Google, Intel, MIT, and more: a NeurIPS conference AI research tour
The 33rd annual NeurIPS conference on artificial intelligence kicks off in Vancouver this weekend. Check out some of the research highlights in this selective review.
The 33rd annual NeurIPS conference on artificial intelligence kicks off in Vancouver this weekend. Check out some of the research highlights in this selective review.
Google DeepMind scientists built a computer program that gives signals from future to past, in a kind of theoretical model that feels like things people do when they learn from their mistakes. Just remember, it's only a game.
Pamela McCorduck produced a groundbreaking history of artificial intelligence forty-one years ago. Fortunately for the world, she's returned with another volume, one that emphasizes the humanity that creates AI in all its idiosyncrasies.
Google scientist François Chollet has made a lasting contribution to AI in the wildly popular Keras application programming interface. He now hopes to move the field toward a new approach to intelligence. He talked with ZDNet about what he hopes to accomplish.
MLPerf is the widely cited benchmark test for how fast computers are at crunching artificial intelligence problems. Cerebras Systems, which unveiled its first AI computer system Tuesday, said it spent no time optimizing for the test, given that it has little to do with real-world problems.
Raja Koduri of Intel helped kick off the movement of GPU computing 14 years ago when he was at AMD. This time, he's refining the strategy for a world of more heterogeneous computing.
Moveworks has been bringing natural-language bots to help desk applications, and it just got a giant new round of funding to commercialize large-scale NLP processing models such as Google's BERT.
Facebook AI research's latest breakthrough in natural language understanding, called XLM-R, performs cross-language tasks with 100 different languages including Swahili and Urdu, but it's also running up against the limits of existing computing power.
Machines don't understand much of anything, especially not things such as ironic speech, but machine learning may be able to assist humanity in some way by counting the instances of linguistic and semantic constructions that indicate satire or misleading news, according to a new study by tech startup AdVerifai, in partnership with George Washington University and Amazon’s AWS.
At its user conference in Florida, IBM offered to demystify the term AI. The effort seemed only mildly successful, but the company nevertheless conveyed a lot of energy and drive behind its various offerings that pertain to machine learning and that may be enough to excite its customers.