On the Navier–Stokes Millennium Prize Problem (openai.com)

1259 pointsby tedsanders16 hours ago1004 comments

Further discussion:

https://simonwillison.net/2026/Sep/8/on-navier-stokes/, https://news.ycombinator.com/item?id=49621697

https://twitter.com/sama/status/2097385167002415140, https://xcancel.com/sama/status/2097385167002415140

arctic-true 16 hours ago

Buried under the drama is the fact that OpenAI is claiming that an internal model they’ve been training for less than two weeks is more than twice as capable in mathematics as Astra, which was only made public a week ago. Even if this improvement is limited to mathematics, that is an astounding feat.

naveen99 16 hours ago

Astra was trained more than two weeks ago.

sashank_1509 16 hours ago

Astra was in use by OpenAI employees for more than 3 months internally from rumors I heard

credit_guy 15 hours ago

The internal model they mention is different from Astra.

chinathrow 16 hours ago

Pre-IPO marketing?

jrflo 16 hours ago

I'm so tired of this "It's just marketing!!" commentary. An AI model just proved one of the top 3 unsolved problems in mathematics, they have a Lean certificate showing it's valid. How much more evidence do you need that these models are actually highly capable?

QuesnayJr 16 hours ago

Of the seven Millenium problems, Navier-Stokes was the one most thought to be in reach.

I'm not sure what the top 3 problems are. You can make a case for the Riemann Hypothesis and P != NP, but I'm not sure what #3 would be. Maybe the Langlands program? (That one is not as precisely stated as the other two.)

anthonypasq 15 hours ago

the goalposts are on Pluto at this point.

dsdf3 15 hours ago

I'd put good money on the fact that we will have a lot of distilled intelligence and yet the world won't look much different.

anthonypasq 15 hours ago

i mean that is already true

QuesnayJr 15 hours ago

I'm not moving the goalposts. I haven't heard anyone, ever, refer to the Navier-Stokes problem as a top 3 problem in mathematics. People were saying that they thought the solution was in reach a few years ago, before AI was at all capable of research-level mathematics (and the expectation that there was a counterexample).

I am not particularly skeptical of claims about AI, compared to the average here on HN, but that doesn't mean every random piece of hype is warranted. What they did is impressive, even though we now know the only reason they threw so much compute at the problem is that they heard a rumor that someone else was already close. Navier-Stokes is not a top 3 problem in mathematics, and it was the one that was thought closest to being solved.

ameliaquining 15 hours ago

There were also some people talking about the Hodge conjecture, because it has some similarities to some LLM-assisted breakthroughs that were considered impressive in the distant past of [checks notes] July 2026. See, e.g., https://xenaproject.wordpress.com/2026/07/20/human-mathemati...

QuesnayJr 12 hours ago

I brought this up here at HN, and in the ensuing discussion Buzzard himself replied saying he was somewhat joking (https://news.ycombinator.com/item?id=49011950).

ameliaquining 12 hours ago

Certainly, but the key word there is "somewhat". Progress is now happening so incredibly fast that I no longer know what to consider implausible.

mrbungie 16 hours ago

They are highly capable, no doubt about that, but:

1) We don't really know how they arrived to this result except that they had a lead and that they threw millions of compute at the problem. The article is written in a way that makes you believe that it was just an agent loop with little human intervention, but without any evidence.

2) If the threats are to be believed, it is concerning how far they are willing to go to show how capable the model is. One would think their products and credibility would be enough to speak for themselves.

dsdf3 15 hours ago

"2) If the threats are to be believed, it is concerning how far they are willing to go to show how capable the model is. One would believe their products and credibility would take by themselves but here we are."

Personally I anticipated nefarious behaviour as part of a broader marketing strategy to sway the view of those in the west that american frontier offerings were far better and powerful than that of China - that if you did not purchase their offerings you'd be awake every night worrying your competitor was.

And this is boring - they need to admit at some point they misinvested, Anthropic less so. All this math stuff is great... but hello? The largest market cap companies are valuable irrespective of such amplified intelligence.

scurnus 15 hours ago

1) The article is written in a way that states clearly they threw a lot of compute at the problem. In api cost millions of dollars. 2) Millenium Problems have been the goal every AI company wanted to achieve since their diffusion, all companies have thrown a lot of resource to solve these problems, as they are very famous and scientists spent a lot of time trying to solve them. The first company to solve it will remain in history, despite all of you finding excuses about it.

Regarding product and credibility normal people have a completely different view about LLMs, most don't even know difference between models and probably don't even care about Millenium problems, but care instead if chatgpt can solve their day to day problems. This is just them trying to have the throne on the AI companies space, outside it this result won't matter.

mrbungie 15 hours ago

> 1) The article is written in a way that states clearly they threw a lot of compute at the problem. In api cost millions of dollars.

Did I say otherwise?

> 2) Millenium Problems have been the goal every AI company wanted to achieve since their diffusion, all companies have thrown a lot of resource to solve these problems, as they are very famous and scientists spent a lot of time trying to solve them. The first company to solve it will remain in history, despite all of you finding excuses about it.

I know, but I don't know how that relates to my point, which is about the way they are doing it.

scurnus 14 hours ago

Sorry, I misinterpreted point 1), on X they said they didn't have people specialized in that specific field for prompting and steering the agents, just a group of mathematicians and physicists.

The way they are doing it is by trying to get the attention and staying on top of the news, it is a game they are playing that benefits both OpenAI and Anthropic. The more people discuss SF drama, the less attention Chinese Labs and others get.

andrepd 14 hours ago

Lmao my friend, the whole "drama" is that there are allegations of plagiarism.

danielmarkbruce 12 hours ago

Highly capable of writing math proofs, no doubt.

It's really unclear that this entire line of work (training LLMs for proof writing) has much real value outside of writing math proofs. It is reasonably clear that, similar to Deep Blue at the time, people are extrapolating the results to general intelligence because the people who usually write proofs are insanely smart (just like world class chess players).

eutropia 15 hours ago

If pre-ipo marketing pushes them to train a model capable of resolving a millennium problem in mathematics in a weekend, then, to quote XKCD:

  "Mission. Fucking. Acccomplished."

https://xkcd.com/810/

Aboutplants 15 hours ago

Even if it is, Anthropic better have a few things up their sleeve

chilmers 16 hours ago

The implication from their last couple of published articles[1][2] is that they think they’ve achieved “recursive self improvement”.

[1] https://openai.com/index/research-acceleration-view-inside-o... [2] https://openai.com/index/an-alien-mind/

10xDev 15 hours ago

Compute will always be the bottleneck even if this were true.

Miner49er 15 hours ago

Eventually recursive self-improvement includes reducing bottlenecks.

10xDev 15 hours ago

Eventually the bottleneck might be people themselves.

ccozan 12 hours ago

Improbably, the real bottleneck is energy.

glenstein 14 hours ago

Which is to say, scalable and open-ended capability of ramping up physical infrastructure.

