r/MachineLearning • u/Shizuka_Kuze Student • Sep 08 '26
News OpenAl Says It Has Cracked One of Math's “Millennium Problems” (Navier-Stokes) [N]
As reported by the New York Times:
OpenAI’s announcement:
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u/dksprocket Sep 08 '26
This is something I am really curious about: is OpenAI (and other AI providers) training their models on theirs users private and potentially unpublished work?
I am working on image generation using procedural algorithns in a somewhat novel way. I have been using ChatGPT for development. It's fairly low stakes, but the images look very different than pretty everything else. I tried getting a friend to see if he could get ChatGPT to guess how the image was produced and we did the same test with Claude as well.
ChatGPT knew pretty accurately how it was made. Claude had no clue. It's not a smoking gun, but pretty worrying if your private stuff is being made public through training before you get a chance to release it.
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u/dramatic_typing_____ Sep 08 '26 edited Sep 09 '26
I've had this same experience with something 'novel' I did for rendering to a depth buffer with 3DGS scenes.
I HIGHLY suspect OpenAI does something shady such as creating derived data from your conversations and using it for training; that way they can still claim they don't directly use your data.
EDIT: Someone with access to a lawyer, please check me on this-
https://openai.com/policies/row-privacy-policy/1. The Opt-Out is Specifically for Model Training The privacy settings allow you to opt out of having your content (like your ChatGPT conversations) used to "train the models." The policy states:
"As noted above, we may use Content you provide us to improve our Services, for example to train the models that power ChatGPT. Read our instructions on how you can opt out of our use of your Content to train our models."
2. Aggregated and De-Identified Data is Still Created and Used Even if you opt out of model training, OpenAI reserves the right to create derived, anonymized data from your personal data (which includes your User Content and conversations). The policy clearly states:
"We also aggregate or de-identify Personal Data so that it no longer identifies you and use this information for the purposes described above, such as to analyze the way our Services are being used, to improve and add features to them, and to conduct research."
Because this data is stripped of personally identifiable information (de-identified), OpenAI treats it as derived data and can use it to research how people use the tool and to develop new features, regardless of your model-training opt-out status.
3. "De-identified" removes who you are, not what you said When OpenAI (or almost any tech company) de-identifies data, they strip away Personally Identifiable Information (PII) like your name, account details, email, and IP address. However, the actual text of your prompt - the sentences describing your novel idea, business plan, or code - is the core data being processed. The de-identification process disconnects the idea from your identity, but the text containing the idea itself remains in their system logs.
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u/corruptbytes Sep 08 '26
if you’re not paying API rates with ZDR add-on, don’t assume anything is safe
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u/TrueDuality Sep 08 '26
There are indications elsewhere in this thread that even with ZDR, derived data may still be getting used. My company has triggered a full contract review as a result of these random Reddit comments.
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u/Alwaysragestillplay Sep 09 '26
Can you point to the evidence for this please? My company is also leaning pretty heavily on ZDR.
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u/zephyr707 Sep 09 '26
i saw this, too, but can’t find in the thread search anymore, but there are so many threads on this event could have been in another thread. if you have links to comments abt ZDR not being what sold as what it sounds like, e.g. derived data mining still applies to ZDR, please share.
did openai think this would be a win for them? seems like a lot of users of their products will now be more aware of how vulnerable their data is if not already aware. if ZDR gets called into question that must be bad for potential enterprise customers and another firm could capitalize and offer better guarantees
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u/1998marcom Sep 09 '26
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u/zephyr707 Sep 10 '26
thank you! the post was clipped when searching for “zdr”
re: “ rewritten data is fair game”
if i’m understanding this correctly is it openAI’s policy/agreement that ZDR protects your input data/query, but the response from its models is fair game for derivative mining?
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u/j0j0n4th4n Sep 08 '26
Obviously yes, how is that even a question? Their whole business started from stealing copyrighted data from everyone, what makes you think they stopped just cause you checked a box on their site?
