Researchers normally don't pay each other to read each other's work. It's a symbiotic relationship. If they think the AI results are nonsense, they could ignore it like any other crank. If they think it seems plausible and it's relevant to them, they can try to understand it. Seems fine?
Why's that? Do you think that institutions and funding agencies won't cover researchers' use of advanced models, or what? The group I worked in in undergrad had millions of dollars of equipment for doing experiments. I'd have to imagine they could get funding for a few thousand dollars in tokens for the theoreticians to have AI assistance.
Okay? Again, when I was in my group, money would flow to Nvidia to buy GPUs that we would use to run simulations (in addition to the experimental devices I mentioned). The researchers could also request money to use for openrouter or build their own GPU cluster if everyone thinks it's good use of funds.
Shouldn't we pay for the best tools if it helps researchers to be more effective?
The symbiosis here isn't I'll read your paper and you read mine. It's I'll publish my results and you publish yours. Groups share results and cross-pollinate ideas. If people don't want to read OpenAI's papers, no one's going to make them. If no one's interested in the ideas that OpenAI is coming up with, everyone can just ignore them.
The problem people are having is they clearly are interested. They think the ideas are good. In fact, too good. If they thought otherwise, they would just say it's all slop, no one cares, business as usual. And you can tell that there's this phase change in their behavior because previously you could ask chatgpt about math and it would just give you word salad and everyone knew that. Now we can all see that it's not just word salad and people are scrambling to figure out what to make of that. Obviously an accurate answer oracle is still strictly useful even if it makes no attempt to tell you why (you can even use it only to help prove your boring technical lemmas when you have ideas!), so obviously this is an emotional reaction, not a rational one.
yes, but in this case, openai does a lot of PR how their models solve important math problems. if it goes unchallenged, parts of society would think that is true. what would happen if we scale it and 10k companies dump 10k papers every month claiming solved math problems. how is this scalable?
We need the companies to humanly review their papers. in the same way as at other companies we use humans to review the papers.
Well, per another comment in the thread, some 20% of their solutions come with formalization, so there's a very high chance (probably higher than typical asks of research mathematics) that they did solve the problem. And that also presents a pretty easy solution to the scaling issue: demand formal proofs.
(If you're going to object that it's difficult to validate the statement of the problem, please first state your level of experience doing so. It's getting tiring seeing people raise this objection and claim that a statement is just as hard as a proof over and over who don't seem to actually know any math and have never tried to write anything in Lean)
