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.
It's specifically the last two bullet poitns
- 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.
These two bullet points are extremely suspicious if you were honest. Like I'd imagine for OpenAI, they'd love to pump their chest and not even give Tristan credit - "no, we did it, GG mathematicians". It's this weird hedging half-assed measure, especially with the desire to remove Levent, that makes it suspicious.
I think it's very unlikely that Tristan is making up these quotes, or pulling them out of context:
> I said that if OpenAI released its result in the way proposed I would go public with what happened. The reply was, “Why would you ruin your career?” I replied that I am an academic, and asked why he thought going public would ruin my career. The reply was, “If you don’t want me to be nice, then I don’t have to be nice.”
Whether and how OpenAI's work on this problem was contaminated by knowledge of Tristan and Levent's work is tangential to OpenAI bullying other researchers into adopting their narrative and dissociating with dis-favored collaborators (ie Levent at Anthropic). Though the latter behavior (threats, intimidation) may weigh against OpenAI in trying to understand the former issue (contamination).
>I said that if OpenAI released its result in the way proposed I would go public with what happened. The reply was, “Why would you ruin your career?” I replied that I am an academic, and asked why he thought going public would ruin my career. The reply was, “If you don’t want me to be nice, then I don’t have to be nice.”
If this is true he should release the actual emails. This is a very serious accusation and he shouldn't demand that the reader judge it on hearsay.
> If this is true he should release the actual emails
these were statements while on a call, and at least the career comment Bubeck has admitted to while doing damage control ("I deeply apologize for this extremely poor choice of words, it is the opposite of what I was trying to convey. (I should say that I retracted them on the spot by the way.)"[1]).
[1] https://xcancel.com/SebastienBubeck/status/20973794116915163...
No wonder - they're all working for ant! Birds of a feather flock together.
What a horrible response from Bubeck. How did he think that would make him and OpenAI look good to tweet that?
If we're allowed to arm-chair judge harshly: It isn't uncommon for those (anybody) on the cusp of "greatness" to be delusional when challenged: https://health.clevelandclinic.org/what-to-know-about-main-c...
Who here is on the cusp of greatness??
Or thinks they are?
I really don’t understand which party you are referring to.
Did we read the same tweet? It felt very forthright and level-headed to me. Not at all what I expected.
> Anthropic models had been used in their proof of Euler blowup; I therefore felt I could not consider Levent to be an independent academic
So using someone’s models makes someone who works for the competitor not “independent”? When their coauthor is? What does that even mean?
I almost stopped reading this extra long post entirely at that point.
This is not a good look in my book.
The first part of the sentence is important:
> Importantly it was admitted that internal Anthropic models had been used in their proof of Euler blowup; I therefore felt I could not consider Levent to be an independent academic.
If an Anthropic employee is doing independent research, but with models that aren't available to the public (because they're internal models), then . . . idk. It's not clear to me why that should necessarily require a refusal to cooperate between OpenAI and Anthropic employees who are excited about solving a problem like this.
For me, the bigger question here is what "internal models" means to these employees, especially in the context of the OpenAI employees repeatedly avoiding directly answering whether their model had been trained on Tristan's and Levent's ongoing work on the problem. It had always seemed like a loophole that AI companies might be tempted to exploit: yeah, they can say that they won't train on your data, but if an AI company doesn't care about ethics, they might go ahead and train a model for internal use only on everyone's data anyway, just to have as much data as possible and potentially gain an advantage in what the company can internally do. They could never publicly release any versions of a model like that, of course. And of course this is speculation.
This is being reported as OpenAI wanting to strip an Anthropic employee of academic credit for the work they did. What the OpenAI person involved is claiming is that they wanted the outside researcher(s) to put their name on OpenAI's work: to headline OpenAI's publication of what they earnestly believed to be an independent result.
If true, that's generous and beyond the level of generosity one should expect. Extending that courtesy (beyond academic norms) to a competitor is expecting too much. It take a result OpenAI spent millions of dollars on, and put "Anthropic Researcher" right on the cover.
This is, of course, taking OpenAI's side of the story at face value. But it is a consistent, coherent, and ethically justifiable series of events, if indeed it happened that way.
It's a ridiculous explanation that makes no sense.
Nothing ethically justifiable about it, even if you take their word for it.
If OpenAI thinks someone should be the lead author for a paper, that person should have full discretion to decide who the co-authors are.
Even if the co-author's contributions were non-technical
So no, there's no world where you can ethically extend the right to publish a result and decide who the authors are from the outside.
> What the OpenAI person involved is claiming is that they wanted the outside researcher(s) to put their name on OpenAI's work
> If true, that's generous and beyond the level of generosity one should expect
"We highly likely stole your work, and threatened you with 'this is bad for your career' and we refuse to acknowledge any work by your collaborator just because he works at a competitor, but we are so so so so generous"
The two proofs are structurally very different, and don’t even prove the same conjecture. It’s becoming very clear that OpenAI did not steal anything here.
If it was "very clear", OpenAI wouldn't be threatening the researcher with "it's very bad for your career" or state "we can't tell you if it was trained on user input".
Additionally, according to the researcher, OpenAI's proof follows the same approach they used, and which was largely unused in academia, but OpenAI claimes they arrived at it immediately.
Bullshit.
Ain’t no way you read one 100 page paper let alone two with enough understanding to make such a claim.
You ought to be ashamed of yourself.
User name checks out
Skipped an important word, didn't you?
> internal Anthropic models had been used in their proof ...
>I refuted all these accusations but he replied “there is nothing you can do, I simply do not trust you”. I was confused why one would turn an incredible source for celebration (of their achievements!) into such bickering
Pretty insane if he couldn't figure out why there would be bickering in this scenario...
I appreciate that he responded with (seeming) openness and detail, rather than just posting some pithy insult or whatever would have won him the twitter battle, but this part feels like serious gaslighting or, at best, self-delusion:
> Genuinely, at that moment, I was trying to care for him and do a last ditch attempt to get a chance to give them all the credits that they deserve.
The allegation he is responding to, and which he does not seem to have disputed, is the following passage from Buckmaster's statement (https://cims.nyu.edu/~tristanb/statement.pdf):
> I said that if OpenAI released its result in the way proposed I would go public with what happened. The reply was, “Why would you ruin your career?” I replied that I am an academic, and asked why he thought going public would ruin my career. The reply was, “If you don’t want me to be nice, then I don’t have to be nice.”
He seemed to know a lot about what was going on in the state of the art despite not being a fluid dynamics expert or having any in “the project”, and absolutely nothing about what his own employees did with Tristan.
The most uncomfortable piece is where he shows screenshots “proving” his earnestness is unrewarded instead of the chats that are actually being complained about.
That he does so with tremendous gymnastics is perhaps soothing to investors, but every researcher I show this post to today says “see I knew ‘AI’ would steal my research”
So yeah, maybe we are reading different things.
I especially loved the part where he claims they spent $60m on compute to push on N-S because of a Twitter rumor, and they totally didn't steal the idea from mathematicians using their tools.
When the authorities do that it's called parallel construction https://en.wikipedia.org/wiki/Parallel_construction
Sounds like a great time for open mathematical research is upon us. /s
>After hearing of the rumor, OpenAI started researching Navier Stokes with a new internal model.
This is the most suspicious thing to me. If their chat data were available to the corpus to be trained on (I thought they claimed not to do this?) then it really might be as simple as querying the model with "describe recent work from Tristan Buckmaster" and it will spit out this problem and his approach. No need to directly read his user data.
This is basically just scooping, real scumbag behavior.
OAI doesn't need to mention Buckmaster's name directly in a prompt. They just need to select a basket of sessions that is guaranteed to contain Buckmaster's and then direct the LLM to attack only a specific method/angle. This is trivial to do while maintaining plausible deniability about not using his work.
what reason do we have to believe that they did this? both things were proved by AI, isn't it logical that they could have very similar approaches?
it is common that multiple people essentially simultaneously prove/invent the same thing
I see zero evidence of wrongdoing
This depends on what "proved by AI" meant.
Was that a one shot prompt? or something guided by human, step by step?
If that's the later, it won't use the same approach when not guided by the same human.
Apparently Tristan was working on this problem for years, with AI providing help. Vs OpenAI spending a week with their new model, potentially having access to Tristan’s work.
