Meet the 13-year-old prodigy taking IBM and artificial intelligence by storm

Meet the 13-year-old prodigy taking @IBM and artificial intelligence by storm  @BreakfastNews

  • Tanmay Bakshi fell in love with computers at five, released his first iPhone app at nine, and now at just 13 years old is working with IBM on artificial intelligence.
  • He is currently in Australia for the IBM Watson Summit, which brings together experts in artificial intelligence to discuss how the technology can help people and businesses in the future.
  • “If you think about it, really anything would fascinate a five-year-old, especially a computer,” Tanmay told News Breakfast.
  • Tanmay names Apple co-founder Steve Jobs as an inspiration — “especially his passion and dedication towards his work” — and is now most excited by how artificial intelligence can be used in health care.
  • Tanmay has toured the world to spread the word on computer programming, including giving public lectures and joining forum discussions, which has meant he has left traditional school in lieu of home schooling.

Tanmay Bakshi isn’t your typical 13-year-old. Rather than playing video games he’s blazing new trails in AI and has become one of the youngest app developers in the world.
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Google’s plan to best Amazon rests on one particular piece of software

#Google's plan to best #Amazon rests on one piece of software  #aws #cloud #AI

  • Two years later the tool, which is used in building machine-­learning software, underpins many future ambitions of Google and its parent company, Alphabet.
  • But just months after TensorFlow was released to Google’s army of coders, the company also began offering it to the world for free, as an open source tactic.
  • S. Somasegar, a managing director at venture fund Madrona who was previously head of Microsoft’s developer division, says TensorFlow’s prominence poses a genuine challenge to Google’s cloud rivals.
  • The company has created specialized processors to make TensorFlow faster and reduce the power it consumes inside Google’s data centers.
  • Since Google released TensorFlow, its competitors in cloud computing, Microsoft and Amazon, have released, or started supporting, their own free software tools to help coders build machine-learning systems.

Google has pinned its cloud computing hopes on a bit of software that helps programmers build artificial intelligence apps called TensorFlow.
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This machine-learning software has transformed Google, and the rest of the world may be next

Google Stakes Its Future on a Piece of Software #ML #AI #tensorflow #Google

  • Early in 2015, artificial-intelligence researchers at Google created an obscure piece of software called ­TensorFlow.
  • But just months after TensorFlow was released to Google’s army of coders, the company also began offering it to the world for free.
  • S. Somasegar, a managing director at venture fund Madrona who was previously head of Microsoft’s developer division, says TensorFlow’s prominence poses a genuine challenge to Google’s cloud rivals.
  • The company has created specialized processors to make TensorFlow faster and reduce the power it consumes inside Google’s data centers.
  • Since Google released TensorFlow, its competitors in cloud computing, Microsoft and Amazon, have released or started supporting their own free software tools to help coders build machine-learning systems.

Alphabet thinks it can wrest the cloud computing market away from Amazon by helping companies make use of machine learning with a tool called TensorFlow.
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Guide to Advanced Safety Systems for Cars

The Positive Impact of Advanced Safety Systems for Cars  #m2m #MachineLearning

  • Why Do We Have Campaigns?
  • Join our campaigns and together, we’ll hold corporations and lawmakers accountable.

Consumer Reports survey on Advanced Safety Systems for Cars looks at driver experiences with safety features on 66,000 vehicles and rates the systems.
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Nvidia CEO: Software Is Eating the World, but AI Is Going to Eat Software

Nvidia CEO: “Software is eating the world, but #AI is going to eat software” on @techreview

  • At the company’s annual developer conference in San Jose, California, this week, the company’s CEO Jensen Huang spoke to MIT Technology Review about how the machine-learning revolution is just starting.Nvidia has benefitted from a rapid explosion of investment in machine learning from tech companies.
  • Software is eating the world, but AI is going to eat software.What industry will be transformed by machine learning next?
  • Arterys recently got FDA approval for their cardiac imaging [which annotates scans of the heart], and I know of many others that are in the pipeline.Using machine learning in cars will also create new challenges for regulators.
  • We probably have to break down some of these problems into smaller chunks.Your chips are already driving some cars: all Tesla vehicles now use Nvidia’s Drive PX 2 computer to power the Autopilot feature that automates highway driving.
  • I’m not exactly sure, but we’ll find out.Intel, Google, and several other companies are now working on chips designed to accelerate machine learning (see “Battle to Provide Chips for the AI Boom Heats Up”).

Jensen Huang predicts that health care and autos are going to be transformed by artificial intelligence.
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OpenAI will debut a novel approach to machine learning needed to sustain the momentum of AI research

Evolutionary strategies talk by Ilya Sutskever: Comments  #DeepLearning #ML#AI

  • Ilya Sutskever, director of OpenAI, an independent research group, will describe what might be the next big breakthrough in artificial intelligence today at EmTech Digital, a conference organized by MIT Technology Review in San Francisco.
  • The OpenAI researchers compare their evolutionary strategies approach to reinforcement learning, a technique that has produced some impressive results in the past year or so, including enabling a computer to defeat one of the world’s best Go players (see “10 Breakthrough Technologies: Reinforcement Learning”).
  • “This is very interesting and could indeed be the start of something larger,” says Pedro Domingos, a professor at the University of Washington and the author of The Master Algorithm, a book about different machine-learning methods.Domingos questions whether the technique will surpass reinforcement learning, but he adds: “There is a delightful history in machine learning of very simple methods coming along and beating much more complex ones.
  • For instance, deep learning, a technique that involves using very large neural networks to find patterns in data, and which has proved to be a very powerful voice- and image-recognition technique, is rapidly finding applications in medical research and health care.At the same time, however, it has become clear that these technologies alone will not provide the general artificial intelligence that has long been the dream of the field.
  • The tension between new opportunities and the continued need for innovations will be prominent themes at EmTech Digital.Even with the emergence of new machine-learning techniques, such as reinforcement learning and OpenAI’s evolutionary strategies approach, the ultimate goal of the field—some form of artificial general intelligence—remains a distant vision.Still, the spread of powerful machine learning into new industries and areas of daily life will heighten attention on the unintended consequences that may result.Speakers at EmTech Digital will discuss the issue of the bias that can become embedded in machine-learning algorithms that are increasingly used to guide important decisions such as the appropriate length of a sentence for a person convicted of a crime, or who is granted a bank loan.

OpenAI will describe a new machine-learning approach at MIT Technology Review’s EmTech Digital conference.
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Andrew Ng: Why AI Is the New Electricity

What’s slowing down #AI adoption? 

Two problems: scarcity of data and talent. —@AndrewYNg

  • Still, computer scientist and Coursera co-founder Andrew Ng says, fears that AI will replace humans are misplaced: “Despite all the hype and excitement about AI, it’s still extremely limited today relative to what human intelligence is.”
  • “Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years,” Ng says.
  • “I would say the most scarce resource today is actually talent, because AI needs to be customized for your business context,” Ng says.
  • “Worrying about evil AI killer robots today is a little bit like worrying about overpopulation on the planet Mars.”
  • Evil AI hype, he says, is being used to whitewash a much more serious issue, which is job displacement.

A computer scientist discusses artificial intelligence’s promise, hype, and biggest obstacles.
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