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u/flowithego Sep 09 '26
It is mind blowing to me that people do not assume OpenAI (with the best AI legal team) will fight all these cases for decades to come and not fuck them over for their data.
Even wallstreetbets is not this highly regarded.
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u/techlos Sep 09 '26
if the model isn't local, the chat history isn't either. Always assume any model inputs are used as training data.
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u/cpt_ppppp Sep 08 '26
have you toggled the "don't use my conversations for training"? That's maybe a good place to start
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u/oceanbreakersftw Sep 09 '26
Whoa, that's scary. I was thinking about potential other frontier providers to use if Anthropic does a rug-pull on pricing but this would definitely keep me off OpenAI. I already am a bit worried about my own work being done using Claude, but this is just way worse.
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u/sciphilliac Sep 10 '26
Maybe I'm misreading the chatGPT TOS, but they are clear to collect the data you put in your prompts. From https://openai.com/policies/privacy-policy/:
> User Content: We collect Personal Data that you provide in the input to our Services (“Content”), including your prompts and other content you upload, such as files(opens in a new window), images(opens in a new window), audio and video(opens in a new window), and data from connected services(opens in a new window), depending on the features you use. Some of our Services allow you to interact with other users, such as post, comment, or send messages, and we treat those interactions as Content, too.
So yes, if you use ChatGPT for personal use, OpenAI keeps that data (mind you, I'm only referring to non-corporate licenses)
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u/Shizuka_Kuze Student Sep 08 '26
There is howeverpossibility that OpenAI used some unpublished work from other researchers, even though they have claimed otherwise in the announcement:
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u/funky-chipmunk Sep 08 '26
They haven't - The core breakthrough leaked 100% - They are outright using evasive language:
https://openai.com/index/navier-stokes-solution/
> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.56
u/funky-chipmunk Sep 08 '26
From OpenAI CRO: https://x.com/markchen90/status/2097400166554993041?s=20
> Two things to distinguish:
> Did any human or agent look at user data as part of the Navier Stokes effort? No.
> Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes. And so does every LLM company.
Basically confirms contamination IMHO. But the bigger news is training data/privacy.
https://x.com/aidangomez/status/2097381789039837637
> Synthetic data derived from production user data of consumer AI tools is used for training. I’ve heard this rumour from both large labs’ employees.
> In particular, if you’re doing something “interesting” like working on complex math/business/software/bio problems you’re dramatically more likely to get trained on because they filter/up-weight towards those usecases where the model has the most to learn.
> Even in ZDR and “we won’t train on you” regimes, derivative data is usually carved out. The promise is only not to train on exactly the data you put in, rewritten data is fair game.
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u/funky-chipmunk Sep 08 '26
To truly prove some incidental usage data made no difference we'd have to (a) identify any of their de-identified data that came from their usage of ChatGPT, (b) train a bunch of expensive giant models, and (c) ask them all to solve the Navier-Stokes Millenium problem until hitting some level of statistical significance. It's just not feasible to run experiments like this to prove whether a piece of data has an effect on model behavior.
As a parallel example, can we prove the phase of the moon had no impact on the NS solution? No, not without a bunch experiments run at different phases of the moon.
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. And knowing most of the recipes we use, there's really no reason to think such contamination is possible. I've asked the team to make a clearer, less-lawyerly statement here - let's see what happens.
My opinion: I think they are being needlessly obtuse and evading more. My guess is they shouldn't have to train models to check for contamination - just clarify what they were fed.
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u/PM_ME_YOUR_PROFANITY Sep 08 '26
I agree with you.
Why would it be impossible to prove it? Their conversation data is either in the training set or it's not. The model solution tokens can be gone through as well to see what it accessed and how it came at its solution
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u/muntoo Researcher Sep 09 '26 edited Sep 09 '26
... can we prove the phase of the moon had no impact on the NS solution?
