diagram below shows the different stages the data goes through during indexing.

data_index_lifecycle.png#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

The first step involves transforming the raw data into the JSON documents we will index into Elasticsearch. How much this changes the size of the data will depend on the original format and the structure added, but also the amount of data added through various types of enrichment. This can differ significantly for different types of data. If your logs are already in JSON format and you are not adding any additional data, the size may not change at all. If you on the other hand have text based web access logs, the added structure and information about user agent and location might be considerably larger.

Once we index this data into Elasticsearch, the index settings and mappings used will determine how much space it takes up on disk. The default dynamic mappings applied by Elasticsearch are generally designed for flexibility rather than optimized storage size on disk, so you can save disk space by optimizing the mappings you use through custom index templates. Further guidance around this can be found in the tuning documentation.

In order to estimate how much disk space a specific type of data will take up in your cluster, index a large enough amount of data to make sure you reach the shard size you are likely to use in production. Testing using too small data volumes is a quite common mistake that can give inaccurate results.

How do I balance ingest and querying?

The first benchmark most users run when sizing a cluster is often to determine the maximum indexing throughput of the cluster. This is, after all, a benchmark that is quite easy to set up and run, and the results can also be used to determine how much space the data will take up on disk.

Once the cluster and ingest process has been tuned and we have identified the maximum indexing rate we can sustain, we can calculate how long it would take to fill up the disk on the data nodes if we could keep indexing at maximum throughput. This will give us an indication of what the minimum retention period would be for the node type assuming we want to maximize the use of the available disk space.

It may be tempting to directly use this to determine the size needed, but that would not leave any headroom for querying, as all system resources would be used for indexing. After all, most users are storing the data in Elasticsearch in order to be able to query it at some point and expect good performance when doing so.

How much headroom do we then need to leave for querying? This is a difficult question to give a generic answer to as it depends a lot on the amount and nature of querying that is expected as well as what latencies users expect. The best way to determine this is to run a benchmark simulating realistic levels of querying at different data volumes and indexing rates as described in this Elastic{ON} talk about quantitative cluster sizing and this webinar about cluster benchmarking and sizing using Rally.

Once we have determined how large a portion of the maximum indexing throughput we can sustain while at the same time serve queries to users with acceptable performance, we can adjust the expected retention period to match this reduced indexing rate. If we index at a slower pace, it will take longer to fill up the disks.

This adjustment may give us the ability to handle small peaks in traffic, but generally assumes a quite constant indexing rate over time. If we expect our traffic levels to have peaks and fluctuate throughout the day, we may need to assume the adjusted indexing rate corresponds to to the peak level and even further reduce the average indexing rate we assume each node can handle. In the case where fluctuations are predictable and last for extended periods of time, e.g. during office hours, another option may be to increase the size of the hot zone just for that period.

How do I use all this storage?

In hot-warm architectures, the warm nodes are expected to be able to hold large amounts of data. This also applies to data nodes in a uniform architecture with a long retention period.

Exactly how much data you can successfully hold on a node often depends on how well you can manage heap usage, which often becomes the main limiting factor for dense nodes. As there are a number of areas that contribute to heap usage in an Elasticsearch cluster — e.g. indexing, querying, caching, cluster state, field data and shard overhead — the results will vary between use-cases. The best way to accurately determining what the limits are for your use-case is to run benchmarks based on realistic data and query patterns. There are however a number of generic best practices around logging and metrics use-cases that will help you get as much from your data nodes as possible.

Make sure mappings are optimized

As described earlier, the mappings used for your data can affect how compact it is on disk. It can also affect how much field data you will use and impact heap usage. If you are using Filebeat modules or Logstash modules to parse and ingest your data, these come with optimized mappings out of the box, and you may not need to worry too much about this point. If you however are parsing custom logs and are relying extensively on the ability of Elasticsearch to dynamically map new fields, you should continue reading.

When Elasticsearch dynamically maps a string, the default behaviour is to use multi-fields to map the data both as text, which can be used for case-insensitive free-text search, and keyword, which is used when aggregating data in Kibana. This is a great default as it gives optimal flexibility, but the downside is that it increases the size of indices on disk and the amount of field-data used. It is therefore recommended to go through and optimize mappings wherever possible, as this can make a significant difference as data volumes grow.

Keep shards as large as possible

Each index in Elasticsearch contains one or more shards, and each shard comes with overhead that uses some heap space. As described in this blog post about sharding, smaller shards have more overhead per data volume compared to larger shards. In order to minimize heap usage on nodes that are to hold large amounts of data, it is therefore important to try to keep shards as large as possible. A good rule of thumb is to keep the average shard size for long-term retention at between 20GB and 50GB.

As each query or aggregation runs single-threaded per shard, the minimum query latency will typically depend on the shard size. This depends on data and queries, so can vary even between indices within the same use-case. For a specific data volume and type of data, it is, however, not certain that a larger number of smaller shards will perform better that a single larger shard.

It is important to test the effect of shards size in order to reach an optimum with respect to query usage and minimal overhead.

Tune for storage volume

Efficiently compressing the JSON source can have a significant impact on how much space your data takes up on disk. Elasticsearch by default compresses this data using a compression algorithm tuned for balance between storage and indexing speed, but also offers a more aggressive one as an option – the best_compression codec.

This can be specified for all new indices but comes with a performance penalty of around 5-10% during indexing. The disk space gain can be significant, so it may be a worthwhile trade-off.

If you have followed the advice in the previous section and are force merging indices, you also have the option to apply the improved compression just before the force merge operation.

Avoid unnecessary load

The last thing contributing to heap usage that we are going to discuss here is request handling. All requests that are sent to Elasticsearch are coordinated at the node they arrive. The work is then partitioned and spread out to where the data resides. This applies to indexing as well as querying.

Parsing and coordinating the request and response can result in significant heap usage. Make sure that nodes working as coordinating or indexing nodes have enough heap headroom to be able to handle this.

For nodes tuned for long-term data storage, it often makes sense to let them work as dedicated data nodes and minimize any additional work they need to perform. Directing all queries either to hot nodes or dedicated coordinating only nodes can help achieve this.

How do I apply this to my Elasticsearch Service deployment?

The Elasticsearch Service is currently available on AWS and GCP, and although the same instance configurations and deployment templates are available on both platforms, the specification differs a little. In this section we will look at the different instance configurations and how these fit in with the architectures we discussed earlier. We will also look at how we can go about estimating the size of the cluster needed to support an example use-case.

Available instance configurations

The Elasticsearch Service has traditionally had Elasticsearch nodes backed by fast SSD storage. These are referred to as highio nodes, and have excellent I/O performance. This makes them very well suited as hot nodes in a hot-warm architecture, but they can also be used as data nodes in a Uniform architecture. This is often recommended if you have a short retention period that requires performant storage.

On AWS and GCP highio nodes have a disk to RAM ratio of 30:1, so for every 1 GB of RAM there is 30GB of storage available. Available node sizes on AWS are 1GB, 2GB, 4GB, 8GB, 15GB, 29GB and 58GB, while they GCP the nodes come in the sizes 1GB, 2GB, 4GB, 8GB, 16GB , 32GB and 64GB.

Another node type that has recently been introduced on Elastic Cloud is the storage optimized highstorage node. These are equipped with large volumes of slower storage, and have a 100:1 disk to RAM ratio. A 64GB highstorage node on GCP comes with over 6.2TB of storage while a 58GB node on AWS supports 5.6TB. These node types come in the same RAM sizes as highio nodes on the respective platform.

These nodes are typically used as warm nodes in a hot/warm architecture. Benchmarks on highstorage nodes have shown that this type of node on GCP have a significant performance advantage compared to AWS, even after the difference in size has been accounted for.

Using 2 or 3 availability zones

In most regions, you have an option to choose running on either 2 or 3 availability zones, and you can choose different number of zones per zone in the cluster. When staying within a fixed number of availability zones, the available cluster sizes increase by roughly doubling in size, at least for smaller clusters. If you are open to using either 2 or 3 availability zones you can size in smaller steps as going from 2 to 3 availability zones with the same node size increases capacity by only 50%.

Sizing example: Hot-warm architecture

In this example, we will look at sizing a hot-warm cluster that is able to handle ingestion of 100GB of raw web access logs per day with a retention period of 30 days. We will compare deploying this with Elastic Cloud on AWS and GCP.

Please note that the data used here are just an example, and it is very likely that your use-case will be different.

Step1: Estimate total data volume

For this example, we are assuming that the data is ingested using Filebeat modules and that the mappings therefore are optimized. We are sticking to a single type of data for simplicity in this example. During indexing benchmarks, we have seen that the ratio between the size of raw data and the indexed size on disk is around 1.1, so 100GB of raw data is estimated to result in 110GB of indexed data on disk. Once a replica has been added that doubles to 220GB.

Over 30 days that gives a total indexed and replicated data volume of 6600GB that the cluster as a whole need to handle.

This example assumes 1 replica shard is used across all zones, as this is considered best practice for performance and availability.

Step 2: Size hot nodes

We have run some maximum indexing benchmarks against hot nodes using this data set, and we have seen that it takes a around 3.5 days for disks on highio nodes to fill up on AWS and GCP.

In order to leave some headroom for querying and small peaks in traffic, we will assume we can only sustain indexing at no more than 50% of the maximum level. If we want to be able to fully utilize the storage available on these nodes we therefore need to index into the node during a longer time period, and we therefore adjust the retention period on these nodes to reflect that.

Elasticsearch also needs some spare disk space to work efficiently, so in order to not exceed the disk watermarks we will assume a cushion of 15% extra disk space is required. This is shown in the Disk space needed column below. Based on this, we can determine the total amount of RAM needed for each provider.

Platform Disk:RAM Ratio Days to Fill Effective Retention (days) Data Volume Held (GB) Disk Space Needed (GB) RAM Required (GB) Zone Specification
AWS 30:1 3.5 7 1440 1656 56 29GB, 2AZ
GCP 30:1 3.5 7 1440 1656 56 32GB, 2AZ

Step 3: Size warm nodes

The data that exceeds the retention period on the hot nodes will be relocated to the warm nodes. We can estimate the size needed be calculating the amount of data these nodes need to hold, taking the overhead for high watermarks into account.

Platform Disk:RAM Ratio Effective Retention (days) Data Volume Held (GB) Disk Space Needed (GB) RAM Required (GB) Zone Specification
AWS 100:1 23 5060 5819 58 29GB, 2AZ
GCP 100:1 23 5060 5819 58 32GB, 2AZ

Step 4: Add additional node types

In addition to the data nodes, we generally also need 3 dedicated master nodes in order to make the cluster more resilient and highly available. As these do not serve any traffic, they can be quite small. Initially allocating 1GB to 2GB nodes across 3 availability zones is a good size to start with. Then scale these nodes up to about 16GB across 3 availability zones as the size of the managed cluster grows.

What’s next?

If you haven’t already, start your 14-day free trial of the Elasticsearch Service and try this out! See for yourself how easy it is to set up and manage. If you have any questions, or want additional advice on how to size your Elasticsearch Service on Elastic Cloud, either contact us directly or engage with us through our public Discuss forum.


          Data Scientist (Python, R, Strategy, Machine Learning, AI, DevOps)      Cache   Translate Page   Web Page Cache   
Anson McCade - The City, London - Data Scientist (Python, R, Strategy, Machine Learning, AI, DevOps) My client is heavily expanding and needs experienced Data Scientists... about statistics, artificial intelligence and machine learning then we want to hear from you. The focus of the role will be applying data science methods...
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          ML.Net aims to provide machine learning for .Net developers      Cache   Translate Page   Web Page Cache   

A new machine learning framework from Microsoft is aimed at .Net developers who want to run common machine learning tasks using a cross-platform, open source system. The beta Version 0.4 is now available.

The features in ML.Net

ML.Net was first announced in May 2018. It provides ways for .Net developers to create models for specific tasks and to make them available to .Net applications via high-level APIs for model training and prediction serving.

To read this article in full, please click here


          Data in, intelligence out: Machine learning pipelines demystified      Cache   Translate Page   Web Page Cache   

It’s tempting to think of machine learning as a magic black box. In goes the data; out come predictions. But there’s no magic in there—just data and algorithms, and models created by processing the data through the algorithms.

If you’re in the business of deriving actionable insights from data through machine learning, it helps for the process not to be a black box. The more you understand what’s inside the box, the better you’ll understand every step of the process for how data can be transformed into predictions, and the more powerful your predictions can be.

Devops people speak of “build pipelines” to describe how software is taken from source code to deployment. Just as developers have a pipeline for code, data scientists have a pipeline for data as it flows through their machine learning solutions. Mastering how that pipeline comes together is a powerful way to know machine learning itself from the inside out.

To read this article in full, please click here

(Insider Story)
          [ASAP] Transferability in Machine Learning for Electronic Structure via the Molecular Orbital Basis      Cache   Translate Page   Web Page Cache   

TOC Graphic

Journal of Chemical Theory and Computation
DOI: 10.1021/acs.jctc.8b00636

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Qualcomm's new Snapdragon 670 processor will bring faster machine learning to more people through mid-range phones.
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By combining advanced machine learning and cyber-attack modeling, BAE Systems’ unique solution intends to automatically detect and defeat advanced cyber threats that could currently go undetected. The U.S. Defense Advanced Research Projects Agency (DARPA) has selected BAE Systems to develop data-driven, cyber-hunting tools that detect and analyze cyber threats to help protect extremely large enterprise networks. The contract for Phase 1, 2, and 3 of the program is valued at approximately
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          Notes from Silicon Beach: AI and Hollywood – What is killing you will make you stronger      Cache   Translate Page   Web Page Cache   

“Hollywood and Silicon Valley are in the same business: producing algorithms,” writes artificial intelligence (AI) pioneer Yves Bergquist, one of a new breed of data scientists focused on the entertainment and media business. Scientists like Berquist believe that to survive and thrive, the media and entertainment industry needs to embrace cognitive science. That’s how they can hope to compete with tech companies and address their failing business models.

The cluster of technologies generally called artificial intelligence (AI) or machine learning (ML), including fields such as big data analytics, deep machine learning, semantics and natural language processing, visual and auditory recognition, prediction and personalization, and conversational agents, among others. These tools enable the creation of software that can be taught to learn and program itself – to automate repetitive tasks and to provide insights that were never before possible.

Tech-assisted Content Development

One active area of AI in the industry is content development. For example, the studio-funded think tank, USC Entertainment Technology Center, where Bergquist leads an AI and neuroscience group, is mapping box office returns against elements of the film narrative. Bergquist is working on data breakdowns of movies, as shown in this demo, the work of two Bergquist AI startups, Corto and Novamente:

Another example is Greenlight Essentials, a member of IDEABOOST Network Connect. They have broken down decades of film screenplays into more than 40,000 unique plot elements, analyzing more than 200 million audience profiles to help filmmakers improve scripts, target audiences and improve marketing. Their product’s analytic terminal allows users with neither programming nor mathematics background to explore and discover repeatable patterns from decades of film data.

Scriptonomics is a ML application that breaks down movie scripts by scene, character, location and other components. Writers and producers can leverage insights and comparisons that the tool extracts from its massive database of past successful movies to improve subsequent drafts, as well as aid in making pitches and targeting audiences – as can be seen in this example of Scriptonomics breakdown for Titanic.

Founder Tammuz Dubnov says that Scriptonomics generates a geometric model of a screenplay – its DNA, if you will – to compare and improve elements when compared with financially successful films of the past. As discussed here, Dubnov believes that this data-driven, quantitative filmmaking process will give rise to a new generation of data-assistant content studios that will help create more hits and fewer flops.

RivetAI offers Agile Producer, a pre-production platform that automates script breakdown, storyboard, shot lists, scheduling and budgeting. Before RivetAI, Toronto native Debajyoti Ray built the earlier AI startup, Video AMP. This AI-powered video advertising solution helped him understand how much commercials owe to storytelling. So he decided to build an AI engine based on thousands of movie scripts, both produced and unproduced, which became RivetAI.

Some early RivetAI projects were: Sunspring, a short film starring Thomas Middleditch; a script credited to “Benjamin, an artificially intelligent neural network,” in conjunction with LA-based production company End Cue; “Bubbles,” an animation about Michael Jackson’s chimpanzee that Ray found while analyzing unproduced screenplays, a project Netflix acquired.

RivetAI’s 500 production companies’ customers will feed ever more data to its self-learning system to augment their storytelling efforts. Ray compares RivetAI to AutoCAD – software that began as a drafting tool and has become a central platform for many creative professionals. To that end, RivetAI is developing products for screenwriters, corporate branded content, series television and reality shows. 


A computer monitor with an image of a man on the screen. The man is standing in front of a green background. #source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

A demonstration of the artificial intelligence software, Arraiy, being used to process green screen footage quickly.

Photo by Christie Hemm Klok for The New York Times


Content Creation with an AI Assist

Computer-generated visual effects are widely used in blockbuster movies, TV shows and games. Sensei, Adobe’s AI, is now being deployed across the company’s cloud platforms to automate functions and provide intelligence. The more Sensei is used, the smarter it gets.

Also, 3D software giant AutoDesk is moving towards AI-assisted generative design, which the company used on its own new facility in downtown Toronto. Massive Software, which has been used on Peter Jackson’s massive CG films, now uses AI to automate crowd simulation and other time-sucking tasks. Its Ready to Run Agents are prefabricated AI agents that can be dropped into scenes by visual effects artists, saving time in the creation of CGI characters.

Arraiy is a well-funded Silicon Valley startup that uses computer vision and machine learning to automate time-consuming visual effects like rotosoping, to separate layers of an image to allow manipulation. The Black-Eyed Peas’ music video for their song, “Street Living,” utilized Arraiy to superimpose band members over images from the civil rights era.

The work involved in modeling, texturing, lighting, animation and performance will ultimately be automated with machine learning, says Derek Spears, Emmy Award-winning VFX artist for Game of Thrones. “Then, the next frontier will be AI-driven actor performances.”

Simulating People

We’ve seen Carrie Fischer exhumed into Star Wars movies, using past performances. Now we’re seeing the emergence of simulated video and voice. Rival Theory's RAIN AI creates human-like AI for more than 100,000 game developers and agencies. Lyrebird is a tool for the creation of artificial voices. Adobe has demoed Voco, a prototype that generates speech that sounds like a specific person.

Clarifai is a platform that uses “computer vision,” a form of machine learning, to help customers detect and predict demographics of faces, identify celebrities, and much more. Face2Face offers real-time facial capture and reenactment. Check out this clip of a speech by President Barack Obama which he never gave:

Software pioneer Marc Canter has developed a new AI-based storytelling platform called Instigate, which takes an Instagram or Snapchat story and adds intelligence and interactivity to create what he calls “beings” – who then can have content-enabled conversations with friends.

Canter, who developed Micromind Director multimedia authoring tools, sees Instigate as an AI authoring environment for a new form of storytelling. AI makes Instigate’s beings more intelligent than the standard-issue bots that perform repetitive pre-defined tasks. 

The Ubiquity of AI and ML

Over time, this new layer of AI/ML capabilities will become standard for every company and every product’s technology stack. It will generate billions of dollars for companies across the global business value chain. We can see how media businesses such as digital video, advertising, marketing and VR/AR are already fundamentally driven by AI and ML capabilities, as seen in these examples:

  • Digital Video: AI optimizes video encoding and delivery. Visual and pattern recognition automates editing and content creation. AI-based fingerprinting protects copyright and aids in licensing and micropayments. AI detects “anomalies” like piracy, violence, adult and fake content. AI will lead to almost real-time video quality assessment, which will lead to shorter timelines for content release. IBM’s Watson AI platform released what it called a cognitive movie trailer for the Fox film, Morgan, and has automated highlight reels for the World Cup and other sports events.
  • VR and AR: These applications depend on AI to create viable experiences, and are closely aligned with visual effects and game design. Cloud providers Google, Amazon and Microsoft, all of whom are committed to AR and VR as an engine of growth, are embedding AI into the platforms that will increasingly power immersive applications and experiences.

In the end, Hollywood is just like any other industry – as investor Ben Evans put it, “eventually, pretty much everything will have ML somewhere inside and no one will care.”


Two women standing face to face and between them is a glass wall.#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

The cognitive trailer for the AI thriller film Morgan was created with the help of IBM's AI platform, Watson.


Nick DeMartino is a Los Angeles-based media and technology consultant. He served as Senior Vice President of the American Film Institute. He has been part of the IDEABOOST team since its launch in 2012, now serving as chair of its Investment Advisory Group.


          Data Science Analyst - Strategic Data Solutions - Apple - Austin, TX      Cache   Translate Page   Web Page Cache   
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          Data Science Analyst - Strategic Data Solutions - Apple - Austin, TX      Cache   Translate Page   Web Page Cache   
We apply data science and machine learning to drive strategic impact across multiple lines of business at Apple....
From Apple - Fri, 06 Jul 2018 13:47:35 GMT - View all Austin, TX jobs
          Sr Software Engineer - Applied Machine Learning - Apple - Austin, TX      Cache   Translate Page   Web Page Cache   
We work on many high-impact projects that serve various Apple lines of business. Understanding of machine learning, statistics....
From Apple - Fri, 15 Jun 2018 01:48:26 GMT - View all Austin, TX jobs
          Director, Customer Service Product and Tools - Kabam - Austin, TX      Cache   Translate Page   Web Page Cache   
Enthusiastic about the latest mobile trends and emerging technologies (IE Machine Learning, AI). Providing leadership and supporting for the technology...
From Kabam - Thu, 24 May 2018 02:31:26 GMT - View all Austin, TX jobs
          CSIS RIST Relativity Project Coordinator - CSIS Lead Investigator - Citi - Tampa, FL      Cache   Translate Page   Web Page Cache   
Diversity is a key business imperative and a source of strength at Citi. Degree in Computer Science, Machine Learning, Information Retrieval or related field,...
From Citi - Sun, 05 Aug 2018 06:14:57 GMT - View all Tampa, FL jobs
          MACHINE LEARNING ENGINEER FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Engineer for Speech related Applications (6 months contract)....
From Huawei Canada - Mon, 18 Jun 2018 23:46:16 GMT - View all Montréal, QC jobs
          MACHINE LEARNING INTERN FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Intern for Speech related Applications....
From Huawei Canada - Mon, 18 Jun 2018 17:50:57 GMT - View all Montréal, QC jobs
          MACHINE LEARNING HARDWARE RESEARCHER OR DEVELOPER - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Hardware Researcher or Developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:32 GMT - View all Montréal, QC jobs
          Machine Learning Software Developer - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. ML Software developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:31 GMT - View all Montréal, QC jobs
          Royal Caribbean Introduces SoundSeeker      Cache   Translate Page   Web Page Cache   

Published in: Cruise News

Sound SeekerRoyal Caribbean International has designed and built a first-of-its-kind tool that transforms photos into an original, shareable soundtrack with a video to match. More than a year in the making, SoundSeeker is powered by artificial intelligence.

The tool is specifically designed to use machine learning to seamlessly create original soundtracks based on the content of each photograph, the company said. 

By simply visiting www.SoundSeeker.com, users can upload three photos of their choice, and the AI analyzes them based on color, landscape, backdrop, emotion, body language and facial expression. SoundSeeker then turns them into a shareable and soundtrack – virtually DJing life’s most brag-worthy moments, Royal Caribbean said. 

“SoundSeeker is the latest proof point of Royal Caribbean innovation and how we focus it on delivering unexpected, memorable experiences; whether that is the SkyPad, which uniquely combines bungee jumping with virtual reality or live streaming your favorite shows from the middle of the ocean using VOOM, the fastest internet at sea,” said Jim Berra, chief marketing officer, Royal Caribbean International. “People of all ages crave new ways to share their best experiences on social media. This unprecedented tool allows you to put a completely unique, multisensory spin on sharing those memories – now friends and followers can see and hear your life’s adventures.” 

Royal Caribbean teamed up with experts from Berklee College of Music, and technologists from around the world, to create the unique song generator.

“We were excited to work with Royal Caribbean International on this new technological innovation, and in the process, redefine what creative collaboration means," said Panos A. Panay, Berklee vice president for Innovation and Strategy and managing director of BerkleeICE. “The work of BerkleeICE expands our students’ definition of what can be accomplished with music education by pushing the boundaries of creative expression utilizing technology. By harnessing AI to develop customized soundtracks for treasured memories, together, we have created a new way for people to share their experiences with one another.”

SoundSeeker uses machine learning, an artificial intelligence technique that enables computers to simulate human intelligence and make decisions on their own without explicit instructions. The learning process entailed more than 600 hours in which Royal Caribbean and a team of musicians and technologists reviewed hundreds of music tracks along with 10,000 photos, matching each of the 2.5 million combinations to one of 10 moods.

The AI in SoundSeeker uses Google Cloud Vision to identify objects, facial expressions and colors in a user’s photo by referencing the roadmap developed by the leaders in music theory at Berklee. SoundSeeker then finds the musical elements corresponding to each mood in the photo to compose a genuinely distinct audio and visual photo album. The Royal Caribbean tool is equipped to generate over one million unique tracks, based on custom base tracks, composed exclusively for the cruise line. The customized tracks take inspiration from a wide variety of music, including 90s hip-hop, rock, modern and electronic dance music. 


          Offer - Machine Learning Training in Austin - USA      Cache   Translate Page   Web Page Cache   
If you are looking for the best software training institute and getting trouble for searching the best Calfre is the best website for your solution. Calfre was well experienced in search engine services and shows the best institutes In your city. For example your search is like Machine Learning training in Austin. then calfre shows top trending institutes for Oracle training. https://www.calfre.com/USA/Texas/Austin/Machine-Learning-Training/listing
          iOS Developer - PGS SOFTWARE - Rzeszów, podkarpackie      Cache   Translate Page   Web Page Cache   
Augmented Reality, Machine Learning, iBeacons, Top Level Security. Elastyczne godziny pracy....
Od PGS SOFTWARE - Wed, 08 Aug 2018 14:51:19 GMT - Pokaż wszystkie Rzeszów, podkarpackie oferty pracy
          Economist - Forecasting - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience with machine learning applications. We are breaking fresh ground, pioneering in a program that is crucial for future Amazon growth, and our business...
From Amazon.com - Wed, 27 Jun 2018 07:21:23 GMT - View all Seattle, WA jobs
          Multistage and Elastic Spam Detection in Mobile Social Networks through Deep Learning      Cache   Translate Page   Web Page Cache   
While mobile social networks (MSNs) enrich people's lives, they also bring many security issues. Many attackers spread malicious URLs through MSNs, which causes serious threats to users' privacy and security. In order to provide users with a secure social environment, many researchers make great efforts. The majority of existing work is aimed at deploying a detection system on the server and classifying messages or users in MSNs through graph-based algorithms, machine learning or other methods. However, as a kind of instant messaging service, MSNs continually generate a large amount of user data. Without affecting the user experience, with existing detection mechanisms it is difficult to implement real-time detection in practical applications. In order to realize real-time message detection in MSNs, we can build more powerful server clusters or improve the utilization rate of computing resources. Assuming that computing resources of servers are limited, we use edge computing to improve the utilization rate of computing resources. In this article, we propose a multistage and elastic detection framework based on deep learning, which sets up a detection system at the mobile terminal and the server, respectively. Messages are first detected on the mobile terminal, and then the detection results are forwarded to the server along with the messages. We also design a detection queue, according to which the server can detect messages elastically when computing resources are limited, and more computing resources can be used for detecting more suspicious messages. We evaluate our detection framework on a Sina Weibo dataset. The results of the experiment show that our detection framework can improve the utilization rate of computing resources and can realize real-time detection with a high detection rate at a low false positive rate.
          Word-Fi: Accurate Handwrite System Empowered by Wireless Backscattering and Machine Learning      Cache   Translate Page   Web Page Cache   
Word-Fi is a handwriting input system, driven by wireless backscattering technology and machine learning methods. It could effectively mitigate the surrounding noise and extract the weak signals incurred by tiny writing gestures accurately. Leveraging our customized wireless backscattering system, Word-Fi could be noise tolerant across relatively complex environments, especially when multiple persons are presented around, which significantly differs from status quo wireless sensing systems that suffer from multi-user presentation. For weak signal extraction, Word- Fi incorporates an efficient feature selection scheme for classification and improves the classifier by fully exploiting the physical layer information. After using the word suggestion module, it could recognize writing words with fairly high accuracy (above 90 percent) across different volunteers (7-10).
          Ανακοινώθηκε και επίσημα το νέο Android 9 ή αλλιώς "Android Pie"      Cache   Translate Page   Web Page Cache   

Η Google ανακοίνωσε την νέα έκδοση του Android, την έκδοση 9, η οποία έχει και αυτή κωδική ονομασία γλυκού, όπως και οι προηγούμενες εκδόσεις. Έτσι μετά το Oreo της έκδοσης 8, η έκδοση 9 είναι η Pie, δηλαδή τάρτα. Η νέα αυτή έκδοση επικεντρώνει στον τομέα της τεχνητής νοημοσύνης με πολλά από τα νέα χαρακτηριστικά να προσαρμόζονται στον χρήστη της συσκευής, μαθαίνοντας από τις συνήθειές του.

