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.