Deep learning: Hope and hype

February 2, 2019
Why researchers at the year’s biggest AI conference focused on how to keep human bias out of computer algorithms.

This is one of the latest editions of “Business Lab“, MIT Technology Review’s new podcast helping business leaders make sense of new technologies coming out of the lab and into the marketplace. In this episode:

Both the progress and the hype around cutting-edge machine learning techniques were on vivid display at the December 2018 NeurIPS Conference in Montreal, Quebec, says Will Knight, MIT Technology Review’s senior editor for artificial intelligence. One big question hanging over the meeting, he says, was how to detect and reverse the sexism, racism, and other forms of bias that seep into machine-learning algorithms that train themselves using real-world data. Participants also previewed the coming generation of chips designed specifically to support deep learning—a field where US manufacturers face growing competition from China. Separately, Will looks to the most exciting AI trends for 2019, including the generative adversarial networks, or GANs, being used to generate authentic-looking photos and videos.