Minds and machines: can we work together in the digital age?

Minds and machines: can we work together in the digital age? @iansample   #AI #ML #industry40

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    In 2016 Klaus Schwab, founder and chairman of the World Economic Forum, wrote: “We stand on the brink of a technological revolution that will fundamentally alter the way we live, work, and relate to one another.”

  • This fourth Industrial Revolution, he said, will fuse the physical, digital and biological worlds, and affect all corners of society – even challenging ideas of what it means to be human.
  • Andrew McAfee and Erik Brynjolfsson of the the Massachusetts Institute of Technology think not.
  • And in their latest book Machine, Platform, Crowd, they tell us why.
  • Joining Ian Sample in the studio, Andrew and Erik lay out their blueprint for the future of the workplace, including the role big data will play, how some processes involving decision-making could be automated, and how minds and machines can come together to cancel out each other’s errors.

Ian Sample sits down with Andrew McAfee and Erik Brynjolfsson to discuss the future of the workplace and the role artificial intelligence will play
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This new AI can read your mind and predict your thoughts

This new AI can read your mind and predict your thoughts -   #ArtificialIntelligence  #AI

  • Today, various pieces of software can do everything from chat with us on Facebook Messenger to guiding the Mars rover Curiosity while its human engineers catch a nap.
  • The group’s new software takes a novel approach to guessing what is going on inside a human brain, using data gathered from brain scans via fMRI to predict human thoughts by seeing how the pattern of brain activity that produces them, then detecting it in reverse.
  • “One of the big advances of the human brain was the ability to combine individual concepts into complex thoughts,” lead researcher Marcel Just explains.
  • The discovery of this correspondence between thoughts and brain activation patterns tells us what the thoughts are built of.”
  • The algorithm was then trained using this data, and learned to detect the same patterns occurring again, accurately predicting what a person was about to say a stunning 90 percent of the time.

At one point in our history, the most impressive example of artificial intelligence was a computer that was really, really good at chess. Today, various pieces…
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Human-Level AI Is Right Around the Corner—or Hundreds of Years Away

#Human level #ai is in sight

  • Robin Hanson
    Martine Rothblatt
    Ruchir Puri
    Ray Kurzweil
    Carver Mead
    Nick Bostrom
    Rodney Brooks
    Gary Marcus
    Jürgen Schmidhuber

    Robin Hanson
    Author of The Age of Em: Work, Love, and Life When Robots Rule the Earth
    When will we have computers as capable as the brain?

  • Ray Kurzweil
    Cofounder and chancellor, Singularity University
    When will we have computers as capable as the brain?
  • Carver Mead
    Professor emeritus, California Institute of Technology
    Do you have any qualms about a future in which computers have human-level (or greater) intelligence?
  • Since we won’t have intelligent computers like humans for well over 100 years, we cannot make any sensible projections about how they will change the world, as we don’t understand what the world will be like at all in 100 years.
  • Computers are already far more capable than brains in many respects (for example, arithmetic and memory), but I think it could still be 20 to 50 years before machines have the ability to read and comprehend and reason about novel situations as fluently as people can.

Ray Kurzweil, Rodney Brooks, and others weigh in on the future of artificial intelligence
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Google’s new machine learning framework is going to put more AI on your phone

Google’s new machine learning framework is going to put more AI on your phone

  • At the moment, artificial intelligence lives in the cloud, but Google — and other big tech companies — want it work directly on your devices, too.
  • At Google I/O today, the search giant announced a new initiative to help its AI make this leap down to earth: a mobile-optimized version of its machine learning framework named TensorFlowLite.
  • The newly announced version, TensorFlowLite, will build on this, helping users slim down their machine learning algorithms to work on-device.
  • The company also announced that an API for making machine learning work better with phone chips would be coming sometime in the future — a clear sign that Google thinks your next phone will have an AI-optimized chip in it.
  • TensorFlowLite should help Google (and the wider AI research community) bring even more interesting functions like this to our most-used and most-important devices.

At the moment, artificial intelligence lives in the cloud, but Google — and other big tech companies — want it work directly on your devices, too. At Google I/O today, the search giant announced a…
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Practical Deep Learning For Coders—18 hours of lessons for free

Practical #DeepLearning For Coders—18 hours of lessons for free

  • After this course, I cannot ignore the new developments in deep learning—I will devote one third of my machine learning course to the subject.
  • I’m a CEO, not a coder, so the idea that I’d be able to create a GPU deep learning server in the cloud meant learning a lot of new things—but with all the help on the wiki and from the instructors and community on the forum I did it!
  • Sometimes I feared whether I would be able to solve any deep learning problems, as all the research papers I read were very mathy beyond reach of simple intuitive terms.
  • But Jeremy and Rachel (Course Professors) believe in the theory of ‘Simple is Powerful’, by virtue of which anyone who takes this course will be able to confidently understand the simple techniques behind the ‘magic’ Deep Learning.
  • The course exceeded my expectations and showed me first hand how both Deep Learning and ourselves could change the world for better.

fast.ai’s practical deep learning MOOC for coders. Learn CNNs, RNNs, computer vision, NLP, recommendation systems, keras, theano, and much more! neural networks!

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The Dark Secret at the Heart of AI

The Dark Secret at the Heart of AI  #AI

  • ‘Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey.
  • The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence.
  • The car didn’t follow a single instruction provided by an engineer or programmer.
  • Getting a car to drive this way was an impressive feat.
  • But it’s also a bit unsettling, since it isn’t completely clear how the car makes its decisions.

‘Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence. The car didn’t follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an algorithm that had taught itself to drive by watching a human do it.
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Facebook Messenger adds payment prompts using artificial intelligence • NFC World

  • Facebook Messenger users across the US are now being prompted to send and request money transfers by an artificial intelligence-based feature that detects when a payment is being discussed in a conversation on the social media platform and responds with a suggestion designed to help the user complete that payment.
  • “M offers suggestions by popping into an open conversation to suggest relevant content and capabilities to enrich the way people communicate and get things done,” the social media giant says.
  • M may make a suggestion in a conversation relevant to one of the core actions, and then the M logo and suggestion will appear — it’s that simple.”
  • Facebook began testing payments through its Messenger service in July 2016.
  • The social media giant also updated its Messenger chatbot platform to enable bots to accept payments without having to send shoppers to external sites to complete the checkout process in September 2016.

Facebook Messenger users across the US are now being prompted to send and request money transfers by an artificial intelligence-based feature.
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