“Machine learning is really good at what's been trained on. But scientific discovery is almost by definition what you haven't been trained on.”

RSI. That's the biggest idea of firewall. But does that mean that is it plausible that fable six or something or GPT eight could just have a which has been tuned on these sort of higher order reasoning traces could actually just do this without any logic? Because it's sort of the same thinking process, right?

Yeah, I mean, I think there's decision-making under uncertainty. Obviously, in machine learning, there's noise in running the AI loops. But we do think there's a different set of challenges when you're actually interfacing with the physical world. But also, I think there's another piece too, which is getting the compression of everything into weights is still really valuable. If inference time reasoning was sufficient, all of the Frontier labs would have stopped training at Like GPT-4, and we're like, okay, from now on out, we're going to get really good at inference time improvements. And so we think that by, you know, because of the differences between physical sciences and machine learning, getting that compressed into our own weights will lead to different types of systems and different types of capabilities.

Yeah, there's not going to be like, no one's going to zero shot the room temperature actually.

That would be pretty cool. Yeah,

yeah. I mean, as someone who has worked closely with wet labs before, it's certainly I am more skeptical about zero shotting like scientific results than some, but it is something that I think some people might ask. So