Thomas Ahle: commitment

Transcript context

…Yeah, That's an interesting thing as well. So we can hill climb in a partial knowledge regime, right? So we might have a verifier. And as you say, like a lot of science is a form of intelligence where you're using MATLAB and you do like a Laplacian or you do an image plot, you take a distribution and it takes shape 1 step at a time. So what you're doing is you're taking steps into the unknown and every single it's like there's a generation discrimination asymmetry. Right? So we can discriminate well, but we can't generate yet. But we take these steps, and then when we get there, we now kind of collapse that into a model, and then that's the artifact of the intelligence. Right. It's like star search or something where you kind of, you, like, prune your search tree as you go, and, like, what what seems most successful so far, like? Exactly. But to your point, every single step of the way, we're using the toolbox. So, know, there are some folks that are really good at riddles or intelligence tests, and a lot of it is skill, right? Because they they have a toolbox of abstract tricks that they use, and but but then there's this question of, maybe that's all it is. Maybe there are these natural patterns, these abstractions that we can compose together and handle any kind of novelty in the intelligence setting. Yeah. So therefore, maybe language models could do this autonomously. I think they possibly could, yeah. This is good point, because…

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