Experimental particle physicists cannot "prove" with 100% certainty that the discovery of the NS solution in 2026 had no impact CERN's discovery in 2012.
Nothing can be proven.
But, with some agreed upon prior model about how reality tends to work, scientists can come to a reasonable consensus that what I had for lunch today had no effect on the NS solution yesterday, which in turn had no effect on CERN's discovery in 2012.
it's just impossible for us to truly prove it.
Sure. But there is still evidence one can present. Preferably evidence that is statistically meaningful. Unless the solution to NS was once-in-a-lifetime fluke, which cannot be replicated with any significant probability, which would raise questions about the generalizability of LLMs being able to solve other problems in mathematics. (Which I don't believe is the case.)
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u/Shizuka_Kuze Student Sep 08 '26 edited Sep 08 '26
You took the one sentence that sounds like they admitted they were wrong out of context. While I’m personally inclined to believe OpenAI stole the result, they certainly have not revoked their claim of original discovery, pretending otherwise only minimizes their attempts at stealing the spotlight.
> We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem.
> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.
> However, our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs unforced).
They even have an entire section titled “How we found the proof,” so I believe it’s fair to say they have not yet revoked their claim of original discovery, even though it’s dubious at best.
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u/purplebrown_updown Sep 08 '26
The fact that OpenAI tried to offer shared ownership, but wanted to leave out Levent because he worked at Anthropic, reveals the whole game. They knew they stole the work, offered a compromise, threatened Brubeck - not something an ethical person would do.
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u/funky-chipmunk Sep 08 '26
My point stands above yours - They would have outright been screaming at top of their lungs if there was no leakage.
Edit: They should use Astra to audit - It shouldn't be that hard.
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u/Shizuka_Kuze Student Sep 08 '26
Actually, our points are orthogonal. I’m not denying leakage, in-fact I think it’s likely! I’m denying the fact they’ve revoked their claim, which is simply untrue.
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u/elsjpq Sep 09 '26
I feel like this should be possible for OpenAI to test: take an older model with only data acquired before Tristan & Levent started working on it. Then try to solve Navier Stokes again with the old model. If it can't be solved with the old model, then OpenAI's result depended on Tristan's result.
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u/MuonManLaserJab Sep 09 '26
That assumes incorrectly that Tristan's result is the only difference between the model they used and the previous one.
There were probably many small algorithmic differences, maybe some big ones, and of course different random starting weights resulting in entirely different final weights.
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u/G_fucking_G Sep 10 '26
OpenAI has now completely dismissed the claims (NYTimes):
The Wednesday evening statement from OpenAI was more emphatic: “We can say categorically that it is impossible for Dr. Buckmaster’s Codex prompts over the last two months to have influenced the system in any way, including training.” The statement added, “After investigating, we can say with full confidence that no user inputs past July 3rd could have influenced this system in any way.”
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u/purplebrown_updown Sep 08 '26
this fits their pattern of lying and cheating. Be very cautious about using OpenAI models.
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u/srpulga Sep 08 '26
To clarify, no "solution" to the equations has been found. The millenium problem is to prove or disprove the existence of smooth solutions. Open AI has found a counter example of initial conditions that don't have a smooth solution, i.e. they have disproven the existence problem.
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u/moschles Sep 09 '26 edited Sep 09 '26
Correct. What had occurred over the course of several weeks (days?) is that Terry Tao said that there was nothing stopping the Euler trick from being extended all the way to Navier-Stokes. OpenAI simply had 10,000 agents fill in that extension and bridge the gap.
It is important to note here that the human mathematicians working in this space were already copiously utilizing AI-assisted technologies and AI proof systems -- including in particular NYU's Tristan Buckmaster.
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u/FernandoMM1220 Sep 08 '26
so what happens after this if the proof is good?
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u/Shizuka_Kuze Student Sep 08 '26
Some people scream AGI, others dismiss it, life goes on.