 

Η Google ελπίζει ότι με την βοήθεια της τεχνητής νοημοσύνης, ο χρήστης θα μπορεί να κάνει περισσότερα πράγματα με την συσκευή του, κάνοντας ταυτόχρονα λιγότερες κινήσεις προκειμένου να την προσαρμόσει στις δικές του ανάγκες. Η Google ισχυρίζεται ότι με την νέα έκδοση του Android, μια συσκευή είναι εξυπνότερη, ταχύτερη και καλύτερα προσαρμοσμένη στον χρήστη της.

 

Το Android 9 έρχεται με πλήθος νέων χαρακτηριστικών. Από αυτά η Google εστιάζει σε μερικά από αυτά. Έτσι τα "Adaptive Brightness" και "Adaptive Battery", αξιοποιούν τεχνητή νοημοσύνη προκειμένου να μειώσουν την κατανάλωση της μπαταρίας της συσκευής, βασιζόμενα στις μέχρι εκείνη την στιγμή διαθέσιμες πληροφορίες για το πως χρησιμοποιεί ο χρήστης την συσκευή του. Το "App Actions" είναι ένα εργαλείο που τρέχει στο παρασκήνιο και αξιοποιεί επίσης τεχνητή νοημοσύνη, προκειμένου να μαντέψει ποια θα είναι η επόμενη εφαρμογή που θα θελήσει να χρησιμοποιήσει ο χρήστης.

 

36562800_Android9piefeatures1.jpg#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

 

Το Android 9 διαθέτει επίσης ένα νέο σύστημα πλοήγησης εφαρμογών, το οποίο ουσιαστικά αντικαθιστά το κουμπί επιλογής εφαρμογών που βρίσκεται σε πολλά σύγχρονα smartphones. Με ένα απλό swipe προς τα πάνω, θα σας δοθεί μια γρήγορη προβολή όλων των εφαρμογών που είναι ανοιχτές στη συσκευή σας, με τη δυνατότητα να μετακινείστε μεταξύ τους κατά βούληση. Ενώ βρίσκεστε σε αυτή την προβολή εφαρμογών, μπορείτε να επιλέξετε κάποιο κείμενο και να θέσετε την τεχνολογία τεχνητής νοημοσύνης του Android 9 να λειτουργήσει. Έτσι, για παράδειγμα, αν επιλέξετε το όνομα ενός εστιατορίου, το Android 9 μπορεί να σας εμφανίσει ένα κουμπί με κριτικές στο Yelp, πέραν των τυπικών επιλογών αντιγραφής, αναζήτησης και κοινής χρήσης.

 

Ένα ακόμα σημείο στο οποίο η Google θέλει να βοηθήσει τους χρήστες των συσκευών με Android, είναι στον έλεγχο του χρόνου που περνάνε με την συσκευή τους και ειδικότερα με συγκεκριμένες εφαρμογές. Με πολύ κόσμο να εθίζεται στην χρήση ενός smartphone, η Google έρχεται και προσφέρει την δυνατότητα, μέσω του χαρακτηριστικού "Digital Wellbeing", να θέτουμε όρια στον χρόνο χρήσης της συσκευής μας ή στον χρόνο που ξοδεύουμε ασχολούμενοι με κάποια εφαρμογή. Μέσω του Digital Wellbeing και με την μορφή ενός κυκλικού διαγράμματος μπορούμε να δούμε ποιες εφαρμογές ή υπηρεσίες χρησιμοποιούμε περισσότερο, επιτρέποντάς μας να διακόψουμε τις εφαρμογές αυτές ή να θέσουμε όρια στον χρόνο χρήσης αυτών. Μια νέα λειτουργία "Μην ενοχλείτε", επιτρέπει την σίγαση όλων των ειδοποιήσεων, τόσο αυτών που εμφανίζονται στην οθόνη, όσο και των ηχητικών, ενώ η ενεργοποίηση της λειτουργίας "Wind Down", γυρνάει την οθόνη σε ασπρόμαυρη λειτουργία, σε μια προσπάθεια να οδηγηθεί πιο εύκολα ο χρήστης στην επιλογή να κλείσει την συσκευή του.

 

960273632_Android9piefeatures2.jpg#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

 

Το Android 9 Pie είναι διαθέσιμο ήδη από σήμερα στους κατόχους συσκευών Pixel, με τους κατόχους άλλων συσκευών να πρέπει να περιμένουν λίγο καιρό ακόμα. Η Google ελπίζει να είναι σε θέση να διαθέσει το Android 9 στους συνεργάτες της κάποια στιγμή μέσα στο έτος.

 

Περισσότερα για το Android 9 Pie μπορείτε να διαβάσετε εδώ: Android 9 Pie

Η λίστα με τα νέα χαρακτηριστικά του Android 9 Pie, όπως αναγράφεται στην παραπάνω σελίδα, είναι η εξής:

 

 

See all features

Accessibility Menu: With Android 9's new accessibility menu, common actions like taking screenshots and navigating with one hand are now easier for motor impaired users.

Select to Speak - OCR in Camera View: With Select to Speak, you can select text on the screen and the content will be read aloud. Now, Android 9 has added added OCR support for S2S in Camera and Pictures to make text even more accessible. Simply select text when using the camera or in picture, and the text will be highlighted and read aloud.

Sound amplifier: This new Accessibility Service makes it easier to understand conversations by dynamically adjusting over 100 settings to boost the audio in scenarios such as a loud restaurant, bar, or concert.

Battery Saver: Battery Saver keeps your charge going longer than ever by turning off features like the Always-On display. Plus, you have more control over when it comes on - so you can go further on one charge.

Adaptive Battery: This feature uses machine learning to predict which apps you'll use in the next few hours and which you likely won't, so your phone only spends battery power on the apps you care about.

Adaptive Brightness: With Adaptive Brightness, your phone learns how you set your screen's brightness in different lighting environments and automatically does it for you over time.

Background restrictions: Now, you'll see recommendations in Settings to restrict certain apps that use too much battery, so you can have more control over your battery.

Multi-camera support: With Android 9, developers can now create immersive experiences using streams from two or more physical cameras, such as on devices with either dual-front or dual-back cameras. Examples include depth, bokeh, stereo vision, and more.

External camera support: Android 9 now supports external USB / UVC cameras on certain devices.

Do Not Disturb: Improvements to Do Not Disturb to silence not just notification sounds, but also all the visual interruptions. Calls from starred contacts will still come through, so you don't have to worry about missing something urgent.

App dashboard: Get a daily view of the time spent on your phone, how frequently you use different apps, and how many notifications you get.

Wind Down: Set a daily schedule to get your phone ready for bed. Grayscale fades your screen to gray while Do Not Disturb silences notifications for a restful sleep.

App timers: App timers let you set daily time limits for your apps. When you reach the limit, the app is paused for the rest of the day.

Display cutout: Support for devices with cutouts to make use of available screen space.

Edge-to-edge screens: Support for devices with 18:9 and taller aspect ratios, and devices with display cutouts.

Multiple users on dedicated devices: Android 9 makes it easy for users to share a single device, good for shift workers or public kiosks.

Work tab in launcher: Now, you can visually separate your work apps. Tap on the work tab to see work apps all in one place, and turn them off with a simple toggle when you get off work.

Postpone Over-the-air (OTA) updates: Android 9 now provides the ability for Enterprise IT admins to define freeze periods up to 90 days during which time devices in their fleet will not update the Android OS. This ensures their devices states remain unchanged during critical time like holidays.

Multiple Bluetooth connections: With Android 9, you can connect up to five Bluetooth devices and switch between these devices seamlessly. Incoming phone calls will be sent to all connected Bluetooth devices that can accept, so you'll never miss a call.

Sound delay reporting: Android 9 offers support for headsets with sound delay reporting, so video on your device and audio on your headphones can always stay in sync.

Volume memory per Bluetooth device: Android 9 will now remember the last volume you set for each of your Bluetooth devices. No more blasting music too loudly when you reconnect to your car or headphones.

HDR: Android 9 adds built-in support for High Dynamic Range (HDR) VP9 Profile 2, so you can watch HDR-enabled movies on YouTube and Google Play Movies. HDR improves the brightness and color range of video to improve the picture quality and experience.

HD Audio: Improved performance and support for HD audio delivering clearer, sharper, and richer quality sound.

HEIF: Android 9 now supports HEIF photos on the Android platform to improve compression of pictures and reduce the amount of storage needed.

Notification enhancements for messaging: Now, messaging apps can provide suggested 'smart replies' in the notification, so you can respond in a tap. Plus, any inline reply drafts won't disappear if you navigate away, and you'll be able to see images sent from your friends right in the notification.

Manage Notifications: You now have a quick way to turn off notifications from a range of apps, so you only receive those that are helpful to you. You'll also get a smart prompt if you're swiping away certain notifications whether you want to keep receiving them.

Android Backups: Android 9 enables encryption of Android backups with a client-side secret (the device PIN, pattern or password) for greater security.

Android biometric prompt: Android 9 introduces a number of new security features, including a standardized biometric authentication prompt to provide a more consistent authentication experience across Android.

Android Protected Confirmation: On compatible hardware, apps can now use UI controlled by the secure hardware to get your confirmation for a sensitive transaction, such as making a payment.

StrongBox: On compatible hardware, apps can now take advantage of tamper-resistant hardware to protect their private keys, making it harder than ever for malware to steal their credentials.

Privacy enhancements: Android 9 safeguards privacy in a number of new ways. Now, Android will restrict access to your phone's microphone, camera, or other sensors when an app is idle or running in the background. (If an app does need to access a sensor, it will show a persistent notification on your phone.) Android 9 also brings important improvements that protect all web communications and offer private web surfing.

At-a-Glance on Always-on-Display: See things like calendar events and weather on your Lock Screen and Always-on Display.

Redesigned Quick Settings: A more consistent user experience for Quick Settings with all toggles, plus an updated visual design and added informational subtext.

Volume controls: Simpler, more accessible volume controls let you control media volume instantly, as well as quickly toggle call and notification volume settings.

Screenshots: Now, you can take screenshots easily from the power menu and draw, annotate, or crop them quickly.

Rotation: Get more control over your phone’s display rotation with a simple button that confirms when you’d like to change the rotation on your device - even when your orientation is locked.

New system navigation: Re-design of Android's system navigation to help make it simpler to search and move between apps. Swipe up from anywhere to see full-screen previews of recently used apps, swipe left and right to easily navigate between them, and tap on one to jump in.

App Actions: App Actions predicts what you’ll want to do next based on your context and displays that action right on your phone, saving you time.

Slices: Interactive snippets of your favorite apps can be surfaced in different places, like Google Search.

Overview Selection: Long-press to select text or image in Overview mode and see actions based on what you've selected (for example, an option to route to an address with Google Maps or share for an image).


          Economist - Forecasting - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience with machine learning applications. We are breaking fresh ground, pioneering in a program that is crucial for future Amazon growth, and our business...
From Amazon.com - Wed, 27 Jun 2018 07:21:23 GMT - View all Seattle, WA jobs
          Product Manager, Marketplace Growth - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sat, 14 Jul 2018 06:23:30 GMT - View all New York, NY jobs
          QA Engineer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Fri, 08 Jun 2018 16:35:13 GMT - View all New York, NY jobs
          Data Scientist - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Tue, 05 Jun 2018 16:15:49 GMT - View all New York, NY jobs
          Back End Engineer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sun, 03 Jun 2018 06:21:49 GMT - View all New York, NY jobs
          UI Engineer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sun, 27 May 2018 20:27:03 GMT - View all New York, NY jobs
          AI Conversation Designer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sat, 14 Apr 2018 06:15:32 GMT - View all New York, NY jobs
          Sr.SDE - Amazon.com - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Build Products for amazon external facing and internal facing systems. The team uses various content classification and machine learning algorithms for solving...
From Amazon.com - Wed, 18 Jul 2018 19:20:37 GMT - View all Bellevue, WA jobs
          Software Development Engineer: Machine Learning Service - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Build, operate and optimize critical AWS services enabling machine learning capabilities for internal use and by AWS customers....
From Amazon.com - Wed, 08 Aug 2018 01:22:33 GMT - View all Seattle, WA jobs
          Software Development Engineer - Prime Video Customer Growth - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience building machine learning enabled services. Amazon is an Equal Opportunity-Affirmative Action Employer - Minority/Female/Disability/Vet....
From Amazon.com - Sat, 04 Aug 2018 01:28:01 GMT - View all Seattle, WA jobs
          Principal Product Manager, Amazon Process Automation - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience implementing machine learning based solutions. You will be working closely with businesses and understanding the requirements, working actively with...
From Amazon.com - Thu, 02 Aug 2018 19:20:59 GMT - View all Seattle, WA jobs
          Product Manager - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
You will be working closely with businesses and understanding the requirements, working actively with Technology, Machine learning and Operations teams, making...
From Amazon.com - Thu, 02 Aug 2018 19:20:51 GMT - View all Seattle, WA jobs
          Machine Learning in Node.js With TensorFlow.js      Cache   Translate Page   Web Page Cache   

TensorFlow.js is a new version of the popular open-source library which brings deep learning to javascript. Developers can now define, train, and run machine learning models using the high-level library API .

Pre-trained models mean developers can now easily perform complex tasks like visual recognition , generating music or detecting human poses with just a few lines of JavaScript.

Having started as a front-end library for web browsers, recent updates added experimental support for Node.js. This allows TensorFlow.js to be used in backend JavaScript applications without having to use python.

Reading about the library, I wanted to test it out with a simple task…

Use TensorFlow.js to perform visual recognition on images using JavaScript from Node.js

Unfortunately, most of the documentation and example code provided uses the library in a browser. Project utilities provided to simplify loading and using pre-trained models have not yet been extended with Node.js support. Getting this working did end up with me spending a lot of time reading the Typescript source files for the library. :-1:

However, after a few days’ hacking, I managed to get this completed ! Hurrah!

Before we dive into the code, let’s start with an overview of the different TensorFlow libraries.


          Sr. Risk Manager, Product Quality - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience working with Data Scientists and Economists to develop and improve Machine Learning models. Author and edit risk assessments and program updates for...
From Amazon.com - Wed, 01 Aug 2018 08:07:28 GMT - View all Seattle, WA jobs
          MACHINE LEARNING ENGINEER FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Engineer for Speech related Applications (6 months contract)....
From Huawei Canada - Mon, 18 Jun 2018 23:46:16 GMT - View all Montréal, QC jobs
          MACHINE LEARNING INTERN FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Intern for Speech related Applications....
From Huawei Canada - Mon, 18 Jun 2018 17:50:57 GMT - View all Montréal, QC jobs
          MACHINE LEARNING HARDWARE RESEARCHER OR DEVELOPER - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Hardware Researcher or Developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:32 GMT - View all Montréal, QC jobs
          Machine Learning Software Developer - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. ML Software developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:31 GMT - View all Montréal, QC jobs
          [آموزش] دانلود Lynda Siemens NX: Surfacing - آموزش زیمنس ان ایکس: کفپوش      Cache   Translate Page   Web Page Cache   

دانلود Lynda Siemens NX: Surfacing - آموزش زیمنس ان ایکس: کفپوش#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

نرم‌افزار اِن ایکس که سابقاً یونیگرافیکس (Unigraphics) نامیده می‌شد، محصول شرکت زیمنس پی ال ام آمریکا (شاخه نرم‌افزاری و اتوماسیون شرکت زیمنس آلمان)، یکی از قوی‌ترین نرم‌افزارهای جامع طراحی به کمک رایانه، مهندسی به کمک رایانه و ساخت به کمک رایانه است. این نرم‌افزار در سال ۱۹۶۰ توسط شرکت مک‌دانل داگلاس که سازندهٔ هواپیما و فضاپیما بوده، معرفی شد و تاکنون در کاربردهای متنوعی از طراحی تا ساخت مورد استفاده قرار گرفته‌ است. نرم‌افزار یونیگرافیکس به دلیل امکانات فراوانی که دراختیار کاربر قرار می‌دهد، موجب ارائهٔ سریع‌تر و ارزان‌تر محصولات پیچیده و کاهش هزینه‌های طراحی تا ساخت محصول شده‌است.در ...


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          Larry Ellison Announces Availability of Oracle Autonomous Transaction Processing      Cache   Translate Page   Web Page Cache   

According to a recent press release, “Oracle Executive Chairman and CTO Larry Ellison today marked a major milestone in the company’s autonomous strategy with the availability of the latest Oracle Autonomous Database Cloud Service, Oracle Autonomous Transaction Processing. Leveraging innovative machine learning and automation capabilities, Oracle Autonomous Transaction Processing delivers unprecedented cost savings, security, availability, […]

The post Larry Ellison Announces Availability of Oracle Autonomous Transaction Processing appeared first on DATAVERSITY.


          Traffic Management Systems Market Will Be Worth over US $75,228.8 Mn by 2028      Cache   Translate Page   Web Page Cache   

Smart City Initiatives to Augur Well for the Global Traffic Management Systems Market.

Valley Cottage, NY -- (SBWIRE) -- 08/08/2018 -- Future Market Insights (FMI) has published a new report on the global traffic management systems market. The report has been titled "Traffic Management Systems Market: Global Industry Analysis (2013-2017) and Opportunity Assessment (2018-2028)." The global traffic management systems market is likely to foresee an extensive growth over the course of the forecast period. This growth can be attributed to the burgeoning congestion levels that offer tremendous potential for traffic management systems. The traffic management systems market is also increasing due to increasing government focus on boosting safety as well as expanding the smart city initiatives along with rapid advancements in technology.

In order to capitalise on this opportunity, the players operating in the market are launching new products and entering into mergers and acquisitions in order to acquire new technology and stay competitive in the market. For instance, in May 2015, IBM Corporation launched a transportation management solution for the New Jersey Turnpike Authority (NJTA). The launch is aimed at reducing traffic congestions and improving the traffic flow employing enhanced system that assimilates the Internet of Things to provide advanced analytics and predictive capabilities. Moreover, the system provides central management of approximately 900 devices including drum and portable signs, variable messages, traffic cameras and hybrid displays. The other companies operating in the market are Siemens AG, Thales Group Ad, Mitsubishi Electric Corporation, Kapsch Trafficcom, Iskra, Telegra, SWARCO, and SICE, among several others.

Request to View Sample of Research Report @ https://www.futuremarketinsights.com/reports/sample/rep-gb-6469

According to the report, the global traffic management system market is expected to witness a CAGR of 18.2% from 2018 to 2028. The market is expected to reach a worth of US$ 14, 178.4 Mn in 2018 and touch a valuation of US$ 75,228.8 Mn by the end of 2028.

Technological Advancements to Trigger Adoption Rate of Traffic Management Systems

With the growing traffic congestion levels across cities, the implementation of TMS is increasing exponentially. This growing adoption has induced the development of advanced traffic management system devices as well as software to provide extraordinary capabilities and highly improved performances. For instance, the current technologies in TMS include integrated machine learning, wireless charging sensors, integrated toll management systems, weather monitoring solutions, IOT based ITS, ITS for connected vehicles, IOT for autonomous vehicles, and many more.

Owing to the numerous benefits of traffic management systems, governments across various countries in the world are actively engaging themselves in the deployment of smart traffic management systems. This is being done in order to smoothen traffic flow by reducing traffic congestion and reducing pollution levels across cities, by prioritising traffic in accordance with real-time traffic information. For instance, in July 2017, Miami-Dade County signed a smart traffic contract of US$ 11.1 Mn with Econolite Control Products. As part of this contract, the company will install 300 new smart traffic signals that will work on a new technology, namely, changing the flow of vehicles. The traffic signals cover nearly 10% of all Miami-Dade traffic lights. The growing initiatives for successful traffic management and increasing investments are projected to bode well for the global traffic management systems market in the long run.

Request Report for Table of Contents @ https://www.futuremarketinsights.com/askus/rep-gb-6469

Budget Constraints to Restrain Market Development

Notwithstanding all the benefits offered by traffic management systems, the restricted budgets allocated to the traffic industry remain a serious issue. Local authorities are usually budget-constrained, and try to save costs by avoiding the adoption of advanced traffic management systems. Furthermore, the authorities of some developing and underdeveloped regions do not have sufficient budgets to implement the systems across certain countries. Moreover, the additional costs involved in installation, repairs, and maintenance of these systems will increase the overall expenses, eventually deteriorating the situation. Consequently, budgetary restrictions and high costs involved with advanced traffic management systems are impacting the market in a negative manner, thereby encumbering the growth of the market.

For more information on this press release visit: http://www.sbwire.com/press-releases/traffic-management-systems-market-will-be-worth-over-us-752288-mn-by-2028-1025685.htm

Media Relations Contact

Abhishek Budholiya
Manager
Future Market Insights
Telephone: 1-347-918-3531
Email: Click to Email Abhishek Budholiya
Web: https://www.futuremarketinsights.com

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          Principal Program Manager - Microsoft - Redmond, WA      Cache   Translate Page   Web Page Cache   
Our internal customers use machine learning models to analyze multi-exabyte datasets. The Big Data team builds solutions that enable customers to tackle...
From Microsoft - Sat, 28 Jul 2018 02:13:20 GMT - View all Redmond, WA jobs
          Senior Software Engineer - Microsoft - Redmond, WA      Cache   Translate Page   Web Page Cache   
Experience with leveraging machine learning and AI for Analytics. The Big Data Fundamentals team focuses on Engineering systems, Advanced data Analytics /...
From Microsoft - Fri, 27 Apr 2018 19:10:03 GMT - View all Redmond, WA jobs
          Software Development Manager - Core Video Delivery Technologies, Prime Video - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Strong business and technical vision. Experience in machine learning technologies and big data is a plus. We leverage Amazon Web Services (AWS) technologies...
From Amazon.com - Thu, 02 Aug 2018 19:21:25 GMT - View all Seattle, WA jobs
          Solutions Architect - Amazon Web Services - Amazon.com - San Francisco, CA      Cache   Translate Page   Web Page Cache   
DevOps, Big Data, Machine Learning, Serverless computing etc. High level of comfort communicating effectively across internal and external organizations....
From Amazon.com - Thu, 26 Jul 2018 08:17:05 GMT - View all San Francisco, CA jobs
          Machine Learning leveraging NVIDIA GPUs with Bitfusion on VMware vSphere (Part 2 of 2)      Cache   Translate Page   Web Page Cache   

In Part 1 we described the solution components and the test cases. In this part we will look a the results from our testing. Benchmark: tf_cnn_benchmarks suite (TensorFlow)   The testing was done with tf_cnn_benchmarks, one of Tensorflow benchmark suites. This benchmark suite is designed for performance, since its models utilize the strategies employed in

The post Machine Learning leveraging NVIDIA GPUs with Bitfusion on VMware vSphere (Part 2 of 2) appeared first on Virtualize Applications.


          Machine Learning/AI Engineer - Groom & Associates - Montréal, QC      Cache   Translate Page   Web Page Cache   
Expérience avec tensorflow ou d'autres backends, keras ou autres frameworks, scikit-learn, OpenCV, Pandas. Experience with tensorflow or other backends, keras...
From Groom & Associates - Thu, 07 Jun 2018 14:58:16 GMT - View all Montréal, QC jobs
          Data Scientists / AI & Machine Learning Engineer - IVADO Labs - Montréal, QC      Cache   Translate Page   Web Page Cache   
Experience implementing AI/data science algorithms using one or more of the modern programming languages/frameworks (e.g., Python, Pandas, Scikit-learn,...
From IVADO Labs - Sat, 05 May 2018 03:10:45 GMT - View all Montréal, QC jobs
          Platform Developer, Machine Learning - Kinaxis - Ottawa, ON      Cache   Translate Page   Web Page Cache   
Experience with Machine Learning projects, familiarity with platforms or languages such as scikit-learn, Pandas, NumPy, SciPy, R, TensorFlow....
From Kinaxis - Wed, 08 Aug 2018 20:38:15 GMT - View all Ottawa, ON jobs
          Machine Learning Developer - Kinaxis - Ottawa, ON      Cache   Translate Page   Web Page Cache   
Experience with ML platforms and languages including scikit-learn, Pandas, NumPy, SciPy, Python, R woult be an asset....
From Kinaxis - Wed, 08 Aug 2018 20:38:15 GMT - View all Ottawa, ON jobs
          Hybrid Smart Parking Platform Industry Research Report and Growth Trends 2018-2025      Cache   Translate Page   Web Page Cache   

In terms of consumption side, this report focuses on the consumption of Hybrid Smart Parking Platform by regions and application. The key regions like North America, Europe, Asia-Pacific, Central & South America, Middle East and Africa etc.

City of Industry, CA -- (SBWIRE) -- 08/09/2018 -- This study focuses on the production side and consumption side of Hybrid Smart Parking Platform, presents the global Hybrid Smart Parking Platform market size by manufacturers, regions, type and application, history breakdown data from 2013 to 2018, and forecast to 2025. In terms of production side, this report researches the Hybrid Smart Parking Platform capacity, production, value, ex-factory price, growth rate, market share for major manufacturers, regions (or countries) and product type.

Hybrid smart parking platform helps in optimizing parking resources with continuous streaming of data from streets. It offers real time analysis of data and accurate results on parking occupancy based on multiple data sources.

Smart parking solutions are a need for today owing to the increasing number of vehicles and the lack of parking spaces. Many companies are investing into the smart parking management market. Streetline has been recognized by Frost & Sullivan with the global product line strategy leadership award for the year 2016. Streetline uses machine learning techniques to deploy hybrid smart parking platform in order to merge data that is collected for real time parking guidance and analytics. Streetline is considered to be a world leader in smart parking solutions and management.

North America region holds the largest market share of global hybrid smart parking platform market followed by Europe and Asia Pacific regions. The growth is North America region is mainly dominated by U.S. and Canada and is attributed to the increasing number of vehicles on street and growing awareness about pollution measures in the region. The region also has a well-established infrastructure which allows implementation of advanced technologies and better connectivity for real time data streaming.

Request To buy Full Report @ https://www.qyresearch.com/settlement/pre/ac1e6117769bf0aa31c996bf259a3d5a,0,1

Hybrid smart parking platform market has been segmented on the basis of component, parking type, solution and application. The parking type segment is further bifurcated into on street parking and off street parking. On street parking refers to parking of vehicles along the streets whereas off street parking refers to parking of vehicles in the garages and parking lots. This is owning to the growing demand for smart city solutions and increasing need for parking space management in order to avoid traffic congestion and maintain better air quality by reducing the traffic problems.

The Hybrid Smart Parking Platform market was valued at 790 Million US$ in 2017 and is projected to reach 2830 Million US$ by 2025, at a CAGR of 17.4% during the forecast period. In this study, 2017 has been considered as the base year and 2018 to 2025 as the forecast period to estimate the market size for Hybrid Smart Parking Platform.

This report includes the following manufacturers; we can also add the other companies as you want.

Streetline

Libelium

Tata Elxsi

IPS Group

Kapsch TrafficCom

NuPark

Siemens

Robert Bosch

Huawei Technologies

Acer

Market Segment by Product Type

Hardware

Software

Service

Market Segment by Application

Government

Residential

Commercial

The study objectives are:

To analyze and research the global Hybrid Smart Parking Platform status and future forecast, involving capacity, production, value, consumption, growth rate (CAGR), market share, historical and forecast.

To present the key Hybrid Smart Parking Platform manufacturers, capacity, production, revenue, market share, and recent development.

To split the breakdown data by regions, type, manufacturers and applications.

To analyze the global and key regions market potential and advantage, opportunity and challenge, restraints and risks.

To identify significant trends, drivers, influence factors in global and regions.

To analyze competitive developments such as expansions, agreements, new product launches, and acquisitions in the market.

Request Sample Copy of Report @ https://www.qyresearch.com/sample-form/form/646957/global-hybrid-smart-parking-platform-industry-research-report-growth-trends-and-competitive-analysis

In this study, the years considered to estimate the market size of Hybrid Smart Parking Platform are as follows:

History Year: 2013-2018

Base Year: 2017

Estimated Year: 2018

Forecast Year 2018 to 2025

About QYResearch
QYResearch always pursuits high product quality with the belief that quality is the soul of business. Through years of effort and supports from huge number of customer supports, QYResearch consulting group has accumulated creative design methods on many high-quality markets investigation and research team with rich experience. Today, QYResearch has become the brand of quality assurance in consulting industry.

