Gary Marcus: evaluation

Transcript context

…Well this part wasn't in ANT 20 27. This is sort of So it wasn't in that appendix. I admit I didn't read the whole appendix. I read some of it. I think that's a really fascinating thought experiment. So maybe I've said enough. So just to lay it out, like there's 1 way to extrapolate on basis of things like compute and I think you've done a masterful job of doing that as well as can be done And acknowledging that there's still an element of pulling things out of one's, behind which is true on you know any any account. Like nobody can really do this in a closed form way. And then I have a different slice on it which is like where are the qualitative things that I want to have solved? I think Jan Lecun who I often disagree about, many things with actually would be closer to mine. He would probably give a different set of litmus tests that he's looking for. We would both emphasize world models. We have slightly different ideas about world models. But he would say, I don't think we're close because we don't really have world models and neither of us I think are satisfied with the current thing that some people call reasoning but neither of us think is robust enough. And so I think he and I both take an architectural approach or a cognitive approach. Great. So I'll list a bunch of bullet points of things we could discuss, and then hopefully we can get through them each. And if we miss some, well, least I put them out. So in reverse order, 10 to the 45 scenario where you just sort of brute force evolve intelligence, indeed, you would not understand how it works at all. But nevertheless, you would have it. And you could sort of take those evolved creatures out of their simulated environment and then start, you know, plugging them into, like, chat products and stuff and using them in your economy. And they would be smart. You know, they evolved their they built their own civilization in there, you know, so so they're pretty smart and they're pretty good at generalizing and so forth. So you wouldn't understand how it works, but you'd still nevertheless have the AI system. And then and indeed, that's kind of what I think is happening today for us. Like, we don't understand how these AI systems work very well. We're sort of just throwing giant blobs of compute at giant data sets and training environments and then toying out or playing around with them afterwards and seeing what they're good at.…

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