Comment by svara

1 day ago

I want to agree with this, but I have a hard time seeing how it can be done.

Tao is speaking of a very particular kind of mathematics, that done out of pure curiosity.

But maths, even at the highest levels, often finds applications sooner or later.

It will be economically impossible to justify boycotting correct mathematics that no humans understand on grounds only of purity.

This may happen very soon: one of the obvious applications of novel mathematical results is in building stronger AI models.

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svara

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traes  1 day ago

> one of the obvious applications of novel mathematical results is in building stronger AI models.

This gets repeated a lot and seems to be one of the primary stated goals of making AI solve math problems, but I still have no idea by what mechanism this is even supposed to happen. I guess they could make some minor improvements to matrix multiplication algorithms or whatever but I don't see what groundbreaking theorem could possibly significantly improve LLMs.

  • svara  1 day ago

    It's the kind of thing where it's sort of expected that you wouldn't know, right?

    I think we don't really understand why deep learning works as well as it does, the thinking around that is, as far as I can tell, mostly a collection of empirical observations.

    A fundamental theory of learning that can be used to predict optimal network architectures might enable smaller models that consume less energy.