|Partner Development Manager - Machine Learning and Artificial Intelligence - Amazon Web Services, Inc. - Herndon, VA Cache Translate This Page||We are looking for a motivated, technically savvy person to build upon our ecosystem of partners who build solutions with Amazon artificial intelligence and...|
From Amazon.com - Tue, 08 Jan 2019 09:37:16 GMT - View all Herndon, VA jobs
|IBM Watson Senior Architect - Artificial Intelligence - Accenture - Austin, TX Cache Translate This Page||IBM Cloud Platform, IBM Watson AI / Data / Vision / Speech / Language, Machine Learning, Intelligent Automation, APIs, and Application Integration....|
From Accenture - Tue, 20 Nov 2018 20:30:56 GMT - View all Austin, TX jobs
|Global Artificial Intelligence in Healthcare Market to 2025: Market is Expected to Grow from USD 2.1 Billion in 2018 to USD 36.1 Billion by 2025, at a CAGR of 50.2% Cache Translate This Page||...Biobeats 12.3.12 Healthcare Assistance Robots 188.8.131.52 Pillo 184.108.40.206 Catalia Health For more information about this report visit https://www.researchandmarkets.com/research/dp4bzk/global_artificial?w=5 Research and Markets also offers Custom Research ...|
|Open Borders Cache Translate This Page|
The traveler comes to a divide. In front of him lies a forest. Behind him lies a deep ravine. He is sure about what he has seen but he isn’t sure what lies ahead. The mostly barren shreds of expectations or the glorious trappings of lands unknown, both are up for grabs in the great casino of life.
First came the numbers, then the symbols encoding the symbols, then symbols encoding the symbols. A festive smattering of metamaniacal creations from the thicket of conjectures populating the hive mind of creative consciousness. Even Kurt Gödel could not grasp the final import of the generations of ideas his self-consuming monster creation would spawn in the future. It would plough a deep, indestructible furrow through biology and computation. Before and after that it would lay men’s ambitions of conquering knowledge to final rest, like a giant thorn that splits open dreams along their wide central artery.
Code. Growing mountains of self-replicating code. Scattered like gems in the weird and wonderful passage of spacetime, stupefying itself with its endless bifurcations. Engrossed in their celebratory outbursts of draconian superiority, humans hardly noticed it. Bits and bytes wending and winding their way through increasingly Byzantine corridors of power, promise and pleasure. Riding on the backs of great expectations, bellowing their heart out without pondering the implications. What do they expect when they are confronted, finally, with the picture-perfect contours of their creations, when the stagehands have finally taken care of the props and the game is finally on? Shantih, shantih, shantih, I say.
Once the convoluted waves of inflated rational expectations subside, the reality kicks in in ways that only celluloid delivered in the past. Machines learning, loving, loving the learning that other machines love to do was only a great charade. The answer arrives in a hurry, whispered and then proudly proclaimed by the stewards of possibility. We can never succeed because we don’t know what success means. How doth the crocodile eat the tasty bits if he can never know where red flesh begins and the sweet lilies end? Who will tell the bards what to sing if the songs of Eden are indistinguishable from the lasts gasps of death? We must brook no certainty here, for the fruit of the tree can sow the seeds of murderous doubt.
Just so often, although not as often as our eager minds would like, science uncovers connections between seemingly unrelated phenomena that point to wholly new ways forward. Last week, a group of mathematicians and computer scientists uncovered a startling connection between logic, set theory and machine learning. Logic and set theory are the purest of mathematics. Machine learning is the most applied of mathematics and statistics. The scientists found a connection between two very different entities in these very different fields – the continuum hypothesis in set theory and the theory of learnability in machine learning.
The continuum hypothesis is related to two different kinds of infinities found in mathematics. When I first heard the fact that infinities can actually be compared, it was as if someone had cracked my mind open by planting a firecracker inside it. There is the first kind of infinity, the “countable infinity”, which is defined as an infinite set that maps one-on-one with the set of natural numbers. Then there’s the second kind of infinity, the “uncountable infinity”, a gnarled forest of limitless complexity, defined as an infinity that cannot be so mapped. Real numbers are an example of such an uncountable infinity. One of the staggering results of mathematics is that the infinite set of real numbers is somehow “larger” than the infinite set of natural numbers. The German mathematician Georg Cantor supplied the proof of the uncountable nature of the real numbers, sometimes called the “diagonal proof”. It is like a beautiful gem that has suddenly fallen from the sky into our lap; reading it gives one intense pleasure.