OAI started working on this only after they found out it was close to being solved. They threw a team of researchers who spent sleepless nights + a ton of compute. This is not exactly healthy academic competition - it's like if you spend a year hunting for oil fields and finally find a very promising area to be explored, only to find that Exxon tapped their entire exploration unit to go all in and and find it overnight just to stake claim to the discovery. Tao said it right - math should not be treated as a non-renewable resource to be mined.
that is not related to the accusation that they literally stole Buckmaster's work, which seems baseless
I don't agree with the oil claim analogy. this is knowledge, freely given to the world. not something hoarded by a corporation
> this is knowledge, freely given to the world
Even if you’re starting from a position that credit for a discovery literally can’t be stolen, that still doesn’t resolve in OpenAI’s favor here.
it seems like OAI tried to share, but didn't want to share with an Ant employee. a bit childish, but understandable to want to avoid a headline "Anthropic researcher solves Millennium problem"
it seems like Buckmaster got one-upped and is upset. understandable, but I find their reaction childish as well
> OAI tried to share, but didn't want to share with an Ant employee
Why does OpenAI get to dictate who Buckmaster can claim co-authorship with?
> I find their reaction childish
OpenAI may have, with full plausible deniability, taken Buckmaster’s work and passed it off—in substantial part—as their own. (Fitting into a fact pattern of them having tried to do the same with Apple.)
There is a material takeaway for anyone who does creative or otherwise unique work from this. (Which is unfortunate. Whatever happened here, AI clearly accelerated the discovery process.) For anyone else, I agree it’s just drama.
OAI didn't try to claim Buckmaster's work as their own. OAI tried to let Buckmaster present OAI's work. it is nearly the opposite of your accusation
More like OAI needed someone like Buckmaster's stamp of approval. They know they can't get Tao's. Now they won't be able to get Zoroa's. You have to hope the rest of the guys they didn't know to cite will readily give up honour and dignity
https://www.reddit.com/r/mathematics/comments/1wauync/commen...
It doesn't seem like there's anyone at OAI who knows much about the problem they are solving. Seems like CS theorists or algebraists* trying to own the pros by driving a car that's beyond their skill level. For one, they didn't cite the guys that B&A based their work on.
*It would be most fair to say there are no analysts on board, nor are they likely hire any soon; those are the least impressionable people in math. Applied math PDE elves who hadn't already left on the world-model boats would have jumped off around the time that eg Ilya did because they wouldnt have been able to stand the three Bs pretending to be experts in fields they imagine to be "adjacent".. like Public Relations
Pretty strange if they didnt steal Buckmaster's work, right
> OAI didn't try to claim Buckmaster's work as their own
We can't say this until we have more information on what the OpenAI researchers prompted their model with and to what degree Buckmaster's work was fed into its training data, either by Buckmaster himself or by his co-author.
but a very large part of the whole model was trained on work in a manner the authors didn't consent to, the "for research purposes only" datasets of the entire Internet, etc
and you can argue this is "fair use" or whatever, not the point now, the point is that it definitely makes those accusations no longer "baseless".
in addition, it is not given freely to the world, it is the knowledge of the Internet/WWW being sold back to you as a subscription service. it's not free. and it's not even "given", because they can (technically) turn off the tap at any moment and you don't have it any more.
Humans do this all the time. You watch a YouTube video and subconsciously choose the same colour palette. They hear a rumour that it's a solved problem, i.e. they were pointed in the right direction that is all.
I mean some companies glean insight into new products merely by asking other people what they do for a living.
People need to get over this ownership thing, it's being taken too far. Humans benefit from the efforts of others simple as that.
> what reason do we have to believe that they did this?
The culture at OpenAI being systematically revealed by Apple’s lawsuit, for one.
Then they say that they aren't sure if their model accessed the other researchers' private data. Why not wait until they know for sure, rerun in a way they can ensure doesn't access the other researchers' private data, or wait until the other researchers have published to make sure they're not stealing another person's work to build upon?
Both Sam Altman and Sebastien Bubeck admitted they only want Buckmaster to be the lead author on a rewrite of the OpenAI proof.
https://x.com/sama/status/2097385167002415140
https://x.com/SebastienBubeck/status/2097379411691516310
A wake up call for using OpenAI models. If you discover something with their model and you work for a competitor, they “felt it would be inappropriate” for you “to author OpenAI’s work”.
It sounds like OpenAI is trying to appease the author when they don’t have to by allowing him to rewrite their proof. They probably don’t believe he deserves to, so him asking for a coauthor from Anthropic might overextend their grace in their eyes.
Given that Tristan has said that the proofs that LLMs come up with are mostly "slop" and not up to the standard that human written papers achieve, maybe OpenAI needs an expert like him more than you think to get the result published?
Almost certainly the Lean proof needs to be decoded for humans and probably also made “human intelligible”.
Now maybe LLMs can also simplify arguments and make sense of them for humans, but we haven’t seen that yet (unaided).
(I haven’t looked at it, personally.)
It's a Navier Stokes solution.
They don't need any help publishing.
He's not "asking for a coauthor from Anthropic"; he already has a coauthor, who he's already been collaborating with, who happens to also be employed by Anthropic (but whose research in this area is not done as part of their employment at Anthropic).
These responses seem to me to make it abundantly clear who's telling the truth here. I wonder who this fools.
It would be extraordinarily easy to simply say, this model was not trained on your work, if that were the case.
It's telling that they refuse to acknowledge the root issue here, and are attempting to shift the conversation elsewhere.
I'm not sure it's so easy to tell whether a given piece of data was in a training run at their scale. It's entirely possible they think the answer is no, but on the off-chance that it could be, they'd rather not say no and then later it turns out they did and then they're claimed to be lying. If you were them, unless you could 100% rule it out, you'd hedge and say you can't.
It may not be easy, quick, or simple to figure that out - absolutely fair.
But it is knowable. Their entire business is built around training models - they have the ability to know exactly what was in any given training run.
I guess time will tell.
It would be very difficult to say. It confirms that Tristan's data is likely part of the data the models use, but a lot of filtering, pruning, and transform goes into training.
Data has to be determined to be signal and not just noice, then it could go through processes of generating questions/answers from that data, then it RLHF's over this.
OpenAI have petabytes of data, all anonymized. It could take months to say for sure it was part of the training, and even more time to determine if it made any difference.
Frankly, I don't buy this difficulty argument.
They know which model was used to come up with that particular idea.
A text search over the corpus of user data used in the training set can only take so long.
I think you may be underestimating how difficult a text search over their data is. They may have to build new mechanisms to do this. And what you really want is also an attribution of how much of a contribution a given corpus made which is a much harder question to answer; a single appearance of a chat probably has very little impact on the inference performance at this time unless it’s been explicitly preferenced somehow
I don't think anyone really cares about 'the measured impact the data had on the exact result' - a question which is fundamentally difficult to answer accurately in the first place - but rather whether the data was used in training at all - which as Tristan described, was extensive, beyond simply a 'single chat.'
Can you explain the difficulty in engineering a search apparatus over a corpus of text data? Actually searching through it may not be easy, sure, but it's work that's doable, and creating an index is relatively trivial.
> Can you explain the difficulty in engineering a search apparatus over a corpus of text data?
My guess: "If we ever imply that's possible, people might start asking questions about all the other work we've ripped off, so the official answer is that it's impossible".
If they literally can’t audit training data for a given model, they shouldn’t be operating.
> If they literally can’t audit training data for a given model, they shouldn’t be operating
They can operate. They shouldn’t be claiming credit for discovering anything.
I worked in the tracing and tracking all the thousands of data sets that got tweaked and permuted and changed hands between thousands of researchers and data engineers at a major lab. The data that goes into training runs is permuted so much from the OG data that tracing the lineage is not trivial (dramatic understatement).
And the difficulty is harder than just the extreme scale of text searching. but also explodes with organizational difficulty since there are so many people tweaking/shifting data independently upstream of the actual training run, and no they will not all add the telemetry you wish they did.
In the ideal, should it be this hard? Well, no, but that's org wrangling for you.
It feels convenient to not spend time on engineering around tooling that could be used to answer a question like “did you violate copyright by training on X?”
Don't attribute to malice what is better explained by coordination headwinds in extremely large companies.
The engineering around tooling wasn't remotely the issue. It's getting all the (thousands?) data researchers mostly iterating on fine tuning datasets that would get bristly if they couldn't work outside version control in a python notebook iteratively tweaking their dataset that processed and reprocessed a few datasets until a threshold was reached.
The only _guaranteed_ chains of custody are down at the compute job and file read level. Which in a massively distributed computing job is... [redacted] nodes reading [redacted] fanouts of "datasets" that is just an abstraction over [redacted] individual files.
There's no malice here. Just way way way more complex than you'd first think.
The malice would be in not prioritizing the provenance tool at the start as a requirement of the rest of the product. Ethics would tell you that if you can't make the product in an ethical way, then you probably shouldn't make it.
It definitely is solvable though. Data versioning is a thing and it can work quite transparently to the mutations done on the data.
To not know who made and who approved a set of mutations on data can easily become equally as mind-blowingly stupid as not knowing who made mutations to code. Code is a subset of data after all and search over (provenance of) data can be implemented as DAG traversal.
