Evidence receipt / belief
Published · transcript-backedKenneth Stanley: belief
6 Jul 2025 Machine Learning Street Talk The Fractured Entangled Representation Hypothesis (Kenneth Stanley, Akarsh Kumar)
“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.”
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- Speaker
- Kenneth Stanley
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- Claim type
- belief
- Recorded
- 6 Jul 2025
- Publisher
- Machine Learning Street Talk
Transcript context
…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. And the the actually, this question came up, Ken, in your doom debate, which is, you know, is survival an objective or a constraint? And I think, you know, Ken, I think and and by the way, I I wanna say that was a brilliant interview. I thought your performance was excellent. I really enjoyed watching that debate. I saw it from start to finish. I think, you know, your communication of open ended search and and kind of these this take on it has has been sharpened, you know, significantly since like 4 years ago when we talked. I found it like really compelling. So I thought that was a great a great conversation. And in there you say, look, you know, survival of the fittest is is not an objective. It's a constraint. It's like it's a constraint on the system. You have to survive if you're gonna propagate but subject to that binary, you know, survive or not survive, it's not part of any objective. You know, I think is the way you kinda communicated that.…
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