The continuum hypothesis asks whether there is an infinity whose size is between the countable infinity of the natural numbers and the uncountable infinity of the real numbers. The mathematicians Kurt Gödel and – more notably – Paul Cohen were unable to prove whether the hypothesis is correct or not, but they were able to prove something equally or even more interesting; that the continuum hypothesis cannot be decided one way or another within the axiomatic system of number theory. Thus, there is a world of mathematics in which the hypothesis is true, and there is one in which it is false. And our current understanding of mathematics is consistent with both these worlds.
Fifty years later, the computational mathematicians have found a startling and unexpected connection between the truth or lack thereof of the continuum hypothesis and the idea of learnability in machine learning. Machine learning seeks to learn the details of a small set of data and make correlative predictions for larger datasets based on these details. Learnability means that an algorithm can learn parameters from a small subset of data and accurately make extrapolations to the larger dataset based on these parameters. The recent study found that whether learnability is possible or not for arbitrary, general datasets depends on whether the continuum hypothesis is true. If it is true, then one will always find a subset of data that is representative of the larger, true dataset. If the hypothesis is false, then one will never be able to pick such a dataset. In fact in that case, only the true dataset represents the true dataset, much as only an accused man can best represent himself.
This new result extends both set theory and machine learning into urgent and tantalizing territory. If the continuum hypothesis is false, it means that we will never be able to guarantee being able to train our models on small data and extrapolate to large data. Specific models will still be able to be built, but the general problem will remain unsolvable. This result can have significant implications for the field of artificial intelligence. We are entering an age where it’s possible to seriously contemplate machines controlling others machines, with human oversight not just impossible in practice but also in principle. As code flows through the superhighway of other code and groups and regroups to control other pieces of code, machine learning algorithms will be in charge of building models based on existing data as well as generating new data for new models. Results like the current result might make it impossible for such self-propagating intelligent algorithms to ensure being able to solve all our problems, or solve their own problems to imprison us. The robot apocalypse might be harder than we think.
As Jacob Bronowski memorably put it in his “The Ascent of Man”, one of the major goals of science in the 20th century was to establish the certainty of scientific knowledge. One of the major achievements of science in the 20th century was to prove that this goal is unattainable. In physics, Heisenberg’s uncertainty principle put a fundamental limit on measurement in the world of elementary particles. Einstein’s theory of relativity put a fundamental limit on the speed of light. But most significantly, it was Gödel’s famous incompleteness theorem that put a fundamental limit on what we could prove and know even in the seemingly impregnable world of pure, logical mathematics. Even in logic, that bastion of pure thought, where conjectures and refutations don’t depend on any quantity in the real world, we found that there are certain statements whose truth might forever remain undecidable.
Now the same Gödel has thrown another wrench in the machine, asking us whether we can indeed hold inevitability and eternity in the palm of our hands. As long as the continuum hypothesis remains undecidable, so will the ability of machine learning to transform our world and seize power from human beings. And if we cannot accomplish that feat of extending our knowledge into the infinite unknown, instead of despair we should be filled with the ecstatic joy of living in an open world, a world where all the answers can never be known, a world forever open to exploration and adventure by our children and grandchildren. The traveler comes to a divide, and in front of him lies an unyielding horizon.
|Artificial Intelligence in Healthcare Market Value Expected to Touch $22,790 Million by 2023 Cache Translate This Page|
"Different interventions ranging from maintenance of patient records & electronic health records (EHR) to application in surgical procedures are gradually incorporating artificial intelligence, thereby revolutionizing healthcare and clinical settings." Artificial Intelligence involves the science and engineering of intelligent computer programs. It
|Comment on Unforced Variations: Jan 2019 by Ray Ladbury Cache Translate This Page||Kevin McKinney: "But that is not the entire scope covered by the word “knowledge”. You can’t rock a guitar solo, heal a patient, close a sale, inspire a student, or shape a piece of wood (absent a CCM setup, anyway) solely by science, or by any subset reasonably covered by the term 'conceptual knowledge.'"
