- This, from Tristan Buckmaster's writeup yesterday, indicates to me that there was more than incidental inspiration from Alpoge and Buckmaster.
- This, from Tristan Buckmaster's writeup yesterday, indicates to me that there was more than incidental inspiration from Alpoge and Buckmaster.
- "very little human" input feels ambiguous, and if someone spends a few days prompting a model to solve a super hairy problem requiring a 100-page proof, I can understand reasonable people interpreting that as both "very little" and "not very little" human input
- it's all true that a team worked on this, a bunch of compute was burned, and the problem was solved in stages and pieces
I'm not sure how any of this provides evidence that OpenAI took any of their work.
As evidence against, we never looked at any of their ChatGPT conversations and our model's proof is quite different from theirs.
(I work at OpenAI, but not on the team that did this proof.)
It's unknowable and not possible to prove if any one specific conversation was the key to solving Navier–Stokes.
If the conversation was in the training set, there's a high likelihood that the small set of conversations related to solving Navier-Stokes was used by the model. I get Astra to still quote some of my friends' books or blogposts nearly verbatim on certain niche issues.
Much more importantly, we _can_ determine whether a conversation was used in the training data. And if it was, it gives us a great idea whether that logic was captured in reasoning for a novel problem never yet solved.
Given that you don't see any of this as below the belt according to your other comments, maybe your contribution here is more for yourself than a fair conversation about attribution.
You might retort that ChatGPT used the training data to copy their approach, but the approach Buckmaster and Alpöge chose was already published by Luis and Diego in 2023 and in every frontier model's training set.
If I were at OpenAI, I'd naturally want to snipe that from them. I am completely unsurprised they formed a crack team to steal Anthropic's glory, and do so in just five days.
All this to say, trust is important, and grounded in social convention. So I do agree with you, but also disagree.
Whenever this is OK or not really depends on how the breakthrough is contextualized, and how there people at play, here, agree to contextualize it.
In my view, in the blog post, there is much discussion about who will be publishing the paper. If instead it was just a blog post that said "oops, we beat you to it, our model is the best", it would have been different.
However the way you are conducting yourself in public, while announcing yourself as an OpenAI employee is doing enormous harm to the greater and magnanimous aim of your organisation. Take a step back and read the temperature of the room. Being the smartest guy in the room will never protect you from alienating the rest of the room into a baying mob. Right now you are Icarus flying straight into the sun.
FWIW, publicly facing OAI docs are very unclear about whether this setting even applies to Codex conversations.
it is exceptionally unlikely that anything they ever did made it into any part of training, and the chances are zero if they have opted out (likely). it would be a terrible precedent to break the the PII-scrubbing boundary to go and round it down to 0, and we won’t do it
We have lots of examples now of their model doing what they say is impossible.
Now we have another example of something that they say is impossible or very unlikely. Do we take their word for it this time? Really?
Many upstart Chinese labs got around the user data issue by just buying copious amounts of Claude and ChatGPT session logs from model routers.
I don't really understand how the quantity of training data/rollouts used in training is relevant to the question of whether or not it was trained on these conversations.
I also don't really believe that whether or not this model was trained on these conversations is unknowable information.
How many of those trillion conversations were about Navier-Stokes you reckon?
A model being trained on lots of irrelevant information does not mean relevant information was not used.
If prompts were submitted earlier than that and training was not opted out, there's 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, imo.
See: https://www.nytimes.com/2026/09/10/science/tristan-buckmaste...
I'm not coming from a place of distrust here. This should just be definitively answerable given the weight of the claims here. Surely between you, your lawyers, and other members of your team you can just clear this part up.
Sorry, but the burden of proof lies in the other direction: OpenAI needs to definitively prove that their agents did not look at the existing work that was about to be published. Otherwise OpenAI simply stole the glory and the spotlight (and I'm being charitable here).
In other words, yes, they had been using ChatGPT, and yes, ChatGPT could very well have trained on their data. Now that there is evidence, we need an investigation: yes or no, was it the case?
If there's more to the story I'd be interested to hear it.
You don't just get to subpoena your neighbor's bank account because "I know he's stealing from me" you need to first present credible evidence that you were stolen from and that he is among the most likely culprits.
Any other argument, fc417fc802?
See Russell's teapot for an explanation https://en.wikipedia.org/wiki/Russell%27s_teapot
This is incorrect, and you invoke Russell's teapot incorrectly too.
It would only apply if the accusation rested solely on the fact that neither of us have evidence against the accusation.
But that's not the case. First, we know that there could be proof, it's just apparently burdensome and expensive to produce. At that point you're not in fallacy land anymore, you just need a way to balance the cost required of someone to prove the accusations against them false.
Second, we have an arguably plausible mechanism of action that OpenAI does not dispute is possible.
This isn't a legal dispute, so no one is going to force OpenAI to do anything here, but it's not unreasonable (and certainly not fallacious) to suggest that Buckmaster's suggestions are plausible enough it's up to OpenAI to stand behind their denial.
