Tim Scarfe: evaluation

Transcript context

…That yeah. This is a very, complicated question. I think, you know, you have to disentangle the degree to which the human is part of what you're calling creative and the degree to which the model is. So like with the VO3, the human came up with the idea of the ape doing the ASMR or something like that. Who's getting the credit for being creative? It's not that it's not impressive. Mean, certainly the model did something impressive, but where's the creativity? And so I think though in the larger picture, if you want to ask like can the model totally autonomously on its own be genuinely creative, whatever that means, because people are going to disagree about what that means, then is it just a matter of some kind of gradient following algorithm that's going to uncover some really interesting insightful types of creative scenarios that would be really valuable for all of us? And yeah, I think it depends on the underlying representation. Mean, that's like the answer. It's like, is the world represented inside the model? Because that's going to be what determines what are the adjacent points where the gradients can actually get you from where you are. And if the model doesn't represent the world in a coherent parsimonious way, then you're going to find your options more limited. Not so limited that you won't be impressed at all, you'll probably still be impressed. More limited than a really creative auteur or something who's coming up with amazing new genres and a new way of thinking about film or something. That's not probably going to fall out of this. And so it sort of depends on the degree of this creativity that you want. And I do think that I distinguish between, I call it derivative creativity and transformative creativity. You're going to get a lot of the derivative style, but a lot less of the transformative style if you have a bad underlying representation. And so that's the trade off that we're working with. It's still gonna impress a lot of people, but the mode collapse problem, I think, is a real concern here, you know, because as we sort of like freeze pop culture in the year 2025 and just live inside of that bubble for the rest of eternity, it's going to get more and more tiresome. And so the ability to have pathways out of that, again, will depend on how we represent the world. And there's a danger with this road that we're going down that we're going to be trapped. And we're already seeing this. It looks like what's on the radio doesn't sound as different from 20 years ago as it did 20 years before that. And this kind of convergence could be just accelerated by the kind of stuff we're talking about here. And ultimately, think it all boils down to representation. It doesn't work autonomously. It's not creative because it's not built on the foundation of a representation that describes the world well. So as soon as you leave the thing on its own doing anything with any flexibility, it'll just kind of go crazy. But I guess the question is, does it matter? Like we have AI and we use it in tandem and we can do great things with it. Is is that a problem? I mean, I totally agree that in terms of creativity and the amplification of what humans already can do, AI is hugely valuable in its present form. Like, can amplify things in really interesting ways. But it's still ultimately the germ of the ideas is coming out of the human mind. And so you could be satisfied with that or not. You could say, this is good enough, I'm happy. But I think in terms of what we can't do because of that, that we might someday in the future be able to do, The things we can't do are the things where the human mind isn't having the ideas. We're worried about things from a scientific perspective, for example, and the kinds of things like the new place that I work now, Lila Science is thinking about automating the wheel of science, where we would like these ideas to come faster to solve the problems of the world. But it also applies to art as well. It's like when are we going to get the next big idea in music that's going to really shake things up? It's taking a long time here. And so of course, we can just wait for humans to come up with these things and wait long enough and it might happen. But the question is can AI accelerate that process both in the sciences and the humanities? This is a separate question, is that a good thing? But it's just an interesting question, can it be done? And if it can be done, then that's not what's happening with current models yet. And so, I think when we talk about representation, it starts pointing us in the direction of how that will ultimately be done, is by taking seriously the underlying representations and understanding that to actually see something novel in the world in a genuinely interesting and deep way requires you to decompose the world in a special way that's highly organized, and unique. And, that's just not what this fractured and tangled representation seems likely to do, at least as far as we've understand it right now.…

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