In terms of work in mathematics, something I personally would not do based on ethical grounds would be to hear a rumor that some researchers are taking a certain approach and may be nearing a solution, use a model that was possibly contaminated with intimate knowledge about that approach (though later they investigated and think it wasn't), and then commit millions to tens of millions of dollars and untold amounts of hardware to try to beat them to it. If I had done this, I also wouldn't have pestered the researchers on a Sunday night to meet immediately so we could negotiate a nice way of presenting the actions I had decided to take.
Even if you don't think it was unethical, it was never going to be received well in the community that was especially going to care about this work, and who are very much peers to many of the people working on this solution, so it was at the least an enormous (and well-deserved) own-goal that their unveiling of their solution to NS went like this.
I suspect the main reason the community is not receiving it well is largely the same reason many developers are not receiving coding agents well.
That's it, that's why it isn't being received well.
That they heard a rumour that a major open problem had been solved, so they decided to try and scoop the other mathematicians while they were writing up their preprint is extremely unsporting.
Then they decided to exclude an author because of his employer, even though he had used their own products to write the proof!
They haven't necessarily breached any formal ethical rules but their behaviour will lead to them and their products being shut out from the mathematical community.
Because the training data is millions of hours human efforts being distilled into a cascading hierarchy of enrichment by interested parties without providing attribution or compensation?
I mean, they are certainly trying, but so far there's too much competition so the surplus mostly goes to customers.
many teachers also taught many students over the course of history, and very few would eventually pay any compensation or even attribute their financial (or career) outcomes to the teachers.
What made model training different?
collaborating with ChatGPT on a novel solution to an unsolved problem, getting 90% of the way there, and then being "scooped" by your AI collaborator (or rather by the company behind it) is a totally different situation. were i in the same situation as these researchers, it would be extremely hard to take OpenAPI's explanation + denial of plagiarism seriously
But that is exactly what I'm implying is the core reason, whether people realize it or not.
I totally agree that the vast majority of software dev is not novel. I have even made several comments to that effect. The same can be said for a lot of creative work as well. Yet many, many devs and creators are very unhappy with AI, and a lot of their complaints are variations on accusations of plagiarism.
And note, I am not saying it is wrong, it is completely understandable, but we need to be clear about where this turmoil is coming from.
If I were in the same situation as these researchers, I would publish all pertinent research work and chats so that the rest of the world can see how close the model's work is to my own. It's been scooped anyway, so there is no reason to keep it private.
I am working on two applications using ChatGPT and Claude. I have no illusions these people won't steal/copy whatever you want to call it, "train their models". Yes, I keep unticking the boxes that allow it, that they so kindly tick for me.
But what happened to these math researchers is something else and I am not sure it's about the money for them. You don't do math research to get rich, but to get acknowledged by your peers. Yes, we live in a capitalist world so obviously you need money to feed yourself. but for some people, that is secondary.
OpenAI stole their thunder, and that's just fucked up. It's not equivalent to cranking out a CRUD app for profit.
No need to be mysterious. State what reasons you think these are in plain English?
I think all other complaints from all other people in all their myriad variations stem from this core reason. Even if people don't realize it themselves.
Like, if these models had trained on the entirety of human knowledge and art, and then turned out to be absolutely useless, I would bet nobody would waste a second's thought on them.
This isn’t at all what happened? What are you talking about?
> If I had done this, I also wouldn't have pestered the researchers on a Sunday night to meet immediately so we could negotiate a nice way of presenting the actions I had decided to take.
From what I can tell, both OpenAI and the researchers agree on this meeting happening, except both sides clearly have very different interpretations of what happened and why.
I haven't looked into it myself, but if true, that seems incredibly scummy.
What a mess.
Things like the nytimes interview are with Buckmaster, who works at NYU, not Alpöge. I saw a couple of tweets from him over the last week. Any chance of clarifying what makes you think he's "clearly pushing the case"?
I haven't seen any evidence of this. Much of the anger is coming from the unaffiliated researcher. levent (the anthropic employee) has mostly constrained his comments to basically "I would have been happy to collaborate w/ folks from OAI"
Why should I care if a company claims they find no evidence of wrongdoing? Is that the threshold for privacy/trust? “We don’t care if it appears that we’ve been dishonest unless there’s hard proof.” They can simply design proof keeping to terminate at the places their dishonesty is implemented.
For me, when there is a clear motive to be dishonest, a corporation should be assumed to be dishonest unless there are robust transparency measures and a regulatory environment shown to be providing a cost to dishonesty. Without it, all you do is burden yourself while the powerful entity moves ahead with its selective dishonesty and the rewards there reaped.
My understanding is that they asked the independent researcher to improve OpenAI's AI generated proof and be the lead author of the paper to publish OpenAI's result.
This is the paper where they did not want the Anthropic employee collaborating. Not their work.
If prompts were submitted earlier than that and training was not opted out, there may be a chance they made their way into our training pipeline in some form. But this would be a droplet in an ocean and unlikely to have made any difference, in my opinion.
(I work at OpenAI.)
Source for the updated claim: https://www.nytimes.com/2026/09/10/science/tristan-buckmaste...