For more information on this press release visit: http://www.sbwire.com/press-releases/hybrid-smart-parking-platform-industry-research-report-and-growth-trends-2018-2025-1026180.htm

Media Relations Contact

Rahul Singh
Director - Digital Marketing
QY Research, INC.
Telephone: 1-626-295-2442
Email: Click to Email Rahul Singh
Web: https://www.qyresearch.com

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          Junior Software Engineer Cheltenham £30,000 - £40,000      Cache   Translate Page   Web Page Cache   
Junior Software Engineer | Cheltenham | £30,000 - £40,000 Commutable from: Tewkesbury, Gloucester & Worcester. An extremely successful Software Consultancy based in Cheltenham are currently on the lookout for 2 highly passionate Junior Software Engineers with strong Java proficiency and heaps of potential to join the team. They are also open to considering fresh Graduates with a 2:1 or higher Computer Science (or similar) degree who is keen to continuously learn new technologies and work outside of their comfort zone. The successful applicants can look forward to an exciting start-up culture, working with modern technologies on exciting Greenfield projects. You will have the benefit of working closely with highly experienced colleagues who will actively give their time and support to you. You must be passionate about technology and keep up to date with the latest tools, methods and languages. Technologies: * Java * JavaScript * TDD OR BDD * CI * Computer Science Degree (Or Equivalent) Opportunity To Work On: * Data Analytics & Machine Learning * Spring Boot * Elasticsearch * Docker What makes this role different? * Opportunity to learn new technologies on a bespoke project by project basis. * Fantastic atmosphere; friendly, progressive & supportive. Interviews are due to commence with immediate effect so if you, or anyone you know are interested in the role contact me as soon as possible. T: E: Software Engineer | Consultancy | Junior | Java | JavaScript | Cheltenham
          Pace Quickens As Machine Learning Moves To The Edge      Cache   Translate Page   Web Page Cache   
More powerful edge devices means everyday AI applications, like social robots, are becoming feasible.
          A hand gesture could be your next password      Cache   Translate Page   Web Page Cache   

ByJackie Snow 2 minuteRead

A new system can look at a person’s finger making a motion in the air―like a signature or drawing a shape―to authenticate their identity. The framework,called FMCode, employs algorithms fed by a wearable sensor or camera, and can correctly identify users between 94.3% to 96.7% of the time on two different gesture devices after only seeing the passcode a few times, researchers say.

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The method, described in a new paper by computer scientists Duo Lu and Dijiang Huang at Arizona State University, gets around some of the tricky privacy concerns surrounding biometrics like face recognition. It also overcomes the issue of remembering long strings of characters needed for most secure logins. Gesture interactions could be useful when a keyboard is impractical, like using a VR headset, or in a situation where minimizing contact with the surroundings is necessary for cleanliness, like an operating room.

In the paper, which was published on the Arxiv.org preprint server this month, the researchers spell out some of the hurdles they had to overcome to develop FMCode. Unlike passwords, finger motions in the air won’t be exactly the same each time, so a system has to be robust enough to recognize slightly different speeds and shapes while still catching fraudulent attempts. The system has to be able to do that with only a few examples since most users would be unwilling to write their passcode hundreds or thousands of times.

To tackle those issues, the researchers turned to machine learning. The team designed classifiers that can spot spoofs while tolerating minor variations from the real user, and built a convolutional neural network (CNN) to index finger motion signals with data augmentation methods that limits the amount of training needed at setup.


A hand gesture could be your next password
User login through gesture interface using inertial sensor or 3D depth camera under two different scenarios: (left) VR applications with user mobility, (right) operating theater with touchless interface for doctors to maintain high cleanliness. [Images: courtesy of Duo Lu] Giving a finger

FMCode is pretty secure against most guessing attempts and spoofing, or when an attacker knows the gesture, the researchers say. But no system is foolproof. FMCode can be tricked if the system isn’t first set up to verify the user with an account ID. The researchers also say they are planning future work to study attacks where a person’s gesture passcode is recorded and then replayed later in an attempt to fool the system.

Whether many people will be interested in gesture control, at least anytime soon, remains to be seen. The interest in and development of the technology has waxed and waned over the years, with movies like Minority Report and Iron Man causing spikes in attention around the futuristic interactions. Nintendo released a wired glove that could control some gaming aspects to lackluster sales in 1989 to Leap Motion, which was released to good reviews at its launch in 2013 but is still not mainstream. Companies like Sony are trying to make gesture interfaces happen, while Facebook, Microsoft, Magic Leap, and others are betting that we’ll need gesture control in their VR and AR environments.

Related: The future of security? A good old-fashioned key

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The researchers queried the participants in the study on their thoughts on using FMCode versus other login methods, like traditional passwords and face recognition on mobile devices. While FMCode scored high for security, the users found it generally less easy to use and worse for speed. Of course, with improved hardware and a future with more security breaches, those concerns could disappear with a wave of the hand.

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          Dragos Makes Critical ICS Threat Intelligence More Accessible to Cybersecurity C ...      Cache   Translate Page   Web Page Cache   
Dragos to integrate ICS-specific threat intelligence with leading
cyber intelligence partners ThreatConnect, Recorded Future,
ThreatQuotient, and EclecticIQ HANOVER, Md. (BUSINESS WIRE)

Dragos,

, the trusted leader in industrial threat detection and response

technology and services, announced today that its industrial control

system (ICS) specific threat intelligence product, WorldView, will

integrate with partner companies, ThreatConnect ,

Recorded

, ThreatQuotient ,

and EclecticIQ .

These integrations will provide joint customers with seamless

accessibility to Dragos’ ICS threat intelligence, making context-rich,

actionable insight accessible to the greater cybersecurity community.


Dragos Makes Critical ICS Threat Intelligence More Accessible to Cybersecurity C ...

“The ICS cyber threat is real and now affects both business and

said Dragos’ Director of Threat Intelligence Sergio Caltagirone.

“All organizations with industrial operations and

processes need to utilize ICS threat intelligence.Now customers can use

the platforms which work best in their environment to easily consume the

world’s only dedicated ICS threat intelligence and seamlessly integrate

it into their security operations.”

Dragos WorldView

provides organizations with critical insight―designed for analysts and

executives―about

threat

specifically targeting ICS networks around the

world, so defenders are prepared to make tactical decisions and

strategic recommendations about their ICS environments quickly and

confidently.

Customer Offering & Benefits

Now, ThreatConnect, Recorded Future, ThreatQuotient, and EclecticIQ

customers can subscribe directly to Dragos WorldView through their

existing threat intelligence solutions, adding a critical threat view.

This capability not only alleviates the need for multiple platform

logins, but also provides a streamlined view of Dragos WorldView

offerings, including:

ICS-themed malware identification and analysis ICS vulnerability disclosures and analysis ICS adversary research and behavior trends ICS threat/incident media report analysis and commentary ICS relevant Indicators of Compromise (IOCs)

Subscribers of Dragos WorldView will benefit from immediate insight into

rapidly-escalating ICS threat situations, backed by expert threat

identification and analysis. Customers are empowered to reduce adversary

dwell time and mean time to recovery (MTTR) through more informed,

timely, and confident decision making. Dragos WorldView is supported by

Dragos’ comprehensive ICS intelligence-gathering sources and techniques,

including exclusive access to intelligence gained by proactive ICS

threat hunting performed by the Dragos Threat Operations Center.

Integration Timelines

ThreatConnect and Recorded Future customers will have the ability to

sign up for Dragos WorldView access by August 08, 2018. EclecticIQ and

ThreatQuotient customers can expect to sign up for access in the coming

months. To learn more about these integrations, please contact info@dragos.com .

Learn More About the Companies

Built on the industry’s only extensible security platform,
ThreatConnect Inc., provides a product suite designed to meet the
threat intelligence aggregation, analysis, automation, and
orchestration needs of any size security team. For more information,
visit https://threatconnect.com/ Recorded Future arms security teams with the only complete threat
intelligence solution powered by patented machine learning to lower
risk. Its technology automatically collects and analyzes information
from an unrivaled breadth of sources and provides invaluable context
in real time and packaged for human analysis or integration with
security technologies. Learn more at https://www.recordedfuture.com/ ThreatQuotient understands that the foundation of intelligence-driven
security is people. The company’s open and extensible

threat

intelligence platform

, ThreatQ, and cybersecurity situation room
solution, ThreatQ Investigations, empower security teams with the
context, customization and prioritization needed to make better
decisions, accelerate detection and response, and advance team
collaboration. Learn more at
          These 4 Antivirus Tools Are Using AI to Protect Your System      Cache   Translate Page   Web Page Cache   

The future of antivirus protection is exciting. Much like our cars, trains, and boats, the future of antivirus runs on artificial intelligence. AI technology is one of the fastest growing sectors around the world and security researchers are continually evaluating and integrating the technology into their consumer products.

Consumer antivirus products with AI or machine learning elements are appearing thick and fast. Does your next antivirus subscription need to include AI, or is it just another security buzzword? Let’s take a look.

Traditional Antivirus vs. AI Antivirus

The term “artificial intelligence” once conjured fantastical images of futuristic technology, but AI is now a reality. To understand what AI antivirus is, you need to understand how traditional antivirus works.

Traditional Antivirus

A traditional antivirus uses file and data signatures, and pattern analysis to compare potential malicious activity to previous instances. That is, the antivirus knows what the malicious file looks like, and can move swiftly to stop those files from infecting your system, should you pick one up. That’s a very basic explanation. You can read more about how it works and what scans to use right here The 3 Types of Antivirus Scans and When to Use Each One The 3 Types of Antivirus Scans and When to Use Each One Scanning your system with an antivirus program is important for keeping your system secure. But which type of antivirus scan should you use? Full, Quick, or Custom? Read More .

The antivirus on your system works well, don’t get me wrong. However, the number of malware attacks continues to rise, and security researchers regularly discover extremely advanced malware variants, such as Mylobot What Is Mylobot Malware? How It Works and What to Do About It What Is Mylobot Malware? How It Works and What to Do About It Every so often, a truly new malware strain appears. Mylobot is a perfect example. Learn more about what it is, why it's dangerous, and what to do about it. Read More . Furthermore, some traditional or legacy antivirus solutions cannot compete with advanced threats such as the devastating WannaCry ransomworm The Global Ransomware Attack and How to Protect Your Data The Global Ransomware Attack and How to Protect Your Data A massive cyberattack has struck computers around the globe. Have you been affected by the highly virulent self-replicating ransomware? If not, how can you protect your data without paying the ransom? Read More , or the Petya ransomware that encrypts your Master Boot Record Will The Petya Ransomware Crack Bring Back Your Files? Will The Petya Ransomware Crack Bring Back Your Files? A new ransomware variant, Petya, has been cracked by an irate victim. This is a chance to get one over on the cybercriminals, as we show you how to unlock your ransomed data. Read More .

As the threat landscape shifts, so must the antivirus detection mechanisms.

AI Antivirus

AI antivirus (or in some cases, machine learning―more on this distinction in a moment) works differently. There are a few different approaches, but AI antivirus learns about specific threats within its network environment and executes defensive activities without prompt.

AI and machine learning antivirus leverage sophisticated mathematical algorithms combined with the data from other deployments to understand what the baseline of security is for a given system. As well as this, they learn how to react to files that step outside that window of normal functionality.

Machine Learning vs. Artificial Intelligence

Another important distinction in the future of antivirus is between machine learning algorithms and artificial intelligence. The two words are sometimes used interchangeably but are not the same thing.

Artificial Intelligence (AI): AI refers to programs and machines that execute tasks with the characteristics of human intelligence Google Duplex Will Identify Itself as an AI Google Duplex Will Identify Itself as an AI Google Duplex was quite the talking point at I/O 2018, with serious morality questions being asked about the AI. However, Google has now made it clear Duplex will identify itself as not human. Read More , including problem-solving, forward planning, and learning. Broadly speaking, machines that can carry out human tasks in a manner we consider “intelligent.” Machine Learning (ML): ML refers to a broad spectrum of the current applications of AI technologies focusing on the idea that machines with data access and the correct programming can learn for themselves. Broadly speaking, machine learning is a means to an end for achieving AI What Is Machine Learning? Google's Free Course Breaks It Down for You What Is Machine Learning? Google's Free Course Breaks It Down for You Google has designed a free online course to teach you the fundamentals of machine learning. Read More .

Machine learning and AI are deeply intertwined, and you can see how the terms see occasional misuse. The difference in meaning with regards to antivirus is an important distinction. Most (if not all) of the latest antivirus suites implement some form of machine learning, but some algorithms are more advanced than others.

Machine learning in antivirus technologies isn’t new. It is getting more intelligent, and is easier to use as a marketing tool now that the wider public is more aware of ML and AI.

How Security Companies Use AI in Antivirus

There are a few antivirus solutions that use advanced algorithms to protect your system, but the use of true AI is still rare. Still, there are several antivirus tools with excellent AI and ML implementations that show how the security industry is evolving to protect you from the latest threats.

1. Cylance Smart Antivirus

Cylance is a well-known name in machine learning and artificial intelligence cybersecurity. The enterprise-grade CylancePROTECT uses AI-techniques to protect a huge number of businesses, and they count several Fortune 100 organizations among their clientele. Cylance Smart Antivirus is their first foray into consumer antivirus products, bringing that enterprise-level AI protection into your home.

Cylance Smart Antivirus relies entirely on AI and ML to distinguish malware from legitimate data. The result is an antivirus that doesn’t bog your system down by constantly scanning and analyzing files. ( Or informing you of its status every 15-minutes Top Free Antivirus Apps Without Nag Screens and Bloatware Top Free Antivirus Apps Without Nag Screens and Bloatware Nagging antivirus apps are a huge pain. You don't have to put up with them, even for free. Here are the best antivirus programs that don't come with popups or bundled junk. Read More .) Rather, Cylance Smart Antivirus waits until the moment of execution and immediately kills the threat―without human intervention.

“Consumers deserve security software that is fast, easy to use, and effective,” said Christopher Bray, senior vice president, Cylance Consumer. “The consumer antivirus market is long overdue for a ground-breaking solution built on robust technology that allows them to control their security environment.”

Thanks for the shout out @sawaba I can vouch that the primary reason we launched Cylance Smart Antivirus is because our customers have told us they’ve grown frustrated with everything on the market now.

― Hiep Dang (@Hiep_Dang) June 19, 2018

Smart Antivirus does, however, have some downsides. Unlike other antivirus suites with active monitoring, Cylance Smart Antivirus allows you to visit potentially malicious sites. I assume this is confidence that the product will stop malicious downloads, but it doesn’t protect against phishing attacks or similar threats.

A single Cylance Smart Antivirus license costs $29 per year , while a $69 household pack lets you install on five different systems.

2. Deep Instinct D-Client

Deep Instinct uses deep learning (a machine learning technique) to detect “any file before it is accessed or executed” on your system. The Deep Instinct D-Client makes use of static file analysis in conjunction with a threat prediction model that allows it to eliminate malware and other system threats autonomously.

Deep Instinct’s D-Client uses vast quantities of raw data to continue improving its detection algorithms. Deep Instinct is one of the only companies with private deep learning infrastructure dedicated to improving their detection accuracy, too.

3. Avast Free Antivirus

For most people, Avast is a familiar name in security. Avast Free Antivirus is the most popular antivirus on the market, and its history of protections goes back decades. Avast Free Antivirus has been “using AI and machine learning for years” to protect users from evolving threats. In 2012, the Avast Research Lab announced three powerful backend tools for their products.

The “Malware Similarity Search” allows almost instantaneous categorization of huge samples of incoming malware. Avast Free Antivirus quickly analyzes similarities between existing malware files using both static and dynamic analysis. “Evo-Gen” is similar “but a bit subtler in nature.” Evo-Gen is a genetic algorithm that works to find short and generic descriptions of malware in massive datasets. “MDE” is a database that works on top of the indexed data, allowing heavy parallel access.

These three machine learning technologies collectively evolved as the foundation for Avast’s CyberCapture .

CyberCapture is a core feature of the Avast security suite, specifically targeting unknown malware and zero-days. When an unknown suspicious file enters a system, CyberCapture activates and immediately isolates the host system. The suspect file automatically uploads to an Avast cloud server for data analysis. Afterwards, the user receives a positive or negative notification regarding the status of the file. All the while, your data is feeding back into the algorithms to define further and enhance yours and others’ system security.

Download:Avast Free Antivirus for windows | Mac | linux

Download:Avast Mobile Security for Android

4. Windows Defender Security Center

The Windows Defender Security Center for enterprise and business solutions will receive a phenomenal boost as Microsoft turns to artificial intelligence to bulk out its security. The 2017 WannaCry ransomworm ripped through Windows systems Prevent WannaCry Malware Variants by Disabling This Windows 10 Setting Prevent WannaCry Malware Variants by Disabling This Windows 10 Setting WannaCry has thankfully stopped spreading, but you should still disable the old, insecure protocol it exploited. Here's how to do it on your own computer in just a moment. Read More after hackers released a CIA trove of zero-day vulnerabilities into the wild.

Microsoft is creating a 400 million computer-strong machine learning network to build its next generation of security tools. The new AI-backed security features will start with its enterprise customers, but eventually filter down to Windows 10 systems for regular consumers. Windows Defender is constantly improving in other ways, too, and is now one of the top enterprise and consumer security solutions . The below image illustrates a snapshot of how Windows Defender machine learning protections works.


These 4 Antivirus Tools Are Using AI to Protect Your System

Want a prime example of how machine learning antivirus springs into action? Randy Treit, a senior security researcher for Windows Defender Research, writes up the Bad Rabbit ransomware detection example . It’s worth a read (it’s short!).

Antivirus: More Advanced Than You Realized

Is your antivirus suite more advanced than you realized? Machine learning and artificial intelligence are undoubtedly making larger inroads with security products. But their current prominence is more buzzword than effective deployment.

Try not to worry too much about whether your antivirus has AI or is implementing machine learning techniques. In the meantime, here’s a comparison of the best free antivirus products The 10 Best Free Anti-Virus Programs The 10 Best Free Anti-Virus Programs You must know by now: you need antivirus protection. Macs, Windows and Linux PCs all need it. You really have no excuse. So grab one of these ten and start protecting your computer! Read More for you to check out. AI or not, it is important to protect your system at all times.

Image Credit: Wavebreakmedia/ Depositphotos


          ExtraHop Leads the Charge for Network Traffic Analytics at Black Hat USA      Cache   Translate Page   Web Page Cache   
Following a Spate of Industry Recognition from Leading Analysts,
Enterprise-Scale Network Traffic Analytics Solution Poised to Challenge
the SOC Status Quo

LAS VEGAS (BUSINESS WIRE) #BHUSA2018 ExtraHop, a leading provider of analytics for security, is upending the

SOC status quo at the Black Hat USA 2018 Conference. The company will be

showcasing its Reveal(x)

network traffic analytics (NTA) solution at Booth 1004, demonstrating

how real-time analytics and machine learning eliminate the darkspace

within the enterprise. ExtraHop has received industry recognition from

Gartner, EMA, and Ovum as these and other leading industry organizations

recognize the need for NTA at enterprise scale.


ExtraHop Leads the Charge for Network Traffic Analytics at Black Hat USA

The ExtraHop booth at Black Hat USA will feature a series of industry

thought leadership presentations from Phantom, Ixia, and others speaking

on the rapidly emerging role of NTA in the enterprise SOC, the

importance of

TLS

decryption for security visibility, and the power of

orchestration automation. Special sessions will occur throughout the day

at Booth 1004 on August 8 and 9, 2018.

“Security teams are drowning in alerts and many are left without the

resources they need to stay ahead of attackers,” said Bryce Hein, SVP of

Marketing at ExtraHop. “Threat hunting in the modern attack landscape is

not possible without enterprise-class network traffic analytics, making

NTA a must-have for the modern enterprise SOC.”

ExtraHop Reveal(x) significantly reduces dwell time by highlighting

late-stage attack activities and shining light on the darkspace

in the enterprise―the hard-to-see areas of the network along the

east-west corridor. Through comprehensive analysis of network traffic,

Reveal(x) automatically identifies attack behavior, delivering

high-fidelity insights into threats to critical assets. By merging

insights into investigative workflows, Reveal(x) helps security

operations teams shrink detection and response times, disrupt threat

activity, and identify ways to reduce the attack surface.

Analyst Recognition

ExtraHop was listed as a Sample Vendor in the Gartner “

Hype

” report. ExtraHop was

named in the Network Traffic Analysis (NTA) category. According to the

Gartner report, “NTA solutions are valuable tools that assist network

security professionals in the detection of compromised endpoints and

targeted attacks that have not been seen in the past. These tools have

limited blocking ability, or none at all (because they are implemented

outside of the line of traffic), but they are effective in shortening

the incident response window and reducing the dwell time of malware.” 1

The recent analyst report from EMA titled:

Radar

identified

ExtraHop Reveal(x) as a “Value Leader” and “Vendor to Watch,” noting

that, “Reveal(x) exhibited strong functionality due to its impressive

feature differentiation, out-of-box reporting, and high-performance

sustained data capture and processing.” 2

Customers Choose Reveal(x)

Global 2000 customers are already using ExtraHop Network Traffic

Analytics to modernize their programs and protect their enterprises. A

top

is using Reveal(x)

as the cornerstone of their next-generation SOC, while other ExtraHop

customers report improving their security visibility by as much as 75

percent and reducing time to detect threats by as much as 95 percent. 3

Industry Accolades

Reveal(x) has also won numerous cybersecurity industry awards in the

last six months including the

AI

Breakthrough Award for Best AI Solution for CyberSecurity

,

2018

Fortress Cyber Security

,

Best

of Citrix Synergy 2018

, and was
          iOS Developer - PGS SOFTWARE - Rzeszów, podkarpackie      Cache   Translate Page   Web Page Cache   
Augmented Reality, Machine Learning, iBeacons, Top Level Security. Elastyczne godziny pracy....
Od PGS SOFTWARE - Wed, 08 Aug 2018 14:51:19 GMT - Pokaż wszystkie Rzeszów, podkarpackie oferty pracy
          Artificial Intellegence / Machine Learning Developer - SafetyTek Software Ltd. - Saskatoon, SK      Cache   Translate Page   Web Page Cache   
So feel free to ask lots of questions, read up on our company news, check out our website and peep our social media channels. AI / ML Developer —... $75,000 - $85,000 a year
From Indeed - Thu, 19 Jul 2018 20:55:34 GMT - View all Saskatoon, SK jobs
          Telecommute Ad Operations Manager in New York City      Cache   Translate Page   Web Page Cache   
A marketing company is seeking a Telecommute Ad Operations Manager in New York City. Core Responsibilities of this position include: Collaborating with technical teams to drive significant machine learning/product changes Optimizing campaigns for post-install goals Serving as an internal POC for key clients Position Requirements Include: Regularly present at and organize cross-functional team meetings attended by executives and founders Project management skills Performance-focused optimization experience 2-4 years campaign optimization, BI or analytical experience in adtech
          Sr Director, Growth Marketing Technology - eBay Inc. - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Further, the Marketing Tech Leader will apply the latest data analysis and machine learning technologies to innovate applications in both BI analysis and...
From eBay Inc. - Fri, 01 Jun 2018 08:04:49 GMT - View all Bellevue, WA jobs
          Software Engineer - Machine Learning - Convoy - Seattle, WA      Cache   Translate Page   Web Page Cache   
Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes....
From Convoy - Sat, 19 May 2018 10:13:22 GMT - View all Seattle, WA jobs
          Machine Learning & AI for Healthcare      Cache   Translate Page   Web Page Cache   
February 11, 2019 | 8:00 a.m. – 5:00 p.m.Cost: $350Machine Learning & AI for Healthcare brings healthcare IT decision makers together for insights ...
          What’s the difference between artificial intelligence and machine learning?      Cache   Translate Page   Web Page Cache   
Machine learning (ML) does not exist on its own but is a subset of AI. It has been said that without ML, artificial intelligence cannot progress.
          LF Deep Learning Foundation Advances Open Source Artificial Intelligence With Major …      Cache   Translate Page   Web Page Cache   
"The progression of artificial intelligence and machine learning technologies calls for a shift in how we design and implement networks and services," ...
          Can artificial intelligence save merchant lending from the next recession?      Cache   Translate Page   Web Page Cache   
But the onset of artificial intelligence and machine learning could serve as the safety net some companies need, providing a different and more ...
          Innovation Developer - TeamSoft - Sun Prairie, WI      Cache   Translate Page   Web Page Cache   
Are you interested in topics like machine learning, IoT, Big data, data science, data analysis, satellite imagery or mobile telematics?...
From Dice - Thu, 19 Jul 2018 08:35:55 GMT - View all Sun Prairie, WI jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page   Web Page Cache   
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Mon, 14 May 2018 23:57:10 GMT - View all Dallas, TX jobs
          Machine Learning Engineer - Technica Corporation - Dulles, VA      Cache   Translate Page   Web Page Cache   
Technica Corporation is seeking a Machine Learning Engineer to support our internal Innovation, Research and Development (IRD) team....
From Technica Corporation - Wed, 11 Jul 2018 06:07:15 GMT - View all Dulles, VA jobs
          In case you missed it: July 2018 roundup      Cache   Translate Page   Web Page Cache   

In case you missed them, here are some articles from July of particular interest to R users.

A program to validate quality and security for R packages: the Linux Foundation's CII Best Practices Badge Program.

R scripts to generate images in the style of famous artworks, like Mondrian's.

A 6-minute video tour of the AI and Machine Learning services in Azure, including R.

The July roundup of AI, Machine Learning and Data Science news.

An R package for tiling hexagon-shaped images, used to create a striking banner of hex stickers for useR!2018.

Highlights and links to videos from the useR!2018 conference.

Video and R scripts from a workshop on creating an app to detect images of hotdogs

Microsoft has released a number of open data sets produced from its research programs.

R 3.5.1 has been released.

And some general interest stories (not necessarily related to R):

As always, thanks for the comments and please send any suggestions to me at davidsmi@microsoft.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.


          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page   Web Page Cache   
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Mon, 14 May 2018 23:57:10 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Portland, OR      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:10 GMT - View all Portland, OR jobs
          AWS Architect - Insight Enterprises, Inc. - Chicago, IL      Cache   Translate Page   Web Page Cache   
Database architecture, Big Data, Machine Learning, Business Intelligence, Advanced Analytics, Data Mining, ETL. Internal teammate application guidelines:....
From Insight - Thu, 12 Jul 2018 01:56:10 GMT - View all Chicago, IL jobs
          Artificial Intelligence Is Coming for Hiring, and It Might Not Be That Bad      Cache   Translate Page   Web Page Cache   
Instead of relying on people’s feelings to make hiring decisions, companies use machine learning to detect the skills needed for certain jobs. The AI then matches candidates who have those skills with ... - Source: www.itprotoday.com
          Economist - Forecasting - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience with machine learning applications. We are breaking fresh ground, pioneering in a program that is crucial for future Amazon growth, and our business...
From Amazon.com - Wed, 27 Jun 2018 07:21:23 GMT - View all Seattle, WA jobs
          Quantum Computing Market 2018 Analysis by IBM, D-Wave Systems, Lockheed Martin, Intel, Rigetti Computing, QxBranch, Anyon Systems, QC Ware      Cache   Translate Page   Web Page Cache   
Quantum Computing Market 2018 Analysis by IBM, D-Wave Systems, Lockheed Martin, Intel, Rigetti Computing, QxBranch, Anyon Systems, QC Ware Quantum Computing Market, By Application (Optimization, Machine Learning and Simulation), Vertical (BFSI, IT and Telecommunication, Healthcare, Transportation, Government, Aerospace & Defense and Others) - Forecast 2022 According to a recent study report published by the Market Research Future, The global market

          Telefónica's 'Internet para Todos' project uses modern tools to find and connect Latin Americans      Cache   Translate Page   Web Page Cache   
Telefónica's "Internet para Todos" (Internet for All) program is using machine learning and AI to connect 100 million users in Latin America who lack reliable services. As VP of Network Operations Patrick Lopez notes, connectivity "is not only a rural problem, it is necessary to increase efficiency and optimize deployment and operations to keep decreasing the costs."
          Artificial Intelligence Is Coming for Hiring, and It Might Not Be That Bad      Cache   Translate Page   Web Page Cache   
Instead of relying on people’s feelings to make hiring decisions, machine learning can remove information from resumes that lead to discrimination.
          Adversarial Geometry and Lighting using a Differentiable Renderer. (arXiv:1808.02651v1 [cs.LG])      Cache   Translate Page   Web Page Cache   

Authors: Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson

Many machine learning classifiers are vulnerable to adversarial attacks, inputs with perturbations designed to intentionally trigger misclassification. Modern adversarial methods either directly alter pixel colors, or "paint" colors onto a 3D shapes. We propose novel adversarial attacks that directly alter the geometry of 3D objects and/or manipulate the lighting in a virtual scene. We leverage a novel differentiable renderer that is efficient to evaluate and analytically differentiate. Our renderer generates images realistic enough for correct classification by common pre-trained models, and we use it to design physical adversarial examples that consistently fool these models. We conduct qualitative and quantitate experiments to validate our adversarial geometry and adversarial lighting attack capabilities.


