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To become truly intelligent, machines need a sense of the unknown

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The most powerful approach in AI, deep learning, is gaining a new capability: a sense of uncertainty. This will provide a way for the smartest AI programs to measure their confidence in a prediction or a decision-essentially, to know when they should doubt themselves.

Adding it to AI programs could make them smarter and less prone to blunders, says Zoubin Ghahramani, a prominent AI researcher who is a professor at the University of Cambridge and chief scientist at Uber.

“We want to have a rock-solid framework for deep learning, but make it easier for people to represent uncertainty,” Ghahramani told me recently over coffee one morning during a major AI conference in Long Beach, California.

During the same AI conference, a group of researchers gathered at a nearby bar one afternoon to discuss Pyro, a new programming language released by Uber that merges deep learning with probabilistic programming.

Google has rebuilt its entire business around AI and deep learning of late.

David Blei, a professor of statistics and computer science at Columbia University and Tran’s advisor, says combining deep learning and probabilistic programming is a promising idea that needs more work.


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Post Author: Michael Byrne

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