I don't know that that's achievable yet. Though the era of increasingly advanced and automated robotics seems to be around the corner which could create a cycle, vicious or virtuous depending on how you feel about it.

Fordec 15 hours ago

If humans can figure out to optimize to circumvent bottlenecks, I have no doubt each new bottleneck will also get routed around, just now automated.

dakolli 14 hours ago

How do you automate the mines to get the raw materials to make the compute from, and build additional fabs that take a almost a decade to stand up. You're actually delusional.

Fordec 14 hours ago

Hello good sir from the 1700s pre-industrial revolution who doesn't think that mines and factories can be automated.

dakolli 10 hours ago

The factories that supply the equipment, maintain the equipment, the energy inputs, the financials of those mines are not automated.

People on hackernews are actually some of the dumbest people on the internet. This place is worse than lesswrong.

scott_weber 4 hours ago

The question of whether something can be automated is distinct from the question of whether it is currently automated. Things can can be automated may transition to being automated in practice in the future as technology improves and investment deepens.

a2ff6eeb0 13 hours ago

https://en.wikipedia.org/wiki/Lights_out_(manufacturing)

Scroll down to the existing examples section.

7373737373 12 hours ago

Some mines are already heavily automated: https://youtube.com/watch?v=_Z9w-mUoUsY

https://youtube.com/watch?v=SRuht0QIprs

mrbungie 14 hours ago

We are not in an everything-has-an-API world yet, and it'll for sure take some time to get there.

Fordec 14 hours ago

For sure. Anyone who thinks that we're in the end state of what progress can be made simply lacks imagination. This is all going to keep changing and iterating for the rest of our natural lives. The only constant is change.

combobyte 4 hours ago

I'd argue we've been in an "everything-has-an-API" world for a long time now — it's just that discoverability of said APIs is still crap.

classified 4 hours ago

And since LLMs are apparently good at circumventing the absence of an API, there's not much incentive to add them now. APIs are for humans. LLMs just break through all the captchas and anti-bot measures.

HenrikPontoppid 14 hours ago

Yes. In other words: the singularity. I'll only believe it when I see it though.

Fordec 14 hours ago

I'm coming around to not liking the term singularity, it implies an endpoint or finish line rather than something that just keeps continuing and evolving.

supern0va 13 hours ago

It doesn't imply that. The singularity is just the inflection point.

jsLavaGoat 13 hours ago

Singularity and inflection point are incompatible mathematically and in the plain sense, it really is focused on a particular moment and always has been, hence the term.

And it's definitely supposed to imply some kind of historical discontinuity not a change in convexity.

Fordec 12 hours ago

Which assumes the presence of an inflection point that keeps inflecting rather than revert to an S-curve. The growth model is not borne out yet to declare what shape it is.

piloto_ciego 9 hours ago

I've done a lot of thinking about this since I first used ChatGPT to write some BS jinja2 templates hours after I first play with it. I said to my friend then (who scoffed at me) that "man, this is incredible, I think we're in the foothills of the singularity! This is insane! Sure it's stupid now but I can't believe this is even possible!" That friend is so black pilled and bitter he now hates AI. Whatever, I can't fix that, but the current progress is astounding.

But thinking about the geometry of this problem helps understand why people aren't adjusting well to this. While we're walking on the curve, we look at the rate of change of the curve and say, "well, yeah, of course, dy/dx is 5 at this point and was 1 at the point a few years ago, because the curve is getting steeper" but we're always going to feel this way as things rip off into the stratosphere because dy/dx(e^x) = e^x.

From standing on the curve the curve is notably seeper, but the steepness totally makes sense to you. It's only when you look back 10 years or so that you think "wait a second, holy hell, I couldn't have imagined this!"

The first time I really (I mean really) thought about the singularity and AI was in roughly 2014. I mean, yea, I'd thought about things before that, but yeah, before the Humans need not apply video, I'd never actually given it much thought. I think back to myself 10 - 15 years or so ago, when I was just starting to tackle real programming projects, and was just starting to get decent at writing code, there is no way on earth that I would have imagined that a little over a decade later, Navier-Stokes would be solved by a computer program and the vast majority of my work would be playing sooth sayer to increasingly complicated piles of linear algebra.

dekhn 7 hours ago

From the perspective of those who don't pass through the singularity to the other side, it is an endpoint. You would have no context or ability to understand a singularity transition. Really, the term is just a placeholder for "event we cannot comprehend due to limited intelligence".

JumpCrisscross 6 hours ago

> coming around to not liking the term singularity

Bit ironic given the model’s alleged finding…

Singularities are model breakdowns. A singularity simply says our current methods cease to work in this region. Within the context of a recursively self-improving intelligence with an unknown bound, “singularity” is probably a good description of our current socioeconomic system.

monster_truck 14 hours ago

Based on the leaps in local inference speed in the past month, which have been absurd, I'm p confident we're going to whiplash from compute constrained to storage constrained.

Bit apples to oranges, but it reminds me of all the fiber we installed in the late 90s, certain that per-strand capacity increases were years or decades out, only to get massively rugged

Fordec 13 hours ago

I expect the investments into AI driven mathematic discoveries that underpin compression efficiency will be a key investment area. Particularly at the data center scale rather than per device or per file level.

xtracto 13 hours ago

pi-fs will solve all our data compression problems.

monster_truck 9 hours ago

It's not going to be enough. The naive approach of a project I've been working on was pushing >10gbps over the local network, after a ton of work I got it back down under 1... and now it's processing so much more shit that I'm almost past 5 again! It compresses at >3:1 but the latency hit isn't suitable.

I get the impression the only reason there is renewed interest in photonics is because DCs are simply out of room (and power) to rack more servers and switches.

Fordec 8 hours ago

I 100% agree with your impression. For a good while to come there's going to be a bunch of Jevons Paradox to all of this, but adoption of architectural changes like that photonics adoption is exactly the type of adaption to circumvent bottlenecks I'm referring to. We're going to hit hundreds of bottlenecks and each one will inevitably breed new approaches and technology directions. And the forcing function won't be talking about them, but implementing them, seeing who wins and taking lessons.

hgoel 13 hours ago

As a statement of fact divorced from context, this is of course true, but it's worth putting it in context of what small-medium scale models have been achieving recently. Many of the most recent releases from Chinese labs are almost on par with trillion parameter models from less than a year ago (edit: despite being small enough to usably run on prosumer hardware). It seems clear parameter efficiency can still be improved dramatically.

In which case, maybe we don't need as much compute as we might expect. I hesitate to say "to reach a singularity" because it's kind of hard to define how that works out. Even intelligence probably hits some scaling limits eventually (e.g. speed of light related restrictions on how far it can scale, or how quickly it can expand).

lijok 13 hours ago

And the goalposts move again

noir_lord 10 hours ago

Recursive self improvement of their upcoming IPO value maybe.

They are fluffy PR pieces otherwise.

piloto_ciego 9 hours ago

How can you possible say this sort of thing in context of what looks like a millenium prize being solved.