          Highly Accelerated Multishot EPI through Synergistic Combination of Machine Learning and Joint Reconstruction. (arXiv:1808.02814v1 [eess.IV])      Cache   Translate Page   Web Page Cache   

Authors: Berkin Bilgic, Itthi Chatnuntawech, Mary Kate Manhard, Qiyuan Tian, Congyu Liao, Stephen F. Cauley, Susie Y. Huang, Jonathan R. Polimeni, Lawrence L. Wald, Kawin Setsompop

Purpose: To introduce a combined machine learning (ML) and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI), and demonstrate its application in high-resolution structural imaging.

Methods: Singleshot EPI is an efficient encoding technique, but does not lend itself well to high-resolution imaging due to severe distortion artifacts and blurring. While msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot physiological variations which disrupt the combination of the multiple-shot data into a single image. We employ Deep Learning to obtain an interim magnitude-valued image with minimal artifacts, which permits estimation of image phase variations due to shot-to-shot physiological changes. These variations are then included in a Joint Virtual Coil Sensitivity Encoding (JVC-SENSE) reconstruction to utilize data from all shots and improve upon the ML solution.

Results: Our combined ML + physics approach enabled R=8-fold acceleration from 2 EPI-shots while providing 1.8-fold error reduction compared to the MUSSELS, a state-of-the-art reconstruction technique, which is also used as an input to our ML network. Using 3 shots allowed us to push the acceleration to R=10-fold, where we obtained a 1.7-fold error reduction over MUSSELS.

Conclusion: Combination of ML and JVC-SENSE enabled navigator-free msEPI at higher accelerations than previously possible while using fewer shots, with reduced vulnerability to poor generalizability and poor acceptance of end-to-end ML approaches.


          A General Theory of Sample Complexity for Multi-Item Profit Maximization. (arXiv:1705.00243v4 [cs.LG] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik

The design of profit-maximizing multi-item mechanisms is a notoriously challenging problem with tremendous real-world impact. The mechanism designer's goal is to field a mechanism with high expected profit on the distribution over buyers' values. Unfortunately, if the set of mechanisms he optimizes over is complex, a mechanism may have high empirical profit over a small set of samples but low expected profit. This raises the question, how many samples are sufficient to ensure that the empirically optimal mechanism is nearly optimal in expectation? We uncover structure shared by a myriad of pricing, auction, and lottery mechanisms that allows us to prove strong sample complexity bounds: for any set of buyers' values, profit is a piecewise linear function of the mechanism's parameters. We prove new bounds for mechanism classes not yet studied in the sample-based mechanism design literature and match or improve over the best known guarantees for many classes. The profit functions we study are significantly different from well-understood functions in machine learning, so our analysis requires a sharp understanding of the interplay between mechanism parameters and buyer values. We strengthen our main results with data-dependent bounds when the distribution over buyers' values is "well-behaved." Finally, we investigate a fundamental tradeoff in sample-based mechanism design: complex mechanisms often have higher profit than simple mechanisms, but more samples are required to ensure that empirical and expected profit are close. We provide techniques for optimizing this tradeoff.


          Candidate Labeling for Crowd Learning. (arXiv:1804.10023v2 [stat.ML] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez

Crowdsourcing has become very popular among the machine learning community as a way to obtain labels that allow a ground truth to be estimated for a given dataset. In most of the approaches that use crowdsourced labels, annotators are asked to provide, for each presented instance, a single class label. Such a request could be inefficient, that is, considering that the labelers may not be experts, that way to proceed could fail to take real advantage of the knowledge of the labelers. In this paper, the use of candidate labeling for crowd learning is proposed, where the annotators may provide more than a single label per instance to try not to miss the real label. The main hypothesis is that, by allowing candidate labeling, knowledge can be extracted from the labelers more efficiently by than in the standard crowd learning scenario. Empirical evidence which supports that hypothesis is presented.


          Progressive Evaluation of Queries over Tagged Data. (arXiv:1805.12033v3 [cs.DB] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: Dhrubajyoti Ghosh, Roberto Yus, Yasser Altowim, Sharad Mehrotra

Modern information systems often collect raw data in the form of text, images, video, and sensor readings. Such data needs to be further interpreted/enriched prior to being analyzed. Enrichment is often a result of automated machine learning and or signal processing techniques that associate appropriate but uncertain tags with the data. Traditionally, with the notable exception of a few systems, enrichment is considered to be a separate pre-processing step performed independently prior to data analysis. Such an approach is becoming increasingly infeasible since modern data capture technologies enable creation of very large data collections for which it is computationally difficult/impossible and ultimately not beneficial to derive all tags as a preprocessing step. Hence, approaches that perform tagging at query/analysis time on the data of interest need to be considered. This paper explores the problem of joint tagging and query processing. In particular, the paper considers a scenario where tagging can be performed using several techniques that differ in cost and accuracy and develops a progressive approach to answering Select-Project-Join (SPJ) queries (with a restricted version of the join predicates) that enriches the right data to the right degree so as to maximize the quality of the query results. The experimental results show that the proposed approach performs significantly better compared to baseline approaches.


          A Machine Learning Framework for Stock Selection. (arXiv:1806.01743v2 [q-fin.PM] UPDATED)      Cache   Translate Page   Web Page Cache   

Authors: XingYu Fu, JinHong Du, YiFeng Guo, MingWen Liu, Tao Dong, XiuWen Duan

This paper demonstrates how to apply machine learning algorithms to distinguish good stocks from the bad stocks. To this end, we construct 244 technical and fundamental features to characterize each stock, and label stocks according to their ranking with respect to the return-to-volatility ratio. Algorithms ranging from traditional statistical learning methods to recently popular deep learning method, e.g. Logistic Regression (LR), Random Forest (RF), Deep Neural Network (DNN), and the Stacking, are trained to solve the classification task. Genetic Algorithm (GA) is also used to implement feature selection. The effectiveness of the stock selection strategy is validated in Chinese stock market in both statistical and practical aspects, showing that: 1) Stacking outperforms other models reaching an AUC score of 0.972; 2) Genetic Algorithm picks a subset of 114 features and the prediction performances of all models remain almost unchanged after the selection procedure, which suggests some features are indeed redundant; 3) LR and DNN are radical models; RF is risk-neutral model; Stacking is somewhere between DNN and RF. 4) The portfolios constructed by our models outperform market average in back tests.


          Climbing Mt Peer Review: May AI help you with that?      Cache   Translate Page   Web Page Cache   
It was this which led to a collaboration with scientific data experts, SciBite, to develop a machine learning technology with the potential to accelerate ...
          Facebook Wants to Teach Machine Learning      Cache   Translate Page   Web Page Cache   
When you think of technical education about machine learning, Facebook might not be the company that pops into your head. However, the company ...
          A machine learning system trained on scholarly journals could correct Wikipedia’s gendered under …      Cache   Translate Page   Web Page Cache   
Quicksilver is a machine-learning tool from AI startup Primer: it used 30,000 Wikipedia entries to create a model that allowed it to identify the ...
          There’s something eerie about bots that teach themselves to cheat      Cache   Translate Page   Web Page Cache   
One of the holy grails of computer science is unsupervised machine learning, where you tell an algorithm what goal you want it to attain, and give it ...
          JAIC: Pentagon debuts artificial intelligence hub      Cache   Translate Page   Web Page Cache   
These issues—according to Brendan McCord, head of machine learning at the Pentagon entity known as Defense Innovation Unit Experimental—will ...
          The Newest Digital Trend In Oil & Gas      Cache   Translate Page   Web Page Cache   
Artificial intelligence, or rather things like machine learning and automation, which are often wrongly called artificial intelligence, is a big thing in oil ...
          Is Machine Learning Worth For All Businesses?      Cache   Translate Page   Web Page Cache   
Artificial Intelligence (AI) and machine learning have influenced multiple industries by changing the dimensions of the data and technology. In the rat ...
          Deep learning useful in diabetic retinopathy screening      Cache   Translate Page   Web Page Cache   
Deep learning is a type of machine learning shown to be remarkably effective in the past few years, but is not a new science, she explained. “It's based ...
          How is machine learning transforming the finance industry?      Cache   Translate Page   Web Page Cache   
Machine learning builds upon a range of existing disciplines. Econometrics, computational statistics and pattern recognition are all furthered with ...
          ML.Net aims to provide machine learning for .Net developers      Cache   Translate Page   Web Page Cache   
A new machine learning framework from Microsoft is aimed at .Net developers who want to run common machine learning tasks using a cross-platform ...
          Seven steps to a successful AI implementation      Cache   Translate Page   Web Page Cache   
Artificial intelligence (AI) and machine learning (ML) are shifting from being business buzzwords toward wider enterprise adoption. The efforts around ...
          Android 9 Pie ausprobiert: Das bringt Googles nächstes großes Update      Cache   Translate Page   Web Page Cache   
Android 9.0 Pie ist da und wir haben seit der ersten Beta fleissig mit dem neuen OS herumgespielt. Vieles gefällt, manches kann indes noch mutiger umgesetzt werden. Bei Android 9 Pie stehen im Unterschied zum Oreo-Update, bei dem die Neuerungen überschaubar waren, wieder zahlreiche optische Optimierungen bereit. Am offensichtlichsten ist dabei die neue gestenbasierte Steuerung – nichtsdestotrotz hat Google auch unter der Haube vieles umgebaut und mehr KI-Funktionen integriert. Wir werfen einen Blick auf die wichtigsten Änderungen.

Android 9 Pie: Endlich zeitnahe Updates?

Google hat mit Android N(ougat) einen neuen Releasezyklus eingeführt, mit dem Smartphone-Hersteller und Entwickler genügend Zeit bekommen sollten, ihre Software und Apps an die neuen OS-Versionen anpassen zu können. Wie sich herausstellte, war es in der Theorie eine gute Idee, in der Realität zeigten die meisten Hersteller wenig Ambitionen, ihre Geräte zeitnah auf eine neue Android-Version zu hieven. Beim Update auf Oreo haben sich Smartphone-Hersteller richtig viel Zeit genommen. [caption id="attachment_1100562" align="alignnone" width="620" class="tg-noadgoal"]Android 9 Pie gibt es unter anderem schon für das Nokia 7 Plus als Beta. (Foto: t3n.de) Android 9 Pie gibt es unter anderem schon für das Nokia 7 Plus als Beta. Das finale Update dürfte nicht lange auf sich warten lassen. (Foto: t3n.de)[/caption] In diesem Jahr sehen wir aber die Hoffnung auf eine Trendwende, die Google schon mit Android 8.0 und dem Project Treble angestoßen hat. Denn Android wurde auf eine modulare Architektur gestellt, die für Hersteller weniger Aufwand bedeutet, das OS mit den eigenen Modifikationen beziehungsweise Nutzeroberflächen zu versehen. Dass der Umbau funktioniert, stellten Entwickler bereits unter Beweis. Überdies hatte das Startup von Android-Gründer Andy Rubin am 6. August eine Überraschung parat: Das Essential-Phone hat sein Pie-Update am gleichen Tag wie Googles Pixel-Modelle erhalten. Die Hoffnung ist groß, dass andere Hersteller auch schneller liefern werden. Aber auch mit Pie wird Android nicht so eine rasche Verbreitung finden, wie Apple es mit seinen iOS-Updates schafft.
Jetzt lesen: Android 9.0 Pie: Diese Smartphones bekommen das neue Update

Die neue Gestensteuerung in Android 9 Pie: Guter Ansatz, nicht perfekt

Während Hersteller die schnellen Updates erst noch unter Beweis stellen müssen, widmen wir uns mit der neuen Gestensteuerung einer konkreten Funktion. Ähnlich wie bei Apples iPhone X bringt das Pie-Update eine Gestensteuerung, die sich an Palms webOS anlehnt. [caption id="attachment_1085890" align="alignnone" width="620" class="tg-noadgoal"]Der Android-Pie-Launcher mit seinen neuen Gesten. (Foto: t3n.de) Der Android-Pie-Launcher mit seiner neuen Gestenavigation. (Foto: t3n.de)[/caption] Sieben Jahre nach Einführung der Onscreen-Tasten mit dem Galaxy Nexus entledigt Google sich dieses Features und ersetzt es durch die Gestensteuerung. Anstelle der drei klassischen Tasten prangt nur noch ein länglicher Button mit abgerundeten Ecken, der an ein „Tictac“ erinnert, und nicht nur die Aufgabe des bisherigen mittigen Homebuttons übernimmt. So könnt ihr damit mit einem Tap nicht nur auf den Homescreen zurückkehren und per Langdruck den Google Assistant aktivieren. Ein Wisch ins Display hinein öffnet den Multi-Tasking-Button, der die zuletzt genutzten Apps anzeigt. Durch die Apps navigiert ihr, indem ihr das Tictac nach rechts zieht, ein kurzer Zug daran bringt euch in die zuletzt genutzte App. Wollt ihr den App-Drawer öffnen, müsst ihr eine eine längere Wischbewegung nach oben ins Display durchführen. Das Ganze klingt vielleicht etwas umständlich, funktioniert aber ausgesprochen gut. Es sollte zudem erwähnt werden, dass ihr dank der neuen Gestensteuerung selbst aus jeder App heraus in den App-Drawer gelangen könnt – bislang musste stets erst per Druck auf den Homebutton auf dem Homescreen zurückgekehrt werden. [video width="360" height="720" mp4="https://t3n.de/news/wp-content/uploads/2018/06/android-9-launcher.mp4"][/video] In der Multitasking-Ansicht befindet sich unter der Übersicht außerdem eine Google-Suchleiste und eine Auswahl an Apps, die sich je nach Nutzungsverhalten anpasst. Hier kommen Googles Machine-Learning-Algorithmen ins Spiel, die lokal auf dem Gerät ausgeführt werden – die Google-Cloud ist nicht erforderlich. Öffnet ihr den App-Drawer, wandert diese Übersicht übrigens über die komplette App-Auswahl. Im Alltag entpuppen sich die von der KI angebotenen Anwendungen als durchaus nützlich. Die Umgewöhnung an die neue Navigation geht überraschend schnell vonstatten und fühlt sich wie ein Schritt in die richtige Richtung an. Allerdings hat Google sie noch nicht so konsequent umgesetzt wie etwa Apple. Zum einen nimmt der Tictac-Button immer noch unnötigen Raum auf den Display ein, zum anderen vermissen wir eine Zurückgeste – unter Android 9 wird in der Multi-Tasking-Ansicht immer noch der Zurück-Button eingeblendet. Eine Wischgeste nach Links hätte es womöglich auch getan. Entsprechend mutet die Steuerung ein wenig wie ein Zwischenschritt an. Immerhin: Das umgestaltete Design des App-Switchers, in dem ihr eine App mit einem Wisch nach oben auswerfen könnt, ist überwiegend gelungen. [caption id="attachment_1100599" align="alignnone" width="620" class="tg-noadgoal"]Der Multi-Window-Modus ist unter Android 9 Pie schwerer als noch unter Oreo zu erreichen. (Foto: t3n.de) Der Multi-Window-Modus ist unter Android 9 Pie schwerer als noch unter Oreo zu erreichen. (Foto: t3n.de)[/caption] Verbesserungswürdig ist allerdings noch die Art und Weise, wie der Multi-Window-Modus aktiviert wird. Bislang genügte ein Tap auf den Multitasking-Button und eine Wischbewegung der jeweiligen App Richtung oberer Displayrand. Unter Pie müsst ihr erst die Multitasking-Übersicht aufrufen, auf das runde App-Icon der jeweiligen Anwendung drücken, wodurch sie ein Menü öffnet. Dort tappt ihr dann auf Bildschirm teilen – eindeutig zu viele Schritte. In der Übersicht findet ihr zudem die Möglichkeit, direkt zur App-Info zu springen, wo ihr etwa die Hintergrunddaten und mehr einschränken könnt. Die Gestensteuerung dürfte beim Pixel 3, das im Herbst erscheinen wird, als Standard eingestellt sein. Smartphone-Hersteller haben derweil immer noch die Option, auf die klassischen drei Onscreen-Buttons zu setzen. Langfristig wird Google die neue Navi mit Sicherheit zum Standard machen – und sinnvoll erweitern. [gallery title="Pixel 3 und 3 XL: So sollen die Google-Phones aussehen" ids="1091537,1091539,1091538,1091536,1091535,1091533,1091531,1091554"]

Mehr lokales Machine-Learning mit Android 9 Pie

Eine weitere große Neuerung ist wie schon angedeutet die Integration von Machine Learning. Neben der Anzeige besagter individueller Apps im Taskswitcher hat Google zusätzlich App-Aktionen integriert, die kontextbasiert Aktionen oder Apps im App-Drawer zwischen der App-Übersicht einblenden. [caption id="attachment_1100576" align="alignnone" width="620" class="tg-noadgoal"]App-Aktionen sollen euch relevante Apps und Aktionen anzeigen. (Bild: t3n.de) App-Aktionen sollen euch relevante Apps und Aktionen anzeigen. (Bild: t3n.de)[/caption] Laut Google soll das Feature voraussagen, was ihr als nächstes tun wollt und diese Aktion direkt auf eurem Handy anzeigt. Beispielsweise könnte euch morgens auf dem Weg zur Arbeit die Navigation zum Büro per Google Maps vorgeschlagen werden. Ebenso könnte auch Google Play Books oder die Podcast-App angeboten werden, um das zuletzt gehörte Hörbuch oder einen Podcast fortzusetzen. Im Alltag empfand ich die vorgeschlagenen App-Aktionen zwar als teils sinnvoll, jedoch hat sich mein Smartphone-Nutzungsverhalten derart eingeschliffen, dass ich nie auf die Idee kam, diese Buttons zu drücken. [caption id="attachment_1100574" align="alignnone" width="620" class="tg-noadgoal"]Android 9 Pie mit KI-Funktionen zur Optimierung von Akkulaufzeit und Displayhelligkeit. (Bild: t3n.de) Android 9 Pie mit KI-Funktionen zur Optimierung von Akkulaufzeit und Displayhelligkeit. (Bild: t3n.de)[/caption] Das lokale Machine Learning kommt zudem auch bei Funktionen zur Verlängerung der Akkulaufzeit und der Displayhelligkeit zum Einsatz. Mit der Funktion Intelligenter Akku wird den Batterieverbrauch von selten verwendeten Apps begrenzt, während Akkuleistung von häufig genutzten Apps entsprechend priorisiert wird. Mit der Funktion Automatische Helligkeit lernt das System, wie ihr die Bildschirmhelligkeit in verschiedenen Situationen einstellt – und übernimmt es dann automatisch für euch.

Android 9 Pie mit aufgebohrtem Benachrichtigungssystem

[caption id="attachment_977282" align="alignnone" width="620" class="tg-noadgoal"]Der Benachrichtigungsbereich wird unter Android Pie umgestaltet. (Bild: Google) Der Benachrichtigungsbereich wird unter Android Pie umgestaltet. (Bild: Google)[/caption] Erweitert und mit Intelligenz ausgerüstet hat Google auch das schon gute Benachrichtigungs-Management. Stellt Android Pie etwa fest, dass ihr bestimmte Benachrichtigungen ohne weitere Interaktion wegwischt, empfiehlt euch das System, den entsprechenden Kanal zu deaktivieren. Bestimmte App-Benachrichtigungen könnt ihr außerdem manuell abstellen oder nachträglich wieder aktivieren. Hierfür bewegt ihr euch in den Menü-Punkt Apps und Benachrichtigungen, wählt dort die entsprechende App aus und öffnet den Punkt Benachrichtigungen. In Instagram stehen euch etwa diverse Optionen zur Auswahl. Beispielsweise könnt ihr Benachrichtigungen über Uploads oder Anfragen von Direktnachrichten und weitere ausstellen. [caption id="attachment_1100564" align="alignnone" width="620" class="tg-noadgoal"]Mit Android 9 Pie könnt ihr einstellen, welche Art von Benachrichtigungen angezeigt werden sollen. (Foto. t3n.de) Mit Android 9 Pie könnt ihr einstellen, welche Art von Benachrichtigungen angezeigt werden sollen. (Foto: t3n.de)[/caption] Zudem sind die Benachrichtigungs-Kanäle nun in Kategorien aufgeteilt worden, wodurch sie einerseits übersichtlicher werden. Andererseits besteht die Option, ganze Kategorien auszustellen.

Antworten direkt aus der Benachrichtigungsleiste – auch mit Stickern

[caption id="attachment_1100572" align="alignnone" width="620" class="tg-noadgoal"]Auf Nachrichten Antworten aus der Benachrichtigungsleiste wird unter Android 9 Pie vielseitiger. (Bild: Google) Auf Nachrichten zu antworten aus der Benachrichtigungsleiste wird unter Android 9 Pie vielseitiger. (Bild: Google)[/caption] Mit Android 9 Pie erhält die Benachrichtigungsleiste noch weitere praktische Features: Viele Messaging-Apps zeigen dort künftig nicht nur die letzte Nachricht an, sondern einen Teil des Chats. Insbesondere bei Gruppenchats muss nicht mehr zwingend in die App gewechselt werden, um den Kontext zu erfassen. [caption id="attachment_1085906" align="alignnone" width="620" class="tg-noadgoal"]Android 9.0 Pie hält viele neue Emoji für euch bereit. (Bild: Emojipedia) Android 9.0 Pie hält viele neue Emoji für euch bereit. (Bild: Emojipedia)[/caption] Darüber hinaus erlaubt Pie es auch, direkt aus Benachrichtigungsleiste Sticker und Bilder einzufügen. Des Weiteren müsst ihr nicht mehr jede Antwort tippen, wie etwa in Gmail könnt ihr aus vorgefertigten Antworten, den Smart-Replys, wählen.

Android 9 Pie: Google hat an der Bluetooth-Schraube gedreht

Nett: Das Bluetooth-Symbol wird in der Benachrichtigungsleiste nur dann angezeigt, wenn eine aktive Verbindung zu einem Gerät besteht. Bei verbundenen Smartwatches wird es indes nicht angezeigt. Etwas weniger durchdacht: Um Kopfhörer oder andere Bluetooth-Geräte, die schon einmal mit dem Smartphone gekoppelt waren, neu zu verbinden, ist es erforderlich, in die Bluetooth-Einstellungen zu gehen und entsprechendes Gerät eine Ebene tiefer nach dem Tap auf Zuvor verbundene Geräte auszuwählen. Das ist ein Schritt mehr, als noch unter Android Oreo erforderlich war.

Android Pie merkt sich die Lautstärke-Einstellungen für jedes Bluetooth-Gerät

Google hat in Sachen Bluetooth weitere Dinge verändert: So lassen sich unter Pie bis zu fünf Geräte verbinden und nahtlos zwischen ihnen hin- und herwechseln. Android Oreo unterstützte lediglich zwei gleichzeitige Verbindungen. Zudem merkt sich das System die letzte Lautstärkeposition jedes Bluetooth-Lautsprechers und -Kopfhörers.

Android 9 Pie mit Designanpassungen und neuem Textauswahl-Werkzeug

Positiv hervorhebenswert ist das verbesserte Textauswahl-Tool: Orientiert an Apples iOS wird der ausgewählte Teil mitsamt Cursor wie durch eine Lupe vergrößert. [caption id="attachment_1100588" align="alignnone" width="620" class="tg-noadgoal"]Ein wenig an iOS angelehnt: Das Textauswahlwerkzeug besitzt nun eine Lupe. (Bild: t3n.de) Ein wenig an iOS angelehnt: Das Textauswahlwerkzeug besitzt nun eine Lupe. (Bild: t3n.de)[/caption] Android Pie hat auch einige Designoptimierungen an Bord. Benachrichtigungen und Elemente zur Mediensteuerung sind wie etwa in der Google-App in abgerundeten Karten untergebracht, was optisch schon was hermacht. Die Systemeinstellungen hat Google ebenso überarbeitet und mit bunten Icons versehen, was jedoch ein wenig an die Samsung-Experience als an Googles Material Design anmutet. [caption id="attachment_1100580" align="alignnone" width="620" class="tg-noadgoal"]In den Einstellungen könnt ihr zwischen hellem, dunklem und adaptivem Theme wählen. (Bild: t3n.de) In den Einstellungen könnt ihr zwischen hellem, dunklem und adaptivem Theme wählen. (Bild: t3n.de)[/caption] Mit Pie ist es ferner möglich, zwischen einem hellen und dunklen Theme zu wählen. Die dunklen Elemente reduzieren sich jedoch auf zentrale System-Komponenten wie den Launcher, die Schnelleinstellungen (die Quick-Settings) und den Google Feed. Die Systemeinstellungen werden jedoch nicht in den Farbwechsel einbezogen und bleiben stets hell. Apps von Drittanbietern sind ebenso ausgenommen. [caption id="attachment_1100585" align="alignnone" width="620" class="tg-noadgoal"]Die Themen-Änderungen wirken sich nicht auf das komplette System aus. (Bild: t3n.de) Die Themen-Änderungen wirken sich nicht auf das komplette System aus. (Bild: t3n.de)[/caption]

Lockdown: Android 9 Pie mit „Antipolizeitaste“

Google hat Pie eine Prise mehr Sicherheit verpasst. Nicht nur sind in die neue Android-Version ein verbessertes Sicherheitsmodell für Biometrie und relevante Verbesserungen der Privatsphäre wie standardmäßiges TLS und DNS über TLS integriert. Falls ihr euer Gerät vor Dritten oder Behörden schützen wollt, bietet Pie eine Sperrfunktion, ähnlich wie Apple sie in iOS 11 hineingebacken hat. [caption id="attachment_1100567" align="alignnone" width="620" class="tg-noadgoal"]Android 9 Pie besitzt wie schon iOS 11 eine „Antipolizeitaste“. (Foto: t3n.de) Android 9 Pie besitzt wie schon iOS 11 eine „Antipolizeitaste“. (Foto: t3n.de)[/caption] Durch Aktivierung der Sperrfunktion werden biometrische Entriegelungsmethoden wie Gesichtserkennung oder der Fingerabdrucksensor deaktiviert. Nur durch die Eingabe eurer Pin oder des Entsperrmusters kann das Gerät freigeschaltet werden. Standardmäßig ist die Funktion deaktiviert, sie lässt sich in den Einstellungen unter Sicherheit und Standort > Einstellungen für den Sperrbildschirm aktivieren. Der entsprechende Sperr-Button zeigt sich, wenn ihr auf den Powerbutton drückt.

Android 9 Pie: Viele Optimierungen im Detail

[caption id="attachment_1100590" align="alignnone" width="620" class="tg-noadgoal"]Scrrenshots lassen sich unter Android 9 Pie über einen Button erstellen. (Foto: t3n.de) Scrrenshots lassen sich unter Android 9 Pie über einen Button erstellen. (Foto: t3n.de)[/caption] In Android 9 Pie sind noch viele weitere kleine und größere neue Features versteckt, mit denen das System noch besser wird. Dazu gehören etwa der Button zum Erstellen von Screenshots, der über den Powerbutton erreicht wird. Erstellte Screenshots lassen sich außerdem in einem Editor schnell mit Anmerkungen versehen oder bearbeiten und versenden.
[caption id="attachment_1100606" align="alignnone" width="620" class="tg-noadgoal"]Screenshots lassen sich unter Android 9 Pie schnell bearbeiten und mit Anmerkungen versehen. (Foto: t3n.de) Screenshots lassen sich unter Android 9 Pie schnell bearbeiten und mit Anmerkungen versehen. (Foto: t3n.de)[/caption] Auf dem Ambient-Display wird fortan neben der Uhrzeit und dem Wetter auch der Akkustand in Prozent eingeblendet, sodass ihr immer im Blick habt, ob das Gerät aufgeladen werden muss. Ebenso praktisch: Ist das Display nicht auf automatische Rotation gestellt, wird euch beim Drehen vom Porträt- in den Landscape-Modus in der Navigationsleiste ein kleines Icon angezeigt. Erst wenn ihr darauf tappt, wird der Displayinhalt gedreht. [caption id="attachment_1100593" align="alignnone" width="620" class="tg-noadgoal"]Der kleine Buttons zur Displayrotation ist nicht zu verachten. (Bild: t3n.de) Der kleine Buttons zur Displayrotation ist nicht zu verachten. (Bild: t3n.de)[/caption] Der mobile Hotpost zum Aufbau einer WLAN-Verbindung ist auch ein wenig „smarter“ geworden: Er wird automatisch deaktiviert, wenn kein Gerät mehr verbunden ist. Auf diesem Wege wird der Akku geschont. Das Feature ist standardmäßig aktiviert, kann bei Bedarf aber ausgestellt werden.

Digital Wellbeing kommt später

[caption id="attachment_1099767" align="alignnone" width="620" class="tg-noadgoal"]Digital Wellbeing ist wie bei Apple iOS 12 ein elementarer Bestandteil des Systems. (Bild: Google) Digital Wellbeing ist wie bei Apple iOS 12 ein elementarer Bestandteil des Systems. (Bild: Google)[/caption] Mit Digital Wellbeing hatte Google schon im Mai auf der Entwicklerkonferenz I/O eine Funktion angekündigt, die euch mehr Kontrolle über euer Smartphone-Nutzungsverhalten geben soll. Teil der finalen Pie-Version ist es jedoch noch nicht, weshalb wir an dieser Stelle noch nicht darauf eingehen. Das Unternehmen bietet für Besitzer eines Pixel-Geräts jedoch die Möglichkeit, sich zu einem Betaprogramm anzumelden, um das Tool vorab auszuprobieren. Digital Wellbeing wird Google zufolge im Laufe des Herbsts offiziell auf Pixel-Smartphones landen, Android-One- und andere Geräte sollen noch in diesem Jahr folgen.

