Mazviita Chirimuuta: evaluation

Transcript context

…The problem is these 2 goals actually pull against each other. I think we're at this moment in science now because we have these tools like LLMs for language and convnets and visual neuroscience are being used as predictive models of neuronal responses which don't have that mathematical legibility that originally, so when I was trained in the field that people aspired to have. And so you have this possible conflict, you can either pursue that goal of understanding or you can pursue the goal of prediction but it seems like you can't have both at the same time. Now on the 1 hand people go into neuroscience because they want to understand the mind. They want that feeling where something clicks and you suddenly get how it works. That's what drew Chiromuta to the field in the first place. That's what keeps people up late at night reading papers. But on the other hand, there's just prediction. Building tools that work. If your model forecast data accurately, maybe you don't care whether it's true in some deeper sense. So LLMs are getting unreasonably good. They are winning math Olympiads. They are I mean, as of last week actually, GPT 5.2 apparently discovered a new theory. Well, it's it's solved 1 of these problems that Terence Tau had on on his website. This is insane. But does it actually understand anything? And does it matter if it does or doesn't, as long as it works? Chomsky had an amazing commentary on this a few years ago when we spoke and I think it's still as relevant today as it was then.…

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