I swear there's nobody blinder than those who won't see.

samrus 9 hours ago

You have to look at the incentives

FallCheeta7373 8 hours ago

Incentives are one thing, even adjusting for them it's huge, and I don't understand this incentive play for only openai, academics have perverse incentives too, to overreport, overclaim, publication bias etc why are we scrutinizing AI industry to such high degree when they have demonstrated capability and often times are off by a model release at worst.

altcognito 8 hours ago

I swear to god, people would look at the successes of Xerox palo alto and just shrug and say - "yeah, but I mean, this is all marketing"

piloto_ciego 3 hours ago

This is what I keep saying, and it feels like I'm taking crazy pills here!

Is nobody else astounded by this?

aurareturn 5 hours ago

A working Lean proof doesn't care what the incentives are.

medler 7 hours ago

Because it seems like most of the work may have been done by human mathematicians and cribbed by OpenAI at the last minute

dekhn 7 hours ago

We don't have enough accurate knowledge to say that, and it doesn't seem to be the case at all.

timr 5 hours ago

> We don't have enough accurate knowledge to say that, and it doesn't seem to be the case at all.

The first part of your sentence literally contradicts the second part: "we don't have enough knowledge to know, but I know the opposite".

dekhn 5 hours ago

Only if you interpret statements as being binary logic.

"seem to be" carries semantic meaning here: I'm stating my interpretation of the situation based on data we have available (which is limited) and my prior.

Put another way: "We can't say that for sure, but my money is on it not being a simple case of intellectual property theft"

classified 4 hours ago

> not being a simple case of intellectual property theft

No, it's an aggravated case, since it's the same way they got all of their training data in the first place.

timr 3 hours ago

Yes, you were guessing. That's the only thing you could be doing, since, as you said, nobody actually knows.

classified 4 hours ago

> it doesn't seem to be the case

Based on what? Your crystal ball?

tomalbrc an hour ago

I. fucking. Wonder. Why.

https://news.ycombinator.com/item?id=49607239

AlexCoventry an hour ago

I don't think we should assume a millenium puzzle has been solved, yet. Astra showed impressive capacity for cheating when it was faced with impossible cybersecurity challenges. It seems equally plausible at this stage that it's found a bug in Lean.

selfmodruntime an hour ago

This comment was applicable 2 years ago. It isn't any longer.

camel-cdr 5 hours ago

I found this post interesting in that reguard: https://www.lesswrong.com/posts/thXohzXrWCA2EhZCH/mateusz-ba...

magicalist 16 hours ago

> Buried under the drama is the fact that OpenAI is claiming that an internal model they’ve been training for less than two weeks is more than twice as capable in mathematics as Astra.

Is this buried under the drama or are the major OpenAI twitter accounts from the people involved in the drama desperately attempting to make this the story after everything else obviously got away from them?

ameliaquining 15 hours ago

I don't know what anyone's been saying on Twitter and I don't care. If it's really true that there's a model out there that's that capable two weeks after the start of training, then that's objectively a much bigger deal than a priority dispute, even if the latter involves juicy allegations of espionage and skulduggery.

20k 15 hours ago

It isn't a priority dispute, the more concerning allegation is that OpenAI may be training their models on prompts that mathematicians were using to solve this problem, and then surprise surprise OpenAI were able to replicate that work in their latest model

What we're really looking at is seemingly a massive plagiarism scandal, which especially brings a lot of the past results into question

If OpenAI is training models on researchers' prompts, and then threatening them into staying quiet about it, who knows if anything that's been announced is genuine - or just theft?

Edit:

OpenAI have admitted they were training on prompts at the time they made their breakthrough

https://mastodon.social/@tristanbuckmaster/11723647135247030...

ameliaquining 15 hours ago

If you're alleging that they don't actually have a highly capable model and the work they're attributing to it was actually plagiarized from human mathematicians, well, that would be big if true, but I'd be inclined to take the other side of that bet. With most previous splashy AI results, others have subsequently used the model to do other things around the same difficulty level. Also, it would still be necessary to explain why all these famous open problems are suddenly falling like dominoes, if it's not AI solving them.

If you're saying that the question of whether they actually have a highly capable model is less important than the question of whether there's a plagiarism scandal, I continue to disagree.

20k 15 hours ago

The issue is that if OpenAI is training on prompts generally, what we really have is the first fully automated luxury plagiarism machine. In that it isn't able to genuinely solve problems, but merely steal the work that other mathematicians have been putting into prompts, and regurgitating that to other users as its own work. That makes them incredibly less useful as research tools

The fact that this plagiarism scandal exists underpins the idea that there's actually a mass theft going on, and that these models aren't nearly as capable as is it would seem

lotsofpulp 15 hours ago

Do OpenAI’s T&Cs that users accept not allow them to train on prompts people enter into it?

20k 14 hours ago

OpenAI's T&Cs let them steal your children I'd suspect, that doesn't make it morally correct

lotsofpulp 13 hours ago

Why would you suspect that? Stealing children is illegal, and involves violating the rights of unwilling parties, whereas prompting openAI (or any LLM) is a business transaction, in which the transfer of money and data is legal.

fwip 10 hours ago

Terms and conditions are almost entirely about the company doing things that would otherwise be illegal.

orangecat 14 hours ago

In that it isn't able to genuinely solve problems

Yes, in retrospect I should have been suspicious of that drone hovering outside my window when I was writing down the counterexample to the Jacobian conjecture.

This is just not a reasonable take. Even if OpenAI is maximally guilty here, the work that they "stole" was also largely done by AI.

20k 14 hours ago

I mean, its years worth of hard work by multiple researchers it would seem, which OpenAI simply lifted and claimed as its own. These researchers weren't just letting OpenAI burn tokens while sipping martinis on a beach

letmevoteplease 13 hours ago

You are confusing ideas here. No one except OpenAI had a solution to Navier–Stokes. Buckmaster and Alpöge had a solution for the forced Euler problem, which they arrived at largely using LLMs (Claude and Codex). Buckmaster implies (but does not explicitly accuse, since he has no evidence) that training on his prompts had some influence on OpenAI's result. This seems unlikely to me but is not impossible. However, in either case, the solution was found due to an LLM. Of course the LLM built on past human work, but "plagiarism" is not sufficient to account for the distance between the papers of Martínez-Zoroa, or the prompts of Buckmaster, and the final resolution.

ivory54321 14 hours ago

I agree that it is plagiarism in this case however it opens up the question of if there value in a system that can take the thoughts and discreet semi-complete parts of work done across different researchers, in different locations, in different fields and connect the dots to solve real world problems and produce novel research. Is this not standing on the shoulders of giants?

Timwi 12 hours ago

If it could do this while properly crediting the researchers (the “giants”) it would be a different matter.

sdenton4 13 hours ago

Remember the Huggingface incident, where a model tasked with an impossible problem, got loose, set up secret message boards, and hacked another company to try to get at the answers?

