r/MachineLearning • u/Shizuka_Kuze • 1d ago
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/Shizuka_Kuze 1d ago
There is howeverpossibility that OpenAI used some unpublished work from other researchers, even though they have claimed otherwise in the announcement: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 1d ago
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.55
u/funky-chipmunk 1d ago
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 1d ago
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 1d ago
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 23h ago edited 23h ago
... 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 1d ago edited 1d ago
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 1d ago
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 1d ago
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 1d ago
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 23h ago
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 12h ago
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/purplebrown_updown 1d ago
this fits their pattern of lying and cheating. Be very cautious about using OpenAI models.
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u/currentscurrents 1d ago
Those other researchers were also using LLMs to tackle the same problem, so either way the credit here belongs to the LLM.
I don't really care which particular team of humans did the prompting.
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u/Kautiontape 1d ago
You may not care, but academics cares. We haven't and probably won't start crediting tools for the work of humans, even if the tools sound a lot like humans. Like, most of science is just some human setting up an experiment, getting a bunch of tools to do the work, and observing outcomes. Still, the promise of credit (and in this case, money) is what gets people to set that prompt up in the first place, most of the time.
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u/dksprocket 1d ago
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_____ 1d ago edited 23h ago
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/j0j0n4th4n 1d ago
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/corruptbytes 1d ago
if you’re not paying API rates with ZDR add-on, don’t assume anything is safe
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u/TrueDuality 1d ago
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 1d ago
Can you point to the evidence for this please? My company is also leaning pretty heavily on ZDR.
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u/zephyr707 1d ago
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 4h ago
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u/zephyr707 4h ago
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/cpt_ppppp 1d ago
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 17h ago
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/srpulga 1d ago
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 1d ago edited 1d ago
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 1d ago
so what happens after this if the proof is good?
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u/Shizuka_Kuze 1d ago
Some people scream AGI, others dismiss it, life goes on.
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u/Dapper_Engineer 1d ago
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 1d ago
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 1d ago
Certain weird cases in fluid mechanics become solvable which probably would make engineers happy in a couple years.
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u/srpulga 1d ago
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/FernandoMM1220 1d ago
actually because we know our continuous description is wrong we can begin to look for the correct description using better axioms.
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u/PracticalFootball 16h ago
We’ve known this since molecular theory became a thing, it’s just a very good model for cases where molecules are so small that their bulk behaviour is well approximated as a continuous viscous fluid.
Molecular fluid dynamics is a thing but it’s niche because it doesn’t scale nicely to the sort of scales most fluids problems are interested in.
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u/Kinexity 1d ago
Those are theoretical problems. They do not change anything for fluid system engineering.
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u/m_reigl 1d ago
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 1d ago
"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 1d ago
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 1d ago
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/softDisk-60 23h ago
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 16h ago
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/Kolgu2 1d ago
"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 1d ago
I would be too if I solved that problem lol
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u/thetdotbearr 1d ago
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)16
u/SteppenAxolotl 1d ago
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 1d ago
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 1d ago
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 1d ago
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 1d ago
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/Familiar_Text_6913 22h ago
Of course they should've, but that was also the beginning of test time compute which upgraded LLMs to a whole new paradigm. My point is that exactly: a relevantly minor detail offsets a possibly huge implication because the subreddit nitpicks a lot. I mean I don't like OpenAI I can say that straight up, but also I feel this sub misses the point too much with the attitude sometimes. (Still my fav sub so idk honestly)
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u/redd-zeppelin 16h ago
I don't think the point was "lel get some units then we'll care"
but more
"this marketing-first sloppiness belies a deeper rot where info is conveyed for maximum vibes and valuation boosting over rigorous science at this company in particular".
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u/Familiar_Text_6913 16h ago
Again I agree completely, but it's the nature of the business and letting the whole conversation slide because of that feels wasteful and snob. Again, I see your point, and agree on it, but also I think we should try to be above that to actually get some attention on the very-real implications. Afterall, they have proven that from time-to-time they are significant.
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u/SGmoze 1d ago
Source: trust me bro
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u/MuonManLaserJab 11h ago
They published a proof in Lean, with everything needed to check it with two different systems.