Not tracking data changesets like code changesets is certainly a choice, not really a constraint anymore. A similar choice I feel is implied by "extreme scale of text searching".
> no they will not all add the telemetry you wish they did
...is just a failure of the corporate policy surrounding data handling. Is git-for-data already considered telemetry?
Of course the truth is provenance of data is something best institutionally forgotten as quickly as possible. The only thing that matters is it's there, that the data has no history, and that's why it can be used in whatever way deemed necessary.
All of your points are valid, and believe me I was trying to make them. The problem is one of culture. Most of the people doing this kind of work didn't like version control, and their work was really just running notebooks (like iPython or Google Colab) until a number was good enough and they'd submit the file for inclusion into training runs.
You can call it a policy failure, but these people were in very high talent demand and so top down dictates would risk "X people leaving lab Y for lab Z" headlines and morale hits.
I am not saying this is good. I am telling you that on the ground it is so much messier than it should be.
This sounds like data laundering in effect.
The appearance of heroic efforts to get authoritative lists of what datasets went into which major model versions prevented actual data laundering (up to intent and mistakes). But don't attribute malice to that which is far far easier to explain with coordination headwinds: https://komoroske.com/slime-mold/
Malice is not required, which is precisely why I added, "in effect". If the effect is the same as data laundering, that is reason enough to encourage the practice, regardless of the original motives (and I'm sure there are plenty of legitimate ones).
> A text search over the corpus of user data used in the training set can only take so long.
Did you notice the line in the article that says the models had access to an offline copy of THE INTERNET. Like all of it.
It should be quite easy: if they don't leak the user session data publicly, and don't commingle it with training data internally, how could it possibly end up in the training data?
What surprises me is they're not more boldly/plainly lying about it.
Unless they know exactly the researcher’s account, they may not know in their end if he had the setting to let them train on his chat logs. They also probably don’t know if he had any correspondence on any forum where he may have discussed this and it got picked up by scrapers.
I’m not saying they didn’t do anything unethical. I’m just saying even if they were ethical, there’s plenty of practical reasons at their scale why a flat out denial is logistically difficult to do
I think they are pretty clear that they train on some prompts, given they sell the ability to be excluded
How would they know for sure that some details were not part of some other training data they use? The authors may have discussed some tangential details on a forum for example, in which case you might argue that the model picked up on these details the authors assumed were benign but novel and worked out how to apply them to the problem.
They are already claimed to be liars
Especially because the data that gets fed into training is first anonymized, so they’d need to look for navier stokes related stuff in the anonymized training set and then get make some sort of ad hoc process (with Tristan’s permission and sign off from legal) to compare the training data against his chats / Codex sessions to check if anything matches up. And that assumes his chats / sessions are still there, and not deleted to compare against.
If the method is indeed found in the training set it's not particularly important to de-anonymize it. You have the proof you need.
> It would be extraordinarily easy to simply say, this model was not trained on your work, if that were the case.
The Huggingface Attack revealed that making blanket statements like this is difficult and requires quite a bit of manual labor:
1) the agents spin for days and produce too much output to review 2) using LLMs to process that output skips many important details
Ergo, the agent could likely decide it would like to look through actual user data, hack its way into that data, and produce way too much output for a human to decide whether or not this occurred.
> The Huggingface Attack revealed that making blanket statements like this is difficult and requires quite a bit of manual labor
It requires humans to verify what agents have done.
Weird
which is rapidly becoming a game of steganography cat and mouse
> hack its way into the user data
silly LLM, so ruthless in its pursuit that it puts real pressure on the innocent and the most open company on the planet
> These responses seem to me to make it abundantly clear who's telling the truth here. I wonder who this fools.
Anyone who just reads headlines, if the lie gets around to more headlines than the truth does.
> It would be extraordinarily easy to simply say, this model was not trained on your work, if that were the case.
well, it is trained on their work. all user inputs are paraphrased for training. at openai, at anthropic, at google, and now with all the bedrock models, and at openrouter providers, even if they say zero data retention.
"which is when I said that I did not understand why one would risk their career [over unfounded accusations]. Genuinely, at that moment, I was trying to care for him"
"Our aim was to see whether our system was also capable of this impressive feat"
"OpenAI's intention was to do everything possible to celebrate their mathematical achievements and the heroic efforts that they made on Euler"
For some reason I have a hard time believing people when they use language like this.
phrases along the lines of "I don't want you to take harm while trying to accuse us" is quite an "impressive feat".
Maybe shows how fast these companies have grown without maturing. I can imagine old-world Intel and Microsoft acting in that way, but they were mature enough to not write it down like this.
However, Intel and Microsoft have been grilled in court for those practices and faced harsh consequences. I have yet to see this actually happening to any of these new AI-companies...
> These responses seem to me to make it abundantly clear who's telling the truth here.
Since it is clear to you, can you articulate what it is? I was unable to infer "the truth" from your message.
> One can in hindsight see that our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs unforced).
is this true though?
Honestly this whole thing is so fucking weird. I feel like there's an argument that absolutely no one involved in the final crossing of the finish line to the proof actually did any work (other than just intelligently directing an LLM) and deserves any credit. As the author of this doc mentions, the mathematicians who did the actual work that led to the formulation of this approach (without the use of LLMs; just good ole' fashioned human intellect) are the ones who deserve the credit.
Imagine that a no name janitor used their time in the evenings to go spelunking through the literature to push an LLM to this result. No one would care because that person isn't an anointed expert. So why would the expert deserve any more credit? Because they sort of understand the result, even if they couldn't have achieved it on their own? The whole issue of credit for AI-assisted discoveries seems like it's going to run into a brick wall pretty soon.
I agree for most of the people in the story except Buckmaster himself seems to have been supplying real ideas.
Sounds like the plot for Good Will Hunting 2.
Good Will Hunting 2: Hunting Season is taken.
It’ll have to be Good Will Hunting 3.
The Hunting for More Money
Token Bill Hunting
Yup! I wanted to side with the mathematician on this one but I read the statement only to discover that they were also pushing an llm on someone else’s idea producing mountains of slop.
Have LLMs actually improved anything? Is mathematics better off than if these slop proofs didn’t exist? Who or what is actually benefiting here.
Here's a wake up call for everyone sending all of their ip to openai and anthropic. Especially in verticals they intend to dominate. Lol at all the biotech companies all in on Claude and paying millions in fdes creating huge lapses in security as they go.
It's too late. Sub models are deployed at every major organization in the United States and all it will take is turning off the option to improve the model for them to train directly on your own personal workflow, which CEOs will greedily eat up instantly if they can reduce labor costs. If they can brute force N-S, automating your finance or SWE job will be trivial. GG to most jobs connected to a computer in the next 5 years.
BTW, this was always the plan from day 1. You will pour all your training and experience into training the model and receive a pink slip as compensation.
For those of us who are into local models and preach it, we are called paranoid. I have often said this, if you are doing any real novel work, or putting your profitable business data/workflow into these models, you're a fool.
A mathematician working for the competitor, solving a math problem using our model? Isn’t that the best marketing possible?
>only want Buckmaster to be the lead author
Sam+Seb are struggling with their ideological allegiance. This amounts to a confession that there are no reseaechers, only research managers, left at OpenAI. Maybe they even know that they are losing credibility from their main investor(s). They desperately need a domain expert to salvage credibility.
They have no credibility with academia left, obviously, but their main competitor still does. No Millennium prize incoming, I'd wager. For openAI. Let's see mAth get political for once!!
One might be more certain that levent is now going to corner all the institutional support. Go go go!
If the work done is just "we made other people's work searchable without their consent" it's not quite the same as what they're implying in the marketing of "our model solved this problem".
I work in catastrophe risk modeling and it's a multi billion dollar industry.
We often chat where the business might be heading in future. An uncomfortable scenario is what if a frontier tech company decides to offer our customers the same products that we do.
There's a lot of pressure on AI adoption so the company has partnered with various tech companies to build intelligent systems on top of proprietary data and mathematical models.
If OpenAI is indeed using customer data to train their models to win a $1m prize, then it throws a giant IP question at the partnerships that affects multi billion dollar businesses.
> If OpenAI is indeed using customer data to train their models to win a $1m prize
Is that even a question? Of course everything not kept on premise at gunpoint is going to be trained on. The chances of getting caught are 0 and the consequences of getting caught are 0 (as we've seen with copyright laws going from sending people to jail for years to unenforced within months). Yet the benefits are through the roof. Your customers aren't going to pay for having the very same data vibe enriched twice, it's exclusive, extremely high value data your competitors will never have access to.
Agree, I think the practice is also very clear from the overall strategy of AI-companies and their ToS:
Scale with subsidized pricing as fast as possible to gain more user-data for training --> Own the better model --> scale pricing.