Android Pie: Pixel zuerst, viele andere schon im Herbst – sagt Google

[caption id="attachment_1085929" align="alignnone" width="620" class="tg-noadgoal"]Android 9.0 auf dem Pixel 2 XL. (Foto: t3n.de) Android 9.0 auf dem Pixel 2 XL. (Foto: t3n.de)[/caption] Wie für Android üblich haben die Pixel-Geräte Googles zuerst ihr Stück Torte (Pie) erhalten, laut Google soll das Update bis zum späten Herbst für viele andere Geräte folgen. Wie eingangs erwähnt, könnte der Update-Prozess der Hardware-Partner in diesem Jahr dank Project Treble schneller angekurbelt werden – Essential hat gezeigt, dass es geht. Welche Smartphones im Laufe der kommenden Monate ihr Stück vom Pie bekommen dürften, haben wir in folgendem Artikel zusammengefasst:
          Android 9 Pie ausprobiert: Das bringt Googles nächstes großes Update      Cache   Translate Page   Web Page Cache   
Android 9.0 Pie ist da und wir haben seit der ersten Beta fleissig mit dem neuen OS herumgespielt. Vieles gefällt, manches kann indes noch mutiger umgesetzt werden. Bei Android 9 Pie stehen im Unterschied zum Oreo-Update, bei dem die Neuerungen überschaubar waren, wieder zahlreiche optische Optimierungen bereit. Am offensichtlichsten ist dabei die neue gestenbasierte Steuerung – nichtsdestotrotz hat Google auch unter der Haube vieles umgebaut und mehr KI-Funktionen integriert. Wir werfen einen Blick auf die wichtigsten Änderungen.

Android 9 Pie: Endlich zeitnahe Updates?

Google hat mit Android N(ougat) einen neuen Releasezyklus eingeführt, mit dem Smartphone-Hersteller und Entwickler genügend Zeit bekommen sollten, ihre Software und Apps an die neuen OS-Versionen anpassen zu können. Wie sich herausstellte, war es in der Theorie eine gute Idee, in der Realität zeigten die meisten Hersteller wenig Ambitionen, ihre Geräte zeitnah auf eine neue Android-Version zu hieven. Beim Update auf Oreo haben sich Smartphone-Hersteller richtig viel Zeit genommen. [caption id="attachment_1100562" align="alignnone" width="620" class="tg-noadgoal"]Android 9 Pie gibt es unter anderem schon für das Nokia 7 Plus als Beta. (Foto: t3n.de) Android 9 Pie gibt es unter anderem schon für das Nokia 7 Plus als Beta. Das finale Update dürfte nicht lange auf sich warten lassen. (Foto: t3n.de)[/caption] In diesem Jahr sehen wir aber die Hoffnung auf eine Trendwende, die Google schon mit Android 8.0 und dem Project Treble angestoßen hat. Denn Android wurde auf eine modulare Architektur gestellt, die für Hersteller weniger Aufwand bedeutet, das OS mit den eigenen Modifikationen beziehungsweise Nutzeroberflächen zu versehen. Dass der Umbau funktioniert, stellten Entwickler bereits unter Beweis. Überdies hatte das Startup von Android-Gründer Andy Rubin am 6. August eine Überraschung parat: Das Essential-Phone hat sein Pie-Update am gleichen Tag wie Googles Pixel-Modelle erhalten. Die Hoffnung ist groß, dass andere Hersteller auch schneller liefern werden. Aber auch mit Pie wird Android nicht so eine rasche Verbreitung finden, wie Apple es mit seinen iOS-Updates schafft.
Jetzt lesen: Android 9.0 Pie: Diese Smartphones bekommen das neue Update

Die neue Gestensteuerung in Android 9 Pie: Guter Ansatz, nicht perfekt

Während Hersteller die schnellen Updates erst noch unter Beweis stellen müssen, widmen wir uns mit der neuen Gestensteuerung einer konkreten Funktion. Ähnlich wie bei Apples iPhone X bringt das Pie-Update eine Gestensteuerung, die sich an Palms webOS anlehnt. [caption id="attachment_1085890" align="alignnone" width="620" class="tg-noadgoal"]Der Android-Pie-Launcher mit seinen neuen Gesten. (Foto: t3n.de) Der Android-Pie-Launcher mit seiner neuen Gestenavigation. (Foto: t3n.de)[/caption] Sieben Jahre nach Einführung der Onscreen-Tasten mit dem Galaxy Nexus entledigt Google sich dieses Features und ersetzt es durch die Gestensteuerung. Anstelle der drei klassischen Tasten prangt nur noch ein länglicher Button mit abgerundeten Ecken, der an ein „Tictac“ erinnert, und nicht nur die Aufgabe des bisherigen mittigen Homebuttons übernimmt. So könnt ihr damit mit einem Tap nicht nur auf den Homescreen zurückkehren und per Langdruck den Google Assistant aktivieren. Ein Wisch ins Display hinein öffnet den Multi-Tasking-Button, der die zuletzt genutzten Apps anzeigt. Durch die Apps navigiert ihr, indem ihr das Tictac nach rechts zieht, ein kurzer Zug daran bringt euch in die zuletzt genutzte App. Wollt ihr den App-Drawer öffnen, müsst ihr eine eine längere Wischbewegung nach oben ins Display durchführen. Das Ganze klingt vielleicht etwas umständlich, funktioniert aber ausgesprochen gut. Es sollte zudem erwähnt werden, dass ihr dank der neuen Gestensteuerung selbst aus jeder App heraus in den App-Drawer gelangen könnt – bislang musste stets erst per Druck auf den Homebutton auf dem Homescreen zurückgekehrt werden. [video width="360" height="720" mp4="https://t3n.de/news/wp-content/uploads/2018/06/android-9-launcher.mp4"][/video] In der Multitasking-Ansicht befindet sich unter der Übersicht außerdem eine Google-Suchleiste und eine Auswahl an Apps, die sich je nach Nutzungsverhalten anpasst. Hier kommen Googles Machine-Learning-Algorithmen ins Spiel, die lokal auf dem Gerät ausgeführt werden – die Google-Cloud ist nicht erforderlich. Öffnet ihr den App-Drawer, wandert diese Übersicht übrigens über die komplette App-Auswahl. Im Alltag entpuppen sich die von der KI angebotenen Anwendungen als durchaus nützlich. Die Umgewöhnung an die neue Navigation geht überraschend schnell vonstatten und fühlt sich wie ein Schritt in die richtige Richtung an. Allerdings hat Google sie noch nicht so konsequent umgesetzt wie etwa Apple. Zum einen nimmt der Tictac-Button immer noch unnötigen Raum auf den Display ein, zum anderen vermissen wir eine Zurückgeste – unter Android 9 wird in der Multi-Tasking-Ansicht immer noch der Zurück-Button eingeblendet. Eine Wischgeste nach Links hätte es womöglich auch getan. Entsprechend mutet die Steuerung ein wenig wie ein Zwischenschritt an. Immerhin: Das umgestaltete Design des App-Switchers, in dem ihr eine App mit einem Wisch nach oben auswerfen könnt, ist überwiegend gelungen. [caption id="attachment_1100599" align="alignnone" width="620" class="tg-noadgoal"]Der Multi-Window-Modus ist unter Android 9 Pie schwerer als noch unter Oreo zu erreichen. (Foto: t3n.de) Der Multi-Window-Modus ist unter Android 9 Pie schwerer als noch unter Oreo zu erreichen. (Foto: t3n.de)[/caption] Verbesserungswürdig ist allerdings noch die Art und Weise, wie der Multi-Window-Modus aktiviert wird. Bislang genügte ein Tap auf den Multitasking-Button und eine Wischbewegung der jeweiligen App Richtung oberer Displayrand. Unter Pie müsst ihr erst die Multitasking-Übersicht aufrufen, auf das runde App-Icon der jeweiligen Anwendung drücken, wodurch sie ein Menü öffnet. Dort tappt ihr dann auf Bildschirm teilen – eindeutig zu viele Schritte. In der Übersicht findet ihr zudem die Möglichkeit, direkt zur App-Info zu springen, wo ihr etwa die Hintergrunddaten und mehr einschränken könnt. Die Gestensteuerung dürfte beim Pixel 3, das im Herbst erscheinen wird, als Standard eingestellt sein. Smartphone-Hersteller haben derweil immer noch die Option, auf die klassischen drei Onscreen-Buttons zu setzen. Langfristig wird Google die neue Navi mit Sicherheit zum Standard machen – und sinnvoll erweitern. [gallery title="Pixel 3 und 3 XL: So sollen die Google-Phones aussehen" ids="1091537,1091539,1091538,1091536,1091535,1091533,1091531,1091554"]

Mehr lokales Machine-Learning mit Android 9 Pie

Eine weitere große Neuerung ist wie schon angedeutet die Integration von Machine Learning. Neben der Anzeige besagter individueller Apps im Taskswitcher hat Google zusätzlich App-Aktionen integriert, die kontextbasiert Aktionen oder Apps im App-Drawer zwischen der App-Übersicht einblenden. [caption id="attachment_1100576" align="alignnone" width="620" class="tg-noadgoal"]App-Aktionen sollen euch relevante Apps und Aktionen anzeigen. (Bild: t3n.de) App-Aktionen sollen euch relevante Apps und Aktionen anzeigen. (Bild: t3n.de)[/caption] Laut Google soll das Feature voraussagen, was ihr als nächstes tun wollt und diese Aktion direkt auf eurem Handy anzeigt. Beispielsweise könnte euch morgens auf dem Weg zur Arbeit die Navigation zum Büro per Google Maps vorgeschlagen werden. Ebenso könnte auch Google Play Books oder die Podcast-App angeboten werden, um das zuletzt gehörte Hörbuch oder einen Podcast fortzusetzen. Im Alltag empfand ich die vorgeschlagenen App-Aktionen zwar als teils sinnvoll, jedoch hat sich mein Smartphone-Nutzungsverhalten derart eingeschliffen, dass ich nie auf die Idee kam, diese Buttons zu drücken. [caption id="attachment_1100574" align="alignnone" width="620" class="tg-noadgoal"]Android 9 Pie mit KI-Funktionen zur Optimierung von Akkulaufzeit und Displayhelligkeit. (Bild: t3n.de) Android 9 Pie mit KI-Funktionen zur Optimierung von Akkulaufzeit und Displayhelligkeit. (Bild: t3n.de)[/caption] Das lokale Machine Learning kommt zudem auch bei Funktionen zur Verlängerung der Akkulaufzeit und der Displayhelligkeit zum Einsatz. Mit der Funktion Intelligenter Akku wird den Batterieverbrauch von selten verwendeten Apps begrenzt, während Akkuleistung von häufig genutzten Apps entsprechend priorisiert wird. Mit der Funktion Automatische Helligkeit lernt das System, wie ihr die Bildschirmhelligkeit in verschiedenen Situationen einstellt – und übernimmt es dann automatisch für euch.

Android 9 Pie mit aufgebohrtem Benachrichtigungssystem

[caption id="attachment_977282" align="alignnone" width="620" class="tg-noadgoal"]Der Benachrichtigungsbereich wird unter Android Pie umgestaltet. (Bild: Google) Der Benachrichtigungsbereich wird unter Android Pie umgestaltet. (Bild: Google)[/caption] Erweitert und mit Intelligenz ausgerüstet hat Google auch das schon gute Benachrichtigungs-Management. Stellt Android Pie etwa fest, dass ihr bestimmte Benachrichtigungen ohne weitere Interaktion wegwischt, empfiehlt euch das System, den entsprechenden Kanal zu deaktivieren. Bestimmte App-Benachrichtigungen könnt ihr außerdem manuell abstellen oder nachträglich wieder aktivieren. Hierfür bewegt ihr euch in den Menü-Punkt Apps und Benachrichtigungen, wählt dort die entsprechende App aus und öffnet den Punkt Benachrichtigungen. In Instagram stehen euch etwa diverse Optionen zur Auswahl. Beispielsweise könnt ihr Benachrichtigungen über Uploads oder Anfragen von Direktnachrichten und weitere ausstellen. [caption id="attachment_1100564" align="alignnone" width="620" class="tg-noadgoal"]Mit Android 9 Pie könnt ihr einstellen, welche Art von Benachrichtigungen angezeigt werden sollen. (Foto. t3n.de) Mit Android 9 Pie könnt ihr einstellen, welche Art von Benachrichtigungen angezeigt werden sollen. (Foto: t3n.de)[/caption] Zudem sind die Benachrichtigungs-Kanäle nun in Kategorien aufgeteilt worden, wodurch sie einerseits übersichtlicher werden. Andererseits besteht die Option, ganze Kategorien auszustellen.

Antworten direkt aus der Benachrichtigungsleiste – auch mit Stickern

[caption id="attachment_1100572" align="alignnone" width="620" class="tg-noadgoal"]Auf Nachrichten Antworten aus der Benachrichtigungsleiste wird unter Android 9 Pie vielseitiger. (Bild: Google) Auf Nachrichten zu antworten aus der Benachrichtigungsleiste wird unter Android 9 Pie vielseitiger. (Bild: Google)[/caption] Mit Android 9 Pie erhält die Benachrichtigungsleiste noch weitere praktische Features: Viele Messaging-Apps zeigen dort künftig nicht nur die letzte Nachricht an, sondern einen Teil des Chats. Insbesondere bei Gruppenchats muss nicht mehr zwingend in die App gewechselt werden, um den Kontext zu erfassen. [caption id="attachment_1085906" align="alignnone" width="620" class="tg-noadgoal"]Android 9.0 Pie hält viele neue Emoji für euch bereit. (Bild: Emojipedia) Android 9.0 Pie hält viele neue Emoji für euch bereit. (Bild: Emojipedia)[/caption] Darüber hinaus erlaubt Pie es auch, direkt aus Benachrichtigungsleiste Sticker und Bilder einzufügen. Des Weiteren müsst ihr nicht mehr jede Antwort tippen, wie etwa in Gmail könnt ihr aus vorgefertigten Antworten, den Smart-Replys, wählen.

Android 9 Pie: Google hat an der Bluetooth-Schraube gedreht

Nett: Das Bluetooth-Symbol wird in der Benachrichtigungsleiste nur dann angezeigt, wenn eine aktive Verbindung zu einem Gerät besteht. Bei verbundenen Smartwatches wird es indes nicht angezeigt. Etwas weniger durchdacht: Um Kopfhörer oder andere Bluetooth-Geräte, die schon einmal mit dem Smartphone gekoppelt waren, neu zu verbinden, ist es erforderlich, in die Bluetooth-Einstellungen zu gehen und entsprechendes Gerät eine Ebene tiefer nach dem Tap auf Zuvor verbundene Geräte auszuwählen. Das ist ein Schritt mehr, als noch unter Android Oreo erforderlich war.

Android Pie merkt sich die Lautstärke-Einstellungen für jedes Bluetooth-Gerät

Google hat in Sachen Bluetooth weitere Dinge verändert: So lassen sich unter Pie bis zu fünf Geräte verbinden und nahtlos zwischen ihnen hin- und herwechseln. Android Oreo unterstützte lediglich zwei gleichzeitige Verbindungen. Zudem merkt sich das System die letzte Lautstärkeposition jedes Bluetooth-Lautsprechers und -Kopfhörers.

Android 9 Pie mit Designanpassungen und neuem Textauswahl-Werkzeug

Positiv hervorhebenswert ist das verbesserte Textauswahl-Tool: Orientiert an Apples iOS wird der ausgewählte Teil mitsamt Cursor wie durch eine Lupe vergrößert. [caption id="attachment_1100588" align="alignnone" width="620" class="tg-noadgoal"]Ein wenig an iOS angelehnt: Das Textauswahlwerkzeug besitzt nun eine Lupe. (Bild: t3n.de) Ein wenig an iOS angelehnt: Das Textauswahlwerkzeug besitzt nun eine Lupe. (Bild: t3n.de)[/caption] Android Pie hat auch einige Designoptimierungen an Bord. Benachrichtigungen und Elemente zur Mediensteuerung sind wie etwa in der Google-App in abgerundeten Karten untergebracht, was optisch schon was hermacht. Die Systemeinstellungen hat Google ebenso überarbeitet und mit bunten Icons versehen, was jedoch ein wenig an die Samsung-Experience als an Googles Material Design anmutet. [caption id="attachment_1100580" align="alignnone" width="620" class="tg-noadgoal"]In den Einstellungen könnt ihr zwischen hellem, dunklem und adaptivem Theme wählen. (Bild: t3n.de) In den Einstellungen könnt ihr zwischen hellem, dunklem und adaptivem Theme wählen. (Bild: t3n.de)[/caption] Mit Pie ist es ferner möglich, zwischen einem hellen und dunklen Theme zu wählen. Die dunklen Elemente reduzieren sich jedoch auf zentrale System-Komponenten wie den Launcher, die Schnelleinstellungen (die Quick-Settings) und den Google Feed. Die Systemeinstellungen werden jedoch nicht in den Farbwechsel einbezogen und bleiben stets hell. Apps von Drittanbietern sind ebenso ausgenommen. [caption id="attachment_1100585" align="alignnone" width="620" class="tg-noadgoal"]Die Themen-Änderungen wirken sich nicht auf das komplette System aus. (Bild: t3n.de) Die Themen-Änderungen wirken sich nicht auf das komplette System aus. (Bild: t3n.de)[/caption]

Lockdown: Android 9 Pie mit „Antipolizeitaste“

Google hat Pie eine Prise mehr Sicherheit verpasst. Nicht nur sind in die neue Android-Version ein verbessertes Sicherheitsmodell für Biometrie und relevante Verbesserungen der Privatsphäre wie standardmäßiges TLS und DNS über TLS integriert. Falls ihr euer Gerät vor Dritten oder Behörden schützen wollt, bietet Pie eine Sperrfunktion, ähnlich wie Apple sie in iOS 11 hineingebacken hat. [caption id="attachment_1100567" align="alignnone" width="620" class="tg-noadgoal"]Android 9 Pie besitzt wie schon iOS 11 eine „Antipolizeitaste“. (Foto: t3n.de) Android 9 Pie besitzt wie schon iOS 11 eine „Antipolizeitaste“. (Foto: t3n.de)[/caption] Durch Aktivierung der Sperrfunktion werden biometrische Entriegelungsmethoden wie Gesichtserkennung oder der Fingerabdrucksensor deaktiviert. Nur durch die Eingabe eurer Pin oder des Entsperrmusters kann das Gerät freigeschaltet werden. Standardmäßig ist die Funktion deaktiviert, sie lässt sich in den Einstellungen unter Sicherheit und Standort > Einstellungen für den Sperrbildschirm aktivieren. Der entsprechende Sperr-Button zeigt sich, wenn ihr auf den Powerbutton drückt.

Android 9 Pie: Viele Optimierungen im Detail

[caption id="attachment_1100590" align="alignnone" width="620" class="tg-noadgoal"]Scrrenshots lassen sich unter Android 9 Pie über einen Button erstellen. (Foto: t3n.de) Scrrenshots lassen sich unter Android 9 Pie über einen Button erstellen. (Foto: t3n.de)[/caption] In Android 9 Pie sind noch viele weitere kleine und größere neue Features versteckt, mit denen das System noch besser wird. Dazu gehören etwa der Button zum Erstellen von Screenshots, der über den Powerbutton erreicht wird. Erstellte Screenshots lassen sich außerdem in einem Editor schnell mit Anmerkungen versehen oder bearbeiten und versenden.
[caption id="attachment_1100606" align="alignnone" width="620" class="tg-noadgoal"]Screenshots lassen sich unter Android 9 Pie schnell bearbeiten und mit Anmerkungen versehen. (Foto: t3n.de) Screenshots lassen sich unter Android 9 Pie schnell bearbeiten und mit Anmerkungen versehen. (Foto: t3n.de)[/caption] Auf dem Ambient-Display wird fortan neben der Uhrzeit und dem Wetter auch der Akkustand in Prozent eingeblendet, sodass ihr immer im Blick habt, ob das Gerät aufgeladen werden muss. Ebenso praktisch: Ist das Display nicht auf automatische Rotation gestellt, wird euch beim Drehen vom Porträt- in den Landscape-Modus in der Navigationsleiste ein kleines Icon angezeigt. Erst wenn ihr darauf tappt, wird der Displayinhalt gedreht. [caption id="attachment_1100593" align="alignnone" width="620" class="tg-noadgoal"]Der kleine Buttons zur Displayrotation ist nicht zu verachten. (Bild: t3n.de) Der kleine Buttons zur Displayrotation ist nicht zu verachten. (Bild: t3n.de)[/caption] Der mobile Hotpost zum Aufbau einer WLAN-Verbindung ist auch ein wenig „smarter“ geworden: Er wird automatisch deaktiviert, wenn kein Gerät mehr verbunden ist. Auf diesem Wege wird der Akku geschont. Das Feature ist standardmäßig aktiviert, kann bei Bedarf aber ausgestellt werden.

Digital Wellbeing kommt später

[caption id="attachment_1099767" align="alignnone" width="620" class="tg-noadgoal"]Digital Wellbeing ist wie bei Apple iOS 12 ein elementarer Bestandteil des Systems. (Bild: Google) Digital Wellbeing ist wie bei Apple iOS 12 ein elementarer Bestandteil des Systems. (Bild: Google)[/caption] Mit Digital Wellbeing hatte Google schon im Mai auf der Entwicklerkonferenz I/O eine Funktion angekündigt, die euch mehr Kontrolle über euer Smartphone-Nutzungsverhalten geben soll. Teil der finalen Pie-Version ist es jedoch noch nicht, weshalb wir an dieser Stelle noch nicht darauf eingehen. Das Unternehmen bietet für Besitzer eines Pixel-Geräts jedoch die Möglichkeit, sich zu einem Betaprogramm anzumelden, um das Tool vorab auszuprobieren. Digital Wellbeing wird Google zufolge im Laufe des Herbsts offiziell auf Pixel-Smartphones landen, Android-One- und andere Geräte sollen noch in diesem Jahr folgen.

Android Pie: Pixel zuerst, viele andere schon im Herbst – sagt Google

[caption id="attachment_1085929" align="alignnone" width="620" class="tg-noadgoal"]Android 9.0 auf dem Pixel 2 XL. (Foto: t3n.de) Android 9.0 auf dem Pixel 2 XL. (Foto: t3n.de)[/caption] Wie für Android üblich haben die Pixel-Geräte Googles zuerst ihr Stück Torte (Pie) erhalten, laut Google soll das Update bis zum späten Herbst für viele andere Geräte folgen. Wie eingangs erwähnt, könnte der Update-Prozess der Hardware-Partner in diesem Jahr dank Project Treble schneller angekurbelt werden – Essential hat gezeigt, dass es geht. Welche Smartphones im Laufe der kommenden Monate ihr Stück vom Pie bekommen dürften, haben wir in folgendem Artikel zusammengefasst:
          KI für den Raspberry Pi: Tensorflow macht’s möglich      Cache   Translate Page   Web Page Cache   
Das KI-Framework Tensorflow von Google unterstützt jetzt auch den Raspberry Pi. Machine Learning ist damit für den Einplatinen-Rechner kein Problem mehr. KI-Lösungen auf dem Einplatinen-Rechner Raspberry Pi: Das ist mit dem neuen Update 1.9 des Machine-Learning-Frameworks Tensorflow ohne Probleme möglich.

Was ist Tensorflow?

Tensorflow ist ein von Google entwickeltes Machine-Learning-Framework. Ursprünglich wurde Tensorflow für den internen Bedarf bei Google entwickelt. Später wurde das Framework jedoch unter einer Open-Source-Lizenz veröffentlicht. Genutzt wird Tensorflow hauptsächlich mit der Sprache Python. Denkbar sind aber auch Java, C oder Go.
Als Google Tensorflow veröffentlicht hat, sollte es auf so vielen Plattformen wie möglich laufen. Unterstützt wurden bislang Windows, macOS, Linux, iOS und Android. Die Entwicklung für den Einplatinen-Rechner war hingegen mit großem Aufwand verbunden, schreibt einer der Tensorflow-Developer auf Medium. Dank einer Zusammenarbeit mit der Raspberry-Pi-Foundation ist die Unterstützung jedoch ab der Version 1.9 geglückt.