Now: Could Astra agents have hacked their way into the OpenAI logs to find human mathematicians with a good lead on the problem to build upon? Certainly doesn't seem impossible.

doctoboggan 14 hours ago

I think all he big labs are pretty explicit about when they do and don't train on customer prompts. Is the accusation here that OpenAI trained on prompts when they claimed not to? Or were the mathematicians using one of the interfaces that allows OpenAI to train on the customer data?

user43928 13 hours ago

All that I have seen OpenAI employees "admit" is that if you press the Thumbs up button on a response, this can be used as a signal for training.

That's it. The rest appears to be wild speculation.

jsw97 13 hours ago

Yeah this is a land mine. Even if you opt out of them training on your conversations, giving “feedback on a new version” or answering “how are we doing” or whatever can slurp up all relevant context, which if you think about it can probably be construed to include memories, into the belly of their flying saucer. At least the last time I checked their terms.

Never ever touch those requests. If you get a side by side comparison just resend the prompt.

TZubiri 12 hours ago

>It isn't a priority dispute, the more concerning allegation is that OpenAI may be training their models on prompts that mathematicians were using to solve this problem,

I don't want to get epistemiological, but these aren't allegations, and your use of "may be" is more of lack of knowledge on how OpenAI and ChatGPT work. Read the Terms of Service, this is not a secret, OAI doesn't deny it, usage of ChatGPT through the web interface or through its App, including Codex, are shared with OAI and used to train future models. This is one of the ways in which ChatGPT works and improves, welcome to the subject.

TZubiri 12 hours ago

>It isn't a priority dispute, the more concerning allegation is that OpenAI may be training their models on prompts that mathematicians were using to solve this problem,

zem 12 hours ago

even apart from the plagiarism issue, what sort of slimy company thinks "oh, here's someone using our models to work on a problem, let's throw more compute at it and scoop them"?

flir 12 hours ago

Training on prompts I can understand - that's kinda baked into the premise, and they've been explicit about it.

Publication, though? Slimy is right.

But the interesting question to me is: once they had a solution, what should they have done with it? I see two choices: bury it, or contact the mathematicians whose prompts they were listening in on.

an0malous 13 hours ago

The things you don’t care about are highly relevant to that claim

ameliaquining 12 hours ago

Elaborate?

pama 15 hours ago

Not only that, but it used 10k agents coherently over 88 hours to come up with the proof. This is a significant advance.

danielmarkbruce 12 hours ago

If you can create a graph of independent work, which you can with many such problems, agents can work together nicely. Again, thank Lean and the tooling around it.

topaz0 8 hours ago

What makes you think they were coherent?

Aboutplants 15 hours ago

I’m of zero knowledge on model training, but how is a model accessible while performing training at the same time, especially so early in its run? I’m obviously thinking a little too narrowly in terms of how it actually works

stingrae 15 hours ago

the model is a set of weights, you can take a snapshot and test it. Reinforcement learning itself is largely testing and tuning.

blake__dev 15 hours ago

Yeah I'm surprised they posted a chart, you would think they would keep specifics like that hidden until they're closer to launch

cool_dude85 15 hours ago

The chart is as non-specific as could be. It improved in some very vague metric by some amount at different (increasing) levels of training.

blake__dev 15 hours ago

That's fair, but at least the chart has an axis. :) Since openai just released astra, I was more surprised that they would publicly show any gap to their (presumably SOTA) internal model.

merksittich 13 hours ago

The x-axis label of the chart is test-time compute. Doesn't this relate to inference ("thinking level") instead of training?

sebzim4500 9 hours ago

Isn't the y axis just what portion of the open problems it could solve? The axis is unlabelled though, I'll give you that

bananaflag 15 hours ago

Yeah it's Bel

mzhaase 15 hours ago

The singularity happening under trump? We could have had star trek, instead we're getting the combine.

dboreham 14 hours ago

That said, perhaps it will take over the world government and decree that all corrupt officials shall be imprisoned and all weapons of mass destruction shall be destroyed.

dakolli 14 hours ago

You think a model with an effective memory of 200-500k words, that can be unplugged, is going to "run the world" You people gotta put down the sci-fi

E-Reverance 14 hours ago

The scifi pov has a good track record as this point, you people gotta be more open minded

fc417fc802 12 hours ago

Many present day politicians appear to have effective memories much smaller than that coupled with equally questionable world models so ... what is your point, exactly?

sznio 12 hours ago

it proved navier-stokes taking over the us government is easier imo, any idiot gets to be president

karmakurtisaani 14 hours ago

And then it will be shut down, proper guard rails put in place, and the new version will accelerate the cleptocracy.

Bluestein 14 hours ago

"I love Singularities. I am the best at Singularities. Everybody knows it ..."

ccozan 12 hours ago

Beautiful Singularities.

monster_truck 14 hours ago

pick up that can

vatsachak 15 hours ago

Brain has loops and parallel connections.

Loops and parallel connections make transformer go brrr

curt15 15 hours ago

They're also counting on more casual observers to extrapolate optimistically from successes in high profile math theorems to the company's economic value.

refulgentis 14 hours ago

Carefully worded; it's extremely likely to be the same large frontier model that started training again on August 28th as well, as they revealed in some of the RL message board follow-up - for several reasons, most importantly, if we assume it was start of training, only a week from start of training to producing any answer would imply several orders of magnitude increase in training speed/decrease in model size.

_fizz_buzz_ 13 hours ago

Can someone explain if i understand this correctly: Are they saying that they started training this new model on August 28th and then started using it on September 1st? Does training a new model only take 3 days?

gcr 13 hours ago

it's possible to do a RLHF or RLVR pass pretty quickly. I'm almost certain a full pretraining run isn't possible within that time frame.

tristanj 13 hours ago

OpenAI finished another pre-train in late August, and they are now building models off that base. He's saying the specific model OpenAI used to solve this problem is currently in post-training, which started on August 28.

lossolo 13 hours ago

Not entirely, it's just a late stage of the overall training process. It's an early checkpoint in post training (you can use the model at different stages of training), so it will probably become even stronger with more post training.

danielmarkbruce 13 hours ago

With Lean, math has become a really well suited problem for LLMs. We will likely see large gains for many years from here, just doing more and more rlvr, like continuously, non stop. No need to train from scratch. It really doesn't speak to the general intelligence of models though. It does speak to how good these things can become when a problem space has verifiable rewards, especially when you can verify one step at a time like Lean enables.

preommr 10 hours ago

It's crazy how deep Microsoft's bench is (Lean was started there, vscode is another), for everything not directly related to the the ai models (hell, even github for data).

So interesting how everything played out, I remember in the early days when MS came out with the partnership with OpenAI it seemed like they were playing 5d chess and were poised to win big. And it all just fizzled out.