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u/Dapper_Engineer Sep 08 '26
Agreed, although it might depend a lot on if it can be demonstrated that there was unpublished work in the training corpus since that would suggest that this was just a very expensive search and someone else should get author / co-author credit.
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u/Shizuka_Kuze Student Sep 08 '26
Im still combing through it myself, but I’d suggest reading the mathematician controversy breakdown shared by Andrew Akbashev
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u/m_reigl Sep 08 '26
Certain weird cases in fluid mechanics become solvable which probably would make engineers happy in a couple years.
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u/srpulga Sep 08 '26
This is not what happened. No analytical solution has been found to the equations. The solution found is for the millenium problem which is to either prove a smooth solution always exists, or to provide a counter example disproving it. Open AI has provided the counter example: there are initial smooth conditions that can be proven to not have smooth solutions.
This doesn't make any fluid dynamics problem more solvable.
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u/_RADIANTSUN_ Sep 09 '26
Soooo... We won't be having cool volumetric fluid hypercomputers ever? :(
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u/muntoo Researcher Sep 09 '26
The guaranteed existence of that has not yet been proven nor has a counterexample been provided. :)
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u/altmly Sep 08 '26
Please don't mislead people. This theoretical result wouldn't change anything in practice.
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u/Kinexity Sep 08 '26
Those are theoretical problems. They do not change anything for fluid system engineering.
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u/m_reigl Sep 08 '26
Not on their own, definitely. But theoretical breakthroughs usually lead to practical advantages a couple of years down the line, don't they?
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u/Kinexity Sep 08 '26
"usually" being a load bearing word here. Fluid dynamics is computationally modelled. Analytical breakthroughs are of no importance to that as long as the equations themselves do not change. NS smoothness is only a problem in non-physical situations.
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u/FollowingHumble8983 Sep 08 '26
No there is no practical advantages.
Navier stokes dont apply to real life liquids at scales which blowups can occur.
As real life liquids are made of atoms. This in a way, requires infinitely many infinitely small atoms, which does not exist.
This is purely for the sake of better understanding of numeric techniques.
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u/moschles Sep 09 '26
People who work in physics and the theoretical side of mechanical engineering know this is huge. The question is to what extent these idealized mathematical models to fluids stop extending to the real world. It is -- of course -- physically impossible for a fluid to have an infinite velocity. Navier-Stokes is a question about whether under well-behaved conditions the equations will spit infinities at you. It turns out they do.
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u/techlos Sep 09 '26
the practicality is limited to situations where you're working with a fully continuous liquid, and as far as i know the liquids we work with tend to be made of discrete particles.
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u/softDisk-60 Sep 09 '26
Proofs in the perfect , closed world of mathematics are great, but the real impact will come from solving Biology.
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u/brokebeany Sep 09 '26
Not much will change except for certain edge cases. Other models like General Relativity admits singularity as r goes to 0 but doesn't make it a bad model for predicting celestial bodies.
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u/TheDuhhh Sep 08 '26
Ok it seems this is what happened. Tristan and Levent (anthropic employee) solved the Euler problem which makes it easy to solve the NS problem. Before Tristan and Levent publish their euler and NS work, rumors spread that Anthropic solved the problem.
OpenAI heard the rumors and got scared that they were beaten by anthropic, so they assembled a team and put their strongest model with most comoute and possibly training on the most recent deidentified user data. OpenAI model then came up with a solution and the solution costed 20-30 millions.
What really worries me is how much did their model depend on the users data. As we all know, LLMs are insane in compressing data. It's really possible that their model attempted many attempts and one attempt was inspired by Tristan's work which he used chatgpt.