Unglaubliche Raspberry-Pi-Projekte

Was alles mit dem Raspberry Pi möglich ist, zeigen euch bereits diese unglaublichen Projekte. Mit dem Open-Source-Framework erweitern sich die Möglichkeiten aber nochmal deutlich, da nun der Einsatz von KI und Machine Learning auf dem Minirechner denkbar einfach geworden ist. Wozu Tensorflow in der Lage ist, zeigen auch ein Großteil der Google-Lösungen. Denn bei vielen kommt das Framework bereits zum Einsatz. Etwa beim Google-Übersetzer oder der Bildersuche. [gallery booster="true" title="Magic Mirror: Spiegel zeigt Wetter und Nachrichten – dank Raspberry Pi" id="560292" ids="560301,560300,560302,560304,560305,560306,560303"] Um loszulegen, benötigt ihr lediglich das Betriebsystem Raspbian ab der Version 9 auf eurem Raspberry Pi. Für die Entwicklung kommt ihr außerdem nicht um Python herum. Benötigt wird entweder die Version 2.7 beziehungsweise 3.4 oder neuer. Installieren könnt ihr Tensorflow mit dem Verwaltungswerkzeug „pip“ für Python. Mehr Details zur Installation findet ihr hier. Auch spannend:
          Machine learning for Bs->MuMu decaysStudent Session      Cache   Translate Page   Web Page Cache   
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          Product Manager, Marketplace Growth - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sat, 14 Jul 2018 06:23:30 GMT - View all New York, NY jobs
          QA Engineer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Fri, 08 Jun 2018 16:35:13 GMT - View all New York, NY jobs
          Data Scientist - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Tue, 05 Jun 2018 16:15:49 GMT - View all New York, NY jobs
          Back End Engineer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sun, 03 Jun 2018 06:21:49 GMT - View all New York, NY jobs
          UI Engineer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sun, 27 May 2018 20:27:03 GMT - View all New York, NY jobs
          AI Conversation Designer - Wade & Wendy - New York, NY      Cache   Translate Page   Web Page Cache   
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sat, 14 Apr 2018 06:15:32 GMT - View all New York, NY jobs
          Открытый курс по ML      Cache   Translate Page   Web Page Cache   
Курс по машинному обучению от mail.ru

См. также другие публикации по machine learning и поиск учебных курсов


          Data Scientist & Machine Learning Engineer - Telenor Microfinance Bank Limited - Islamabad      Cache   Translate Page   Web Page Cache   
Position / Title: Data Scientist & Machine Learning Engineer Job Type: Permanent Department: Digital Business Location: Islamabad Qualification & Experience...
From jobssection.com - Fri, 03 Aug 2018 03:16:55 GMT - View all Islamabad jobs
          Offer - Machine Learning classroom course Pune - INDIA      Cache   Translate Page   Web Page Cache   
Python will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods.Deep Learning with Python introduces the field of deep learning using the Python language.The Training is organizing by the Best Machine Learning Training Company NearLearn. Enroll Today for Machine Learning Certification in Pune. Near Learn has been designed for the requirement of having the stronghold in planning Machine learning algorithms from the bottom . This has been favored as the best and robust platform for having Machine Learning systems.For More Details Contact Us Himansu: +91-9739305140Email: info@nearlearn.com
          A probabilistic graphical model based data compression architecture for Gaussian sources      Cache   Translate Page   Web Page Cache   
A probabilistic graphical model based data compression architecture for Gaussian sources Lai, Wai Lok, M. Eng. Massachusetts Institute of Technology Data is compressible because of inherent redundancies in the data, mathematically expressed as correlation structures. A data compression algorithm uses the knowledge of these structures to map the original data to a different encoding. The two aspects of data compression, source modeling, ie. using knowledge about the source, and coding, ie. assigning an output sequence of symbols to each output, are not inherently related, but most existing algorithms mix the two and treat the two as one. This work builds on recent research on model-code separation compression architectures to extend this concept into the domain of lossy compression of continuous sources, in particular, Gaussian sources. To our knowledge, this is the first attempt with using with sparse linear coding and discrete-continuous hybrid graphical model decoding for compressing continuous sources. With the flexibility afforded by the modularity of the architecture, we show that the proposed system is free from many inadequacies of existing algorithms, at the same time achieving competitive compression rates. Moreover, the modularity allows for many architectural extensions, with capabilities unimaginable for existing algorithms, including refining of source model after compression, robustness to data corruption, seamless interface with source model parameter learning, and joint homomorphic encryption-compression. This work, meant to be an exploration in a new direction in data compression, is at the intersection of Electrical Engineering and Computer Science, tying together the disciplines of information theory, digital communication, data compression, machine learning, and cryptography. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.; Cataloged from PDF version of thesis.; Includes bibliographical references (pages 107-108).
          Teach2Learn : gamifying education to gather training data for natural language processing      Cache   Translate Page   Web Page Cache   
Teach2Learn : gamifying education to gather training data for natural language processing O'Sullivan, John J. D Teach2Learn is a website which crowd-sources the problem of labeling natural text samples using gamified education as an incentive. Students assign labels to text samples from an unlabeled data set, thereby teaching superised machine learning algorithms how to interpret new samples. In return, students can learn how that algorithm works by unlocking lessons written by researchers. This aligns the incentives of researchers and learners to help both achieve their goals. The application used current best practices in gamification to create a motivating structure around that labeling task. Testing showed that 27.7% of the user base (5/18 users) engaged with the content and labeled enough samples to unlock all of the lessons, suggesting that learning modules are sufficient motivation for the right users. Attempts to grow the platform through paid social media advertising were unsuccessful, likely because users aren't looking for a class when they browse those sites. Unpaid posts on subreddits discussing related topics, where users were more likely to be searching for learning opportunities, were more successful. Future research should seek users through comparable sites and explore how Teach2Learn can be used as an additional learning resource in classrooms. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.; Cataloged from PDF version of thesis.; Includes bibliographical references (pages 65-66).
          Machine Learning Engineer - Technica Corporation - Dulles, VA      Cache   Translate Page   Web Page Cache   
Technica Corporation is seeking a Machine Learning Engineer to support our internal Innovation, Research and Development (IRD) team....
From Technica Corporation - Wed, 11 Jul 2018 06:07:15 GMT - View all Dulles, VA jobs
          Sales Engineer - Hitachi Vantara - New York, NY      Cache   Translate Page   Web Page Cache   
Account Managers, internal specialists and customers. Understanding of Data Science and Machine Learning....
From Hitachi Vantara - Sat, 04 Aug 2018 04:47:47 GMT - View all New York, NY jobs
          iOS Developer - PGS SOFTWARE - Rzeszów, podkarpackie      Cache   Translate Page   Web Page Cache   
Augmented Reality, Machine Learning, iBeacons, Top Level Security. Elastyczne godziny pracy....
Od PGS SOFTWARE - Wed, 08 Aug 2018 14:51:19 GMT - Pokaż wszystkie Rzeszów, podkarpackie oferty pracy
          Product :: Pragmatic AI: An Introduction to Cloud-Based Machine Learning      Cache   Translate Page   Web Page Cache   
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          Ya está aquí Oracle Autonomous Transaction Processing      Cache   Translate Page   Web Page Cache   
Larry Ellison anuncia la disponibilidad de la nueva base de datos autónoma en la nube, que utiliza tecnologías de ‘machine learning’ y de automatización para proporcionar ahorros de costes, seguridad, disponibilidad y productividad.
          Economist - Forecasting - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience with machine learning applications. We are breaking fresh ground, pioneering in a program that is crucial for future Amazon growth, and our business...
From Amazon.com - Wed, 27 Jun 2018 07:21:23 GMT - View all Seattle, WA jobs
          Research Scientist - Machine Learning and NLP      Cache   Translate Page   Web Page Cache   
NY-NEW YORK CITY, Our client is a financial services, data and multiformat media company, highly respected in the market for its leading data, managed services, analytics and equity trading platforms. They are looking to add a skilled research scientist and data science engineer to their machine learning efforts. The company is developing a host of new applications, including market impact indicators, streaming soc
          Machine learning Engineer on IBM technology - Tummyfill Solution - UAE      Cache   Translate Page   Web Page Cache   
These include Finance, HR, Distribution Channels, Order Management and Sales. Machine learning Engineer on IBM technology....
From Tummyfill Solution - Thu, 09 Aug 2018 02:27:44 GMT - View all UAE jobs
          Principal Market Validation Specialist - PTC - Needham, MA      Cache   Translate Page   Web Page Cache   
Advance knowledge and experience with Machine Learning / Data Science / Analytics. Customer Satisfaction focus, both internal and external, with strong...
From PTC - Wed, 16 May 2018 14:29:21 GMT - View all Needham, MA jobs
          Principal Market Validation Specialist - PTC - Needham, MA      Cache   Translate Page   Web Page Cache   
Advance knowledge and experience with Machine Learning / Data Science / Analytics. Customer Satisfaction focus, both internal and external, with strong...
From PTC - Wed, 16 May 2018 14:29:21 GMT - View all Needham, MA jobs
          Does any one use dedi server or VPS as workstation?      Cache   Translate Page   Web Page Cache   

I am a developer and I don't use VPS for commercial purposes. I only use it for personal legal use.

I have a i7-950, 24GB RAM, 3 separate SSDs system. Between the moves, I haven't been turning it on. Also windows 10 update has stopped. (One of the idea is to install Linux directly and use it, or use proxmox and install it. User port forwarding etc.. to access remotely. However upstream bandwidth sucks from the ISP 5mbps. )

A new system would easily cost me over $1200 or a good laptop would cost me $1800. So renting seems like a good idea, specially when you get good pricing from netcup or hetzner.

So given that fact, I am even thinking about renting a dedicated server or a good VPS to use it as a "cloud" workstation. So I am price sensitive and afraid of long commitments.

I plan to have at least 32GB RAM as I plan to run some analytics and machine learning algorithms. I can practically live with under 1TB bandwidth.

Is this a popular idea? Has anyone tried this?


          Linux Foundation and Kernel Development      Cache   Translate Page   Web Page Cache   
  • Containers Microconference Accepted into 2018 Linux Plumbers Conference

    The Containers Micro-conference at Linux Plumbers is the yearly gathering of container runtime developers, kernel developers and container users. It is the one opportunity to have everyone in the same room to both look back at the past year in the container space and discuss the year ahead.

    In the past, topics such as use of cgroups by containers, system call filtering and interception (Seccomp), improvements/additions of kernel namespaces, interaction with the Linux Security Modules (AppArmor, SELinux, SMACK), TPM based validation (IMA), mount propagation and mount API changes, uevent isolation, unprivileged filesystem mounts and more have been discussed in this micro-conference.

  • LF Deep Learning Foundation Advances Open Source Artificial Intelligence With Major Membership Growth

    The LF Deep Learning Foundation, an umbrella organization of The Linux Foundation that supports and sustains open source innovation in artificial intelligence, machine learning, and deep learning, today announced five new members: Ciena, DiDi, Intel, Orange and Red Hat. The support of these new members will provide additional resources to the community to develop and expand open source AI, ML and DL projects, such as the Acumos AI Project, the foundation's comprehensive platform for AI model discovery, development and sharing.

  • A quick history of early-boot memory allocators

    One might think that memory allocation during system startup should not be difficult: almost all of memory is free, there is no concurrency, and there are no background tasks that will compete for memory. Even so, boot-time memory management is a tricky task. Physical memory is not necessarily contiguous, its extents change from system to system, and the detection of those extents may be not trivial. With NUMA things are even more complex because, in order to satisfy allocation locality, the exact memory topology must be determined. To cope with this, sophisticated mechanisms for memory management are required even during the earliest stages of the boot process.

    One could ask: "so why not use the same allocator that Linux uses normally from the very beginning?" The problem is that the primary Linux page allocator is a complex beast and it, too, needs to allocate memory to initialize itself. Moreover, the page-allocator data structures should be allocated in a NUMA-aware way. So another solution is required to get to the point where the memory-management subsystem can become fully operational.

    In the early days, Linux didn't have an early memory allocator; in the 1.0 kernel, memory initialization was not as robust and versatile as it is today. Every subsystem initialization call, or simply any function called from start_kernel(), had access to the starting address of the single block of free memory via the global memory_start variable. If a function needed to allocate memory it just increased memory_start by the desired amount. By the time v2.0 was released, Linux was already ported to five more architectures, but boot-time memory management remained as simple as in v1.0, with the only difference being that the extents of the physical memory were detected by the architecture-specific code. It should be noted, though, that hardware in those days was much simpler and memory configurations could be detected more easily.

  • Teaching the OOM killer about control groups

    The kernel's out-of-memory (OOM) killer is summoned when the system runs short of free memory and is unable to proceed without killing one or more processes. As might be expected, the policy decisions around which processes should be targeted have engendered controversy for as long as the OOM killer has existed. The 4.19 development cycle is likely to include a new OOM-killer implementation that targets control groups rather than individual processes, but it turns out that there is significant disagreement over how the OOM killer and control groups should interact.

    To simplify a bit: when the OOM killer is invoked, it tries to pick the process whose demise will free the most memory while causing the least misery for users of the system. The heuristics used to make this selection have varied considerably over time — it was once remarked that each developer who changes the heuristics makes them work for their use case while ruining things for everybody else. In current kernels, the heuristics implemented in oom_badness() are relatively simple: sum up the amount of memory used by a process, then scale it by the process's oom_score_adj value. That value, found in the process's /proc directory, can be tweaked by system administrators to make specific processes more or less attractive as an OOM-killer target.

    No OOM-killer implementation is perfect, and this one is no exception. One problem is that it does not pay attention to how much memory a particular user has allocated; it only looks at specific processes. If user A has a single large process while user B has 100 smaller ones, the OOM killer will invariably target A's process, even if B is using far more memory overall. That behavior is tolerable on a single-user system, but it is less than optimal on a large system running containers on behalf of multiple users.

read more


          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page   Web Page Cache   
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
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          Senior Manager, Software Engineering - DELL - Austin, TX      Cache   Translate Page   Web Page Cache   
Experience with machine learning and artificial intelligence. Learn more about Diversity and Inclusion at Dell here....
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          Director, Software Engineering - DELL - Austin, TX      Cache   Translate Page   Web Page Cache   
Experience with machine learning and artificial intelligence. Learn more about Diversity and Inclusion at Dell here....
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          Cloud Solution Architect - Microsoft - Philadelphia, PA      Cache   Translate Page   Web Page Cache   
Machine Learning (SAS, R, Python). Problem-solving mentality leveraging internal and/or external resources....
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          Software Development Engineer - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
2 years experience working on machine learning based models. The engineer will play a pivotal role in the expansion of pricing software, with the mission to...
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You plan requirements with internal customers and usher projects through the entire project lifecycle. We build the technologies that transform the way we think...
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          Ingénieur Analyse de Données et Logiciels - Intelligence Manufacturière - Data Analytics and Software Engineer – Manufacturing Intelligence - Alcoa Corp. - Deschambault, QC      Cache   Translate Page   Web Page Cache   
IoT, Connected Worker, Machine Learning, Cloud, Robotics, Augmented Reality. Ce poste peut être basé à l'une ou l'autre des Alumineries d'Alcoa dans le monde/...
From Alcoa Corp. - Fri, 29 Jun 2018 03:08:28 GMT - View all Deschambault, QC jobs
          Ingénieur Analyse de Données et Logiciels - Intelligence Manufacturière - Data Analytics and Software Engineer – Manufacturing Intelligence - Alcoa Corporation - Deschambault, QC      Cache   Translate Page   Web Page Cache   
IoT, Connected Worker, Machine Learning, Cloud, Robotics, Augmented Reality. Description du poste....
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          Best Practices for the Protection of Information Assets, Part 2      Cache   Translate Page   Web Page Cache   

In Part 1 of this article series , we discussed Information Security Management, or ISM. This second installment will cover the implementation and monitoring of security controls, including logical access controls, remote access controls, network security, controls/detection tools against information system attacks, security testing techniques and controls that prevent data leakage.

Implementation and Monitoring of Security Controls

Security controls should focus on the integrity of data, the data classification system, and the policies in places that ensure that data is handled properly.

Logical Access Controls

Ensure there are policies in place on access and access controls logical access controls at both operating system level and the application level are designed to protect information assets by sustaining policies and procedures. The management override is akin to a fail-safe mechanism. Overall, these controls manage the identification, authentication and restriction of users to authorized functions and data.

Types and Principles of Access

Types and principles of access include subject access (identification of individual having an ID), service access (data passing through an access point), least privilege, segregation of duties and split custody.

Example:Target may have avoided their notorious 2013 breach if they had not failed to follow the principle of least privilege. An HVAC contractor with a permission to upload executables broadens the attack surface for cybercriminals.

Example:As an example of Edward Snowden’s revelations, the NSA decided to apply the principle of least privilege and revoked higher-level powers from 90% of its employees.

Passwords

Ensure there are occasional or event-driven change and recovery policies reactivation with a new password so long as the user identity can be verified. People often use weak passwords, tend to share them or transmit/store them in cleartext; a succession of failed attempts to login with a password should result in locking out the account.

Biometrics can replace passwords in future by creating a system that can restrict access based on unique physical attributes or behavior. Issues with this approach include false reject rate (FRR), false accept rate (FAR) and crossover error rate (CER), and privacy.

Example:To unlock mobile devices, the scientist in Yahoo’s Research Labs are experimenting with utilizing ears, knuckles, and fingertips as biometric passwords.

Single Sign-On (SSO)

This technique consolidates access operations among various systems into one centralized administrative function. SSO interfaces with client servers (local and remote users) and distributed systems, mainframe systems and network security, including remote access mechanisms.

Access Control Lists

Access control lists (ACLs) are the equivalent of a register in which the system enlists users who have permission to access and use a given system resource. ACLs can store information on users’ type of access.

Example: To illustrate the usefulness of access control lists, consider a medical research experiment where the files that contain experimental results have an ACL that permits read-and-write access to all members of a research group except for one member, who is working on another experiment whose results should not be influenced by the results of the first one.

System Access Audit Logging

Almost all access control software automatically logs and report access attempts, which forms an audit trail to observe any suspicious activities and potential hacking attempts (e.g., brute-force attack on a specifically-targeted high-profile logon ID). Recording all activities may be useful in the context of digital investigations

Access to the logs should be restricted.

Tools for Log Analysis include, but are not limited to: audit reduction tools, trend/variance detection tools, attack-signature detection tools and SIEM systems.

Actions an Auditor Should Undertake When Evaluating Logical Access Controls

An auditor should identify sensitive data/systems, document, evaluate and test controls over potential access and access paths, and evaluate the adequacy of the security environment.

Controls and Risks Associated With Virtualization of Systems

Moving away from a physical medium towards a virtual one, there are many important aspects one should consider: physical and logical access validation (because many virtual machines may be running in one physical system), proper configuration and network segregation (no interference among various VMs).

A 2015 Kaspersky Labs survey proved that recovery costs in the wake of a cyberattack on a virtualized infrastructure are twice as high as an attack on a physical environment. Moreover, only 27% deployed defensive mechanisms specifically designed to protect virtual environments.

Configuration, Implementation, Operation and Maintenance of Network Security Controls

Perimeter security controls such as firewalls and IDS/IPS ward off most cyberattacks against the enterprise’s network. The auditor needs to know the effectiveness of these security controls and the policies and procedures that regulate network incidents.

Other important matters are network management, legal complications with respect to online activities, network administrator procedures and service legal agreements with third parties.

Internet use, remote access and networks will all require auditing. Network infrastructure security and general network controls will require additional attention.

LAN Security Issues

An auditor should identify and document LAN topology and network design, signs of segmentation, LAN administrator and LAN owner, groups of LAN users, applications used on the LAN, and procedures for network design, support, and data security.

Wireless Security Threats

Security requirements include: authenticity, non-repudiation, accountability and network availability.

There are many forms of malicious access to WLANs. These include but are not limited to: war driving/walking/chalking, passive attacks and sniffing.

Detection Tools and Control Techniques Malware

Countermeasures against various types of malware include but are not limited to: policies, education, patch management, anti-virus software, and procedural/technical controls.

Detection Tools

Antivirus software, regular updates, layered systems (e.g., inner, perimeter, and BOYD), and honeypots and are useful detection tools and deterrents against malware.

Employee education is equally important and should not be ignored. Simple common sense on the part of employees can close multiple attack vectors, such as email phishing attempts.

Ethical Hacking Training Resources (InfoSec)

Security Testing Techniques

Begin by knowing your tools. You’ll need tools to evaluate network security and possible risks, as well as suitable mitigation techniques. Be sure to check lists of known network vulnerabilities.

Third parties may be able to provide testing services such as penetration testing. Penetrating testing, also called intrusion testing or ethical hacking, is where outside pentesters use every technique or source a potential attacker could use (open-source gathering, searching for backdoors, guessing passwords, using known exploits) to test your security. This is especially good for testing firewalls.

You should also be aware of social engineering testing. This gives you a chance to see how your staff holds up in case of a social engineering attack, such as a phone scammer trying to get people’s passwords.

Controls and Risks Associated with Data Leakage

Data leakages occur when there is a risk of sensitive information becoming public, typically by accident. The IS auditor needs to ensure that there are effective data classification policies, security awareness training and periodic audits with respect to data leakage prevention.

Note that data leakage has a totally different meaning when it comes to machine learning. Information from outside the training set could corrupt the learning capabilities of the model because it may introduce something that the model otherwise would not know.

Encryption-Related Techniques

Anyone handling or testing encryption should be familiar with encryption algorithm techniques and key length: note that complex algorithms and large keys are somewhat impractical for everyday use. Be aware of cryptographic systems, such as AES 128/256-bit and old 64-bit DES.

Other areas of interest include encryption in communications; secure socket layer (SSL)/transport layer security (TLS); secure HTTP (HTTPS); IPSec Internet protocol security; Secure Shell (SSH);and secure multipurpose Internet mail extensions (S/MIME).

Public Key Infrastructure (PKI) Components and Digital Signature Techniques

PKI establishes a trusted communication channel where parties can exchange digital keys in a safe manner. It’s widely used in e-commerce and online banking.

PKI is based on digital certificates (public key and identifying information) that are issued and cryptographically signed by a certificate authority. Validation is through the certificate authority, while a registration authority ensures third-party validation. When dealing with PKI, watch for digital certificates’ expiration dates, and be certain to check the certificate revocation list (CRL).

Controls Associated with Peer-to-Peer Computing, Instant Messaging and Web-Based Technologies

P2P computing may result in fast dissemination of viruses, worms, Trojans, spyware and so on directly among computers, as there is no central server. Meanwhile, social media risks include inappropriate sharing of information about sensitive data, staffing issues and organizational data; URL spoofing; cyberstalking; using vulnerable applications; phishing; downloading malicious attachments and clicking on malicious links.

Example:In 2016, the Facebook “fake friend” phishing scam rose to prominence. Users received a Facebook message claiming that they had been mentioned by a friend in a comment, but upon clicking on this message, it would automatically download malware onto their computers in the form of a malicious Chrome browser extension. After the installation, this malware snatched users’ Facebook account so that it could steal their data and propagate further.

To control this, implement a P2P computing policy which includes social network use and instant messaging. Corporate messaging boards are more secure than Facebook. Promote monitoring, education and awareness, and ban some types of peer-to-peer communications to narrow the net.

Controls and Risks Associated with the Use of Mobile and Wireless Devices

When dealing with mobile and wireless devices, secure Wi-Fi is required, because most of these devices communicate via a Wi-Fi network.

Implement mobile device controls, including stringent data storage, remote wipes, and theft response procedures. Clarify your workplace’s policy regarding employees bringing their own devices to work.

Voice Communications Security (PBX, VoIP)

In these cases, voice communications have been translated to binary code. This means they are still digitally-based

Increasingly common these days is VoIP or Voice over IP. VoIP boasts lower costs compared to traditional phone services; however, they tend to have worse security than ordinary phones, and one needs to protect both the data and the voice. Wiretapping is a possibility. Security measures include encrypting communications and ensuring that all software is up-to-date and patched.

Alternately, private branch exchange or PBX is a phone system that can operate for both voice and data. It provides simultaneous calls through multiple telephone lines

Example:In 2014, cybercriminals broke into the phone network of Foreman Seeley Fountain Architecture and managed to steal $166,000 worth of calls from the firm via premium-rate telephone numbers in Gambia, Somalia and the Maldives. Typically, hackers pull off such a scheme over a weekend when nobody is at work, forwarding sometimes as many as 220 minutes’ worth of calls per minute to a premium line. The criminals withdraw their cuts usually through Western Union, moneygram or wire transfer.

Conclusion

This concludes our look at best practices for the implementation of monitoring and security controls. Some of our sources are listed below, for your perusal. Join us soon for Part 3, when we’ll be examining physical and environmental protection of information assets.

Sources

What is Least Privilege & Why Do you Need It ?, Beyond Trust

Data-drained Target hurries to adopt chip-and-PIN cards , Naked Security

Yahoo ‘Bodyprint’ Turns Smartphone Touchscreens Into Biometric Sensors , Gadgets 360

NSA to cut system administrators by 90 percent to limit data access , Reuters

Security of Virtual Infrastructure , Kaspersky Lab

Facebook ‘fake friend’ phishing scam uncovered watch for these red flags , Komando

IBM Security Services 2014, Cyber Security Intelligence Index , IBM Global Technology Services


          5 Steps to a Successful Digital Workplace Strategy      Cache   Translate Page   Web Page Cache   

Today’s digital workplace is a beautiful and terrible thing. Technology helps us get more done, more quickly, than ever before, but it comes with its own challenges, from security to sprawl. In fact, the average business today uses over 300 applications, and employees shift between those applications every two to three minutes. This scenario impacts everything from IT’s overall strategy to each individual’s productivity.

 

One key unintended consequence of the digital workplace is the loss of corporate memory – a challenge we at Aurea are working hard to help companies solve with Jive’s interactive intranet. With so many applications and so much content in so many places, company culture gets diluted and eventually lost. Culture is often a fuzzy topic but the ramifications of the loss of corporate memory are serious and tangible: companies spend an average of $430,000 per departing employee due to corporate memory loss in addition to standard replacement costs.

 

What’s the solution? Create a digital workplace strategy optimized to foster corporate memory. I lay out the blueprint for this strategy in my recent article on CMSWire, How to Build a Blueprint for Your Corporate Memory.

 

You can read all the details there, but in a nutshell, it involves 5 main steps:

  1. Categorize your organization’s content.
  2. Create a data pipeline.
  3. Build an organizational knowledge graph.
  4. Add content with semantic search.
  5. Go next-gen with AI and machine learning.

 

None of these are simple, but we believe they’re critical for any company that cares about corporate memory, and we hope to facilitate each step through Jive product innovation over the coming months and years. Done right, the digital workplace can transform an organization in countless ways. It gives us technology tools, but also enables us to connect with each other in new and meaningful ways - and that’s where the real value comes in.

 

Tej Redkar

Chief Product Officer


          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
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          Ingénieur Analyse de Données et Logiciels - Intelligence Manufacturière - Data Analytics and Software Engineer – Manufacturing Intelligence - Alcoa Corporation - Deschambault, QC      Cache   Translate Page   Web Page Cache   
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Nokia is a global leader in the technologies that connect people and things. Investigate and implement machine learning based optimization to control large...
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          Une mise en perspective…      Cache   Translate Page   Web Page Cache   
Annoncés en cascade depuis l'automne 2017, à commencer par la refonte d'Azure Machine Learning et ses nouveaux services (service d'expérimentation, packages Azure Machine Learning, service de gestion des modèles, et application Workbench) – celle-ci a donné lieu à toute une série de billets sur ce même blog, de nombreux services, Framework et outils de Machine...
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Data is changing. Storage analyst Steve McDowell and I have written before about the increasing breadth of enterprise data, the impact of AI and Machine Learning on enterprise data architecture, and the overall changing landscape of data in today’s environment. Here are my thoughts.
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          AWS’ Jennifer Chronis: Cloud Tech Can Help DoD Harness Potential of Machine Learning, AI      Cache   Translate Page   Web Page Cache   
Jennifer Chronis, general manager for the Defense Department market at Amazon Web Services, told Government Matters in an interview that aired Friday she believes DoD organizations can harness the possible advantages of machine learning and artificial intelligence tools in a cloud computing environment. She said that AWS’ technology is designed to manage workload at different […]
          Introducing the Splunk Machine Learning Toolkit Version 3.4      Cache   Translate Page   Web Page Cache   
Check out key features in the Splunk Machine Learning Toolkit version 3.4, including new functionalities, more visualization and a neural network algorithm out of the box
          The rise of the IoT and artificial intelligence in industry [Q&A]      Cache   Translate Page   Web Page Cache   
While the consumer IoT has captured the imagination with smart appliances and devices, the industrial Internet of Things (IIoT) is a rapidly growing market. According to Accenture, the IIoT market could add $14.2 trillion to the global economy by 2030. IIoT is also breathing new life into industries that are in great need of digital transformation, such as manufacturing, oil and gas, and more. As a result, artificial intelligence and machine learning are quickly becoming one of the biggest priorities for companies that want to make the most of their operational data to increase outputs using less energy and costs.… [Continue Reading]

           LF Deep Learning Foundation builds membership      Cache   Translate Page   Web Page Cache   
The LF Deep Learning Foundation, whose mission is to support and sustain open source innovation in artificial intelligence, machine learning, and deep learning, announced five new members: Ciena, DiDi, Intel, Orange and Red Hat.

These companies join founding members Amdocs, AT&T, B.Yond, Baidu, Huawei, Nokia, Tech Mahindra, Tencent, Univa and ZTE.

“We are very pleased to build off the launch momentum of the LF Deep Learning Foundation and welcome new members with vast resources and technical expertise to support our growing community and ecosystem of AI projects,” said Lisbeth McNabb, Chief Operating Officer of The Linux Foundation.

Mazin Gilbert, Vice President of Advanced Technology and Systems at AT&T, has also been elected to the role of Governing Board Chair of LF Deep Learning. This position leads the board in supporting various AI and ML open source projects, including infrastructure and support initiatives related to each project.

“The Deep Learning Foundation is a significant achievement by the open source community to drive harmonization among tools and platforms in deep learning and artificial intelligence,” said Mazin Gilbert, Vice President of Advanced Technology and Systems at AT&T. “This effort will enable an open marketplace of analytics and machine learning capabilities to help expedite adoption and deployments of DL solutions worldwide.”

https://www.deeplearningfoundation.org
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          Innovation Developer - TeamSoft - Sun Prairie, WI      Cache   Translate Page   Web Page Cache   
Are you interested in topics like machine learning, IoT, Big data, data science, data analysis, satellite imagery or mobile telematics?...
From Dice - Thu, 19 Jul 2018 08:35:55 GMT - View all Sun Prairie, WI jobs
          Distilled News      Cache   Translate Page   Web Page Cache   
Machine Learning Canvas The Machine Learning Canvas is a template for developing new or documenting existing intelligent systems based on …

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          Principal Market Validation Specialist - PTC - Needham, MA      Cache   Translate Page   Web Page Cache   
Advance knowledge and experience with Machine Learning / Data Science / Analytics. Customer Satisfaction focus, both internal and external, with strong...
From PTC - Wed, 16 May 2018 14:29:21 GMT - View all Needham, MA jobs
          Can Silicon Valley workers rein in Big Tech from within? | Ben Tarnoff      Cache   Translate Page   Web Page Cache   

In our undemocratic digital world, people have little power to shape the tools that affect their lives. But tech workers could change that

An unprecedented wave of rank-and-file rebellion is sweeping Big Tech. At one company after another, employees are refusing to help the US government commit human rights abuses at home and abroad.

At Google, workers organized to shut down Project Maven, a Pentagon project that uses machine learning to improve targeting for drone strikes – and won. At Amazon, workers are pushing Jeff Bezos to stop selling facial recognition to police departments and government agencies, and to cut ties with Immigration and Customs Enforcement (Ice). At Microsoft, workers are demanding the termination of a $19.4m cloud deal with Ice. At Salesforce, workers are trying to kill the company’s contract with Customs and Border Protection (CBP).

Continue reading...
          The Golf Engine predicts the best bets for the PGA Championship      Cache   Translate Page   Web Page Cache   
We take a break from the football hype to bring you a golf engine which uses machine learning to evaluate 1,500 different statistics for every golfer on the PGA Tour over each tournament since 2004. The analysis of this massive dataset provides an opportunity to predict players that are due to go low. The engine looks […]
          Study: In Search, the News Media are Trump’s Top Competitors      Cache   Translate Page   Web Page Cache   

New Adthena study finds that cnn.com, nytimes.com, twitter.com are top Trump-related search term challengers Adthena, a leader in AI and machine learning-powered search intelligence, announced a new study examining Donald Trump-related search advertising trends. For the study, Adthena analyzed thousands of paid ads and organic searches – across desktop and mobile – from February to March 2018. According to Adthena’s analysis, […]

The post Study: In Search, the News Media are Trump’s Top Competitors appeared first on Adotas.