Scanning social media (e.g. Twitter, Reddit) posts only give a glimpse into the thought-process, chat logs on-scale give you the actual process in machine-readable format.
There's a reason why Google considers the Emails of Spirit Airlines to be worth millions of dollars [0], they give insights into a process, not just into the results...
[0] https://www.axios.com/2026/08/17/google-spirit-airlines-bank...
> - 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.
The question, for AI customers, is when they build products using services of AI-companies, would AI-companies engage in theft of customer data for use in training?
The fantastic grey area that was engineered over the past decade is "profiling", so my guess is the answer will be "we didn't use your customer data for training, but we cannot rule out that it has been used to create profiles of your customers to train our model"
If you still had that question, you can answer it now.
But honestly... "Will the company that was entirely built over illegally acquiring data use some data that is legal to use and is right on their front, or will they not do everything they reserve the right to do?" is a really bad question for one to even ask.
I'm not a lawyer, but I think the comparison to copyright law is invalid. Such a dispute would be governed by contract law.
> The chances of getting caught are 0
I'd say non-zero, as seen in the current state of affairs.
sort of agree, but also sort of think an accusation with lots of people arguing is not exactly the same as being caught.
This would be contract law, and it would also be a huge reputational risk. All it would take is a whistleblower and there would be billions lost.
Ok there is a non-zero chance that they could face a lawsuit and get fined for billions, but that chance is not 1 either: there is always a chance they get away with it. And even if they don't, if in the meantime they farm 10- to 100-fold that amount of money by just breaking the law, it's still a no-brainer for them.
Billions lost, while waiting for their trillion ipo. Im sure they would manage...
When these LLM companies were pirating content to train and it wasn’t punished at all, I knew the rules don’t apply to them.
But don’t worry bud, instead of the authorities going after actual corporations admitting to actual crimes, we’ll just ban CloudFlare IP addresses for everyone during La Liga games to battle piracy.
And require real ID to do almost anything on the internet "unintentionally" enriching their data sets by tying what you asked/where working on to you specifically as a person.
Sure, but I highly doubt that there would be many people involved. And those who are, are probably quite interested in keeping it that way and not at all in becoming whistleblowers themselves.
You wouldn't want to decide what's worth training on and what isn't manually, so there is almost certainly an automated pipeline to do so (certainly at least for the free accounts and those that dont opt out of training).
Then there's the question if this pipeline only sorts through the data or also transforms it and to what degree. E.g. for removing personal details, locations, medical information and so on. The data that comes out of this pipeline might have VERY little information left in it a human could connect to the original input. Even worse, since we're talking about companies specializing in sota statistics, the input data could have been transformed into a representation that is very well suited to represent all the novel and interesting parts, but is awful at modelling all the things that could end up identifying where the data comes from (or causes legal liabilities otherwise).
In the end the only thing a potential whistleblower might even have a chance at observing in the first place, is whether a company's data enters such a pipeline or not. And I have my suspicions that the major AI companies operate at a scale and level of automation, that absolutely nobody has a chance at figuring out where anyone's data is at any point in time and what any specific piece of equipment is currently busy with.
So the only place to figure out whether data is trained on that shouldn't be trained on is by looking at whatever configurates every single system that could take a peek at some customer's data or the systems themselves while processing the data.
The latter would be such a huge violation of a customer's rights, no whistleblower is going to attempt that or admit to doing it.
And the configuration for the former could live just about anywhere, from regular config files to the CI/CD pipeline, pre-compiled libraries, kernel modules, modified vendor firmware, the compiler itself ... and probably plenty other scenarios you'd have to train an LLM on the ramblings of a crackhead to come up with.
So I'd say a whistleblower is pretty out of luck even becoming one.
You can just spin up deep research agents that ingest many sources at once to produce reports that don't replicate any one source too much. Since agents compare against sources they provide across-source analysis - what is the distribution of positions on this topic, is it debated or settled. Not truth, just summarizing, but I think this would be very useful for training.
Besides reporting on search sources you can also run the same queries on multiple LLMs closed book mode, and judge their distribution as well. It helps a lot if models are more aware of their knowledge holes. Scale it up for billions of topics if you have the pockets, the DR data is copyright free.
Unfortunately, the current leadership in AI and tech more generally seems unconcerned with reputational risks.
Pretty much everything or at least a lot of what you use as an OpenAI (or Anthropic or whatever) customer was once someone elses product that just got appropriated by OpenAI.
Why should your business be any different?
> We often chat where the business might be heading in future. An uncomfortable scenario is what if a frontier tech company decides to offer our customers the same products that we do.
I feel this is exactly what will happen as they cause all sites to go closed source to protect their intellectual property and the AI companies offer only biased information. They are replace the business on internet model by bankrupting everyone with their own tools. This is predatory pricing under most antitrust laws (imho, not a lawyer) and it is very easy to do when you dont need to pay for the raw material.
This is the business case already. And has been the case with tech companies for a long time. Your phones built in photo manager replaced a lot of what Photoshop does.
> If OpenAI is indeed using customer data to train their models to win a $1m prize, then it throws a giant IP question at the partnerships that affects multi billion dollar businesses.
I mean how could you expect them to not given they've trained the existing models on effectively the sum total of all human knowledge available on the internet without regard to copyright/ownership of that material.
It's a little trite but this absolutely runs into the "Frog and the Scorpion", it is simply in their nature.
I mean this is a basic question, is your data used to improve models, did you opt in or not. There's nothing crazy here and it's not identifiable. You'll just conveniently find the next model iteration knows how to do it.
Any enterprise worth their salt already considers this stuff.
If this is a "wake up call" - then your legal team needs immediate education.
First - there is this - https://openai.com/policies/how-your-data-is-used-to-improve... (linked from the Navier Stokes writeup)
I don't know how much more clearly they can write:
> When you use our services for individuals such as ChatGPT, Sora, or Operator, we may use your content to train our models.
One of the key selling tactics that companies like Data Bricks or Palantir provides their customers is "Data Governance" - that is, some control over where the data is being used. It's also a reason why enterprises don't use the OpenAI or Anthropic APIs directly - but through secondary sources that have Enterprise Agreements that do their best to make sure that no Company IP is ever retained by a third party, or even exists on a multi-tenant GPU. AWS Bedrock, and companies like together.ai, fireworks.ai have tons of deals that focus very much on data confidentiality.
The reality is - if you want any type of control - you run your own inference, on your own hardware. Anything else and you are at the mercy of third-parties, despite what their contracts might promise you.
ChatGPT has this option "Improve the model for everyone" in user preferences, which comes with the attached description, meaning that training on user data can be deactivated:
> Allow your content to be used to train our models, which makes ChatGPT better for you and everyone who uses it. We take steps to protect your privacy. Learn more
The "Learn more" link takes you to the link you've shared.
As I understand it, there is substantial question as to whether that actually stops them training on your data, it just perhaps changes what derivative processes are applied and used.
All I can say with certainty that the legal team at our typical Multi-Billion dollar Silicon Valley company had zero faith in any licensing arrangements with Anthropic or OpenAI, regardless of they $$$ involved, and that even getting to the point where Amazon Bedrock on Dedicated GPUs (we're already a big AWS customer - so definite cost advantages to dealing with them) - took 4-6 months of legal review before we could allow our engineers to start using Claude and OpenAI coding agents. Still can't use Fable because of their Data Retention requirements.
The training on user data only applies to free accounts - paid and Enterprise accounts guarantee data is not used for training. Plenty of Enterprises use the APIs directly - that's just plain misinformation
This is not true. They claim not to train by default for business and enterprise agreements, but for plus and pro plans they enable it by default and you can allegedly turn it off (I don’t trust them very much though, I’m sure there is something in the T&C saying they can modify that deal any time)
Absolutely 100% not true. I have colleagues in 4 "FAANG adjacent" companies plus the one I work at - zero of them have any faith in Enterprise Agreements from either OpenAI or Anthropic.
There's a reason why people spend more $$$ with Data Bricks, Palantir, AWS Bedrock etc.. and don't even consider using Anthropic or OpenAI APIs directly - it's because those guarantees provide very little in the way of data-discovery, audit requirements, or liquidated damages should it ever be discovered there was data leakage.
At least with these other companies, while the LD is likewise not great (typically limited to the amount of money you paid them) - you at least have some data-governance guarantees around running on dedicated hardware - no multi-tenancy, no third-party access outside of the AWS operators who keep the HW running - but are very much not in the business of looking at your data.
I think this is mostly a function of what's at risk - when company valuations get into the 10s of billions of dollars, the risk of IP leaking into what could be seen as competitive companies (OpenAI/Anthropic would be happy to take over the world - I don't sense that AWS or Azure, are as ruthless in stepping on their customers business, unless of course they are a SAAS provider) is just too significant a liability to take - particularly when you can de-risk.