Well, computers are healing patients as we speak--in some cases more effectively than human physicians.
And a computer inspired me to start taking artificial intelligence more seriously when it defeated a Go master via a strategy utterly alien to a human intelligence. (It also got me thinking about other types of "alien" intelligence--e.g.the hive intelligence of social insects...)
John Von Neumann once noted that when people say that a computer reproduce human intelligence, they are neglecting the paradox that if they could specify precisely what it was that computers could not do, they could do it.
I think it is too early to proscribe boundaries where science is and is not profitable. And, as you noted, I specified "reliably". If it's something that is of critical importance, you need to rely on science.|
|Google Brain built a translator so AI can explain itself Cache Translate This Page||A Google Brain scientist built a tool that can help artificial intelligence systems explain how they arrived at their conclusions — a notoriously tricky task for machine learning algorithms. The tool, called Testing with Concept Activation Vectors or TCAV for short, can be plugged into machine learning algorithms to suss out how much they weighted different factors or types of data before churning out results, Quanta Magazine reports.|
|AI Conference Designed to Lift Health Outcomes for Maori Cache Translate This Page||A Global Artificial Intelligence Conference starting tomorrow at the Auckland Business School will explore the use of predictive data, robotics and new smart technologies to develop better health and wellbeing outcomes for New Zealanders with a strong ...|
|Neurala COO shares insight on gender equity in STEM with NU students Cache Translate This Page|
“If roughly 50 percent of drivers in the United States are women, then why is there nowhere in the car for the driver to put her purse?” Heather Ames Versace posed this question to an audience of Northeastern students Friday night. Versace, co-founder and chief operating officer of the artificial intelligence company Neurala, was invited...
The post Neurala COO shares insight on gender equity in STEM with NU students appeared first on The Huntington News.
|SEMICON Korea Highlights Smart Tech, Industry Growth and Workforce Development Cache Translate This Page||...Samsung Advanced Institute of Technology (SAIT), Samsung Electronics – On-Device Artificial Intelligence • Walden C. Rhines , CEO emeritus, Mentor , a Siemens Business – Domain Specific Processors Drive Changing Outlook for Semiconductor Memory • Myung-Hee Na , distinguished engineer, IBM Research – The Era of AI ...|
|AI 101: How learning computers are becoming smarter Cache Translate This Page|
Many companies use the term artificial intelligence, or AI, as a way to generate excitement for their products and to present themselves as on the cutting edge of tech development.
But what exactly is artificial intelligence? What does it involve? And how will it help the development of future generations?See the rest of the story at Business Insider
|The market for tech products for aging baby boomers is expected to balloon to $20 billion by 2020. Here are some of the best Cache Translate This Page|
Thomas Lohnes/Getty Images
Our elders may be wise in years but they're not always very tech savvy, as anyone who's had to provide tech support to an uncle or grandparent can attest.
But tech products are starting to become more senior-friendly. New innovations, like voice recognition, touch screens and sensors, are making the power of digital technology more accessible to older people. The market for tech products aimed at people aged 60 and over is set to swell by $20 billion in the next two years.
The best tech products for elders need to serve a real purpose in the lives of their users, many of whom may suffer from Alzheimer's or other forms of cognitive impairment — there's no room for superfluous gizmos or useless apps.
This is where apps like Papa and products like Jiobit come in. They answer simple questions like "Where did Grandma wander off to?" and "Who can take Dad to the doctor?" When it comes to tech products for seniors, use will overshadow flash every time.
Check out some the best new, as well as tried-and-true, tech products and services for older adults:
ElliQ, a robot companionElliQ
After winning the Best of Innovation award for the Smart Home category at last year’s CES, Intuition Robotics, an Israeli startup and provider of digital companion technologies, announced this past week that its social robot for older adults, ElliQ, is now available for pre-order starting at $1,499.
