Daniel Litt
@littmath
Assistant professor (of mathematics) at the University of Toronto. "Tireless math ronin,” “forever confused.” Algebraic geometry, number theory, etc. He/him.
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In practice this means that a huge amount of duplicative labor, both in flesh and in silico, is being devoted to work whose marginal value to mathematics is, essentially, the cost of the tokens and perhaps a few bits of information indicating that the problem can be solved by existing models.
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Incidentally I am conceding this bet. Strictly speaking it hasn’t resolved (I think we’ve yet to see an Annals-quality number theory paper) but it’s clear I was wrong about what capabilities were necessary to produce one, and it’s just a matter of time.
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enjoy that sunset while you can—soon a swarm of superintelligent AI agents will be able to appreciate it more rapidly and efficiently than you ever could