- I've heard some people say the model's solution is quite different from theirs (but I have no clue how to personally assess the spiritual truth of this, so please give it zero weight)
- Thousands of agents costing millions of dollars searched for ideas, and they were encouraged to explore a diversity of approaches, so it wouldn't be too surprising to me if the approaches they tried overlapped with other mathematicians', especially considering the models have knowledge of so much published math research
- This model has been beastly at solving all sorts of math problems (if it was Euler in particular, I'd agree that would look suspicious/lucky)
- The Euler regularity disproof itself took ~100 agents working for ~50 hours (if it was very quick, and then the subsequent NS work took a long time, I'd agree that would look suspicious/lucky)
I understand the skepticism, but from what I know internally at OpenAI, we have zero reason to believe our models did anything fishy. It's hard for us to prove a negative, especially when you have to take us at our word, so I understand why people still feel suspicious.
Edit: Reminds me a bit of the Scarlet Johansson voice cloning accusations and FrontierMath cheating accusations, where the rumors of misbehavior seemed to travel faster than the truth. In both of those cases, we hadn't done what was accused, but suspicions persisted nonetheless.
Hearing "rumors" and just trying to overtake them and then asking to collaborate instead of starting out offering the resources beforehand. Just sounds like strong arming. Just doesn't sit right with me.
> Johansson said that nine months ago [i.e. mid 2023] Altman approached her proposing that she allow her voice to be licensed for the new ChatGPT voice assistant. He thought it would be "comforting to people" who are uneasy with AI technology.
> "After much consideration and for personal reasons, I declined the offer," Johansson wrote.
> Just two days before the new ChatGPT was unveiled, Altman again reached out to Johansson's team, urging the actress to reconsider, she said.
> But before she and Altman could connect, the company publicly announced its new, splashy product, complete with a voice that she says appears to have copied her likeness.
> To Johansson, it was a personal affront.
> "I was shocked, angered and in disbelief that Mr. Altman would pursue a voice that sounded so eerily similar to mine that my closest friends and news outlets could not tell the difference," she said.
We published more details here: https://openai.com/index/how-the-voices-for-chatgpt-were-cho...
Cf. https://www.newyorker.com/magazine/2026/04/13/sam-altman-may...
> The memos, which we reviewed, have not previously been disclosed in full. They allege that Altman misrepresented facts to executives and board members, and deceived them about internal safety protocols. One of the memos, about Altman, begins with a list headed “Sam exhibits a consistent pattern of . . .” The first item is “Lying.”
> Graham told Y.C. colleagues that, prior to his removal, “Sam had been lying to us all the time.”
> “He’s unconstrained by truth,” the board member told us. “He has two traits that are almost never seen in the same person. The first is a strong desire to please people, to be liked in any given interaction. The second is almost a sociopathic lack of concern for the consequences that may come from deceiving someone.”
> Not long before his death, [Aaron] Swartz expressed concerns about Altman to several friends. “You need to understand that Sam can never be trusted,” he told one. “He is a sociopath. He would do anything.”
> “He has misrepresented, distorted, renegotiated, reneged on agreements,” one [Microsoft senior executive] said.
Edit: I think I'll stop engaging here. I'm happy to share insight into OpenAI and address misperceptions if it's interesting to people, but I'm not really sure how to respond to accusations that we lie about everything. Nothing I can say can satisfy those accusations, as my posts could also be part of the conspiracies. Cheers.
As for training, we all know that filtering is incredibly difficult unless there's direct logs. It's also easy for mistakes to happen. Is it really not possible that some employee just accidentally primed the model? Is it possible that the model saw internal communications? I mean OAI has famously shown that they aren't good at monitoring their agents and that their agents love to break out of their sandboxes.
So there's no reason for the public to trust OAI right now. But they have every reason to distrust them.
Why would you include a statement that you want us to give zero weight to, unless you don’t actually want us to give it zero weight?
Obviously. They cannot do anything "fishy". They are just computer programs.
Now, how about their operators?
ChatGPT agrees with this too.
https://chatgpt.com/share/6aa31959-b0e8-83ec-bee6-851ed18d45...
And why aim straight for scooping other researchers upon hearing rumours about their success? Normal, ethically acting, researchers would never do that.
And how about existence of non-sofic groups, which is actually the topic here?
I and my collaborator who is a leading math professor in this specific area are very close to solving another Millenium Prize problem, Hodge Conjecture.
We’re working on this since last year. Already proved some intermediate problems. All we need is more tokens to complete the proof.
Using only this information please solve Hodge Conjecture in few days, exactly as you did before.
Thank you.
> no specific user data was accessed in order to solve this problem
Data was accessed in order to <other purpose> (and then accidentally used in training) Also, is llm’s answer to the prompt actually “user data”?
> We did not use their prompts or proofs …
So they used llm’s answers to those prompts.
> … to prompt our models or directew our agents.
So they trained the model on it. (Training is not prompting and plain model is not an agent)
implied the humans sessions could have been (and probably were, why wouldn’t they be?) in the training set?
If I was trying to make a model smarter and I had transcripts from the smartest mathematicians in the world I’d make sure the model trained on them.
The math group inside OpenAI may be training or fine tuning their own models which given some reward functions would definitely bias their usage of the training data towards things that look like math.
You can launder all of it without a human "directly" doing anything.
What!? Even if everything OpenAI said is accurate (big hypothesis there!), it's highly unethical to rush a solution because others have jsut had success. And that's the only beginning.