Geoffrey Hinton develops AI algorithms using physical intuition rather than equations

“I think I was very surprised at how creatively and playfully he approaches research. When we would discuss like algorithms or like optimizers or loss functions, we would discuss them often in like through physical analogy. So we'd spend a lot of time talking about, like, imagine there's, like, a ball here, and, like, an elastic band to this thing, and a pulley here, and, like, this is what the, you know, it's on this kind of a surface, and, like, a lot of it was descriptions in the natural, physical world, and that was very, yeah, like, playful, and a lot of it was approached with, like, oh, what would happen if, you know, with curiosity and I didn't, when working with him, I didn't expect that. I expected it to be much more, like, you know, just, here's the equation. Let's, let's figure out what the derivative is, and let's, let's go from there. Whereas instead, a lot of it's based on, like, intuition.”

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