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LLMs Are Currently Not Helpful at All for Math Research: Hamkins

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Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#21
post #3

> The frustration, for Hamkins, goes beyond mere incorrectness—it’s the nature of the interaction itself that proves problematic. I would assume pairing LLMs with a formal proof system would help a lot. At the very least, the system can know what is incorrect, without lengthy debates, which frustrate him most. This won't help the system discover or solve new math, but it make the experience far more endurable.

That itself may be tricky. Suppose you proof system tells that the proof is correct — how do you verify it is proof of the assertion you want, unless you have beforehand written the "test harness" by hand? At least in programming, formally checking that the code does exactly what is required is orders of magnitude harder than simply writing code that compiles.

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#22
This is quite seriously missing the point: computational theorem-provers and contributions to mathlib (for Lean, anyway) allow for checking "correctness". The LLM is one of the many ways to search for tactics that help complete a proof for a theorem not yet in mathlib.

The LLM is not done until the theorem-prover says it is done - at which point we can be sure of the correctness of the assertion in the context. AFAIK there is no debate about inaccuracy with theorem-provers. Their real limitation continues to be converging in realistic timescales and efficient search over all combinations of proof tactics.

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#23
post #20
post #13

Well folks, Tao says he finds AI useful so I guess we can flag this and other stories that say anything to the contrary, pack it up and go home.

Not only said, but demonstrated. That counts for quite a lot.

I think you are missing the sarcasm of the parent comment.

I am also fairly certain you have yet to actually watch Tao "demonstrate" his interaction with these technologies because if you had you would know in those demonstrations he formally verifies theorems that already have proofs, and even more importantly, that he had already formally verified twice before 'off camera'. Despite these two realities he still spends a lot of time correcting the LLMs or completely ignoring their suggestions while expressing a mostly polite appraisal of the tech's use and capability.

Of course the hype machine takes his politeness, which has more to do with his specific personality than anything to do with the tech, as universal endorsement for the tech and all of its externalities.

I called it when he started getting in bed with these malevolent tech companies that they were laundering their misdeeds through his reputation, and here we are.

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#24
post #8

Terry Tao has found them helpful in the past[0], and I’d trust him over Hamkins. [0] https://terrytao.wordpress.com/2025/12/08/the-story-of-erdos...

For the sake of rigor it appears he found it interesting that someone else found them helpful in the past rather than "Terry Tao[himself] has found them helpful in the past."

> This was one further addition to a recent sequence of examples where an Erdős problem had been automatically solved in one fashion or another by an AI tool.[Aristotle] Like the previous cases, the proof turned out to not be particularly novel

He concludes:

> One striking feature of this story for me is how important it was to have a diverse set of people, literature, and tools to attack this problem. To be able to state and prove the precise formula for {c(n)} required multiple observations

Which looks like he wants to focus the praise for the solution on the "diverse set of people" relegating any "praise" for LLMs to the obfuscated and ambiguous category of "tools" behind literature.

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#25
post #20

Earlier quoted context omitted.

Not only said, but demonstrated. That counts for quite a lot.

I think you are missing the sarcasm of the parent comment. I am also fairly certain you have yet to actually watch Tao "demonstrate" his interaction with these technologies because if you had you would know in those demonstrations he formally verifies theorems that already have proofs, and even more importantly, that he had already formally verified twice before 'off camera'. Despite these two realities he still spen…

Unless you claim Tao is outright lying, his statements say he's getting objective value out of AI tools. They are helping him accelerate actual math research.

Math seems like an ideal target for AI, as it provides a firm basis for identifying correctness (has something actually been proved.) I think the consequences of this are going to be enormous for mathematics, including the conversion of the entire historical math literature to formalized, checked proofs. Once that is done, once all that training data is available, the capabilities of math AIs are IMO likely to be extraordinary. Add to that the sort of Alpha Go-style self training as AI provers work on new problems.

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#26
post #22

This is quite seriously missing the point: computational theorem-provers and contributions to mathlib (for Lean, anyway) allow for checking "correctness". The LLM is one of the many ways to search for tactics that help complete a proof for a theorem not yet in mathlib. The LLM is not done until the theorem-prover says it is done - at which point we can be sure of the correctness of the assertion in the context. AFAIK…

> The LLM is not done until the theorem-prover says it is done - at which point we can be sure of the correctness of the assertion in the context. AFAIK there is no debate about inaccuracy with theorem-provers.