First, the conversations are anonymized, so there's no simple way to inspect the training dataset and identify which specific conversations belong to Buckmaster.
Second, OpenAI uses these anonymized chats to generate synthetic training data, i.e. they fabricate new conversations based on specific conversation patterns where the model performs poorly, and uses these synthetic conversations as training data for future models. The synthetic data could potentially contain some of selections of Buckmaster's original chats, but it is unknowable how his specific writing could have influenced these synthetic data sets or what portion belongs to him. This information is untraceable and effectively double anonymized.
Third, OpenAI explicitly uses user feedback (the thumbs up or thumbs down ratings), as RLHF to train models. However, this feedback is anonymized and stripped of user identifiers. It's not possible to trace a specific feedback to Buckmaster, nor do we know if Buckmaster ever used this feature. I doubt Buckmaster recalls or can provide a list of every time he used this feature over the past year. OpenAI doesn't have one.
Note that the first and second only happen if Buckmaster "Improve the model for everyone" setting enabled, which I find unlikely. But that doesn't exclude option three from this list.
You seem to think that it is some "gotcha" that OpenAI refuses to make a blanket denial, but they cannot do so in good faith, because they have a genuine understanding of their own system. They don't know where the data they have came from.
This situation meets the requirement of Russell's teapot, since neither party has enough evidence to prove nor disprove what information is actually in OpenAI's training set.
Tristan + Levent: 3D incompressible Euler with forcing
OpenAI: 3D incompressible Euler without forcing
OpenAI: Navier-Stokes with forcing
No one: Navier-Stokes without forcing
Euler equations = Navier-Stokes without viscosity. Forcing means external force. Absence of viscosity and presence of external force make blowup easier to construct.Tristan+Levent ticked the weakest case, OpenAI ticked the two next weakest, then the final case is unsolved. Only the last two are eligible for the Millennium Prize. The Navier-Stokes general case remains unsolved.
Tristan and Levent only solved the easiest version of the problem and did not have the key insights to solve the harder versions of the problem required for the Millennium Prize.
The researchers didn't even solve the same problem as OpenAI, so your argument doesn't hold up.
But at that point you've circled back around to my original objection. That reasoning isn't limited to user data but applies to literally all the training data which at this point (AFAIK) covers the vast majority of everything ever written.
If we accept that position then what do we make of all the other output? Isn't everything it spits out plagiarized? So then is everyone who uses a frontier model to help them in their research effectively laundering plagiarized work? But then the other researchers involved in this controversy were also using the openai model ...
Let's check if an OpenAI employee agrees with you: https://news.ycombinator.com/item?id=49614154
Nope. Expensive, yes, impossible, no.
Moreover, you (and Sanders) aren't asking the more fundamental questions (and getting sloppy with your assumptions). - was Buckmaster's account set to prevent conversations from being trained on? This is easily answerable - Was user feedback ever activated on the account? I would bet this is logged, even if not tied to specific data - it's very easy to de-anonymize data in practice. In this case, there will be uncommon phrases used in material not published online until after the training material of their internal model was generated. Do any of these phrases appear in that material?
This is not sharing medical information. Companies publish postmortems relating to specific customers all the time with permission of those customers.
> You seem to think that it is some "gotcha" that OpenAI refuses to make a blanket denial
You're putting incorrect words into my mouth.
What I think is that this whole situation speaks to the character of OpenAI as a participant in the mathematics community, especially when they put no effort into getting to the bottom of this, and, of course, when the extent of them reaching out and collaborating with their peers involves rushed Sunday night video calls and apparent pressure on authorship and credit.
That's their choice, there doesn't appear to be anything illegal here, but they're going to continue to get called out on this kind of nonsense which can ruin the big moment they were clearly hoping to have. Bummer, but there are consequences.
The comment by tedsanders you linked directly contradicts your claim. From your linked comment:
There's no reason to believe that anything they did in ChatGPT led to our solution; it's just impossible for us to truly prove it.
He clearly says it's impossible for OpenAI to prove it.If it was enabled, then their work was included in the training dataset.
At least, as an ignorant outsider, that's how it seems to me.
Only the CIA knows whether or not they're actively covering up reptilian space aliens exerting control over the US government. Therefore the burden of proof remains on the CIA to prove that they are not actively participating in such a scheme.
I didn't realize you had insider knowledge about their systems. Do please explain for the class.
As I understand it they will only have trained on his data if he consented to it. Do you have evidence that they do otherwise?
https://en.wikipedia.org/wiki/Burden_of_proof_(philosophy)#P...
I don’t think they’re too concerned about appeasing you, enraged_camel.
For most reasonable people, achievement in solving the other Millenium Prize problems at an unprecedented rate will be enough. At some point people will see models are capable of solving hard issues without whatever 0.00001% of the training data coming from irate individuals who believe their sample was the key component of the solution.