> We are currently facing the very specific challenge of advising OpenAI on how to coordinate the release of a large number of significant results in mathematics that they report have been produced by their internal model.
The only thing I want to see is the problem statements, solutions, and associated Lean proofs. Anything else is gatekeeping. What a low point for academia.
PhD in maths here, no longer a mathematician, partly because I wanted to do stuff more connected with real life.
I actually want to see interesting theories and mathematical ideas come out of proofs more than I want solutions/proofs. After all most maths doesn't have direct practical applications. So although unsolved problems are a good barometer of 'there's still stuff left to understand here', the interesting part about solving them is less knowing what is true and more 'how does this help us understand this field better than we did before?'.
I would still like to know if the Riemann Hypothesis is true though!
Regarding that last point: You may know where you left your keys, even if you are "only", say, 99% certain where they are. Now, how strongly do mathematicians believe that the Riemann hypothesis is true? 99.9% perhaps? In some sense then, you already consider yourself less ignorant about the truth value of RH than about the location of your keys, or about many other mundane things you know without being perfectly certain about them.
A proof would then merely update you from 99.9% to ~100%, which is a smaller update than the example of checking that your keys are indeed in your pocket, where you go from 99% to ~100%.
I'm not sure how you've ended up so frustrated with an advisory group whose advice has not been given. Human mathematicians routinely delay publication of their results past the point you describe; is someone gatekeeping when they take a month to clean up their paper?
Or are you perhaps sublimating your own AI anxiety into confrontational assertions that other people who discuss AI aren't as AI-pilled as you?
You can delay your own publication as long as you wish to. Bullying somebody else to delay theirs is a different thing entirely.
OpenAI put together an advisory panel to provide guidance on how to release their results. Where do you see bullying?
I'm not sure why you see bullying here? OpenAI has always worked with expert mathematicians; their unit-distance result (https://openai.com/index/model-disproves-discrete-geometry-c...) was a much deeper collaboration. They published the Navier-Stokes result early, to either benchmark or show off their new model depending on how you look at it, and they want to understand more about the negative effects which many mathematicians feel that early publication had.
If the advisory group says something like "AI is bad and nobody should use it in math", I'm pretty confident OpenAI will ignore them.
On UDC, internally they had Alexander Wei, Hongxun Wu, Chen Lijie. TCS people. As gobetweens to Daniel Litt.
On N-S I think nobody internally felt confident enough to publicly step up. So Bubeck had to wing it.
It remains to be seen which of the big names will work with whom inside the org