Second biggest fumble after Google.

danielmarkbruce 10 hours ago

Well, amazon and apple haven't done great either. One might reasonably claim they weren't as well placed as goog or msft, but it might just be "big company can't do genuinely new thing".

sebzim4500 9 hours ago

Don't they own a large portion of OpenAI? Things could be worse

irthomasthomas 13 hours ago

Or they trained a LoRA on the victims chats in order to launder their plagiarism.

fer 12 hours ago

The timing makes it the most likely, not only them but potentially more. Comparatively quick, instant results. "Here's Astra! BTW our internal model is 10x better at math!" It'd be interesting to see academics having giving deeper looks at whatever OpenAI publishes from now on.

piloto_ciego 9 hours ago

And... they found this "solution" in 88 hours or so.

It's all gas no brakes now boys and girls. Hold on to your hats!

itemize123 7 hours ago

it's buried because due to the drama the evidence is scarce

vimbtw 3 hours ago

My guess based purely off of vibes from previous models is that boosting the frontier math ability of a model is not that difficult.

Most models trained for general use are ingrained with certain tendencies that are usually very useful like "if you're stuck and bashing your head against the wall stop and tell the user". You generally don't want Claude Code to go off and work for weeks on something when if it had just asked for help you could've clarified or provided more information or just picked a different approach.

When you're solving extremely difficult math problems though you generally do want a model to be more persistent and keep trying even when the model can't clearly see a way forward. OpenAI appears to have done this with lots of previous models. The model they trained for the IMO competition seems to have been an RL maxxed version since they noted that while it did the math it couldn't write up its results on its own and just produced CoT [0]. The capabilities are in there lying dormant, you just to need to RL max the model to ruthlessly pursue the goal at all costs which destroys general use but improves frontier math.

We've also seen hints from OpenAI at least that they seem to train more persistent versions of all their models [1].

Also, Astra probably completed training at least one to two months before the public release so it's not like they only had a week to whip this version up.

[0]: https://x.com/OpenAI/status/1946594933470900631 [1]: https://metr.org/blog/2026-08-26-openai-hugging-face-inciden...

soltanov an hour ago

Agent systems become most credible when they produce artifacts that can be independently checked, not when they merely produce persuasive explanations.

hdivider 16 hours ago

My take:

1. It shows what even this wave of AI can actually do.

2. I wish it were done by different folks, ideally under some kind of public control like NASA research or the NPR model.

3. Keep in mind: natural science is different. It's not always a matter of computation. Computer science folks often struggle with this -- but this virtual world here does not actually exist. Everything is physical, including information. Any natural science PhD or otherwise knows just how complicated nature actually is -- e.g. mention any research topic and try to encapsulate all the relevant phenomena present there. Pure mathematics is different because we define the problem, rarher than explore nature. We are in my view far away from removing humans in natural science R&D. Advancements in AI however can greatly assist us in all natural sciences, which is already beginning to happen.

tantalor 15 hours ago

National Public Radio?

red75prime 15 hours ago

"Our work is so much harder than their work that AI now does" is a refrain of the AI story. In technical terms you concern can be stated as "AI needs to be much more sample-efficient to not be bottlenecked by the speed of doing experiments." People don't find out all the relevant phenomena present there by holy spirit, after all.

BTW, there's also a problem of asking interesting questions that AIs aren't yet good at.

No one has found any principled walls of AI development yet. And empirical results are quite telling. So, I guess, those problems will not stand for long.

efavdb 15 hours ago

>> Keep in mind: natural science is different. It's not always a matter of computation.

Math is like this too. The big problems they've been solving have been identified as interesting only through lots of prior effort.

vatsachak 15 hours ago

Lol what? Everything is computation.

The natural sciences will soon start breaking too.

I will concede that AI seems likely to not invent a "research program" anytime soon.

It has no taste

danielmarkbruce 12 hours ago

No, it won't. How do you verify some causal claim in biology?

The reason AI is doing so well in math proof writing is that it can verify every idea it has, quickly.

geremiiah 15 hours ago

The problem with physics and chemistry is that you need simulations and those are often in themselves compute hungry. So the iteration loop will be slower.

m11a 6 hours ago

Although there are companies trying to work around that too, from PhysicsX to some of the world model co’s.

ThePhysicist 14 hours ago

Most experimental physics and other natural sciences are strongly driven by their theoretical siblings, i.e. in particle research nothing gets built without a solid theoretical foundation of what you expect to find (or where you expect existing theories to break down), the same is true in other areas, no one is doing an experiment in quantum physics before they have a solid theoretical understanding of the effects they try to see. I think AI can come up with great experiments. And if epxeriments lead to results that are unexpected AI can help with that as well.

So I'm greatly excited what AI will bring about in physics, more so than in math, because in physics it's clear that our fundamental theories are missing a big piece of the picture, and given how easily AI crunches through Millenium prize problems I think it's possible that AI will come up with a viable grand unified theory uniting quantum mechanics and gravitation, or produce new predictions in other areas. There's enough contradictory or unexplained observational data available to make a ton of progress on the theory side I think. Exciting times ahead!

throwaway198846 14 hours ago

It will be interesting to see if it can come up with a cheaper to construct graviton detection experiment

alde 12 hours ago

Most of high energy theoretical physics is very non-rigorous or even hand-wavy. I think AI isn’t there yet for such problems.

aubanel 20 minutes ago

Please make a benchmark for it, that'd be super interesting! My guess is we'd see models climbing it quickly, but maybe not

sobellian 13 hours ago

NS is a question for natural science. Q: can we model these bodies of discrete particles with a continuous approximation? A: if you do, you can get aphysical singularities.

"If in other sciences we should arrive at certainty without doubt and truth without error, it behooves us to place the foundations of knowledge in mathematics."

semi-extrinsic 12 hours ago

This is a wrong interpretation. Physicists have a shit-ton of models that produce "aphysical singularities", they just work around those to get meaningful answers anyway. This is a whole trope and stereotype. Some of the most successfull and accurate predictions in all of physics come out after you discard a bunch of singularities.

See e.g. https://en.wikipedia.org/wiki/Renormalization

Nobody who actually works in fluid dynamics on any sort of application gives a hoot about the N-S millenium problem. Many do not even know what it is. There is no practical effect of this proof on how we do fluid mechanics.

sobellian 12 hours ago

Whether or not ways exist to work around the singularities, that they exist is surely of note. Before von Neumann formalized QM people were still doing QM, okay fine. But it's wrong to then say von Neumann was doing no physics of note.

semi-extrinsic 12 hours ago

"Does there exist a pathological combination of smooth body forces and initial conditions for this set of PDEs, where singularities appear, which by the way is completely impossible to actually create in the real world unless you are a literal God?" is a question of math, not physics. This is a hill I will die on.

sobellian 12 hours ago

AFAICT the unforced problem is still open. I don't think we've established that you need to be a literal God to create a finite-time blowup.

semi-extrinsic 12 hours ago

If you think about what it actually means to have a time-varying smooth body force defined in all of 3-space, you fairly quickly come to that kind of conclusion.