          Vice President, Data Science - Machine Learning - Wunderman - Dallas, TX      Cache   Translate Page   Web Page Cache   
Goldman Sachs, Microsoft, Citibank, Coca-Cola, Ford, Pfizer, Adidas, United Airlines and leading regional brands are among our clients....
From Wunderman - Thu, 26 Apr 2018 16:49:34 GMT - View all Dallas, TX jobs
          Image processing with python      Cache   Translate Page   Web Page Cache   
Classification using image processing in python (Budget: ₹750 - ₹1250 INR, Jobs: Image Processing, Machine Learning, Matlab and Mathematica, Python)
          Business Strategy, Sr. Manager - Hortonworks - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Dallas, TX jobs
          Business Strategy, Sr. Manager - Hortonworks - Atlanta, GA      Cache   Translate Page   Web Page Cache   
Business Strategy, Leadership Opportunity. Experience in the Software and/or Business Impact of Analytics, Big Data, Machine Learning/AI, Cloud is a plus....
From Hortonworks - Mon, 23 Jul 2018 20:31:09 GMT - View all Atlanta, GA jobs
          Server-CPUs: Cooper Lake und Ice Lake nutzen gleichen Sockel      Cache   Translate Page   Web Page Cache   
Intel hat einen Ausblick auf seine Server-Roadmap gegeben: Noch 2018 soll Cascade Lake SP mit einer Befehlssatzerweiterung für Machine Learning erscheinen, 2019 und 2020 dann Cooper Lake SP und Ice Lake SP für einen neuen Sockel. AMD legt bis dahin mit 64 Zen-Kernen vor. (Prozessor, Intel)
          Lifting the Fog for DoD      Cache   Translate Page   Web Page Cache   

While AI provides significant advantages, it can be challenging to adopt without the right computing and development resources to enable it. Many government agencies, however, still struggle with legacy and outdated IT infrastructures. That's why a trusted and robust cloud infrastructure is a critical component of the DoD’s journey to AI and machine learning.

The post Lifting the Fog for DoD appeared first on GovLoop.


          Machine Learning’s Awkward Era      Cache   Translate Page   Web Page Cache   
The whole machine learning field has a huge amount to offer chemistry, medicinal chemistry, and biomedical science in general. I don’t think that anyone seriously disputes that part – the arguing starts when you ask when this promise might be realized. In the abstract, the idea of tireless, relentless analysis of the huge piles of
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Dallas, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:15 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Austin, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all Austin, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - Houston, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:13 GMT - View all Houston, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - South Central, US - Siemens - San Antonio, TX      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:34 GMT - View all San Antonio, TX jobs
          Bell Labs - Integrated Photonics Researcher - NOKIA - Holmdel, NJ      Cache   Translate Page   Web Page Cache   
Nokia is a global leader in the technologies that connect people and things. Investigate and implement machine learning based optimization to control large...
From Nokia - Mon, 18 Jun 2018 15:55:57 GMT - View all Holmdel, NJ jobs
          AA Chief SW Architect - NOKIA - San Jose, CA      Cache   Translate Page   Web Page Cache   
Analytics, AI, and machine learning. Presenting to customers, industry forums, analysts and internal audiences....
From Nokia - Mon, 18 Jun 2018 15:51:40 GMT - View all San Jose, CA jobs
          Kasparov on AI: Can We Create Ethical AI? (Video)      Cache   Translate Page   Web Page Cache   

Ethical AI - Gary Kasparov

One of the machine learning mistakes was the tragic death of Elaine Herzberg in Tempe, Arizona by UBER’s self-driving car. Initially there was a focus on the fact that machine learning made an error, but in fact, the answer was even more unsatisfying: the algorithm did detect the pedestrian but the car was programed to be less sensitive to potential false positives, causing the image and detection of the pedestrian to be ignored.

As people become more aware of the number of decisions driven by artificial intelligence, some have raised a call for so-called “ethical AI.” AI is not ethical, but our use of it and tuning definitely is. At FICO World 2018, I sat down with Chess Grandmaster Garry Kasparov to discuss the hot topics in the world of AI, and asked: What do you think of ethical AI?

Watch the video below, and for more of my conversation with Garry Kasparov on AI go to www.fico.com/ai-analytics, where you can see other excerpts as well as our full discussion.

Do I agree with Garry? Read my own thoughts on AI and related analytic topics on Twitter @ScottZoldi.

The post Kasparov on AI: Can We Create Ethical AI? (Video) appeared first on FICO.


          How Can Machine Learning Fight Application Fraud? (Video)      Cache   Translate Page   Web Page Cache   

Words: Preventing Application Fraud

We are tackling an exponentially growing type of fraud - application fraud – and we recognize that machine learning analytics must be a critical part of a financial institution’s control strategy.

With everyone talking about machine learning and artificial intelligence, it’s important to level-set on what these terms actually mean, and to understand how can we operationalize these analytic innovations. In this clip, Derek Dempsey, FICO’s application fraud analytics practice leader, shares insights into classical and adaptive machine learning concepts that can be used to fight application fraud.

Want to learn more? Check out the full webinar “Layered Defense in the Fight Against Application Fraud”.

The post How Can Machine Learning Fight Application Fraud? (Video) appeared first on FICO.


          Apple Details Improvements to Siri's Ability to Recognize Names of Local Businesses and Destinations      Cache   Translate Page   Web Page Cache   
In a new entry in its Machine Learning Journal, Apple has detailed how it approached the challenge of improving Siri's ability to recognize names of local points of interest, such as small businesses and restaurants.


In short, Apple says it has built customized language models that incorporate knowledge of the user's geolocation, known as Geo-LMs, improving the accuracy of Siri's automatic speech recognition system. These models enable Siri to better estimate the user's intended sequence of words.

Apple says it built one Geo-LM for each of the 169 Combined Statistical Areas in the United States, as defined by the U.S. Census Bureau, which encompass 80 percent of the country's population. Apple also built a single global Geo-LM to cover all areas not defined by CSAs around the world.

When a user queries Siri, the system is customized with a Geo-LM based on the user's current location. If the user is outside of a CSA, or if Siri doesn't have access to Location Services, the system defaults to the global Geo-LM.

Apple's journal entry is highly technical, and quite exhaustive, but hopefully this means that Siri should be able to better understand the names of local points of interest, and also be able to better distinguish between a Tom's Restaurant in Iowa and Kansas based on a user's geolocation.

In its testing, Apple found that the customized language models reduced Siri's error rate by between 41.9 and 48.4 percent in eight major U.S. metropolitan regions: Boston, Chicago, Los Angeles, Minneapolis, New York, Philadelphia, Seattle, and San Francisco, excluding mega-chains like Walmart.

Siri still trails Google Assistant in overall accuracy, according to a recent study by research firm Loup Ventures, but hopefully these improvements eliminate some of the frustration of querying Siri about obscurely named places.


Discuss this article in our forums


          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page   Web Page Cache   
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Mon, 14 May 2018 23:57:10 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Portland, OR      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:10 GMT - View all Portland, OR jobs
          AWS Architect - Insight Enterprises, Inc. - Chicago, IL      Cache   Translate Page   Web Page Cache   
Database architecture, Big Data, Machine Learning, Business Intelligence, Advanced Analytics, Data Mining, ETL. Internal teammate application guidelines:....
From Insight - Thu, 12 Jul 2018 01:56:10 GMT - View all Chicago, IL jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - San Francisco, CA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:12 GMT - View all San Francisco, CA jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Los Angeles, CA      Cache   Translate Page   Web Page Cache   
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:13 GMT - View all Los Angeles, CA jobs
          Instructor (Data Science, Artificial Intelligence, Machine Learning) - Cortechma Inc. - Thornhill, ON      Cache   Translate Page   Web Page Cache   
Cortechma Academy team is looking for professors, instructors and engineers with both academically and professionally strong background specializing in one of...
From Indeed - Wed, 01 Aug 2018 16:56:17 GMT - View all Thornhill, ON jobs
          MACHINE LEARNING ENGINEER FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Engineer for Speech related Applications (6 months contract)....
From Huawei Canada - Mon, 18 Jun 2018 23:46:16 GMT - View all Montréal, QC jobs
          MACHINE LEARNING INTERN FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Intern for Speech related Applications....
From Huawei Canada - Mon, 18 Jun 2018 17:50:57 GMT - View all Montréal, QC jobs
          MACHINE LEARNING HARDWARE RESEARCHER OR DEVELOPER - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Hardware Researcher or Developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:32 GMT - View all Montréal, QC jobs
          Machine Learning Software Developer - Huawei Canada - Montréal, QC      Cache   Translate Page   Web Page Cache   
We thank all applicants for their interest in career opportunities with Huawei. ML Software developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:31 GMT - View all Montréal, QC jobs
          Süni Zəka, Maşın Öyrənməsi və Dərin Öyrənmə arasındakı fərqlər nədir?      Cache   Translate Page   Web Page Cache   
suni zeka, masin oyrenmesi, derin oyrenme, Artificial İntelligence, Machine Learning, Deep Learning arasindaki ferq, texnologiyanin insan davranisarini tekrarlamasi, suni zekanin qurulmasi, masin oyrenmesinin alt coxlugu, problemlerin reqemsal helli, reqemsal metod, reqemsal hell usulu

Süni Zəka (Artificial İntelligence), Maşın Öyrənməsi (Machine Learning) və Dərin Öyrənmə (Deep Learning) arasındakı fərqi müəyyən etmək üçün gəlin, hər birinin qısa təriflərinə nəzər salaq.

Süni Zəka (AI) – texnologiyanın insan davranışlarını təkrarlamasının təmin edilməsidir.


          Data Analizində Ən Vacib Nöqtələr Hansılardır?      Cache   Translate Page   Web Page Cache   
data analizi, big data, verilenlerin analizi, verilenlerin tehlili, data analizinin aparilmasi, verilenlerin tehlilinin heyata kecirilmesi, data analitikasinda kreativlik, regressiya, masin oyrenmesi, machine learning, datanin keyfiyeti, alqoritmler, missing values, catismayan verilenler, Araşdırma Data Analizi, Exploratory Data Analysis, kommunikasiya

Kreativlik deyəndə ilk ağla gələn marketinq olur. Əslində isə kreativliyin ən çox tələb olunduğu sahələrdən biri də data analitikasıdır. Datanın gündən-günə avtomatlaşdırılması data analitiklərinin də süni intellektlə əvəzlənməsini istisna etmir. Nəzərə alsaq ki, datada axtarılan suallar, həllini gözləyən problemlər gizlənir, bu işin robotlara həvalə olunması bir az fantastik yanaşma da ola bilər. “Bütün analizlər fərqlidir.” – deyə, bir anlayış var. Lakin bu, həqiqətən də, belə deyil. Hesablamaların əksəriyyəti oxşardır və müəyyən dərəcəyə qədər avtomatlaşdırıla bilər.


          NSE working on artificial intelligence to boost surveillance operations      Cache   Translate Page   Web Page Cache   
The exchange is harnessing machine learning, artificial intelligence and blockchain technologies to bring in operational efficiencies, improve delivery services and reduce costs.
          Desenvolvedor Java para projetos de IA e Machine Learning - Hop - Belo Horizonte, MG      Cache   Translate Page   Web Page Cache   
Nós somos a Hop, uma empresa que nasceu para dar vida às ideias inovadoras! Unimos metodologias de Design com Inteligência Artificial e Computação Cognitiva...
De Hop - Tue, 24 Jul 2018 13:51:19 GMT - Visualizar todas as empregos: Belo Horizonte, MG
          Comment on Machine Learning with R | Machine Learning Algorithms | Data Science Training | Edureka by edureka!      Cache   Translate Page   Web Page Cache   
Hey Jayamohan, thank you for watching our video. We are glad that you liked our content. Do subscribe and stay connected with us. Cheers :)
          Comment on Logistic Regression in R | Machine Learning Algorithms | Data Science Training | Edureka by edureka!      Cache   Translate Page   Web Page Cache   
Hi Saikat, thanks for the wonderful feedback! We're glad we could be of help. You can check out our complete Data Science with R course here: <a href="https://www.edureka.co/data-science">https://www.edureka.co/data-science</a>.<br />Do subscribe to our channel to stay posted on upcoming tutorials. Hope this helps. Cheers!
          Comment on Machine Learning with R | Machine Learning Algorithms | Data Science Training | Edureka by Jayamohan C      Cache   Translate Page   Web Page Cache   
Can you please provide me the datasets
          Cognitive Automation Developer - ING Services Polska - Katowice, śląskie      Cache   Translate Page   Web Page Cache   
To musisz umieć Doświadczenie w Pythonie Zorientowanie na automatyzację, Machine Learning i/lub Artificial Intelligence Znajomość przynajmniej jednego z...
Od ING Services Polska - Tue, 07 Aug 2018 13:14:37 GMT - Pokaż wszystkie Katowice, śląskie oferty pracy
          DeepMind Chair of Machine Learning to be appointed      Cache   Translate Page   Web Page Cache   
The Department of Computer Science and Technology is to appoint a DeepMind Chair of Machine Learning thanks to a benefaction from the world-leading AI company. The first DeepMind Chair is expected to take up their position in October 2019.
          Cognitive Automation Developer - ING Services Polska - Katowice, śląskie      Cache   Translate Page   Web Page Cache   
To musisz umieć Doświadczenie w Pythonie Zorientowanie na automatyzację, Machine Learning i/lub Artificial Intelligence Znajomość przynajmniej jednego z...
Od ING Services Polska - Tue, 07 Aug 2018 13:14:37 GMT - Pokaż wszystkie Katowice, śląskie oferty pracy
          iOS Developer - PGS SOFTWARE - Rzeszów, podkarpackie      Cache   Translate Page   Web Page Cache   
Augmented Reality, Machine Learning, iBeacons, Top Level Security. Elastyczne godziny pracy....
Od PGS SOFTWARE - Wed, 08 Aug 2018 14:51:19 GMT - Pokaż wszystkie Rzeszów, podkarpackie oferty pracy
          Sr Director, Growth Marketing Technology - eBay Inc. - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Further, the Marketing Tech Leader will apply the latest data analysis and machine learning technologies to innovate applications in both BI analysis and...
From eBay Inc. - Fri, 01 Jun 2018 08:04:49 GMT - View all Bellevue, WA jobs
          Software Engineer - Machine Learning - Convoy - Seattle, WA      Cache   Translate Page   Web Page Cache   
Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes....
From Convoy - Sat, 19 May 2018 10:13:22 GMT - View all Seattle, WA jobs
          SA sees more digital initiatives focusing on learners | Training and e-Learning - ITWeb      Cache   Translate Page   Web Page Cache   
"I-Innovate, Qberty and IFS introduce programmes to help students excel in the digital age" notes Regina Pazvakavambwa, an experienced Journalist.
 
Digital skills initiatives help educators keep up with the changes technology innovation is bringing to classrooms.
Photo: ITWeb

The race to teach students skills is heating up, with three companies this week introducing digital learning initiatives.

Educational specialist company I-Innovate introduced the " and Robotics for the Future" programme at the Diepsloot Combined School.

Sponsored by IT service provider Tata Consultancy Services (TCS) SA, the programme helps learners and educators explore advanced (AI) technologies such as automation, machine learning, pattern recognition and neural networks through a series of hands-on innovation sessions, says I-Innovate.

Grade nine students from the school will learn how to create and use AI to problem-solve and innovate in their own lives and communities. TCS employees will mentor learner-led teams throughout the experience, both in-person and online.

"[The programme] connects learning in the classroom to real-world opportunities and career pathways. It is an inspiring and highly relevant way to show children that they can make giant leaps in learning and be a real part of the solutions to some of our most pressing local and global challenges," says I-Innovate CEO Trisha Crookes.

Learners will be introduced to coding and robotics, and will discover how to use these technologies for creative problem-solving, she notes...

Coding for innovation Meanwhile, Qberty has opened the Coders and Innovators Hub, at Northriding and Northlands Corner Shopping Centre in Randburg.

The centre will be open to children of all ages; however, the main target market is public schools, says Qberty. The company hopes to bridge the digital gap between private and public schools, and offer students an equal chance of digital experiential learning, it says.

Children will learn how to code, create apps and Web sites, and build robotics, notes Qberty, but highlights its main focus is Minecraft in education.
Read more...

Source: ITWeb

          Researchers warn of dangers from AI-driven hacking programs      Cache   Translate Page   Web Page Cache   
A team from IBM has developed machine learning-based programs that can infiltrate top-of-the-line cyberdefense systems.  -More

          Telecommute Lead Data Science Instructor      Cache   Translate Page   Web Page Cache   
A coding program has an open position for a Telecommute Lead Data Science Instructor. Core Responsibilities Include: Planning, writing, and delivering lectures in accordance with the progress and pace of the class Piloting our experimental efforts in curriculum and pedagogical style Developing and leading student project sprints throughout the semester Must meet the following requirements for consideration: Strong Knowledge in Data Science, Data Analytics, R, Python, Etc Strong Knowledge in Statistics, Mathematics and Machine Learning Prior experience teaching code to a class of students Can work cross-functionally with a variety of people from curriculum writers to engineers and designers
          Chemical Engineers Simplify Models Via AI       Cache   Translate Page   Web Page Cache   

Nikolaos Sahinidis

Researchers in the Department of Chemical Engineering are using a novel machine learning approach to build simple, but accurate models for applications that can be used to make sense of massive amounts of data quickly.
          Using AI to Better Diagnose Disorders And Target Drug Treatment      Cache   Translate Page   Web Page Cache   
New research suggests machine learning can improve the diagnosis of complex mental health disorders and aid the selection of pharmacological therapy. Experts welcome the new finding as mood disorders like...
          Node Best Practices, Machine Learning in Node with TensorFlow.js and more      Cache   Translate Page   Web Page Cache   

#250 — August 9, 2018

Read on the Web

Node Weekly

Dumper.js: A Pretty Variable Inspector for Node — If you’re one for ‘print-style’ debugging, this could prove very handy for you. You can either dump out the object of your choice (including nested objects) and keep running or terminate the process.

Zeeshan Ahmed

A Curated Compilation of Node Best Practices — Curated from numerous popular articles, this in-development list of best practices covers topics from error handling to memory use and, most recently, security.

Yoni Goldberg

Move Fast and Fix Stuff. Over 500K Developers Fix Errors with Sentry — Relying on users to report errors? Use Sentry to resolve errors right in your workflow. Route alerts to the right person based on the commit and cut remediation time to 5 minutes. Sentry is open source and loved by 500K developers. Sign up for free.

Sentry sponsor

Got 9.0: A Powerful HTTP Request Library for Node.js — Got is a popular HTTP request library from one-man package powerhouse Sindre Sorhus. Version 9 is a significant release that uses the latest Node 8+ features and has a significantly smaller install size.

Sindre Sorhus

Machine Learning in Node with TensorFlow.js — TensorFlow.js brings TensorFlow’s machine learning capabilities to JavaScript, and while it’s been browser-focused so far, experimental support for Node has now been introduced. Here’s how it works.

James Thomas

Community Questions Following the ESLint Security Incident — Almost a month ago, there was an incident where a heavily used module was hijacked. This post answers a few outstanding questions about what happened and what measures are being taken to avoid similar incidents.

The npm Blog

💻 Jobs

NodeJS Development in Beautiful Norway — We are adding to our team building low latency back-ends for awesome developer experience and scalable software. Check us out.

Snowball Digital

Join Our Career Marketplace & Get Matched With a Job You Love — Through Hired, software engineers have transparency into salary offers, competing opportunities and job details.

Hired

📘 Tutorials

Deploying a Stateful Application on Azure Kubernetes Service — Guides you through the process of deploying a stateful, Dockerized Node app (the Ghost blogging platform) on the Azure Kubernetes Service.

Kristof Ivancza

How to Create a Serverless Twitter Bot on Google Cloud — Google Cloud Functions went GA last week, so why not take it for a spin?

William Saar

▶  An Introduction to Web Scraping with Node and CheerioCheerio provides jQuery-style DOM manipulation server-side.

Traversy Media

The Three Types of Node Profilers You Should Know About — A look at standard profilers, tracing profilers and APM tools.

Ben Putano

Squeeze Node Performance with Flame Graphs — Investigating and optimizing a Node API using flame graphs.

Alexandru Olaru

▶  How to Approach Security with Node.js — A conversation with Google Engineer Mike Samuel.

Node.js Foundation

Best in Class Video Infrastructure in Two API Requests

MUX sponsor

🔧 Code and Tools

PrettyError: See Node.js Errors with Less Clutter and Better Formatting

Aria Minaei

chromium-headless-remote: Dockerized Chromium in Headless Remote Debugging Mode — Ideal to use with Puppeteer.

Kir Belevich

Be the First to Try Powerful CI/CD Pipelines in Semaphore 2.0 — Model your workflow from commit to deploy the simple way with powerful pipelines. Get your invite to try it.

Semaphore sponsor

Camaro: A High Performance XML to JSON Converter — Uses bindings to pugixml, a fast C++ XML parser.

Tuan Anh Tran

Kakapo.js: A 'Next Gen' HTTP Mocking Framework

DevLucky

Fiora: A Chat App Powered by Socket.io, Koa, MongoDB and React

碎碎酱

fast-memoize: The 'Fastest Possible' JS Memoization Library

Caio Gondim


          Machine Learning & Distributed Ledger Sr. Engineer - Mainstreet Technologies, Inc - McLean, VA      Cache   Translate Page   Web Page Cache   
Machine Learning & Distributed Ledger Sr. Engineer Job Description • Responsible for delivery in the areas of: data science/machine learning & Distributed...
From Mainstreet Technologies, Inc - Thu, 02 Aug 2018 00:52:33 GMT - View all McLean, VA jobs
          Senior PM, Data - PitchBook Data, Inc. - Seattle, WA      Cache   Translate Page   Web Page Cache   
Familiarity with machine learning and natural language processing techniques. Play a pivotal role and collaborate with key stakeholders to understand and ensure...
From PitchBook Data, Inc. - Thu, 09 Aug 2018 04:51:17 GMT - View all Seattle, WA jobs
          Data Analyst - FLEXE, Inc. - Seattle, WA      Cache   Translate Page   Web Page Cache   
Amazing location in Pioneer Square – be close to it all .. Experience in computer science fundamentals, machine learning and big data a plus....
From FLEXE, Inc. - Wed, 04 Jul 2018 22:08:38 GMT - View all Seattle, WA jobs
          Software Development Engineer - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Extensive, varied internal and external customer base. Knowledge of statistical analysis, big data, machine learning....
From Amazon.com - Sat, 23 Jun 2018 14:22:29 GMT - View all Seattle, WA jobs
          Sr Business Development Manager - Machine Learning Discovery - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Can you envision a future where smarter machines solve complex business problems? AWS customers are looking for ways to change their business models and solve...
From Amazon.com - Wed, 30 May 2018 01:20:21 GMT - View all Seattle, WA jobs
          Sr Manager, AI/ML Solutions Architecture - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Drive new business and product initiatives, championing ideas that move our business forward. 2+ years machine learning experience....
From Amazon.com - Fri, 27 Apr 2018 07:29:10 GMT - View all Seattle, WA jobs
          Machine Learning/AI Engineer - Groom & Associates - Montréal, QC      Cache   Translate Page   Web Page Cache   
Expérience avec tensorflow ou d'autres backends, keras ou autres frameworks, scikit-learn, OpenCV, Pandas. Experience with tensorflow or other backends, keras...
From Groom & Associates - Thu, 07 Jun 2018 14:58:16 GMT - View all Montréal, QC jobs
          Data Scientists / AI & Machine Learning Engineer - IVADO Labs - Montréal, QC      Cache   Translate Page   Web Page Cache   
Experience implementing AI/data science algorithms using one or more of the modern programming languages/frameworks (e.g., Python, Pandas, Scikit-learn,...
From IVADO Labs - Sat, 05 May 2018 03:10:45 GMT - View all Montréal, QC jobs
          Platform Developer, Machine Learning - Kinaxis - Ottawa, ON      Cache   Translate Page   Web Page Cache   
Experience with Machine Learning projects, familiarity with platforms or languages such as scikit-learn, Pandas, NumPy, SciPy, R, TensorFlow....
From Kinaxis - Wed, 08 Aug 2018 20:38:15 GMT - View all Ottawa, ON jobs
          Machine Learning Developer - Kinaxis - Ottawa, ON      Cache   Translate Page   Web Page Cache   
Experience with ML platforms and languages including scikit-learn, Pandas, NumPy, SciPy, Python, R woult be an asset....
From Kinaxis - Wed, 08 Aug 2018 20:38:15 GMT - View all Ottawa, ON jobs
          Lee Simpson on Why Diverse Experiences Shape Better Designers       Cache   Translate Page   Web Page Cache   

This is the latest installment of our Core77 Questionnaire. Previously, we talked to Ron Faris of the Nike SNKRS app. 

Name: Lee Simpson

Occupation: My current role is Head of Media & Entertainment Products at ustwo, but I'm wearing many hats right now. Predominately, I'm a design lead and product strategist, which means I work closely with our clients in the media and entertainment space to bring new products and digital experiences to market.

Recently, I've been more involved in business development, developing relationships with new and existing clients and identifying strategic growth opportunities for ustwo. I'm also involved in setting the strategic direction for that work globally, basically defining ustwo's proposition, products and services and making sure ustwo (and our clients) are ahead of the curve.

Location: I've been in the U.S. for almost 4 years, but I'm originally from the U.K. I spent the first 3 years in New York, based out of ustwo's office in the Financial District. Last May, I relocated to LA to be closer to our clients.

When did you decide that you wanted to be a designer?

I came to design, as a career, kind of by accident. After leaving high school, I started my own street wear label/company. I worked with graffiti artists and illustrators from my local town, designing and manufacturing t-shirts and hoodies. Over time, our roster of creatives included people from all over the world and the brand grew into a small community.

ustwo's VR work for Google Cardboard

Later on, I met a guy who owned two or three contemporary art galleries North of England. He asked me to curate a show for one of his locations, so we brought a bunch of artists in from Europe and around the U.K. and put on a month long exhibition of their work. We almost sold out, and after that, I came on full time as gallery manager—I spent 2 years organizing shows and developing print releases with artists.

When the recession hit, art sales started to decline and we decided to close the gallery. Beyond art, the only other skill I had was a basic understanding of Photoshop, so I ended up taking a few freelance gigs designing logos and websites for local businesses. It was around that time I became interested in web development, so I started reading books and taking online classes on HTML and PHP. Things developed from there, and I started work at my first start-up in 2008 as a UI Designer and Front-End Engineer. 

What was your first job in media and entertainment design?

My first experience working in media and entertainment was at a small design and development agency in London. The majority of their clients are in the video content space and include a handful of the major U.K. broadcasters. The agency specializes in developing consumer facing, video-on-demand platforms and content management systems, so I got a fairly in-depth look at the industry—including its challenges. Some of these broadcasters are 60-70 years old and their audience numbers are in the millions. I'd always had a bit of an obsession with TV growing up, so getting to work on products of that scale with brands I actually loved was awesome. Working at that agency was definitely a career highlight.

What projects are you most proud of from your time at ustwo so far? 

One of my first projects at ustwo was with Comcast on a new video-streaming product called Watchable. They had an existing library of short-form content and asked us to help create a product that would serve to audiences in a unique way. The challenge was to get casual, short-form consumers to watch more.

Comcast Watchable

We designed the service around an editorial model, basically playlists of video content that were grouped by a theme or an event. The playlists would contain video from popular producers like Screen Junkies or Red Bull and were mixed with lesser-known creators as a way of introducing users to new content based on stuff they like. Rather than follow the YouTube or Facebook trend, we went in a completely different direction with the UI and UX. We wanted to design something that would stand out in a crowded market but would still deliver a good experience.

What are some current projects you're working on at ustwo that you're most excited about?

Augmented Reality and Virtual Reality have been a big focus for ustwo over the past two years, and a lot of our clients in the media and entertainment space are really keen to explore the potential there. As a designer, I'm always excited about new technologies and how they can be applied to solve problems. To go from designing 2D experiences to 3D experiences and overcoming all the challenges that exist with hardware and software is keeping me on my toes.

ustwo's VR work for Google Cardboard

What is the best part of your job?

The best part is definitely the variety. When I freelanced, I spent as much time taking care of the "business" as I did designing. No two days were the same. Since then, I've always looked for jobs that could give me that same freedom, hence why I was drawn to ustwo.

What is the most important quality of someone who works in your field?

I really like people who have had significant experience outside of the 'industry.' Some of the best designers I've worked with have had entirely different careers or studied something unrelated and decided to pivot to design and product. For me, those people always have the most interesting perspectives and their approach to problem solving is different than those who may have come from design school or had more formal training.

What is your favorite productivity tip or trick?

For some reason, to-do lists never really worked for me until recently. Last year, a friend introduced me to Things—a productive app on iOS and Mac that's actually been around for a while. It's fairly simple and doesn't have any bells or whistles, but when you find a process that works for you, it's a game changer! I use it for my daily tasks, as well as a CRM to remind me to reach out to people or follow up on something.

ustwo's office in NYC

I also love early mornings. I wake up around 5:30am most mornings, even on weekends, and use that time to get my focus work (like writing and reading) done, or go for a walk. If you work from home, a morning walk is like an energy power-up for the day. I've seen a significant increase in my focus since I started doing it more regularly.