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u/Kolgu2 Sep 08 '26
"To solve the Navier–Stokes problem, we used an internal model that is significantly more capable than GPT‑6 Astra. We believe it is important to inform the world about the pace of AI progress and what to expect from upcoming models." They are really insufferable
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u/floriv1999 Sep 08 '26
I would be too if I solved that problem lol
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u/thetdotbearr Sep 08 '26
I would be too if I
solved that problem lolstole someone else's breakthrough work, iterated on it and took full credit→ More replies (8)7
u/reefine Sep 08 '26
I just wanted to acquaint everyone of the water that might accumulate in their partner's nether regions when they realize the pace of progress of my internally very large model.
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u/SteppenAxolotl Sep 08 '26
the group that produced the Navier–Stokes resolution involved on the order of 10,000 concurrent agents
Would you feel better if they said they used a weaker model and just 1 concurrent agent?
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u/Kolgu2 Sep 08 '26
No it's just the "you won't believe what we have in store for you, our next model is ten times more ground breaking than the current one be ready to pay" tone in what should be a sort of "scientific" announcement
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u/SteppenAxolotl Sep 08 '26
our next model is ten times more ground breaking
A few more of those and everyone should be less impressed and become more afraid.
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u/Familiar_Text_6913 Sep 08 '26
I remember when this sub was pissed about their "test time compute" graphs when they didnt have units on them.
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u/redd-zeppelin Sep 08 '26
Shouldn't they have had units on them? I thought our conclusion was that that was dumb of them. It sounds like you concluded we were dumb for liking well made graphs.
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u/CommunismDoesntWork Sep 08 '26
No need to be so jaded. What even makes that statement insufferable?
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Sep 08 '26
[deleted]
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u/persedes Sep 08 '26
Them not confirming if they're user sessions might've "leaked" into the training data is gross
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Sep 08 '26 edited Sep 09 '26
[deleted]
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u/persedes Sep 08 '26
Oh I agree, but it's very bad PR to make such an announcement that essentially stole someone else's work and undermines the achievement that the model supposedly made.
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u/PM_ME_YOUR_PROFANITY Sep 08 '26
They have a toggle not to train on your exact data. But a little fudge of your data would be just fine. Just need to identify if it's interesting enough to train the model on it.
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u/PM_ME_UR_FAV_THINGS Sep 08 '26 edited Sep 08 '26
The software toggle button is sacred. If you toggle on “Do not show me this again” you will never see that window again, verily.
Edit to reply to post above me’s edit: you don’t need to train a model from scratch to make use of new training data, there is online machine learning or knowledge base building that could make use of it instantly.
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u/partnerinthecrime Sep 09 '26
edit edit read the supposed logs on bsky and it appears they 100% just read from this individual to finish solving it
Are you talking about the parody image??
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u/G_fucking_G Sep 10 '26
They have now confirmed that nothing leaked
The Wednesday evening statement from OpenAI was more emphatic: “We can say categorically that it is impossible for Dr. Buckmaster’s Codex prompts over the last two months to have influenced the system in any way, including training.” The statement added, “After investigating, we can say with full confidence that no user inputs past July 3rd could have influenced this system in any way.”
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u/persedes Sep 11 '26
Thanks, I've been looking for more news on this and only saw the Altman post on Twitter which was still kind of vague. That clears that up and takes off a good amount of sleaze. Doubt it'll help the fallout though combined with the "I don't have to be nice" comments.
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u/florinandrei Sep 09 '26
Toast as in morally bankrupt?
But that's in their DNA. Don't you know who's boss over there?
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u/Revrak Sep 09 '26
wow, this happened a lot sooner than I expected but at least it’ll serve us a warning. Don’t share your novel ideas with an AI because you’re giving away your work for free.
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u/CyberDainz Sep 11 '26
But if we consider that we are striving for a future where everything will be free thanks to AI, then there is no reason to hide one's work from those companies that will bring this future closer faster.
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u/purplebrown_updown Sep 08 '26
They stole previous work and then built a solution on top of that. It might have proved the result, but this was so beyond unethical. This should be denounced wholeheartedly. Good news is that they wouldn't have been able to do this without seminal work by mathematicians.