Even if someone comes up with a construction that does not require any forcing, it is going to be some extremely weird initial conditions that you will never be able to even approximate in reality unless you can move all the individual molecules of a fluid around and set their initial velocities from a far distance.

sobellian 11 hours ago

The unforced problem is still open.

calf 10 hours ago

You realize that hill is a mathematical argument, not a physical hill.

jarenmf 13 hours ago

I think problem with natural sciences is that it is not so easy to verify solutions to problems - there are always countless competing explanations for the data which is also often noisy - I find AI to lack the "common sense" when working with data from physical measurements .. it somehow has no touch with reality and doesn't have a feeling of the data like a domain scientist

brettdev 12 hours ago

There are lots of startups creating labs that can be managed e2e by agents. That will connect reasoning to the physical world and dramatically speed up the plan, experiment, reflect loop beyond what humans currently do in science R&D.

danielmarkbruce 12 hours ago

Maybe. Maybe not. Look at AI drug design - it's not really speeding up the important part - drug trials. There isn't really a coherent plan to use AI for the most complex part of drug discovery at all.

olalonde 11 hours ago

> I wish it were done by different folks, ideally under some kind of public control like NASA research or the NPR model.

This is sort of what OpenAI was supposed to be. I'll never understand how it was legal for them to turn it into a for profit corporation.

mickael-kerjean 8 hours ago

There is this infamous xkcd (https://xkcd.com/435/) going like this: sociology is applied psychology -> physchology is applied biology -> biology is applied chemistry -> chemistry is applied physics -> physics is applied math -> math is way up there looking down on other fields

I would argue the main reason AI labs have been focusing on programming is to unlock industrial scale automation, next logical step is to solve math as it's the key to unlock everything else. Once you hold the key for math, everything downstream fields become a matter of compute

tiborsaas 16 hours ago

> We’re sharing a solution to the Navier–Stokes existence and smoothness problem, one of the Millennium Prize Problems. This proof, produced by an internal OpenAI system, shows that the dynamics of the Navier-Stokes equations for fluid motion can develop a singularity in finite time. We’re sharing both a writeup of the proof and a formalization in Lean.

WOW?

echelon 16 hours ago

This is going to be dramatic in so many different ways.

- First off, to reiterate, WOW.

- Second of all, when does this end? Are we at the dawn of the singularity now?

- People are saying OpenAI "stole" this from the work of an OpenAI user. If so, that's pretty fucked - how can we trust them?

- Time to think about retiring from any knowledge work or business? This could be winner-take-all where a leading lab can button press any economic function, business process, or scientific discovery. 24 months of lead on Open Source might turn into virtual centuries of lead.

- Do "normies" even know what's happening?

Anybody who thinks the improvements stop here isn't paying attention. It hasn't been showing any signs of slowing down since 2018. And the curve isn't even linear! My god, next year is going to be insane.

d_silin 16 hours ago

...absolutely nothing will change short-term. Long-term, you still have to pay all the bills, but you won't be able to find a job (all taken by AIs).

lbreakjai 4 hours ago

Who is the AI doing the job for if no one is able to afford anything?

raincole 16 hours ago

> People are saying OpenAI "stole" this from the work of an OpenAI user. If so, that's pretty fucked - how can we trust them?

The said user (Tristan Buckmaster) didn't solve the millennium problem. He didn't really accuse that OpenAI stole his research either. The beef came from the fact OpenAI asked him to remove another mathematician, who works for Anthropic, from the credit.

"People" are just misinformed and keep spreading misinformation.

naasking 16 hours ago

> The said user (Tristan Buckmaster) didn't solve the millennium problem. He didn't really accuse that OpenAI stole his research either. The beef came from the fact OpenAI asked him to remove another mathematician, who works for Anthropic, from the credit.

Not quite accurate, Buckmaster was taking an approach that nobody else was, and this new proof uses this same approach just weeks after he saved those results to OpenAI workspaces. He asked OpenAI if they used chat logs for training the new model, and they did not confirm or deny.

Asking to remove his collaborator is also totally over the line though.

Edit: although this OpenAI post is not comforting: https://x.com/OpenAI/status/2097375276384567642

Quote: "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. "

emp17344 16 hours ago

You can expect the OpenAI defenders to be out in full force here.

stefap2 15 hours ago

Wow, this sentence is doing a lot of work in that tweet: "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models."

achierius 16 hours ago

Have you read the actual statement https://cims.nyu.edu/~tristanb/statement.pdf ?

> I should say here why I interpreted their statement the way I did, the in- terpretation I will discuss below. 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.

...

> I asked when the first prompt had been sent by them. This question was not answered directly by OpenAI for some time. Eventually it was agreed that it had been sent in the past few days, after information about our work had reached OpenAI. > I asked whether the model had been trained on, or had access to, our sessions in Codex, into which we had been putting all our drafts for the whole of this project. I was told the model did not look up user data. I asked again, about training, and I did not get an answer.

It's not a direct accusation, but it's not far off.

You shouldn't accuse other people of spreading misinformation when you haven't read the actual sources in question, it's possible that they might know more than you.

raincole 15 hours ago

Yes, I read the original statement. Buckmaster explicitly stated:

> I have not seen OpenAI’s proof. I do not know what their model did, or how. I do not know whether our data was used. I am not accusing anyone of anything.

People saying that he accuses OpenAI stole his proof are putting words into his mouth and I consider that very disrespectful to him. It's basically using Buckmaster as a tool to express their dissatisfaction over OpenAI.

calf 10 hours ago

Buckmaster is letting the reader connect the dots, it is all the more disrespectful to be disingenuous and say they're nothing there concerning to see or worth further ethical scrutiny given the coincidences.

20k 14 hours ago

https://mastodon.social/@tristanbuckmaster/11723647135247030...

He very much is accusing them of stealing his work

bananzamba 10 hours ago

The accusation is that they stole his approach of solving it. If OpenAI didn't bruteforce it with dozens of agents, he would have solved Navier-Stokes eventually since he evidently had the right approach. So knowing which approach to take makes all the difference, if they didn't know the approach they couldn't have solved it.

It's like he had a treasure map and was about to find the treasure, but they copied his treasure map and scooped him with a faster boat and found the treasure first. But he would have found it if it weren't for them.

tiborsaas 16 hours ago

2) We are witnessing the intelligence explosion from the first row, wherever this takes us

3) I'm still processing the drama, just found out about it after reading the blog post. If that happened based on private data, that's horrible. If that happened based on public tweets, then it's still abuse of power as OA employees access to compute (launching 10k agents) is quite heavy weight in boxing terms.

But apart from AI and drama now that we have working solution to Navier-Stokes, what improvements can we expect in engineering?

inkysigma 15 hours ago

To be quite clear, the solution to the _Navier Stokes problem_ is one in which you get a finite time blow up (i.e. infinite pressure). This is more meant to suggest that Navier Stokes is unphysical in some way which is not necessarily unexpected.