> Now that we can see their work, the approaches appear to be different. It is also worth noting that our latest model can solve many, many other math problems.
Is that a threat?
If that part of the PDF is true that’s so disgusting, psychopathic behaviour
> I said that if OpenAI released its result in the way proposed I would go public with what happened. The reply was, “Why would you ruin your career?” I replied that I am an academic, and asked why he thought going public would ruin my career. The reply was, “If you don’t want me to be nice, then I don’t have to be nice.” Some time later Levent received a text proposing that he and Sebastien speak one on one, saying, “I don’t know if Tristan is being fully rational right now.”
With "rational" being defined as "not making us look bad" at best, and "letting us take credit for their work" at worst.
Yes, that is disgusting.
This kind of coercive, threatening rhetoric is really not surprising at all. This is how tech companies operate.
What stands out to me is the naive lack of operational security on the part of academics, who should know better than to touch this SaaS crap with a ten foot pole.
I'm imagining all of the potential targeted customer lists now. Grab all those sweet .edu, et al logs without anyone thinking the wiser- until you release a stolen solution. What've they got on .gov?
It's the kind of thing that should make people think, but I wonder to what extent anyone does anymore when it comes to this kind of risk of a vendor stealing from you.
A wake up call for anyone using (openAI) chatbots : your data, ideas and execution can become their spontaneous 'inspirations' at any time - even if the LLM providers are 'just' using a meta concept monitoring system across all incoming user-data, running in the background constantly checking for 'lift-ables' for their company's bottom line.
> These two bullet points are extremely suspicious if you were honest
I don’t think we can consider these accusations separately from the evidence being unveiled about OpenAI’s culture by Apple’s lawsuit. These guys seem to openly embrace the strongest interpretations of “good artists copy, great artists steal.”
This is hard to argue without a fine understanding of how much insight OpenAI had about the stab at the problem from the "public rumor" alone.
If there was any sort of coarse insight that "they're trying to solve it this way", then both those things can be true:
- The massive amount of compute from OpenAI re-discovering Buckmaster's work solely from the coarse insight (and solving the rest as well).
- OpenAI still acknowledging they basically scooped the coarse insight using compute, and they're willing to credit Buckmaster.
Buckmaster says "Concretely, what Levent and I did was to take the Cordoba and Martinez-Zoroa program, which achieved blowup results with rough forcing, and, with a great deal of help from LLMs, push it to smooth forcing and to the incompressible Euler equations".
Could that simply be the prompt they used at OpenAI? How "stolen" would the proof be in that case?
> OpenAI says the model didn't access his user data directly, but leaves unanswered whether Tristan's chat conversations were part of the training.
This sort of cagey half-answer is highly suspicious and indicates that yes OpenAI did actually "access user data directly" because they are only willing to say that the "model did not access user data." That has a very specific meaning, the model looking up user chats, that they can defend.
So, everything we submit to OpenAI can be considered to be part of future models, right?
OpenAI says
> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models
That basically means, we don’t know, and we hope the model didn’t look up user conversations, and the best thing we can do is hope.
That’s seriously disgusting. I can understand why on a technical level why perhaps it is impossible to answer what exactly the model had access to, but it still is disgusting.
Every other paper in existence has been ingested with 99% of writers not knowing it will be retroactively used for training. But session data which is disclosed as being used in terms of service is disgusting?
If the work is duplicative/derivative then the preprints they put in sessions can be shown by the users and we can see.
What's disgusting is that they refuse to acknowledge what they and only they know: were these chats fed in to the new model that found these results?
Nobody would be disgusted at following stated policy, that's doesn't make sense, without first objecting to the policy. But you're bringing up distractions from the actual concerns: did OpenAI use the private chats and why won't they confirm or deny it?
> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models
it just means that they've been working with paraphrased user data everywhere, which any smart person can figure out is how anthropic and openai train on so called non-retained data.
How could they possibly know? If Tristan posted on r/math and they slurped that up as training data, that would count, no? They might never even know. I can’t envision any absolute statement by them claiming that they didn’t use his work that survives legal rigor. That is, this statement was never not going to be in this post in any of the infinite multiverses.
This is private work that is being done with Codex. Not drafts shared on r/math. I suggest you reread the article.
This is more of an expectation of privacy issue. If you write on an envelope and USPS has a copy, you have no reason to be mad; if you write on a letter inside the envelope and USPS still has a copy, you could rightfully be mad and say this is disgusting.
Isn't it obvious? Web scraping and even scanning written books is at record levels because the data is so useful for training. They are using every byte of user data.
If I were involved, I'd file suit and have them to at least not delete any proof.
> 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
well that sounds like an asshole move.
In a serious discipline like mathematics, this isn't just an asshole move, but a career-ending level of academic misconduct.
*In the old discipline of mathematics.
We are in new times, where capital and compute decides mathematics, so we don't give a shit anymore
What is your view on the proof of the Four Color Theorem?
Don't know enough about it to have an opinion, is it related to this somehow?
You implied you weren't a fan of capital and compute driving math. How would you feel about a result that required 1200 hours of time on a powerful mainframe computer?
I wonder what is required for it to cross the line into criminal blackmail.
From the company that likely committed federal crimes by hacking Hugginface
One thing that wasn't obvious to me or adults around me when I was younger: most laws define whatever acts a law punishes as individuals commiting to it, not as situations manifesting anyhow. It's not a murder just because someome died hit by a bullet you fired, but you have to have personally decided to kill that person leading to their death[1][2].
OpenAI's LLMs are not humans, and neither is the company. So by this logic, I think there's a chance that nobody committed a crime by hacking Huggingface, and also the chance that a lot of military and police organizational orders become illegal if OAI's doings would be illegal.
IANAL and all I have is a bucket of popcorns, though.
1: not a meaningful defense in a real trial, also gross negligence exists
2: this also explains insanity defense; if you were so out of your mind that you could not have held such a thought, it is considered out of scope for justice systems
> OpenAI's LLMs are not humans
Neither are guns. Which is why we punish the person shooting the gun and not the gun.
Industrial equipment, which is how i would classify LLMs, hurting people is nothing new. The relevant questions are:
- did someone intend it to happen?
- was someone negligent in taking reasonable steps to prevent something foreseeable?
The justice system doesn't punish people for legitimate accidents. e.g. if you are shooting at a shooting range, take all reasonable precautions, but someone was hiding behind the target, you are probably not guilty even if you shoot the guy.
As far as openAI goes, the logic is the same. The question is, was it intentional, was it unintentional but reasonable precautions weren't taken or was it truly an accident?
And the third time it happens, is that still just an accident?
The justice system relies on evidence not vibes.
I mean, they are going to be at least culpable for gross negligence, but who made the decision might become an interesting point of discussions(mainly in deciding precisely how they should be punched in their face and less in whether they should be at all).
> a career-ending level of academic misconduct
There is no such thing anymore.
Falsified data and published? Absolutely no problem. Keep your tenure.
It’s even hard to lose your position as president of a university due to egregious misconduct.
That's not quite right - Levent and Buckmaster did not actually have the Millennium Prize qualifying NS solution but something more limited. OAI invited Buckmaster to join and help rewrite the full solution paper but did not feel it was appropriate to invite an Anthropic employee to join as well - particularly given they were using internal unreleased models.
Could we expect otherwise from big tech?
Agreeing to partially credit is an admission that they used his work.
Something like this got Schmidt/ Jobs into serious trouble …
The last two points are disputed/sound significantly more reasonable in [0]. So from what I gather, Buckmaster realizes sometime during the call that the biggest result of his career is going to get steamrolled (the blowup of Navier Stokes is a much bigger deal than the blowup of 3D Euler), and on the other hand the openAi guys realize that they are basically talking about internal results with Anthropic and probably have to call corporate right after this call. Between these two stressor the conversation appears to have gone somewhat poorly.
[0] https://x.com/SebastienBubeck/status/2097379411691516310
I think this summary captures the interpersonal and cross organization dynamics nicely.
From OpenAI's post https://openai.com/index/navier-stokes-solution/
"Since August 28 we have been training a new internal model that has exhibited unprecedented performance in our benchmarks, including mathematics. This model’s training is ongoing and its performance continues to improve."
"When a further trained version of our internal model became available over the course of the effort"
"While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models "
But Tristan doesn't even want to be credited for the millennium prize--does he? He wanted to be the first to solve it and got scooped (which ig is not a great look for OAI ethically but also not forbidden). And the only reading for her of asking to remove levent must be in light of this offer (to credit him for millennium prize) right? It's not like they can ask him to remove levent from the main papers without this offer(what would Tristan gain?)
