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Comment by krupan | Hacker News Reader

The LLM did not solve it. It's not intelligent. Humans did, using a statistics-based computational tool (the LLM). We don't even know all the details of how the tool was used, we haven't been allowed to use the exact tool they used ourselves, we don't know much it really cost in dollars, energy, or time, etc. etc.

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> The LLM did not solve it. It's not intelligent. Humans did,

The humans who are using LLMs to make these groundbreaking advances pretty much unanimously disagree that they lack any intelligence.

I haven't seen any statements from them on that topic. Have they actually made some?

From the open letter signed by Terry Tao and other top mathematicians:

> These models are now operating at the level of the top human mathematicians in many parts of the subject and we must assume there is a significant chance of them developing superhuman abilities within a similarly short timeframe.

https://docs.google.com/document/u/0/d/1N6ThWhupvmH0ofSnaxqn...

Superhuman abilities are not "intelligence." 8bit microprocessors exhibit superhuman abilities in different, smaller ways.

You mean the OpenAI employees? Yeah, I don't see any conflicts of interest there

I’m sorry but you either haven’t been following recent developments or you are pretending not to know the opinions of the top mathematicians on this topic:

> These models are now operating[2] at the level of the top human mathematicians in many parts of the subject and we must assume there is a significant chance of them developing superhuman abilities within a similarly short timeframe.

https://docs.google.com/document/u/0/d/1-xOkPeHmDEdRigT2YcP2...

Instead of desperately clinging to excuses and rationalizations, why don’t you just get used to the fact that these tools are insanely useful for demanding intellectual work, and that is an opinion held by many of the smartest people alive?

I won't because it's all so opaque and proprietary and driven by an insane need for OpenAI and Anthropic to provide a return on MASSIVE investment. There is absolutely some smoke and mirrors involved. How much? We don't know. But it sure is exciting to imagine their product is now smarter than humans and they are totally benevolent corporations. I want that to be true as much as anyone, but I have lived too long on this earth to believe it wholeheartedly

That is a bad faith summary. LLM driven proofs are turning out to be hard to verify, often take invalid shortcuts, and may not actually be helpful in getting humans to understand either the proof or related context. Even if one accepts your "insanely useful" statement, which is a huge stretch, that has to be qualified with the results being insanely complicated to actually verify and use. The point of mathematics is to advance understanding, not merely generate some isolated and incoherent results.

And it may have trained on a NYU professor's work.

Why is this downvoted? Genuine question, I haven't followed up on the drama.

Because it's mostly not true. It is likely that it used the professors work, but the professor did not have a solution. It came up with new insights that solved the problem. Even the humans from the professors side said so.

> Because it's mostly not true. It is likely that it used the professors work

These two statements appear contradictory.

I simply said that it may have trained on a NYU professor's work.

Work that the professor did not believe he was releasing for model training purposes. That feels worthy of mention.

According to OpenAI the cut off date for user data was too early for that (one sided evidence, so I'll give this partial consideration).

The NYU professor was solving a different problem (no viscosity, aka the Euler equations). This is a big difference.

The NYU professors' blowup construction was fundamentally not the same, it was a donut with a cascade of smaller and smaller vortexes driven by each other. OpenAI has that picture they made but its inwards spiraling and speeding up vortex.

My overall opinion is that calling the work plagiarized is really underselling what the AI accomplished. It's like full on cope.

In particular, Buckmaster's main claim to plagiarism is this:

> “Almost nobody was seriously developing this particular constructive program for realizing C/D, and then OpenAI appeared in essentially the same general part of the landscape immediately after hearing about our progress.”

What this fails to realize, is that this only points to plagiarism if the counterparty isn't AI. They had actually launched teams on all cases in parallel.

Who was looking at a subset of the problem, far from what got published by OpenAI in the end.

Sometimes I think this amount of skepticism is not necessary. Leaving the pedantic (its not AI its humans who solved) arguments, its pretty clear that LLMs are able to help solve things. A lot of erdos problems were solved. Millenium problems as well. Cyphers broken. Skepticism is fine but there's a point at which it just looks like cope.

Edit:

> self solving AGI that will replace us all

Which lab says that it will replace us all? All labs have said that some jobs will go away and new jobs will be needed to replace them. I'll change my mind if the labs (or employees on record) have claimed that self evolving AI will replace us all completely.

If that's how it was being sold then it wouldn't be as controversial. But it's being sold both as "self solving AGI that will replace us all" and "useful tool for enhancing existing skill" when there's a lot of real evidence for the latter. But the former it's always second hand claims that don't survive contact with the real world.

It's obvious why that's the case but it's not incumbent on everyone else pump the hype if they don't see it.

How have you missed the many times that Sam Altman and Dario Amodei have said exactly that??

Have you missed their retractions of exactly those statements?

https://fortune.com/2026/05/26/sam-altman-dario-amodei-walki...

Do you understand that this is a classic manipulation tactic? Say the false/provocative/attention grabbing thing loudly then retract/explain/apologize later for it quietly.

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