I love this, entirely separate from any applications or even understanding. It's incredible that we needed this trillion-dollar technology to learn about a faster way to multiply two numbers!

Math is incredibly rich, and even the simplest things have insanely complicated structure when you zoom in. However this all ends up, math is bigger than LLMs, and the people who claim it is getting "solved" and we are running out of open problems haven't stared into the abyss enough.

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E-Reverance 2 hours ago | parent [-]

But who is going to be the one solving them? Just query an LLM no?

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Kotlopou 2 hours ago | parent [-]

Sure, all of this might end up being very unpleasant, and I'm glad not to be a mathematician right now. But that's still better than a future where there aren't even any questions left that we can understand and an AI can't solve.

Also, it still seems that AI has a much different style from humans, with more brute force and using obscure literature results, and the future might still end up human/AI complementary. We aren't in an AlphaZero situation where the AI learns everything through self-play. (Yet? But we don't even seem to be moving that way much? Can anybody qualified help out?) Things are just moving really fast now and it's hard to process everything.

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ks2048 an hour ago | parent | next [-]

> with more brute force and using obscure literature results,

Is that true? Look at the average math paper on arxiv. Of course it's obscure to those not in the exact sub-field - math has become very specialized.

	▲	Kotlopou an hour ago \| parent [-]
		What I meant is e.g. the unit distance construction, which (per mathematicial comments) needed a combination of distant fields, so nobody had the necessary expertise. That's different from working within one obscure field.

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E-Reverance 29 minutes ago | parent | prev [-]

I never said its unpleasant, what I'm meant math in its current (social) form / interface is "solved"