ElliQ, "the sidekick for happier aging" as the company calls it, is radiant and bright, like a table light, with a moving cylindrical robot head that can make animatronic movements and field vocal requests.
It's a combination of a touch screen and a voice-enabled home assistant geared to make it easier for seniors to make video calls, set reminders for medication and arrange doctors appointments. You can even play bridge with it.
The product has successfully been tested with beta users aged 62-97 and will ship some time in the summer of 2019.
Noomi, a wristband combining artificial intelligence and sensorsNoomi
Noomi, a Swedish startup, released its smart wristband a few years back with the goal to better care for the elderly. The wristband itself is filled with hardware sensors and artificial intelligence to monitor all kinds of behavior from sleeping and eating habits to detecting whether a trip or fall happened. Any sort of change, whether minor or major, is relayed to a caregiver.
The wristband's battery life is quite significant, too: up to 12 months. All of the data it collects is stored on its cloud platform and can be shared with a medical professional in real-time, 24 hours a day.
Jiobit, a real-time location trackerJiobit
This small, clip-able device that tracks real-time location was originally designed for children, but can be helpful for seniors with dementia who are prone to wandering off, according to AARP.
Prices start at $99.99 for the device and $8.99 a month with a 2-year commitment. The lightweight gadget, designed so it isn't easily taken off, also has a "geo-fence" alert, which notifies a caregiver if the person goes outside of a "trusted zone." Another plus: it lasts up to one week on a single charge.
The device is used all over the world (and in all 50 states), according to a Jiobit spokesperson, and its encryption and security technologies have even gotten the thumbs-up by law enforcement professionals.
See the rest of the story at Business Insider
|Director of Artificial Intelligence - Micron - Milpitas, CA Cache Translate This Page||Broad, versatile knowledge of artificial intelligence and machine learning landscape, combined with strong business consulting acumen, enabling the...|
From Micron - Fri, 19 Oct 2018 17:30:05 GMT - View all Milpitas, CA jobs
|Systems Engineer (radar/RF/EW) - Polaris Alpha - Baltimore, MD Cache Translate This Page||Parsons has been a leader, innovator, and change agent for 75 years. The pace of adaptation of transformational technologies such as artificial intelligence,...|
From Polaris Alpha - Thu, 03 Jan 2019 15:14:06 GMT - View all Baltimore, MD jobs
|Coding the Cure for Cancer Cache Translate This Page||In this special guest feature, Emily Walsh, the Community Outreach Director for the Mesothelioma Cancer Alliance, discusses how artificial intelligence is helping to detect cancers as well as the role AI is playing in the processing and sorting of data collected by cancer researchers. |
|Equifax Delivers on Data for Customers in 2018 Cache Translate This Page||Equifax Inc. (NYSE: EFX) delivered on its commitment to helping customers make smarter decisions with unique data throughout 2018 with the introduction of new solutions, technologies and services across multiple industries. Hundreds of data scientists in the global Equifax Data & Analytics Lab work every day to better connect the company's unique data with the unique needs of customers through a relentless pursuit of new innovation in predictive analytics, machine learning and explainable artificial intelligence (AI).|
|The Internet of Things, Artificial Intelligence, Blockchain, and Professionalism Cache Translate This Page|| |
|entreconsultas.cl was reported accessible in China Cache Translate This Page||
Title: EntreConsultas.com : Vision Computer + Artificial Intelligence
Report Date: Jan 21, 2019 7:12:50 PM
Reporter Country: China
Comments: Accessible in China according to https://en.greatfire.org/entreconsultas.cl
|Circa 2118 What Humans Will Do When Machines Take Over Cache Translate This Page||If you've listened to this show you know we spend a lot of time discussing AI - artificial intelligence - especially how it relates to talent acquisition and HR.|
|Provide ideas how to patent & protect intellectual property in United States Cache Translate This Page||I am looking for someone to do the following: 1) provide ways and strategies in which my idea can be patented in a utility patent. I already have a few specific ways that it may be patented. 2) search for current patents in the United States... (Budget: $10 - $20 USD, Jobs: Artificial Intelligence, Legal, Legal Research, Legal Writing, Patents)|