Your "in the context" is doing a lot of heavy lifting here, see:

- The Math Is Haunted : https://news.ycombinator.com/item?id=44739315 : https://overreacted.io/the-math-is-haunted/

- Three ways formally verified code can go wrong in practice : https://news.ycombinator.com/item?id=45555727 : https://buttondown.com/hillelwayne/archive/three-ways-formal...

- Breaking “provably correct” Leftpad : https://news.ycombinator.com/item?id=45492274 : https://lukeplant.me.uk/blog/posts/breaking-provably-correct...

- what does a lean proof prove? : https://news.ycombinator.com/item?id=46286605 : https://supaiku.com/what-does-a-lean-proof-prove

> Their real limitation continues to be converging in realistic timescales and efficient search over all combinations of proof tactics.

I agree "efficient search over all combination of proof tactics" will be a defining moment in the field. I disagree these LLMs are it.

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#27
post #25

Earlier quoted context omitted.

I think you are missing the sarcasm of the parent comment. I am also fairly certain you have yet to actually watch Tao "demonstrate" his interaction with these technologies because if you had you would know in those demonstrations he formally verifies theorems that already have proofs, and even more importantly, that he had already formally verified twice before 'off camera'. Despite these two realities he still spen…

Unless you claim Tao is outright lying, his statements say he's getting objective value out of AI tools. They are helping him accelerate actual math research. Math seems like an ideal target for AI, as it provides a firm basis for identifying correctness (has something actually been proved.) I think the consequences of this are going to be enormous for mathematics, including the conversion of the entire historical ma…

> Unless you claim Tao is outright lying, his statements say he's getting objective value out of AI tools. They are helping him accelerate actual math research.

I lack the personal relationship with Tao necessary to determine if his words are truthful or otherwise (namely for me, paid for), but you also failed to provide "his statements" that say either "he's getting objective value out of AI tools" (however one may quantify such a statement) or that "they are helping him accelerate actual math research" choosing instead to simply claim those words as Tao's own.

All of the future tense coded "I think", "going to be", "Once that is done", and "IMO likely" in your second paragraph seem to be at conflict, in the very least tensewise, with your gp comment's past tense of "Not only said, but demonstrated."

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#28
post #25

Earlier quoted context omitted.

Unless you claim Tao is outright lying, his statements say he's getting objective value out of AI tools. They are helping him accelerate actual math research. Math seems like an ideal target for AI, as it provides a firm basis for identifying correctness (has something actually been proved.) I think the consequences of this are going to be enormous for mathematics, including the conversion of the entire historical ma…

> Unless you claim Tao is outright lying, his statements say he's getting objective value out of AI tools. They are helping him accelerate actual math research. I lack the personal relationship with Tao necessary to determine if his words are truthful or otherwise (namely for me, paid for), but you also failed to provide "his statements" that say either "he's getting objective value out of AI tools" (however one may…

I think you're just engaging in passive-aggressive denial here. There's no arguing with that, so I'm going to stop. Good day!

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#29
post #28

Earlier quoted context omitted.

> Unless you claim Tao is outright lying, his statements say he's getting objective value out of AI tools. They are helping him accelerate actual math research. I lack the personal relationship with Tao necessary to determine if his words are truthful or otherwise (namely for me, paid for), but you also failed to provide "his statements" that say either "he's getting objective value out of AI tools" (however one may…

I think you're just engaging in passive-aggressive denial here. There's no arguing with that, so I'm going to stop. Good day!

Just regular ole skepticism in response to claims without substantiative evidence.

Re: LLMs Are Currently Not Helpful at All for Math Research: Hamkins

#30
post #8

Terry Tao has found them helpful in the past[0], and I’d trust him over Hamkins. [0] https://terrytao.wordpress.com/2025/12/08/the-story-of-erdos...

Isaac Newton was deep into alchemy and occult. Even very smart people suffer from confirmation bias, Dunning-Kruger effect & co.
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