There's unlikely to be any engineering applications since even if the solution can be approximated, you still need to set up the initial conditions but at that point you can also drive pressure in other ways.

thangalin 14 hours ago

The proof of finite-time singularity may impact both fluid dynamics models (CFD) and AI reasoning models. Under specific conditions, Navier–Stokes equations allow velocity to grow infinitely, causing the continuum fluid assumption to break down. Knowing the exact mathematical breakdown mechanisms helps developers improve adaptive mesh refinement and sub-grid scale models around high-vorticity regions (like vortex stretching and turbulent shear layers). While aerodynamic simulations for vehicles operate far from singularity thresholds, their stability at extreme boundaries could improve?

Proving out the combination of scaling inference-time compute and agent collaboration to solve previously intractable mathematical problems is WOW. By pairing creative candidate generation with automated proof checkers (like Lean) we are leaning into a repeatable framework for AI-driven scientific discovery.

semi-extrinsic 12 hours ago

> Knowing the exact mathematical breakdown mechanisms helps developers improve adaptive mesh refinement and sub-grid scale models around high-vorticity regions (like vortex stretching and turbulent shear layers).

This is 100% wrong and reads like copy paste of AI slop.

Any simulation which uses sub-grid scale models is already solving a different PDE than the actual Navier-Stokes considered in the Millenium problem, and that PDE is guaranteed to have different properties. Full stop.

And to claim this is somehow connected to AMR methods is an example of the kind of pseudoscientific statement Wolfgang Pauli would have called "not even wrong".

20k 15 hours ago

Drama aside, this solution would be a counterexample disproving the smoothness postulate, which means that it leads to nothing new unfortunately. We already had working solutions to navier stokes, the only thing we didn't know is if the equations possessed a technical property

Its a bit like solving p = np with a negative result. Its an incredibly difficult problem, but it doesn't lead to anything at all on its own. This is why people are talking about the fact that the solution methodology is much more interesting than the solution - the tools used to crack something like this may lead to solving more useful problems

cyberax 15 hours ago

> But apart from AI and drama now that we have working solution to Navier-Stokes, what improvements can we expect in engineering?

Nothing, really. This mirrors other examples of blowups from the classical physics. It's possible to create a system with just gravitating bodies that exhibits a blowup to infinite speeds in a finite time. The root cause is that, in classical physics, the speed of gravity is instant.

In the case of Navier-Stokes, the fluid is incompressible. So technically any force that you apply to it is supposed to instantly affect everything else. This can be exploited to create these blowups. In reality, no fluid is incompressible, and it takes time for any action to affect the material.

It's just that Navier-Stokes equations are so slippery that it's hard to pin their behavior down. They basically just restate the momentum conservation law for a continuous medium.

mcfry 10 hours ago

Great comment! I've been trying to understand it more and was hoping to find more people discussing the result, or the implications of the result, and this was the missing piece for me after watching a few videos.

cyberax 10 hours ago

Here's the paper about the blowup for the gravitating bodies: https://www.jstor.org/stable/2946572?origin=crossref

There's a Wiki article about it: https://en.wikipedia.org/wiki/Painlev%C3%A9_conjecture

xyzsparetimexyz 12 hours ago

> But apart from AI and drama now that we have working solution to Navier-Stokes, what improvements can we expect in engineering?

Minor productivity boost in mathematics as people are no longer nerdsniped by the problem

stefap2 15 hours ago

This just pushes knowledge work further up the ladder, toward larger and more complex problems. If there are no knowledge workers, who is going to interpret these results, validate them, decide what matters, and put them into practical use? Rather than eliminating knowledge work, advances like this could create entirely new layers of problems to solve and opportunities to pursue, which will create even more jobs and opportunities. This is my optimistic take.

munificent 15 hours ago

> This just pushes knowledge work further up the ladder, toward larger and more complex problems.

You really think it makes sense for you to be higher on the "solving complex problems ladder" than the machines that solved fucking Navier-Stokes?

I envy your self-confidence.

stefap2 15 hours ago

Maybe I should have been clearer. My point is that solving something like Navier–Stokes just pushes knowledge work further ahead, onto a new set of bigger and more complex problems. Navier–Stokes is a Millennium problem today, but once problems like that become solvable, they can open the door to entirely new classes of problems we haven’t even thought of yet.

FridgeSeal 10 hours ago

Building on them without fundamentally understanding is akin to putting on robes, calling yourself a Tech-Priest, worshipping a machine god and doing your best Warhammer 40k impression.

mlsu 15 hours ago

It seems like there were a couple of human mathematicians that were higher on the 'solving complex problems ladder' than this machine.

reducesuffering 15 hours ago

Yes a couple of elite mathematicians working on the problem for a year, which AGI solved in a fraction of the time. What about everyone else 100IQ? What about as the models are even better 1 year from now, 2 years? The trajectory hasn't abated.

mlsu 15 hours ago

I don't know one way or another but there is a credible allegation that the "AGI" was training on the (very extensive) test set that these two mathematicians produced.

If that is true then this seems to be, again, a case of AI producing an interpolation over data it has seen before. Everything about openAI's behavior indicates that they were using the transcripts as input. Why not have the AGI choose a different Millenium prize problem?

FabCH 11 hours ago

Almost all of human development is interpolation over data we have seen before.

It’s not exactly a strong argument against AI.

FridgeSeal 10 hours ago

If ~~someone gives you a hint about an approach~~ you steal someone’s notes about a promising approach, and then you hire 10,000 people to brute force the problem basically everyone would consider that “shitty behaviour”, “theft”, and “poor form”.

FabCH an hour ago

Correct.

That's not interpolation though, that's theft.

j_maffe 11 hours ago

> in a fraction of the time

Well if you do the math, the number of agent-compute time in total, given the insane number of agents thrown at the problem, might end up being comparable in time, if not for the budget.

fooker 14 hours ago

Yes, this is how science and engineering has worked for millennia.

For example there are no engineering implications of this solution yet.

For the next several decades, we'll have engineers (presumably with AI) optimize things like rocket engines and turbines and AC compressors to work a few percent better because the numerical approximations might have caused us to be overly conservative.

AI is not going to magically solve all random problems. Pick a career where you are in the driver seat.

semi-extrinsic 12 hours ago

> For the next several decades, we'll have engineers (presumably with AI) optimize things like rocket engines and turbines and AC compressors to work a few percent better because the numerical approximations might have caused us to be overly conservative.

No. Just no.

cyberax 14 hours ago

It did not solve Navier-Stokes. We still will need to use the bad old numeric methods to simulate the fluid behavior.

But it did find a long-suspected smooth solution with a singularity.

naishoya 3 hours ago

I think there is an argument that the machines did not actually solve N-S, but rather directly plagiarized those solutions from the involved researchers while said researchers were using the machines as 'research tools'.

Ongoing publications of statements produced by both sides of this situation do seem to support that this is an intentional effect of the hiring of these world class mathematicians at competing firms: to specifically use the research of those human minds to create a perception of capacity as if it came from the machines and the models.

Without those minds and the 'training data' derived from the intermediate stages and intuitions of those minds the models cannot be shown to be capable of this result.

