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tacomonstrousyesterday at 6:10 AM5 repliesview on HN

Speaking as a mathematician, it does seem like we're a bit fucked as a community. Anything that is at all accessible to currently existing methods and mathematical infrastructure is probably going to fall to the frontier models of today, and at this rate of progress it's likely that, already by next year, we'll see new infrastructure being put into place by AI, giving us a world in which a few designated interpreters of the oracle get to 'do' mathematics, while it withers on the vine as an avenue for the exploration of human meaning.


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pfdietzyesterday at 9:35 AM

Proving theorems will have lower payoff, but posing new questions (for AI to chew on) will have higher payoff. Math will go from theorem proving to conjecture farming/exploration. In a way this could be even more fun.

Of course AI can also farm conjectures, but they have to develop taste, which might be harder than just proving theorems.

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gilgoomeshyesterday at 10:28 AM

Goldbach's Conjecture is very accessible.

muldvarpyesterday at 3:32 PM

Anybody that has to work for a living is fucked and not on the "can't do mathematics which they would find fulfilling"-level but on the "can't afford food, because human intelligence is simply not required anymore"-level.

Davidzhengyesterday at 6:53 AM

next year is a long time away friend

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QuesnayJryesterday at 6:47 AM

I think in the long run mathematicians are probably fucked, but in the short run it's not that bad. All three of the big conjectures solved the answers were at the level where if you had given a grad student the questions and the right background reading there's a good chance they would have solved it. (This example, you could have given an undergraduate good at programming and computer algebra and told them to come up with a counterexample.)

At this point the advantage of AI is that it's read the entire mathematical literature, and it doesn't have to worry about wasting its time. The solved problems have all turned out to be surprisingly easy, so the real lesson is that we're bad at judging how hard problems are.

Assuming this state of affairs lasts, the medium-term problem is that you learn something when struggling with a problem, even if you don't solve it, and if mathematicians become too reliant on AI the skills they develop through struggle will erode.

The long-term problem, of course, is that it seems much more probable that a future model will make mathematicians all obsolete. But so far Fable hasn't. (Anthropic has probably burned a billion tokens on the Riemann hypothesis already, without telling anyone.)

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