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u/aKaizuh Sep 11 '26
Wasn't Tristan's work largely the result of AI generation though?
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u/purplebrown_updown Sep 12 '26
No.
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u/aKaizuh Sep 12 '26
They heavily utilized LLMs.
Buckmaster explicitly called it a "deep blue - Kasparov" moment.
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u/purplebrown_updown Sep 12 '26
Yeah but not in the way open ai did. You can use ai iteratively to help in parts.
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u/aKaizuh Sep 12 '26
OAI did the same thing, money compresses time, and that's the difference.
Not to mention the potential starting point being the conclusion of Buckmasters work, which is the real issue at hand.
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u/senderosbifurcan Sep 09 '26
1M dollars is peanuts to anthropic/openai It's clear they used Tristan's work Why do they need to get Levant out of the picture? Really confusing for me. Just credit both and talk about how gpt can be as good as another mathematician that's millennium prize level.
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u/asingov Sep 09 '26
The issue is that OpenAI promote their tools for research, while (1) publishing results themselves, and (2) training on researcher conversations. They are competing with their own customers.
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u/www3cam Sep 09 '26
OpenAI LLM is so advanced it learned a new way to prove things: proof by plagiarism.
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u/chensium Sep 08 '26
Both OpenAI and Anthropic are scumbags. Do people not realize this yet? They WILL happily steal your data and not blink an eye. Use their APIs and collaborate with them at your own risk.
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Sep 09 '26
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u/mosshero Sep 09 '26
(I certainly disagree with their stance on accessibility and control)
Can I ask why? There are people using ChatGPT to design new proteins and then synthesize them in home lab setups right now. If everyone has access to top-of-the-line models without biosafety controls it will be almost trivial for a single bad actor to unleash epidemics that make the COVID pandemic look like a joke. I totally see where Anthropic is coming from and find it hard to disagree. We're playing with fire here.
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u/lhyebosz Sep 09 '26
Remember that OpenAl gave free accesses of their latest model to scientists, mathematicians, and engineers few months ago?
If a product is given to you for free, YOU are the product.
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u/Stunning_Ad_8664 Sep 09 '26
What about the counting vowels problem? Is it still an issue?
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Sep 12 '26
[removed] — view removed comment
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u/Stunning_Ad_8664 Sep 13 '26 edited Sep 13 '26
lols
tried today instant mode and famous (mb not) strawberry rs counting: wrong answer too1
u/Stunning_Ad_8664 Sep 13 '26
-How many Rs in redcurrant?
Today, instant mode, exact input and output
- redcurrant has 4 R’s. 🍒
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u/AdWestern1314 Sep 08 '26
Can someone explain why this is so impressive if the point is to find a counter example? Isn’t it just brute force search and wouldn’t we expect LLMs to be good at that (if you are willing to simulate thousands of examples to test)? Isn’t this in line with the previous result we have seen? What is so special with this one?
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u/snowrazer_ Sep 08 '26
If brute force search could solve it then it would have been solved a long time ago - you don’t need AI for that.
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u/AdWestern1314 Sep 08 '26 edited Sep 08 '26
I guess I used brute force in a sloppy way - what I mean is that LLMs are great at coming up with examples after you give them the boundaries of the problem. From what I understand, this is exactly how they solved the other famous problems - finding counter examples. My question is if this is any different?
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u/snowrazer_ Sep 09 '26
A better question is why are you so desperate to trivialize this accomplishment?
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u/AdWestern1314 Sep 09 '26
I am not, I am just trying to understand but no one seems to be able to tell me.
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u/WeavileUsedFakeOut Sep 08 '26
You cannot brute force search a continuous domain
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u/AdWestern1314 Sep 08 '26
Of course not, but you can come up with 1000s of plausible counter examples and then test them really quickly with LLMs which resembles brute force.