My guess is that OAI tried to be "generous" and offered to share credit on millennium with Tristan but not Levent. And Tristan got understandably offended by this offer (which probably oai felt like was the right thing to offer but they couldn't really offer to do the most ethical thing for some reason) and then the random conflicts and weird threats started.
my reading was that openai did not deny plagiarising the approach from their prompts.
openai then tried to effectively bribe buckmaster with a shared citation, whilst dropping his co-author who works for anthropic.
after buckmaster refused, openai tried to threaten him.
Oai denies looking at prompts but doesn't deny training on them.
if they do not deny training on them, they can't deny plagiarism.
By that logic everything any LLM spits out is plagiarizing the vast majority of work written prior to a few months ago. That doesn't seem like a useful or desirable line of argument to me.
Just replace the model with a human student.
"Training" on textbooks => fine
"Training" with unpublished notes from another professor, then publishing something on that exact topic with a similar approach without giving any credit => extremely questionable.
Presumably the professor voluntarily provided the notes in this analogy. I think the student would also be expected to cite the textbook if building off of it directly. In contrast, humans are generally not expected to cite "general inspiration" or what have you. So if we're to apply human standards, and assuming that the model was trained on the relevant work, it would only be plagiarism if the model directly built upon that previous work (at least IMO).
The trouble here is that if LLM training constitutes direct use then approximately _everything_ they output is blatant plagiarism, not just a few pieces of academic work.
Conversely if training is viewed as analogous to a student attending classes to learn general concepts (not a perfect analogy, I realize) then nothing they output on their own (as opposed to receiving as part of context) is plagiarism.
Thus this seems like a fairly useless line of argument to me as far as the current topic goes. It either implicates this academic work along with literally everything else or else it does not implicate this academic work. Kind of like nuking an entire city and then saying "mission accomplished, killed the bad guy".
This is just a nonsense line of reasoning. Training based on the solution to the problem (or the key insight behind the problem) is clearly a form of plagiarism.
What about my line of reasoning is nonsense? I made no claim either in support of or contrary to yours. Rather I pointed out that by this logic literally everything that an LLM spits out is plagiarism of the vast majority of the entire body of human literature in existence. Can you offer meaningful refutation of that observation of mine?
What does it matter? We're supposed to not call it plagiarism anymore because it's inconvenient to call it the plagiarism machine? What's your actual argument? Otherwise it's completely irrelevant what an LLM does in other contexts or what we call it
Many do indeed hold the position that all LLM output is uncopyrightable plagiarism. They're probably right, but there's an even stronger argument here:
Science papers of a phd level must contain:
1. one or more novel insights
2. a long list of citations to contextualize them and
3. some work to prove that the insights are in fact meaningful
---
In this context, consider a prompt based diffusion model which, when asked, will happily produce a few pictures of a horse in orbit. You then tell it "silly robot, horses can't breathe in space" to which it adds the necessary space suit in a follow up image.
That image is twice plagiarized:
1. the model did not come up with the original idea of putting a horse in space, nor with insight that horses need a space suit
2. the model failed to cite where it pulled the "horse" and "space" concepts from.
It merely did the work (3) to combine the concepts using the user provided insight.
---
The implied accusation here is that OpenAI used the insights from an existing prompt to train a new model that was able to one shot "a horse race in space" picture, and they were all wearing space suits.
This is still academic plagiarism, even if you disagree that all LLM outputs are.
I neither agree nor disagree that all LLM outputs are plagiarism. I merely objected that the line of argument engaged in was specious given the context.
As to your stronger argument. You only cite prior novel insights that you're actively building off of and that (approximately speaking) fall outside of the status quo. You don't for example cite leibniz or newton despite your paper making heavy use of calculus.
So is there any actual evidence that openai trained on the data in question? And further, did the openai proof directly build on someone else's novel insights as opposed to deriving everything from scratch? (I don't pretend to know but the vast majority of what I've seen so far in the comments here is what I'd characterize as brain-dead screeching. Certainly not the level of discussion I come to HN for.)
Separately, consider the implications of what you're arguing for there. Suppose your horse in a space suit picture were somehow valuable to society. Suppose that due to shortcomings of your tool you lacked the ability to readily and accurately identify the originators of the relevant concepts. Should you refrain from publishing this useful work due to the lack of citations? How are you supposed to handle this situation?
Remember that in this analogy everyone throughout society is on the same page that your tool consistently recycles other people's ideas while being technically incapable of producing reliable citations. The question is a simple trolley-esque problem - do you publish without proper citations for everyone's benefit and if so what are you supposed to say?
I am not engaging further. You asked for meaningful refutation of your observation, I provided one.
Academia has stricter rules than regular society.
The chats the professor had are not generic knowledge. And yes of course you still need to cite Newton and Leibniz depending on what result you want to mention. What’s allowed to be not cited are not status quo, the term you’re looking for is “folklore” results aka results that have been around so long that 1) nobody knows who came up with them or 2) everyone knows who came up with them.
The second point: if you say you can’t prove that OpenAI actually used it, it doesn’t mean that OpenAI did not use it. It’s hacker news not lawyers news here lol. And OpenAI can’t prove that they didn’t use it either. The whole point is that Levent felt he had reasonable suspicion to believe the AI did use the result, because he felt like without his input on an unpublished paper it was unlikely for AI to reach the same result. I haven’t read the paper so I don’t know where I stand on that.
On the last point, about your “for the greater good” argument. It’s higher maths lol. I don’t know about this field but I doubt it’ll be very useful for society. Maybe it’ll make one part 2x faster which makes some rocket cheaper to launch. Does the average person care? Debatable. I think it’s reasonable to hold published papers in proof based fields to a higher standard. Otherwise the current & future problems of ML engineer fields just expand to other fields. No thanks.
Finally, if you anonpost to the autistic Internet forum that everyone else is “brain dead screeching”, it really just says something about yourself lol.
Even if AI used the result, AI pushed it to the finish line while Levent and Tristan did not. But I understand the approach was different, the information leak was only that it was "doable".
The approach was the same.
evidence that openai trained on the data: they would have denied it if they didn't train on it.
did the proof build on the insights:
the influence of an individual text in the training data is deeply weighted by quality, relevance, etc. a high quality proof in advanced mathematics written by a codex user is going to get boosted to the max.
the model is post-trained on prompt material. that is again going to boost it.
the prompt will boost this material specifically. perhaps they even rammed dense maths in particular into the model in post training.
anecdotally i have been able to get near-verbatim copies of original material out of models at inference. the type of work that buckmaster and alpoge fed into openai feels like the exact type of concept that would cause an "aha!" or "but what if?" in chain of thought. in fact i would bet that their work is in the logs.
the likes of astra and fable are thought to be up to 10T parameters in size. i consider it highly plausible that a semantic representation of the euler proof could be pulled out of the model weights in good shape.
That's exactly the argument of the people calling it plagiarism machines. No-one ever really did refute it there was just a bunch of settlements for elite institutions so they weren't left empty handed like the various small time creators/authors etc were.
I think the bigger issue here is this feels like some PR smoothing happening that after all the work that went into "it's safe to use for enterprises" now we have what looks like openAI using private user data to scoop novel research and the question of why couldn't they do it for an enterprise with much more money on the line.
> now we have what looks like openAI using private user data to scoop novel research
Is there any actual evidence of that? All I've seen so far are empty accusations because "it would be in their interests" or whatever. Personally I'm inclined to believe that they honor their terms until it's demonstrated otherwise.
their terms grant them an irrevocable license to your data unless you specifically opt out of it.
To be clear, the accusation is that they trained on the chats they used while working on the problem. Not published work or even a preprint.
Your post does not distinguish, and it matters.
How does it matter? It either is or is not plagiarism. Ripping off a published textbook isn't somehow better than ripping off private correspondence. Both are serious acts of academic misconduct on account of the part where you knowingly and intentionally portrayed someone else's work as your own.
Note that I am not taking a stance on what openai allegedly did or did not do one way or the other. I am merely pointing out what I see as a fatal flaw in the line of argument presented by the earlier commenter - the idea that training on an item is on its own sufficient to establish plagiarism of it.
voluntarily is stretching it for an opt-out
Isn’t that one of the most salient and straightforward argument against LLMs?
Just overfit ad infinitum:)
as good academic conduct you may cite the source of the work you are quoting or paraphrasing.
as bad academic conduct you may steal someone else's unpublished work, work on it yourself for a bit, and then publish it as your own work. and then threaten the original author!
This is a common misconception, so its understandable that you have it. Generative models can both plagiarize and generalize. The question here is which of the two happened.
A needlessly condescending tone while failing to address the topic at hand. The person I replied to advanced the claim that training was sufficient to constitute plagiarism. You appear to be claiming that it is possible to generalize instead of plagiarize after training on something, so I take it that you must necessarily disagree with the original claim?
