Have you done any math hacking with sol/astra or fable? It’s more fun than using them for coding. The models are great at the monotony, like constructing a Gröbner-basis, etc. But they’re all still absolutely awful at coming up with new ideas, new proof methods, or new constructive forms. So you spend all your time on coming up with novel hypotheses yourself and handing off the rote work to an agent.

It’s also quite fun to get instant results by finding isomorphisms into unfamiliar areas of mathematics that previously would’ve required some networking in order to build a collaborative relationship.

But it's not "waiting on the output of an LLM for 40 hours" any more than a regular hackathon is "waiting for my damn teammates to finish their part for 40 hours". From my experience using agentic coding for hackathons, the best teams are those that coordinate with the AI agents in relatively quick cadence, generally giving it small tasks and steering it often. Teams may want to run some long-running sessions too, especially closer to the deadline, but even then, they'd probably want to run and follow several sessions in parallel, and continuously inspect their work so that they have reasonable confidence that their main efforts will wrap up before the deadline. There is an art to it.

Are you sure it’s letting it run and not going back and forth interactively?

If the goal is to accomplish something then why limit yourself with available tools?

I’m not a full on AI optimist but it is absolutely the most powerful tool in a host of applications. From a Hackathon perspective, obviously in the 90s it was much more unorganized, but the same ethos existed. Use all available tools to accomplish the goal/task, it’s where a lot of incredible learning came out of. The same will hopefully happen in scenarios like this one

Obviously the latter - this fact is betrayed by how the page lists the S^6 complex structure result, which was released as a 100 page barely readable mess (in fact even this might be too charitable), as still "unverified". Clearly a situation labs would like to avoid for future claimed results.

Probably many mathematicians want answers to the questions from the page:

> This AI advancement raises the following questions: (a) How much can AI speed up the process from ideation to peer-reviewed publication? (b) What is the role of a mathematician when AI can solve conjectures faster?

and the big AI companies agreed to sponsor them to find out because it is good publicity for the companies.

Yeah it's a bit of a tricky situation. It's almost like a bribe in a sense.