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u/WeavileUsedFakeOut Sep 08 '26
You need an incredibly good heuristic to narrow it down to a tractable set of candidates. You’re underestimating how big infinity is lol
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u/AdWestern1314 Sep 08 '26
So the impressive part here is the narrowing it down process?
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u/KiddWantidd Sep 09 '26
I don't know what your math background is, but if you can understand it, see this great write up by Terence Tao on why Navier Stokes is hard. In very short, this solution is way more than just "brute force search" (have a look at the paper to immediately realize how deep and technical it gets)
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u/AdWestern1314 Sep 09 '26 edited Sep 09 '26
Thank you! I will have read. I have a PhD in mathematical statistics but it was a while ago and I haven’t really kept up with the latest trends unfortunately.
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u/cuttheblue Sep 09 '26
Would it be accurate to say they found an avenue (possibly based on work from other mathematicians) and then created a team of AI mathematicians to go explore different solutions?
Not brute forcing but not super genius AI mathematician either, a large team of strong AI mathematicians doing research on parts of the problem until progress was made?
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u/KiddWantidd Sep 09 '26
yes, per my understanding this is reasonably accurate to say. and the "team" literally consisted of tens of thousands of such mathematicians. the amount of compute they've thrown at this is just ridiculous, especially considering that it seems likely that they had a "good lead" regarding "in which direction" to look.
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u/moschles Sep 09 '26
Can someone explain why this is so impressive if the point is to find a counter example?
You need to consider what LLMs were doing with math 4 years ago. Struggling with high school problems, really. The progress is astounding.
Isn’t it just brute force search and wouldn’t we expect LLMs to be good at that (if you are willing to simulate thousands of examples to test)?
Yep. They used 10 thousand simultaneous agents to brute-force it.
Isn’t this in line with the previous result we have seen?
It is. LLMs are really good at finding counter-examples.
What is so special with this one?
In previous results, we could imagine that the particular conjectures were being berry-picked because they admitted some rare structure that made them extra-easy tasks for LLMs .
That dismissal is violently wiped off the table. Navier-Stokes is a Millennium Prize conjecture.
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u/AdWestern1314 Sep 09 '26
Thank you! I think this very much aligns with my mental model of how LLMs are useful on math problems.
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u/afrancisco555 Sep 09 '26
In any case, it seems like AI participated in this discovery in an enabling way.
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u/darshi1337 Sep 08 '26
Drama/accusation summary:
Aug 15th: Tristan Buckmaster & Levent Alpöge make progress on a few important math problems, "finite-time blowup with smooth forcing for incompressible porous media, for Boussinesq, and for 3d incompressible Euler."
they do NOT have a proof for the $1,000,000 Millenium Prize problem. BUT, they do claim to have a proof for a similar (non-Millenium) Navier Stokes problem that could help lead the way there
Levent works at Anthropic, but this research was independent of his work there, with a mix of GPT and Claude models. Tristan is not related to Anthropic.
Early Sep: Rumor spreads to OpenAI that Anthropic solved a major problem. Tristan emails OpenAI to clarify, without revealing the problem they solved or how they did it.
After hearing of the rumor, OpenAI started researching Navier Stokes with a new internal model.
Sep 6th: OpenAI's Sebastien Bubeck tells Tristan that they solved the $1,000,000 Millenium Prize Navier Stokes problem. The approach is very similar to Tristan & Levent's approach to the non-Millenium problem.
Tristan is suspicious of the timing, as only few others were trying this approach. OpenAI says the model didn't access his user data directly, but leaves unanswered whether Tristan's chat conversations were part of the training.
OpenAI says they would partially credit Tristan for the $1,000,000 discovery (even though Tristan did not solve the $1,000,000 problem) — but only if they remove Levent as an author, as he works for Anthropic.
Sep 8th: Tristan refuses to remove Levent, and rushes to publish their results independently.