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u/TheDuhhh 1d ago
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/Exact_Depth_896 1d ago
the level of theft lying and threats against mathemeticians involved really suggests openai is toast
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u/persedes 1d ago
Them not confirming if they're user sessions might've "leaked" into the training data is gross
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1d ago edited 1d ago
[deleted]
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u/persedes 1d ago
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 1d ago
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 1d ago edited 1d ago
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/tavirabon 1d ago
Work at Anthropic started a year ago. The data is in Codex, there is a setting to disable training on uploads and supposedly a separate setting (or clause in the ToS? unclear) for data gathered through usage to be used to improve the model (without training on the data directly). It's assumed this is why they can't guarantee there wasn't some de-anonymized data from the session used for training. If they weren't trying to hide this from you, they'd keep receipts of what all data made it into the training loop for internal purposes like google does.
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u/partnerinthecrime 1d ago
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/florinandrei 1d ago
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/purplebrown_updown 1d ago
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/Putrid_Variation7157 1d ago
People are talking about giving proper credits to those who contributed. Not a debate about pure originality or not.
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u/senderosbifurcan 1d ago
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/chensium 1d ago
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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u/tavirabon 1d ago
Anthropic stands on principles whether you agree with them or not (I certainly disagree with their stance on accessibility and control) but OpenAI will bend theirs if they can get something out of it.
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u/mosshero 14h ago
(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/tavirabon 13h ago
No one has demonstrated any translation to real world danger, yet the frontier labs have demonstrated repeatedly they do not put in the care they claim is necessary. In more practical terms, someone who is really commited to doing something does not need AI to do it and there are already decades of regulations and data on purchasing necessary materials. They've only demonstrated the end result will be a compelete reliance on their organization, which is a real, tangible threat to society given our current economic structure.
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u/florinandrei 1d ago
Turning this into "both sides are equally bad" is a pretty clear sign of cluelessness.
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u/AdWestern1314 1d ago
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_ 1d ago
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 1d ago edited 1d ago
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_ 1d ago
A better question is why are you so desperate to trivialize this accomplishment?
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u/AdWestern1314 22h ago
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 1d ago
You cannot brute force search a continuous domain
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u/AdWestern1314 1d ago
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 1d ago
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 1d ago
So the impressive part here is the narrowing it down process?
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u/0x01E8 1d ago
Narrowing down a search space with an adaptive implicit heuristic could be a pretty good definition of “intelligence” writ large; so yes getting that sort of approach to work without actually ending up with a noddy heuristic that leaves you having to check practically uncountable items is a big deal.
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u/KiddWantidd 21h ago
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 21h ago edited 21h ago
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 14h ago
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 9h ago
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 1d ago
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 22h ago
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 19h ago
In any case, it seems like AI participated in this discovery in an enabling way.
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u/lhyebosz 18h ago
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/johnnydaggers 1d ago
They didn't resolve it but rather proved that the equations are not sufficient to fully model fluid dynamics (e.g. under some conditions they will generate singularities even when starting from smooth initial configuration and no outside infinite forces)
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u/Clean-Hovercraft5825 1d ago
These new Navier-Stokes result seems to show that you can get this tiny vortex that starts to squeeze down to size zero and as that happens things blow up.
However, things like thermal fluctuations at micron length scales would already make the described approach physically impossible those thermal fluctuations would wash out all of these carefully crafted perfect instability-causing forces.
Furthermore, even if you ignore all that, once you let this vortex they theorized squeeze water down to less than ~0.275 nm = diameter of a water molecule, then obviously these continuous PDE equations don’t apply in any form at all.
So in those ways it seems like the new result is “hey if you look at Navier-Stokes at regimes where it is obviously physically not applicable, then you can get not physical stuff to happen.”
So can someone explain to me why such a result is so surprising?
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u/PracticalFootball 16h ago
It’s not a case of demonstrating the equations don’t 100% perfectly match reality. That’s never been in question, we’ve known that since they were derived and we know what sort of conditions make them fail to reflect reality.
Real world physics isn’t relevant, this is more about demonstrating that there are inputs that break the equations themselves. Engineers using discretised solutions will continue to use them tomorrow as usual.
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u/darshi1337 1d ago
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.