This is horseshit. Mathlib3 and mathlib4 all existed prior to LLMs. Unimath of Agda, mathematical components of Rocq, the list goes on.

LLMs have done nothing for "making large scale mechanization viable." They have been viable. The only thing has changed is the perception of the random developer who never wanted to put the effort into learning what actually needed to be learned and are instead happy to spit our complete garbage, spec and all, and say it's a proof of something.

It's not shocking at all that the people who seem to get any benefit out of LLMs in the proof assistant space are the ones who could have just don't it themselves anyway.

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quasisphere an hour ago | parent [-]

I actually noticed after I posted that I should have said 'by individuals at pace not too different from writing down a standard prose proof' or something similar to address this point. Mathlib for instance is of course a phenomenal project, but it was written by a large amount of people over many years. Granted their goal was not so much speed as it was elegance, but by 'viable' I had in mind something that a research mathematician could actually use in real time along actual math research. The content in Mathlib still falls very much short of being enough for formalizing much of the actual research being done in mathematics, but people are now autoformalizing non-trivial extensions on top of that, both individually and collaboratively (such as the recent Tau Ceti project).

Anyway, what do you mean by 'say it's a proof of something'? If you mean this in technical sense, there are plenty of examples around where single individuals or small teams have autoformalized theorems with tens or hundreds of thousands of lines Lean code that pass a comparator challenge (so the theorem is correct). If you mean this in the sense that the proof is also a proof in the eyes of humans, so that someone has actually read or understood the proof, I'm willing to acknowledge that in this area there is much work still to do. In my own experience the current LLMs are already very strong at formally proving theorems (with correct semantics), but they are still lacking in writing human-readable math prose based on these formalizations, for instance.

	▲	wizzwizz4 20 minutes ago \| parent [-]
		> The content in Mathlib still falls very much short of being enough for formalizing much of the actual research being done in mathematics, but people are now autoformalizing non-trivial extensions on top of that, Formalising non-trivial extensions on top of the standard library is not hard. I could bash out an average textbook formalisation at about half reading speed. The hard part is making something elegant and general, which: and that's something that LLMs don't seem able to do.¹ (If you're lucky, the textbook you're working from has already distilled the best abstractions, and there's very little work left to do to make it good enough for a library: but such textbooks do not exist in research mathematics.) > Granted their goal was not so much speed as it was elegance, Do not underestimate the necessity of mathematical elegance. Mathematical notation is a tool powerful enough to teach machines to think: it is essential to make these tools elegant, or you will not be able to communicate your insight to your colleagues, and certainly not the next generation. Treating the goal of mathematics as "prove the most theorems as fast as possible" is hacking off the lower branches we should be using to climb trees, simply to harvest their fruit. ¹: Anyone familiar with my HN comment history will know that I keep banging on about "cannot in principle" and "there are deep theoretical reasons that an LLM can never". I'm not doing that here: I don't know a reason that LLMs can't produce elegant mathematical abstractions – probably because I don't understand mathematics deeply enough: "LLMs can't do this" is purely an empirical observation. (Believe me, I've read a lot of LLM-generated formal mathematics: it is invariably garbage. I just don't know why.)