Geoffrey Hinton discusses how AI could inform our understanding of the brain

University of Toronto faculty member, Google Brain researcher, and recent Turing Award recipient Geoffrey Hinton spoke this afternoon during a fireside chat at Google's I/O developer conference in Mountain View. He discussed the origin of neural networks -- layers of mathematical functions modeled after biological neurons -- and the feasibility and implications of AI that might someday reason like a human. "It seems to me that there is no other way the brain could work," said Hinton of neural networks. "[Humans] are neural nets -- anything we can do they can do … [Neural networks] work better than [they have] any right to." Hinton, who's spent the past 30 years tackling a few of AI's biggest challenges, has been referred to by some as the "Godfather of AI." In addition to his seminal work in machine learning, he's authored or coauthored over 200 peer-reviewed papers, including a 1986 paper on a machine learning technique called backpropagation.