But you couldn't make me review it. Anyway I think you're just straw manning what I was trying to say. I probably didn't express it terribly clearly and I'm not invested enough in this debate to put any more time in.

He’s not strawmanning you as much as taking OAI at their word. Plausibly the majority of the work was done with a fractional amount of human oversight, and maybe he’s sort of operating on the assumption they’re running “every” open problem continuously, which is pretty sensible. If you’re a mathematician working on an open problem which other people know about (how much of actual mathematics work is this kind of workflow varies from field to field) you can be pretty certain that an AI lab is prompting at it.

Just dropping a comment here to let y'all know I'm all out of time, but yeah, I would definitely put more time into reading hundreds of pages of slop proofs if it was my field, but sorry I really have to run right now.

But you can't do it with their internal model that is the same or a successor to the one that solved the navier stokes millenium prize problem.

With 40% formalized they probably have a good idea of how many were found to have fatal issues in the formalization attempt, and they hired some mathematicians to verify some of them, especially the big headline ones.

That's not what this is about. The person I was responding to said "if a problem I was working on had an AI also working on it, I would want to know as early as possible - even with flaws or gaps". That's what I was responding to. They were basically suggesting that the amount of mathematical slop in the world should be maximized, and then it would be up to humans to choose what they would want to read. You know, a needle in a haystack type of thing, where you're maximizing the size of the haystack.

Nobody solved the navier stokes problem, Jesus. A subproblem was possibly solved (still being verified) based on context in an actual mathematician’s chats with ChatGPT. These models on their own are still incapable of producing anything but slop.

I think it's more likely the millions of dollars of compute than the model, in many cases.