The point is that so far the AI is not doing a good job at explaining the "trick", so we (humans) have to do it. And the way these results are published at the moment (that is, dumping a load of proofs with badly written explanations) is not cooperative to enable this distillation (for example, presenting results at conferences and engaging with mathematicians). I recall Tao working through the disproof of the Jacobian conjecture, stating some steps as "miracles" for lack of better terms. If a human solves a problem in an unexpected way, at least there is some reason why they chose this path, which can help in understanding. This is not available to the same extent with AI generated proofs.

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zozbot234 an hour ago | parent [-]

> The point is that so far the AI is not doing a good job at explaining the "trick", so we (humans) have to do it.

Sure, but that's a real technical limitation with current AIs, not something that AI firms should be blamed for. And if anything, this creates a viable career path for the mathematicians who were "scooped" wrt. the original solution: they can at least puzzle out what exactly the AI managed to do. Many practitioners are actually quite excited by this possibility; Tao's stance is by no means universally shared.

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tim-kt 38 minutes ago | parent [-]

I'm about to start a PhD in mathematics. The idea of puzzling out what an AI did to prove something sounds quite boring and unappealing. But yes, maybe it's a viable career path.

I'm just not happy with the presentation of OpenAIs result. Maybe they could have gotten into contact with the people of the research areas of the problems that they solved and worked with them to create a better exposition. Sure, it's a slow process and requires lots of staff. But I believe that they can afford it.

	▲	zozbot234 16 minutes ago \| parent [-]
		> The idea of puzzling out what an AI did to prove something sounds quite boring and unappealing. The way I see it, it's no different from a lot of grad student work where you have to figure out what a human-written proof is doing. > Maybe they could have gotten into contact with the people of the research areas of the problems that they solved and worked with them to create a better exposition. That's what Anthropic is doing, and the issue is that people will complain that they weren't the chosen "person to work with". OpenAI's approach is more like a race where everyone's at the same starting point: they get the AI's raw proof to work on and have to figure out how it works.