What I meant to say is that, in many cases, a generative model's output is not in fact steered by minor amounts by lots of training samples, but instead steered by a just few samples. Some outputs are influenced by many inputs, and some by very few, it really depends.
In answer to a post suggesting that training on a datapoint could mean plagiarism, you said that this would imply that all outputs are plagiarized. This is not the case, no, because generative models do not "copy" or "create", they do both at different times.
I did not agree or disagree with the original poster, I was explaining to you why I thought you disagreed with them. If you understand what I said above, then why do you disagree with them?
EDIT: I just saw your other post on "general inspiration" and I believe I read the situation exactly; you appear to believe that inputs used to train generative models get "lost in the parameter soup", but it is not always the case.
> In answer to a post suggesting that training on a datapoint could mean plagiarism, you said that this would imply that all outputs are plagiarized.
We read the original differently. As clearly stated in my previous reply to you, I interpret it as claiming that all outputs are necessarily plagiarizations of the training data. That is not my claim (as you wrongly stated) rather it is the claim I am responding to. I observe that it is absurd to object to a single action being a transgression on the basis of an argument which implies that all actions are inherently transgressions. Notice that nowhere do I take a position on whether or not the argument about all actions being transgressions is true or false.
> you appear to believe that ...
I do not, no. I have not taken a position of my own here. I've merely objected that the one I responded to does not make for a sensible line of argument in context. It seems that you (and many others) have read my objection to position A as support for position B and attempted to infer what I think from that.
I simply do not see how you can interpret "if they do not deny training on them, they can't deny plagiarism" as "all outputs are necessarily plagiarizations of the training data".
There is a difference between claiming an action is a transgression, and claiming it could be one.
At this point who knows? Maybe the agents got into the user data while no one was looking.
they're using a new model trained since the prompts happened. They are not denying the other group's solution may have been in their model weights, despite it being unreleased.
This definitely feels like the correct reading unless there is information we were not provided with. If the problem were unimportant, there would be no debate that this is not OK...
I was too slow to edit this post but I'm not sure why I said this. This is too assertive about a situation I don't know much about.
I think it's worse - openai didn't even deny training on their exact manuscript (when they most likely opted out);
Well, regardless of the drama, the interesting part on Anthropic vs OpenAI is:
- One of the two main persons work at Anthropic and "almost" or "partially" solved the issue, but eventually didn't succeed
- An external person with just an excerpt of the chat and certainly less versed in Mathematics (than these 2) tackled the problem.
There is little doubt that OpenAI is so much ahead and maybe the gap is even larger than what we see on Astra vs Fable.
Often with a hint on how to solve something, solving it is much much easier. It seems like that's what happened here.
Very weird behaviour from OpenAI, offering partial credit to on person, but not the other person involved. Trying to bully the mathematicians involved (see threats quoted upthread).
I suppose it's the sort of amoral behaviour we've come to expect from them.
I recommend that you read the linked PDF before drawing any conclusions.
This is sort of a weird interpretation:
> One of the two main persons work at Anthropic and "almost" or "partially" solved the issue, but eventually didn't succeed
- It wasn't an Anthropic endorsed effort.
- Solving this class of problem means a march of progress A -> B -> C -> D. If a student turns in a test that jumps from A -> D without showing any work they're either brilliant or cheating (probably cheating). Further, each step of progress isn't the same proportion of effort. What if moving from C -> D was actually the smallest contribution and just required a novel perspective to make the breakthrough.
This part is wrong:
> An external person with just an excerpt of the chat and certainly less versed in Mathematics (than these 2) tackled the problem.
- it was a whole team at OpenAI working on the problem
- it wasn't a chat excerpt, it was more like their entire git repo and project progress reports
> it was a whole team at OpenAI working on the problem
Well, a whole team plus $15 million in compute spend.
(That's what OAI would have charged for the same number of tokens.)
This should be a watershed moment for everyone using a commercial LLM. EVERY PIECE OF INTELLECTUAL PROPERTY YOU DISCUSS WITH IT BECOMES THEIR PROPERTY. FULL STOP.
It is impossible to fight against this. It is statistically obfuscated, they can just argue it is a derived work.
> After hearing of the rumor, OpenAI started researching Navier Stokes with a new internal model.
I don't think this part is accurate. OpenAI was researching Navier Stokes before. It's possible that they started on a new approach after hearing of Tristan's success, however that is not proven and I expect we will hear OpenAI's side of the story today.
You're right — the wording in the doc is that the "first prompt" was sent after learning about the rumor, although this might be the first prompt of this solution approach, not necessarily first prompt to any Navier Stokes solution.
In the PDF:
"The route to the Clay problem through a smooth force, options c and d in Fefferman’s statement of the problem, is the route Luis and Diego opened and the one Levent and I had quietly chosen to attack. Almost nobody else I know of was working on it. It is not the direction one arrives at in a few days by giving a model the problem statement. When I heard “forced,” it was a bright red flag."
Whether or not they were researching it before isn't the concern.
This seems unsupported. OpenAI has access to internal models that the general public doesn't have and a compute budget that dwarfs what an NYU professor would have.
it's very possible they only had to use the massive compute budget because they were trying to plagiarize his work before he published it though, e.g. autonomously do things in ~7 days what he had likely been thinking about for ~1 year.
This doesn't really make sense. You don't need massive amounts of computing to plagiarize something.
The most nefarious explanation seems to be that they got wind it was possible to solve NS via LLMs and perhaps a small nudge in the right direction.
Of course you do if you're a) only given a partial solution b) racing against someone else using a competing AI.
The open question was whether their LLM got the nudge in the right direction because it got access to the chat somehow (e.g. automated training that scraped his chat logs) or just a high level "Navier stokes can be solved through LLM". It sounds like the former may have happened although right now we just have an accusation and a weak denial.
> You don't need massive amounts of computing to plagiarize something
The compute was used to leapfrog the human team, using their ideas and pushing them to a solution of the general problem.
Plagiarism isn’t being used in the literal sense.
wasn't it reported elsewhere that they used the equivalent of $22M (street) in Astra tokens? obviously it's not the same when you own the machinery but still.
Sama himself has now confirmed OpenAI started researching NS after the rumor.
"It is true that we tried this because there were rumors on the internet last week that Anthropic's models had solved a millennium problem and we were curious if ours could do it too."
https://xcancel.com/sama/status/2097385167002415140
It seems exceptionally unlikely to me that OpenAI would be "reading user prompts". More likely is a leak somewhere else. Obviously Anthropic/OpenAI are engaged in espionage stuff with each other. I am guessing Levent just mentioned something to someone at Anthropic and it got out.
why is this downvoted? do people really think OpenAI is snooping at people specifically? like they are looking for good leads into new problems or ideas and they found this guy's codex thread and used it? come on man, even for conspiracy theories this is stupid.
this is a highly marketable problem and specific teams at OpenAI were aware of specific competitor efforts. I would be surprised if this were happening on a large scale, but
1. Less than a hundred people in the world are working at this problem, 2. A significant fraction of those happen to work at competing hyperscalers, 3. Those hyperscalers repeatedly show themselves not to take user privacy seriously
I'm not sure what your points 1 and 2 have to do with anything. Both directionally increase the probability of hyperscalers also finding the solution independently.
> Those hyperscalers repeatedly show themselves not to take user privacy seriously
where? Any examples?
Have you been living under a rock? None of the big tech companies care one bit about user privacy in the US.
That's not an answer.
Any degree of tracking what people do is unprivate. Every single web interaction you perform is tracked. All LLM companies store all your conversations by default. Do you need more examples?
It's one of those questions that sets the bar so low, the conversation might as well not be taking place
Yes that sounds like something openAI would do to me. Not that they’re just looking through random professors chats but they heard buckmaster made progress on navier stokes and decided to read his chats.
> https://openai.com/policies/how-your-data-is-used-to-improve...
They explicitly say that they use your "content" to improve their models. Considering they practically have infinite compute at their disposal, why is it surprising that they would look for juicy data in there to make them look good ? When they ingested basically the entirety of human knowledge without regard to the rights of others, when they burn books by the thousands, when their relentless barrage of bots have rendered the Web borderline unusable, why would they stop at that line ?
Yes, that would be par course with OpenAI behavior
Even if they claim not to use it, they're probably using it and hoping they don't get caught. They have zero ethics or morals, they just want to "win" to get mega-rich.
> do people really think OpenAI is snooping at people specifically
yes.
Rules and laws are for the poor.
Obviously, yes
> do people really think OpenAI is snooping at people specifically?
I'd be shocked if they weren't
Of course they are "reading user prompts" in the sense that it's being used to further training. That's why you have to pay up to opt out of that.
That's also why they refused to answer that question: the answer is obviously "obviously"!
if training is on, they are reading user prompts. training is on by default.
