A short interview segment in which Yann LeCun and Ruslan Salakhutdinov recount how they first became interested in machine learning and deep learning. LeCun describes reading a debate between Noam Chomsky and Jean Piaget (with Seymour Papert on Piaget's side) and discovering the Perceptron; Salakhutdinov describes a chance encounter with Geoff Hinton in Toronto that led him to start a PhD with Hinton within three months.
Questions this video answers
Geoff (Jeff) Hinton.
Chapters
I stumbled on a book which was actually a philosophy book. It was a debate between Noam Chomsky, the computational linguist at mit, and Jean Piaget, who is cognitive psychologist, sort of psychology of child development in Switzerland. And it was basically a debate between nature and nurture, where Chomsky arguing for the fact that language has a lot of innate structure, and Piaget saying a lot of it is learned, etc. And on the side of Piaget was Seymour Papert from mit, who had worked on the Perceptron model, one of the first machines capable of running. And I never heard of the Perceptron. And I read this article and say, a machine capable of learning. That sounds wonderful.
I started in deep learning to some extent, by luck. I did my master's degree at Toronto, and then I took a year off. I was actually working in the financial sector. It's a little bit surprising. And at that time, I wasn't quite sure whether I want to go for my PhD or not. And then something happened. Something surprising happened. I was going to work one morning and I bumped into Geoff Hinton, and Jeff told me, hey, I have this terrific idea. Come to my office, I'll show you. And so we basically worked together, and he started telling me about, you know, these Boltzmann machines and contrastive divergence and some of the tricks, which I didn't at that time quite understand what he was talking about. But that really, really excited. That was very exciting and really excited me. And then basically, within three months, I started my PhD with Jeff.
