Matthieu Wyart: preference

Transcript context

…And who were your mentors? Who inspired you? What books did you read? How did you kind of land on your current trajectory as a physicist? Well, that's a complex question for me because I have my 2 parents are physicists actually. And when I started to do my PhD, I tried to escape escape them by going to economic mean, doing more finance and economy. And then already during my PhD, started to be fascinated again by physics and how sand flows and and things like that. And then when I was a postdoc, actually, I was always mesmerized by our brain, how we think. And and I I tried at that time to, you know I even spent 1 year in Germany, farm, a place where, you know, a neuroscience institute. And and I met lots of fantastic people and I learned a lot. But I felt at that stage that a lot of the theory, how you have many connected neurons, what their dynamics were a bit applied math and detached from really function and the question of how do you learn intelligence or rules, constraint language, and so on. So it at the was level that I really wanted to operate. And so I gave up, I went back to physics. And then I mean, think it's essentially the development of the technology. It's facing us. I think the analogy I like is industrial revolution when actually heat engine emerged before. Again, 1 case where technology was 1st and then you had to understand what's behind them, how efficient can they be, the limit to the efficiency and so. And so then Carnot actually a French physicist came up and wrote a beautiful title, it reads like philosophies, essentially no math and interesting concept like entropy. And it was the beginning of thermodynamics. Mean very deep ideas coming from some technological facts. And here I think it's the same. Mean, with those machines, it's amazing. They are creative. You give them a bunch of images and those diffusion models suddenly like a painter, build new faces, they compose new faces. How can it be? All they create sentences that they have never heard before and Noam Chomsky and others said that it would be extremely hard to do. They do it. So how? Why? So yeah, it's being fascinated by questions. Yeah. That's what drives me. I mean, I'm sorry to bring Chomsky back again. But he said that LLMs are like bulldozers. He says, I love bulldozers. They're great for clearing the snow, but they're not a contribution to science. And he said, I've got a theory. Anything goes. It explores all the laws of nature, anything that can be. And he says that when you've got a scientific theory, you have to explain why are things this way, why are things not that way. But you were just saying, when we discovered the steam engine, I think you believe that that actually was the stepping stone to building theory. But for Chomsky, there's a huge difference between competence and performance. It's possible. He had this wonderful expression about Deep Blue, the chess thing. And he said that's a little bit like a bulldozer winning a weightlifting competition. So it's almost inconsequential, it's incoherent.…

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