Dan Hendrycks: belief

Transcript context

…I mean, I I feel that scaling large language models will not lead to AGI. I I think there are quite a few things that we have cognitively that LLMs don't have, and and a lot of that is I'm I'm an I'm an externalist. I I think that a lot of the effective computation doesn't happen in our brains. I think it happens memetically. I think it happens culturally. Mhmm. And I don't think I mean, I I guess I believe in principle that we could simulate the entire thing in a computer. And maybe there is like a a lower resolution abstracted version, which would capture enough of the dynamics to produce intelligence. But roughly speaking, you know, I I'm I'm skeptical about superintelligence, particularly skeptical about recursive and super, intelligence, you know, recursively improving superintelligence. Maybe we could touch on that because I felt that you were giving a great account of what recursive superintelligence would look like, and and also the the scale out version of that. So what would happen when we have a super intelligence which could be copied and multiplied a thousand times? But what I didn't really get from reading it was why you believed technically, in principle, it was possible to have a recursively improving intelligence. I think we already have the AIs helping or influencing AI development in a recursive way of partly automating some code, helping design the chips, helping cool the power plants, helping label some of the data, doing the, you know, the constitutional AI related type of stuff. And it's in weak ways though, but the recursion thing that I think is particularly explosive is if you can close the loop, by taking the human out of it and then you can go from human speed to full machine speed, you don't have that impediment anymore. I think if you assume that you have, human level AI researchers or world class AI research AIs, then you just copy paste those. And I think that that'll be technologically feasible. That isn't to say that it's a natural implication of training the AI on more pre training tokens and doing it, you know, a loss function trick. You may need some some extra algorithmic ideas. That isn't to say it wouldn't I I I would still guess it's nearly entirely deep learning though. But I think you'd need some other things taken care of like for instance memory for this externalist picture. It needs memory to inherit some of that culturally computed wisdom and information. And that capability is not particularly developed in my view. So I think we need that. Maybe we'll need some other sorts of things before it has at least the cognitive abilities of a typical human. And then after that, you're needing it to be pretty smart. You're needing high fluid intelligence. You'll need to be crushing, you know, those those arc questions as an example. And you'll need some other sorts of things for it to be a sort of human level AI researcher. But I think that's feasible. There's certainly a question of when. I do think there are some bottlenecks that would need to be resolved for getting there. And it's not. The algorithmic ideas today plus bigger computer is sufficient. But, would you accept though that there is just an epic pyrotechnic orchestra of computation in the universe? I'm I'm not a pan computationalist, so I don't think the universe is digital and made out of computation. So I'm saying that we we could imagine some kind of effective computation that simulated the processes that happened in the universe, and maybe that would be, equivalent. But but do you do you agree, at least in principle, that the amount of, you know, computation we could build on planet Earth would would only ever be a sliver of what goes on in the universe?…

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