How do you procrastinate?

I'm more of a "procrastiworker" than a procrastinator—I really enjoy my work and honestly find it hard to switch off. I'm always trying to learn something new and can't remember a time in the last 14 years when I didn't have some kind of ongoing side project. So outside of my 9-to-5, that keeps me fairly busy.

I watch a lot of YouTube and Twitch. Most of the time I'll have it on in the background, but if I get distracted I go into a hole. I love finding those videos from the deepest, darkest corners of YouTube. I discovered IRL streaming about four to five months ago, and it's been my latest obsession. There's a big community of people who stream their everyday lives—going for breakfast, buying groceries and hanging out with friends. It seems really boring but it's honestly some of the most compelling content on Twitch.

ustwo's VR work for Google Cardboard

What is the most widespread misunderstanding about your job?

It's a cliché, but the most widespread misunderstanding about designers in general is that their only job is to make things that look nice. That attitude is definitely changing, and over the past ten years, design has really earned a seat at the table. For some designers, however, it can be hard to break out of that box. I speak to a lot of designers coming to the end of their junior years, and they don't see a clear career path for themselves.

Do yo have any advice for young designers?

Talent is just one part of the puzzle. You need to work hard and diversify your skill set. I've seen a lot of designers in my career who obviously had natural talent but weren't willing to put the hours in. It's a really competitive market right now, and there are a lot of amazing designers looking for employment. A work-life balance is important, but so is self-discipline. A solid work ethic and those things will show in your work and give you a competitive advantage.

Also, always look for ways to diversify your skill set. The material taught in schools and colleges are already four or five years out of date by the time most young designers graduate. For example, no one could have predicted the impact that augmented reality, virtual reality, machine learning and artificial intelligence would have on the industry. You need to constantly look ahead to see what's coming over the horizon—keep yourself and your skills relevant for the market.


          Apple explains how it uses U.S. Census data and ML to make Siri a local      Cache   Translate Page   Web Page Cache   

In Apple’s latest Machine Learning Journal entry, the Siri Speech Recognition Team shares an overview of the work behind improving Siri’s understanding of names for regional points-of-interest by incorporating the user’s location.

Based in part on data from the U.S. Census Bureau, Apple has been able to tune Siri to better understand users based on where they are and what POIs they’re more likely to ask about.

more…


          Stop getting screwed: Using AI to prevent game fraud (VB Live)      Cache   Translate Page   Web Page Cache   

There are 2.2 billion active gamers, and 100 percent of them are at risk from fraudsters. Also at risk: your game's reputation, customer retention, and your bottom line. Learn how machine learning and AI can keep your game and players safe online criminals, don’t miss this VB Live event.


          Instructor (Data Science, Artificial Intelligence, Machine Learning) - Cortechma Inc. - Thornhill, ON      Cache   Translate Page   Web Page Cache   
Cortechma Academy team is looking for professors, instructors and engineers with both academically and professionally strong background specializing in one of...
From Indeed - Wed, 01 Aug 2018 16:56:17 GMT - View all Thornhill, ON jobs
          After NEXT 2018: Trends in higher education and research      Cache   Translate Page   Web Page Cache   

From classrooms to campus infrastructure, higher education is rapidly adapting to cloud technology. So it’s no surprise that academic faculty and staff were well represented among panelists and attendees at this year’sGoogle Cloud Next. Several of our more than 500 breakout sessions at Next spoke to the needs of higher education, as as did critical announcements like our partnership with the National Institutes of Health to make make public biomedical datasets available to researchers. Here are ten major themes that came out our higher education sessions at Next:

  1. Collaborating across campuses. Learning technologists from St. Norbert College, Lehigh University, University of Notre Dame, and Indiana University explained how G Suite and CourseKit, Google’s new integrated learning management tool, are helping teachers and students exchange ideas.
  2. Navigating change.Academic IT managers told stories of how they’ve overcome the organizational challenges of cloud migration and offered some tips for others: start small, engage key stakeholders, and take advantage of Google’s teams of engineers and representatives, who are enthusiastic and knowledgeable allies. According to Joshua Humphrey, Team Lead, Enterprise Computing, Georgia State University, "We've been using GCP for almost three years now and we've seen an average yearly savings of 44%. Whenever people ask why we moved to the cloud this is what we point to. Usability and savings."
  3. Fostering student creativity. In our higher education booth at Next, students demonstrated projects that extended their learning beyond the classroom. For example, students at California State University at San Bernardino built a mobile rover that checks internet connectivity on campus, and students at High Tech High used G Suite and Chromebooks to help them create their own handmade soap company.
  4. Reproducing scientific research. Science is built on consistent, reliable, repeatable findings. Academic research panelists at the University of Michigan are using Docker on Compute Engine to containerize pipeline tools so any researcher can run the same pipeline without having to worry about affecting the final outcome.
  5. Powering bioinformaticsToday’s biomedical research often requires storing and processing hundreds of terabytes of data. Teams at SUNY Downstate, Northeastern, and the University of South Carolina demonstrated how they used BigQuery and Compute Engine to build complex simulations and manage huge datasets for neuroscience, epidemiology, and environmental research.
  6. Accelerating genomics research. Moving data to the cloud enables faster processing to test more hypotheses and uncover insights. Researchers from Stanford, Duke, and Michigan showed how they streamlined their genomics workloads and cut months off their processing time using GCP.
  7. Democratizing access to deep learningAutoML Vision, Natural Language, and Translation, all in beta, were announced at Next and can help researchers build custom ML models without specialized knowledge in machine learning or coding. As Google’s Chief Scientist of AI and Machine Learning Fei-Fei Li noted in her blog post, Google’s aim “is to make AI not just more powerful, but more accessible.”
  8. Transforming LMS analytics. Scalable tools can turn the data collected by learning management systems and student information services into insights about student behavior. Google’s strategic partnership with Unizen allows a consortium of universities to integrate data and learning sciences, while Ivy Tech used ML Engine to build a predictive algorithm to improve student performance in courses.
  9. Personalizing machine learning and AI for student services. We’re seeing a growing trend of universities investigating AI to create virtual assistants. Recently Strayer University shared with us how they used Dialogflow to do just that, and at Next, Carnegie Mellon walked us through their process of building SARA, a socially-aware robot assistant.
  10. Strengthening security for academic IT: Natural disasters threaten on-premise data centers, with earthquakes, flooding, and hurricanes demanding robust disaster-recovery planning. Georgia State, the University of Minnesota, and Stanford’s Graduate School of Business shared how they improved the reliability and cost-efficiency of their data backup by migrating to GCP.
We've been using GCP for almost three years now and we've seen an average yearly savings of 44%. Whenever people ask why we moved to the cloud this is what we point to: usability and savings Joshua Humphrey
Enterprise Computing, Georgia State University



To learn more about our solutions for higher education, visit our website, explore our credits programs for teaching and research, or speak with a member of our team.


          Understand The Significance For Large Scale Machine Learning      Cache   Translate Page   Web Page Cache   
Machine learning is a fastest-growing area of mathematics, computer science and engineering. It has great impact over the artificial intelligence in making things easier for human beings.
          The Trillion Dollar Question      Cache   Translate Page   Web Page Cache   

Recently, Apple’s stock price rose to the point where the company’s market valuation was above $1 trillion, the first U.S. company to reach that benchmark. Subsequently, numerous articles were published describing Apple’s journey to this point and why it got there. Most people describe Apple as a technology company. They make technology products: iPhones, iPads, Macs, etc. These are all computing devices. But there is another way to think of Apple and what kind of company they are as well as how they became so successful.

Neil Cybart, an analyst over at Above Avalon, likes to describe Apple as a design company focused on building useful tools for people. Of the latest round of profiles on Apple reaching a $1 trillion market valuation, he writes:

Despite supposedly being about chronicling how Apple went from near financial collapse in the late 1990s to a trillion-dollar market cap, a number of articles did not include any mention of Jony Ive [Apple’s Chief Design Officer], or even design for that matter. To not include Jony Ive in an article about Apple’s last 20 years is unfathomable, demonstrating a clear misunderstanding of Apple’s culture and the actual reasons that contributed to Apple’s success. Simply put, such profiles failed in their pursuit of describing Apple’s journey to a trillion dollars. Apple is where it is today because of design – placing an emphasis on how Apple products are used. Every other item or variable is secondary. [emphasis added]

As long as I have followed computers people have complained that Apple’s hardware is substandard. Other companies like Dell, Gateway, Acer, and Lenovo, had long been making computers that were “better” than Apple’s hardware. Apple’s value has always been selling good hardware coupled with premium software. But for a long time that was not appreciated by the market and Apple almost went bankrupt as a result.

The “Speeds and Feeds” Era for Data Analysis

When I was growing up, computers were all about so-called “speeds and feeds”. The only things people talked about were the megahertz of their processor or how many megabytes of RAM a computer had. A computer with a higher megahertz CPU was by definition better than a computer with a lower megahertz CPU. More RAM was better than less RAM and more disk space was better than less disk space. It was easy to compare different computers because we had quantitative metrics to go by. The hardware itself was a commodity and discussion about software was nonexistent because every computer ran the same software: Windows.

We are very much in the “speeds and feeds” era for data analysis right now. There is tremendous focus on and fascination with the tools and machinery underlying data analysis. Deep learning is only one such example, along with an array of related machine learning tools. Web sites like Kaggle promote a culture of “performance” where the person who can cobble together the most accurate algorithm is a winner. It’s easy to compare different algorithms to each other because there is often a single metric of performance that we can easily agree to compare.

Serious investment is being made in improving algorithms to make them more accurate, efficient, and powerful. We need these algorithms to be better so that we can have self-driving cars, intelligent assistants, fraud detection, and music discovery. Even the hardware itself is being optimized to improve the performance of these specific algorithms. This is the call of “more gigahertz, more RAM, more disk space” of our time. As easy hardware wins are fading into the past (as shown by Intel’s struggle), the focus is on improving the performance of machine learning software running on top of it.

All of this is necessary if we want to reap the benefits of machine learning algorithms in our daily lives. But if the computing industry has anything to teach the data science industry, it’s that perhaps the more interesting stuff is yet to come. Furthermore, it suggests that the companies (and perhaps individuals) with the best speeds and feeds will not necessarily be the winners.

What Comes Next?

Today, it could be argued that the most profitable “computer” in the world is the iPhone, which to be sure, has better “speeds and feeds” than any computer from my childhood. But it is by no means the fastest computer today. Nor does it have the most RAM, the most disk space, or the best graphics. How can that be?

Of course, the focus of computing changed from desktop to laptop to mobile, in part due to the great advancement in chip technology and miniaturization. So the benefit was not in greater speeds and feeds, but rather in smaller sizes for the same speeds and feeds. With these smaller, more personal, devices, the software and the design of the system became of greater importance. People were not using these devices to “crunch numbers” or do complex, but highly specialized, tasks. Rather, they were using them to do everyday tasks, like checking email, surfing the web, and communicating with friends. These were not business machines; they were for the mass market.

Arguable, the emphasis that Apple places on design has made it the most successful computer company of today because design is what creates the best user experience today in the mass market. Data science remains a niche area of work today even though its popularity and application has exploded over just a few years. It’s difficult for me to see how it might move into a mass market position, but I can see more and more people doing and consuming data analysis in the future. As the population of data analysis consumers grows, I think people will become less focused on accuracy and prediction metrics and more focused on whether a given analysis achieves a specified goal. In other words, data analyses will have to be designed to accomplish a certain task. The better individuals are at designing good data analyses, the more successful they will be.


          Machine Learning & Distributed Ledger Sr. Engineer - Mainstreet Technologies, Inc - McLean, VA      Cache   Translate Page   Web Page Cache   
Machine Learning & Distributed Ledger Sr. Engineer Job Description • Responsible for delivery in the areas of: data science/machine learning & Distributed...
From Mainstreet Technologies, Inc - Thu, 02 Aug 2018 00:52:33 GMT - View all McLean, VA jobs
          [עושים תוכנה] מצילים חיי אדם באמצעות Deep Learning      Cache   Translate Page   Web Page Cache   

אם אתם מסתובבים בעולם התוכנה וכנראה שגם אם לא, אתם שומעים כמה פעמים ביום את צמד המילים Machine Learning.
פה ושם כנראה גם שמעתם את צמד המילים של המגניבות החדשות בשכונה : Deep Learning

אבל..האם טרחתם להתעמק (מצחיק!) ולהבין מה זה אומר? האם העזתם להתנסות בתחום בעצמכם?

היחס בין הכמות שנאמרות המילים הללו לבין השימוש בהם בפועל בצורה אמיתית ונכונה הוא מקרי בהחלט.
לכן, כדי שתוכלו להבין קצת מעבר , הבאנו בפרק החדש של ״עושים תוכנה״ את גיא ריינר אחד המייסדים של חברת aidoc.

גיא ביחד עם שותפיו הנהדרים אלעד וולך ומיכאל ברגינסקי, פיתחו מערכת שעוזרת לרדיולוגים לנתח צילומי CT ורנטגן ובעצם עוזרת לייעל תהליכים ואולי אפילו מצילה חיי אדם.
בלי השימוש בDeep Learning לא בטוח שהם היו מצליחים לעשות זאת ותהיו בטוחים שהדרך שהם עשו בשנים האחרונות לא הייתה קלה בכלל.

The post [עושים תוכנה] מצילים חיי אדם באמצעות Deep Learning appeared first on עושים היסטוריה.


          Continuum Analytics Blog: Deploying Machine Learning Models is Hard, But It Doesn’t Have to Be      Cache   Translate Page   Web Page Cache   

With free, open source tools like Anaconda Distribution, it has never been easier for individual data scientists to analyze data and build machine learning models on their laptops. So why does deriving actual business value from machine learning remain elusive for many organizations? Because while it’s easy for data scientists to build powerful models on …
Read more →

The post Deploying Machine Learning Models is Hard, But It Doesn’t Have to Be appeared first on Anaconda.


          Everything is … less terrible      Cache   Translate Page   Web Page Cache   

To hack: to study a system’s flaws and emergent properties, and use them for your own ends; to instil your own instructions into a computer’s memory, and coerce its microprocessor to run them. To pick at the air gaps and missed stitches in the many overlapping layers of software from which our modern world is woven.

Et voilà , an entire industry, employing countless thousands. Information Security a.k.a. infosec. It is said that there are four PR people for every journalist in America, which seems high, but I expect the ratio of infosec people to actual hackers is higher yet, even if you count the proverbial script kiddies.

For a long time it was where the counterculture techies went, the curmudgeons, the renegades, in black boots and leather and tattoos and colored hair. By no coincidence they also tended to include many of the smartest ones. (I’m a CTO and to this day I find interview questions about security are the best way to delineate the merely good from the excellent.) And by no coincidence they also included many angry, wounded, and/or terrible people.

That was when the Internet was something people used from time to time, rather than the fundamental substrate of half of human activity. It was OK, as far as its users were concerned, for its walls to be built and defended (and only very rarely womanned, courtesy of infosec’s default oppressive, exclusionary, and often predatory sexual culture) by a cohort of … well … cranky assholes. Not all of them, I hasten to stress. But definitely a disproportionate number.

That was part of its appeal, in many ways. Bad boys in leather who could spin up hard drives and ransom data from across the planet with a few opaque, wizardly shell scripts, in green text on black, using knowledge they’d won the hard way from online duels and grimoires ― that was the Hollywood myth of the hacker, and the much-less-romantic real hackers loved it, as you’d expect, whatever color their notional hats might be.

It was a shitty system and a shitty subculture in many ways ― colorful and dramatic, sure, but essentially shitty ― and it couldn’t last. Nowadays it is big business, on the one hand, and slowly becoming more equitable and less exclusionary, on the other. Don’t get me wrong, there’s much work to be done, but the trajectory is a hopeful one.

Nowadays the security biz is an iterative process rather than an exploratory frontier. Researchers discover vulnerabilities in software; they disclose them to vendors; vendors grumble and fix it. Security vendors offer a growing arsenal of tools to prevent, detect, log, and attribute attacks, iterating as attackers do the same ― and attackers are, increasingly, likely to be 9-5ers paid by a nation state, rather than members of a criminal enterprise.

One of the most respected teams in infosec is Google’s Project Zero, and another is their Chrome security team; both are managed by Parisa Tabriz, who gave the keynote speech at Black Hat today. She pointed out that there has been good and measurable progress in the security world over the last few years. Initially, when Project Zero started giving vendors precisely 90 days to fix their bugs before their exploits were revealed to the world, only 25% complied in time; now that number is up to 98%. Secure HTTPS traffic has risen from 45% to 87% of traffic on ChromeOS, and from 29% to 77% on Android, just over the last three years … and Tabriz attributed this to UI improvements in the Chrome browser as much as to the behind-the-scenes plumbing work.

Once upon a time UX and usability were considered entirely orthogonal to security. This is probably directly attributable to the contemptuous attitudes of infosec at the time. Now, thankfully, the industry knows better. Once “community” was a dirty word among the black-clad lone wolves, and if a “vulnerability” was personal, you didn’t talk about it; now there’s an entire Community Track at Black Hat, discussing addiction, stress, PTSD, burnout, depression, sexual harassment/assault, among other issues that would have been swept under the collective rug not so long ago.

Conventional wisdom has it that everything is terrible and everything can be hacked, and that “attackers have strategies while defenders only have tactics,” to quote Black Hat founder Jeff Moss this morning. And don’t get me wrong: some things do continue to be terrible. ( Border Gateway Protocol , anyone?) But there is room for a kind of guarded optimism. Many of the big new hacks of the last few years aren’t catastrophic flaws in widely used essential infrastructure. OK, some are, but some, like Meltdown/Spectre and Rowhammer , are astonishingly elaborate Rube Goldberg hacks.

This is an extremely good sign. In the same way that airline crashes tend to have a baroque set of perfect-storm causes these days, because the simple errors are guarded against with multiple redundancy, the increasingly baroqueness of major bugs suggests that the software we use is getting noticeably more secure. Slowly. In irregular fits and starts. Over a period of decades. Sometimes in devices which cannot be fixed except by complete replacement. And reducing vulnerabilities still doesn’t fix, say, the password reuse problem. But still.

We’ll see if the rise of machine learning causes a new arms race, or whether it gives us new and better tools against attackers, and/or whether convolutional pattern recognition will unearth an entire new crop of previously undetectable bugs. It’s admittedly worrying that adversarial examples are so effective at tricking current AI models. But even so I’m inclined to agree with Tabriz that there is, at long last, cause for a certain guarded optimism, both for the infosec community and their work.


          Eggplant partners with Matrium Technologies for expansion into Australasian regi ...      Cache   Translate Page   Web Page Cache   
Eggplant names Matrium Technologies, Australia’s leading provider of technology solutions, as a partner for expanding its Customer Experience Optimization offering

London, UK, Boulder, CO - 9th August 2018- Eggplant , the provider of Customer Experience Optimization solutions, today announced its partnership with Matrium Technologies to expand its products and services into the Australasian region.

Eggplant selected Matrium Technologies as its chosen partner due to its experience within the IT and software sector in Australia, New Zealand and Singapore in the areas of network testing, security and visibility. With similar software solutions, Eggplant and Matrium Technologies will partner to expand Eggplant’s Customer Experience Optimization (CXO) offering.

Eggplant’s solution uses artificial intelligence, machine learning, and analytics to predict business and user impacts across different interfaces, platforms, and devices.

Matrium Technologies, which specializes in telecommunication, government and enterprise sectors, will become a reseller providing support and services for Eggplant’s software in the ANZ market. The company is already presenting several opportunities in the ANZ region, and its engineers are undertaking and passing the Foundation and Practitioner certifications.

Quotes and Commentary

Dr. John Bates, CEO of Eggplant, commented: “Matrium Technologies will play a crucial role in Eggplant’s expansion into the Australasia region. Providing an excellent customer experience is paramount in today’s connected world, and we’re excited to help our clients delight their users in new regions.”

Brad Crismale, CEO of Matrium Technologies Pty Ltd, added: “We are really looking forward to representing Eggplant in the Australian and New Zealand marketplace, its Customer Experience Optimization Suite is the perfect complement to our existing automation solution set and it really strengthens and broadens our automation capabilities going forward.”

-END-

About Eggplant

Eggplant, the fastest growing test automation provider and a portfolio company of The Carlyle Group, provides user-centric, intelligent testing and performance solutions designed to optimize the digital experience, delight customers, and drive business success. Only Eggplant enables organizations to test, monitor, analyze, and report on the quality and responsiveness of software applications across different interfaces, platforms, browsers, and devices, including mobile, IoT, desktop, and mainframe.

Learn more at www.eggplant.io

Eggplant

:

Ilona Hitel, +44 (7734 355205)

ihitel@thecommsco.com

US PR contact:

Claire Rowberry, +1 617-785-5571

About Matrium Technologies

Matrium Technologies has been a leading provider of technology solutions in Australia since 1991, with a strong industry background in Network Testing, Visibility, and Security solutions.

Matrium Technologies has been recognised as an industry leader for handling technology disruptions within their customers’ networks in addition to providing a pathway to technology enablement. They deliver tailor-made solutions to suit every customer’s specific business needs.

Matrium has a strong regional presence with offices in Sydney and Melbourne and provides innovative products and services to its customers across Australia, New Zealand and Singapore. The firm works with numerous companies from diverse industries, specialising in Telecommunications Service Providers, Network Equipment Manufacturers, Federal & State Government Agencies, and some of the largest enterprise companies in the region. Matrium takes pride in remaining at the forefront of technology. Matrium has the experience and expertise to offer customers a comprehensive Network Testing Tools Solution Kit that will cater to today’s and the upcoming generation’s Network Security Solutions. A Local Professional Services Team is available 24×7 to offer help to the growing IT industry.


          [Из песочницы] Перевод книги Эндрю Ына «Страсть к машинному обучению» Главы 1 — 14      Cache   Translate Page   Web Page Cache   

Некоторое время назад в моей ленте в фейсбуке всплыла ссылка на книгу Эндрю Ына (Andrew Ng) "Machine Learning Yearning", которую можно перевести, как "Страсть к машинному обучению" или "Жажда машинного обучения".


image<img src="<img src="https://habrastorage.org/webt/ds/rc/ct/dsrcctfottkedkf7o1hxbqsoamq.png" />" alt="image"/>


Людям, интересующимся машинным обучением или работающим в этой сфере представлять Эндрю не нужно. Для непосвященных достаточно сказать, что он является звездой мировой величины в области искусственного интеллекта. Ученый, инженер, предприниматель, один из основателей Coursera. Автор отличного курса по введению в машинное обучение и курсов, составляющих специализацию "Глубокое обучение" (Deep Learning).

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          Firefox Advance, el nuevo motor experimental de recomendación de contenido que se integra directamente en Firefox      Cache   Translate Page   Web Page Cache   

Firefox Advanced

Hace un par de años que el Firefox Test Pilot, un programa de Mozilla para probar funciones experimentales en su navegador, lleva trayéndonos funciones sumamente interesantes con el potencial de hacerse con un hueco en la versión final de Firefox.

Cosas como crear nuestros propios temas, abrir páginas en contenedores aislados, o tener un centro lateral de pestañas son posibles gracias a estos experimentos. Y ahora, el más reciente se ha convertido fácilmente en uno de mis favoritos hasta el momento: Advance.

Recomendaciones en tiempo real mientras navegas

Firefox Test Pilot Advance 2018 08 09 14 32 07

Advance es un nuevo sistema de recomendación de contenido integrado directamente en Firefox. En Mozilla lo han llamado "un nuevo tipo de botón de reenviar". Advance se muestra como un panel lateral a la izquierda del navegador, uno donde aparecen artículos relacionados con lo que estás mirando en ese momento en una pestaña.

Con el tiempo Advanced aprenderá sobre tus gustos y estará personalizado según tus intereses. Pero esto no quiere decir que las recomendaciones estarán vacías cuando lo uses por primera vez, la función empieza a rellenarse con temas relacionados al de esa pestaña.

Incluso en el primer uso, las recomendaciones de contenido de Advanced son bastante acertadas según lo que tengas abierto en la pestaña

Las recomendaciones cambian dependiendo de lo que tengas abierto en cada pestaña, e incluso para el primer uso, muestra contenido bastante relevante. Me sorprendió gratamente, muchas de las cosas que aparecían, serían cosas que me interesa leer.

Firefox Advanced no está disponible en español, pero esto no es un problema en lo absoluto, puesto que las recomendaciones no se ven afectadas por esto, si lees sitios con contenido en español, lo más probable es que veas recomendaciones de otros sitios con contenido en el mismo idioma.

Es algo opcional y puedes ver todos los datos que se recolectan sobre ti

Advance Firefox Recomendaciones

En Mozilla tienen muy en cuenta la preocupación de los usuarios por su privacidad, de hecho, hace un par de meses explicaron cómo querían construir un feed de noticias personalizado que sea mejor que el de Facebook pero sin recolectar tu información.

Para este experimento con Firefox Advance, en Mozilla se han asociado con Laserlike, una startup especializada en machine learning. Explican que están comprometidos con su mantra de que es posible usar estás tecnologías de la forma correcta sin sacrificar el control de los usuarios.

Por esta razón, Advanced es un experimento opcional, y en cualquier momento puedes pausar su recolección de datos. Además puedes ver toda la información que el complemento ha recogido sobre ti y puedes solicitar que se borre en cualquier momento.

En Genbeta | Probamos Tab Center, Snooze Tabs y Activity Stream, los últimos experimentos de Firefox

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-
La noticia Firefox Advance, el nuevo motor experimental de recomendación de contenido que se integra directamente en Firefox fue publicada originalmente en Genbeta por Gabriela González .


          Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies, Third Edition      Cache   Translate Page   Web Page Cache   
#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000\Название: Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies, Third Edition
Автор: Steven Finlay
Издательство: Relativistic
ISBN: 1999730348
Год: 2018
Страниц: 192
Язык: английский
Формат: epub, mobi, rtf, pdf (conv)
Размер: 10.18 MB

Artificial Intelligence (AI) and Machine Learning are now mainstream business tools. They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Organizations which understand these tools and know how to use them are benefiting at the expense of their rivals. Artificial Intelligence and Machine Learning for Business cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is very much on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies.
          Sr.SDE - Amazon.com - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Build Products for amazon external facing and internal facing systems. The team uses various content classification and machine learning algorithms for solving...
From Amazon.com - Wed, 18 Jul 2018 19:20:37 GMT - View all Bellevue, WA jobs
          Quality Assurance Engineer - Amazon.com - Bellevue, WA      Cache   Translate Page   Web Page Cache   
The team uses various content classification and machine learning algorithms for solving complex business challenges....
From Amazon.com - Mon, 04 Jun 2018 19:20:38 GMT - View all Bellevue, WA jobs
          Applied Scientist - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
We are looking for an experienced machine learning scientist to contribute at the forefront of cutting edge machine learning....
From Amazon.com - Wed, 08 Aug 2018 13:26:46 GMT - View all Seattle, WA jobs
          Software Development Engineer: Machine Learning Service - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Build, operate and optimize critical AWS services enabling machine learning capabilities for internal use and by AWS customers....
From Amazon.com - Wed, 08 Aug 2018 01:22:33 GMT - View all Seattle, WA jobs
          Software Development Engineer - Prime Video Customer Growth - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience building machine learning enabled services. Amazon is an Equal Opportunity-Affirmative Action Employer - Minority/Female/Disability/Vet....
From Amazon.com - Sat, 04 Aug 2018 01:28:01 GMT - View all Seattle, WA jobs
          Principal Product Manager, Amazon Process Automation - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
Experience implementing machine learning based solutions. You will be working closely with businesses and understanding the requirements, working actively with...
From Amazon.com - Thu, 02 Aug 2018 19:20:59 GMT - View all Seattle, WA jobs
          Product Manager - Amazon.com - Seattle, WA      Cache   Translate Page   Web Page Cache   
You will be working closely with businesses and understanding the requirements, working actively with Technology, Machine learning and Operations teams, making...
From Amazon.com - Thu, 02 Aug 2018 19:20:51 GMT - View all Seattle, WA jobs
          Sr Director, Growth Marketing Technology - eBay Inc. - Bellevue, WA      Cache   Translate Page   Web Page Cache   
Further, the Marketing Tech Leader will apply the latest data analysis and machine learning technologies to innovate applications in both BI analysis and...
From eBay Inc. - Fri, 01 Jun 2018 08:04:49 GMT - View all Bellevue, WA jobs
          Software Engineer - Machine Learning - Convoy - Seattle, WA      Cache   Translate Page   Web Page Cache   
Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes....
From Convoy - Sat, 19 May 2018 10:13:22 GMT - View all Seattle, WA jobs
          Additional new content PaaS Partner Community      Cache   Translate Page   Web Page Cache   

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