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The biggest AI stories of 2017

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The biggest AI stories of 2017

The biggest AI stories of 2017

Artificial intelligence — already a much-discussed science in recent years — moved to the center of public conversation in 2017. Leading tech voices continued to ring the alarm about the potential for a super-intelligent bot to take over the world in a very unpleasant way; others said the fears are vastly exaggerated. The latter gained more converts, namely because AI is nowhere near super-human intelligence at the moment.

We surveyed the community asking the following question: What was the most important AI story of 2017? Their answers follow.

Rodney Brooks, founder, Rethink Robotics

My most important AI story for 2017 is an advertisement I saw on broadcast TV on Sunday, Dec. 17, 2017, during an NFL game. It was an ad by the NFL saying that it is now using machine learning to reveal insights for fans. The end of the ad showed that the NFL is hosting its ML on AWS (Amazon Web Services). Here is a story about this effort from three weeks ago. The significance is that the hype about ML/AI is now so widespread that it is expected to have a cachet impact on NFL fans.

Andrew Ng, CEO, Landing.AI

AlphaGo demonstrated the power of computing and data. But Carnegie Mellon’s Libratus, its poker-playing program, took much more innovation. From a technical standpoint, it was a delightfully surprising result.

Andrew Moore, dean, Carnegie Mellon’s School of Computer Science

The victory of the Libratus AI over four top professional poker players. This victory in no-limit Texas Hold ’em heralds a new kind of game in which the AI has to take into account that its opponent might be deliberately misleading. In a world of increasing scrutiny of what information is real or unreal, it is amazing that we are seeing the emergence of a new generation of AI that is more skeptical about raw facts.

Greg Diamos, senior researcher, Baidu

This year I was extremely impressed by the team of researchers at Stanford University who developed the first AI radiologists, which can detect heart arrhythmias and better inform human doctors. I think medical applications of AI will be very visible and surprising to many people as technology develops.

Azeem Azhar, founder Peer Index, curator The Exponential View

I would choose two works that looked at the question of the responsible implementation of AI. Both help us to tackle all-too-easy-to-ignore downsides of this powerful technology.
  • The first was a talk by Kate Crawford (of Microsoft Research), who described how machine learning algorithms can go wrong, reinforcing and amplifying existing prejudices.
  • The second is a paper by Adrian Weller (of the University of Cambridge), on building algorithmic systems that map to our intuitions of fairness. It is essential that we manage the downsides addressed by Kate and Adrian in order to spur the acceptance of the tech.

The biggest AI stories of 2017

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Article Credit: Axios

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