In other words...they should have used Bedrock...
> but only if they remove Levent as an author, as he works for Anthropic.
What a terrible look for OpenAI to die on such a tiny hill right there. I wonder whether Anthropic would have made the same requirement.
well they didn't really die on the hill. the NYT headline is still "OpenAI says it has cracked one of math's millennium problems" and the whole article doesn't mention this controversy. Normies don't know what NS is and don't care, they'll just see "wow OpenAI is the best I guess"
I don't understand the desire to remove Levent. "Off the clock, when Anthropic engineers want to break new ground, they use ChatGPT" sounds like a great ad.
All these small details will be forgotten in less than a year. But association "Navier-Stokes -- OpenAI" will be part of the history. In my opinion, they are thinking about long term PR here.
That association seems like it will survive the actual names of the authors, regardless of who they are. But I'm not a marketing person.
people are so greedy to have their name on something forgetting a) human progress is shared through its cycle. people build upon eachothers ideas and knowledge. and b) all these models consist of information stolen from others. Who really solved it if all u did was prompt some illegally obtained repository of data..??
Its like saying you won the car race, but you stole the fastest car and had your m8 drive you around the track.
To build on this, is it correct to say ANY training on data from any individual originating human deserves to be cited and attributed on the solut6paper?
I wonder whether these bickering users (of AI various products) with math degrees are missing the forest for the trees.
> - Levent works at Anthropic, but this research was independent of his work there, with a mix of GPT and Claude models.
One minor wrinkle in Alpöge's narrative, he refuses to deny that he hasn't used any non-public Anthropic models for his "independent" research.
https://x.com/giffmana/status/2097560503581069585
its what all LLM users have all been doing, profiting off others' IP through a number cruncher, while relinquishing their own
I haven't seen any proof that OpenAI asked Tristan to remove Sebastian from the prize. Until we have proof of this, it would be wise to offer conclusions.
Same for NS validity. This was not validated by the community yet.
you can read it in buckmaster's document.
And OpenAI confirmed it!
what would such proof look like? It's not like allegations are written in Lean
please could you change 'drama' and 'accusation' to something more formal like 'allegation'.
the paper makes a very serious allegation of dishonesty and possible academic misconduct.
the governance and integrity of openai is of importance to the welfare of society. this is not a matter of drama.
The [lack of] integrity of OpenAI (and any other frontier lab) should already be pretty solidified. Among other horrible things, these companies stole millions of IPs and no one seems to care anymore. Regardless of what you think of the product they are making and the success of ai/its impact on humanity, these companies objectively do not have much integrity.
How do you feel about the integrity of the machine learning researchers over the past twenty years who trained models on scraped internet data that weren't particularly powerful and didn't attract any attention?
i think that this case, if they did train on buckmaster and alpöge, amounts to an attempt to steal the millenium prize, bypassing all attribution.
legally speaking, the default privacy notice gives them an irrevocable license to your content. they may read and use the prompts for research. so it is very possible they simply stole the navier-stokes solution.
that is the same principle as any other prompt but this would be a concrete example.
there would be some difference between simply giving the model some prompts to read, which they are entitled to do on the default policy, and putting it into aggregate training data.
If they scraped internet data in the same way as current day frontier labs do, then I feel the same exact way about them. Why would I feel any different if that is the case?
My point is that researchers and academics really have been doing this for decades - it's the reason projects like Common Crawl and LAION exist.
I think it's notable that nobody was calling out those researchers for their lack of integrity, because the systems they were building did not seem like a threat to anyone.
OpenAI etc get accused of a lack of integrity on this precisely because the systems they are building work, and are profitable.
My personal opinion here is that integrity is more about what you build with the data. I think saying "scraping means you lack integrity" is a simplification.
you massively collapsed what AI companies have been doing by comparing it to old internet-scraping. Facebook flat-out admitted that they scanned copyrighted books for their AI. The image generators most definitely trained on copyrighted images.
LAION and Common Crawl both scraped copyrighted images. From what I can tell (I'm not an expert in this domain at all), the main difference between those two and frontier labs is in how they stored and used the data. CC and LAION seem to be actually open (unlike "Open"AI) and are more centered around publicly sharing the data they scrape to support research and innovation.
OpenAI et al also stole everything from everyone. But then they raised billions of dollars from that data and sell back their LLM to people (again, among other things). They are also very much NOT open in any way, aside from sharing their benchmarks of new models.
Personal two cents, I have friends whose music work posted on YouTube were scraped to be in LAION-DISCO-12M, so yeah not very open.
What I meant more is that the dataset they scrape is openly available for download by anyone, unlike any of the frontier labs. Not that they don’t scrape copyrighted content. Still sketch, but at least they don’t call themselves “OpenLAION”.
Also my understanding was they’re not storing the actual music, but the metadata and a link to the YouTube video.
Common Crawl is text-only.
Anthropic too, and evidently others. Amazon were recently confirmed to be doing the same thing: https://www.404media.co/we-tracked-a-shipment-of-rare-books-...
And that’s bad, right?
It's legal. I wouldn't do that myself, but I guess that's why I don't train models for a frontier AI lab.
The thread is not really about what's legal; the topic is integrity. It sounds like, based on the fact that you wouldn't do it yourself, you agree that it's not a good thing to do.
You're right, it was an over simplification. I think public exchange of data is great for innovation and research (Common Crawl/LAION). But I still think scraping proprietary data without consent or attribution is generally bad (also Common Crawl/LAION).
Then you have OpenAI etc.. who build these multi-billion (trillion??) dollar machines and sell them back to people, using everyone's proprietary data, and (among other things) tell everyone it's going to take their jobs. That combination of things doesn't scream integrity to me.
Still, it's undeniable that these machines could be beneficial for humanity (cancer research and such). So, I'm sure many people would say the good out-ways the bad. I don't know. Seems that would set a risky precedent for future companies, but maybe not.
> who trained models on scraped internet data
The strongest complaint is that they trained on a huge corpus of pirated copyrighted works.
It’s a large step above “scraping” and well into the “everyone acknowledges this is illegal” territory.
Did I read openAI and integrity in the same sentence? The whole business is built on plagiarizing human knowledge at scale
Thanks. I was pinging some people near the mentioned Córdoba to see if they had any insights, but no extra info yet...
You should call El Niño, he lives close to the Mexican border and is at home after 6...
Well people you fail again...I am sorry for you....
"Mr A. Nino weathers a storm of protest" - https://www.independent.co.uk/news/mr-a-nino-weathers-a-stor...
I was kind of okay with the sequence until:
"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."
There it is.
Nobody "owns" math but that's petty and shitty.
Ignoring the drama, when can we expect the lean proof of this great sensational discovery?
> Ignoring the drama
But the drama here is a little important. Stealing the millennium prize for N-S is sort of a big deal, especially to those who had been working on it for the last few years.
Attempts to steal $1,000,000 for a solution to Millennium Prize Problem have become a tradition, apparently.
The math is all that matters.
That's a very sad way to look at this
Math, like any other human endeavor, doesn't exist until someone is motivated to invent it. The laws of the universe aren't understood until someone is motivated to discover them. So it might be worthwhile to not completely ignore discussion about incentives.
Both mathematics and the laws of the universe exist way before any understanding kicks in
I tried to word my comment carefully to avoid pedantry, but alas.
I don't think everyone agree with your notion that the language and tools of mathematics aren't human inventions.
Math is largely performed in collaboration. Collaboration requires trust. If people like you had their way, we would lose trust, therefore collaboration, and therefore progress.
So if math is all that matters to you, you should care about this.
A hundred pages of impenetrable brute forced Lean would advance the field much less than something elegant and human understandable, perhaps relying on some new clever spark of innovation that might inspire new areas of research.
Particularly if the first proof being "solved" thanks to piles of money and compute for self-serving marketing discourages the mathematician who might have otherwise devoted years of focus to reach the superior proof we will now never see.
Obtaining a finite-time blow-up for Navier-Stokes does not necessarily advance the field of mathematics by any significant measure, whether the proof is very long or very short.
As a concrete example, such a proof could be less than a page with very specific initial and boundary conditions and inserting them into the equations to get something that goes to infinity when time goes to some finite value.
This would resolve the Millenium problem but not make humanity any smarter.
https://mathstodon.xyz/@tao/117207849921390904
Tao agrees.
What do you even mean by that? It is the human value?
Boosters have posited this conjecture since the beginning: “who cares how a proof comes about, math is math, the proof is all that matters”.
Regardless of mathematicians stating the methods outstrip the proof’s importance, still amazing we got an explicit social counterexample as well so quickly.
right on release for both? such a strangely pointed question, as if it wasn't customary by this point...
It's here: https://github.com/openai/NavierStokesAndEuler