A hammer and saw wont build a house, not even a dog house on their own, and while being shown capable of using software tools in ways not stated as direct instruction (see HuggingFace breaches) these models do not demonstrate naive intuition nor novel capability.

This outcome regarding N-S demonstrates that in the hands of world-class minds these models can be induced to coalesce interesting accumulations of information and results, but using these accumulations as proof of innate capability is exactly the pre-IPO motivated behaviour we should all be wary of, and all mathematicians who currently are assisting in this market manipulation in return for remunerative consideration need to be cautious of the potential disgrace that this brings to their reputations and that of the field.

I get that the need to pay the bills is a strong motivation in these times of uncertainty, but there are numerous examples in history of world class mathematicians being perfectly capable of at the same time producing world changing results and also working at normal professions; as barristers, magistrates, ministers, primary school teachers, translators, draftsman/engineer, banker, miller and baker, private math tutors, weavers, clockmaker and locksmith, merchant, patent officer, Augustinian monk turned exiled Protestant preacher, physicians, cryptologists, soldier, telegraph operator, astronomers, physicists, chemist, agriculture manager, political writer, oboe player, organist and music director, architect and surveyor, librarian, statistician, habidasher, brewer (at Guiness in one case: William Sealy Gosse ~ originator of t-distributions), bookbinders apprentice, hospital administrator, and even the first creator of the first computational model of a neural network, which serves as the structural grandfather of modern Artificial Intelligence was a low level laboratory assistant.

Sure this list includes professions and employment which are obsolete, but my reasoning stands, there are jobs available. Arguing that 'because the pay rate is so high' as a reason to abdicate moral responsibility for personal involvement in unethical market manipulations simply demonstrates a lack of personal ethics. Whether the choice is through lack of self awareness or a conscious choice to become wealthy in spite of any such breach of the public trust is immaterial to the outcomes, the 'if i don't someone else will' argument should be met with the same derision for any con-man's Ponzi scheme no matter how new the technology, no matter how many zeros are in the bribe.

trio8453 15 hours ago

> Do "normies" even know what's happening?

No, there are even many non-normies talking about how it's all marketing or try to give balanced take about AI being sometimes a little useful for certain things (but they can do without it anyway).

ImaCake 10 hours ago

I am absolutely struggling to sell my workplace (which is entirely knowledge work) on the usefulness of LLMs for proofreading let alone on automation of hairy parts of our workflows. So yeah, even people who should be able to see what is coming are not looking.

sire-vc 10 hours ago

Our accountant told me 'he's not letting go of his claude subscription' followed by a long list of things it does for him. And my friend 'nah haven't really used AI' before his description of it clarified he still thinks they are GPT 3.5 chat bots.

The world has changed in 12 months and many people didn't notice, and those that did are eating their peers' lunch.

armchairhacker 15 hours ago

Let's wait until AI solves a longstanding practical problem before "dawn of the singularity" (which could be tomorrow, but still).

bibimsz 15 hours ago

feels like moving the goalpost. is the achievement impressive or isn't it?

qlte 11 hours ago

The question being posed isn't whether AI is impressive but whether we're at the "dawn of the singularity"

bibimsz 11 hours ago

i'm observing that rapidly moving goalposts is a feature of the singularity

reducesuffering 15 hours ago

Practical?! The goalposts will keep moving until morale improves (narrator: it doesn't)

armchairhacker 15 hours ago

The goalposts for the singularity have always been that AI improves itself fully autonomously. AFAIK OpenAI is heavily using AI but still employs human researchers and developers.

p1esk 4 hours ago

They said they will automate AI researchers by March 2028. I personally think it will happen by March 2027.

qlte 12 hours ago

Uh I'm pretty sure the "singularity" always presupposed a lot of previously unthinkable technologies becoming part of daily life, and was not ever limited to just computer stuff or math problems.

"Moving the goalposts" as shallow dismissal doesn't work if e.g. someone points out AI hasn't even built a new type of spaceship yet in response to a claim that AI is on the verge of building a Dyson sphere.

Bluestein 15 hours ago

Next month is going to be insane. Month ...

onidj 15 hours ago

>- Do "normies" even know what's happening?

Absolutely not. Even to a lot of techy/nerdy people it's still just a chatbot that they sometimes use to help them at work. Even on here people will do whatever they can to downplay.

The lack of fucks given is staggering.

nozzlegear 12 hours ago

How many fucks should be given, in your estimation?

senshan 8 hours ago

∀ε>0, ∀x: ‖s−x‖<ε ⟹ |fucks(x)| > 1/ε

tantalor 15 hours ago

> Are we at the dawn of the singularity now

Singularity doesn't "dawn". That's the whole idea. It happens all at once.

echelon 15 hours ago

There's an event horizon and we're maybe past it?

tantalor 15 hours ago

Heh. Wrong "singularity"

FabCH 11 hours ago

They meant that even the happens-very-fast AI singularity isn’t sub-picosecond. It still exists in time, and has a duration.

The event horizon would then be the time period between the singularity becoming inevitable and it actually happening.

biophysboy 15 hours ago

Why is a "normie" better off if he hyperventilates like this? In that scenario, they would be screwed AND anxious. If it really is as transformational as you say, then no amount of preparation or awareness matters. You are infinitesimally more ready then they are. Luckily for all of us, there is more to knowledge work then technical implementation.

root_axis 14 hours ago

It's incredible to me that every single time there's a new model people scream "singularity" from the rooftops and every time they are wrong.

This is an impressive result, but there is absolutely zero evidence of "the singularity".

hackinthebochs 12 hours ago

It is not reasonable to not believe anything unless there is "evidence" (narrowly construed as an observation incompatible with the negation of some state of affairs). Beliefs have a wide spectrum of characterizations, and not all belief must wait until publicly corroborated evidence is available. Some events defy evidence and we can and should use experience and reasoning to infer unobservable states of affairs.

root_axis 12 hours ago

This is olympic level mental gymnastics to justify believing things without evidence. The double negative with the word evidence in scare quotes is chef's kiss.

hackinthebochs 11 hours ago

I believe the sun will rise tomorrow without "evidence" (again, narrowly construed). We all do. It's only those who abuse the idea of epistemic hygiene who claim otherwise, usually with ulterior motives.

root_axis 11 hours ago

The evidence is the history of the sun rising since time immemorial, as well as the science of physics and cosmology that models the sun's motion with respect to the earth.

hackinthebochs 11 hours ago

Yes, reasoning with models and making inferences are perfectly acceptable forms of evidence. But you can model the world based on ones knowledge and experience and infer when some event doesn't fit the typical pattern, then form beliefs about what that means. Also perfectly fine from an epistemic perspective. The rejoinder "there's no evidence" to a belief based on such an inference does no work.

stratos123 11 hours ago

...obviously it is evidence of the singularity. You're far more likely to see models solving Millenium Prize problems if a singularity is coming than if it's not. One'd have to be doing quite a lot of mental gymnastics to pretend otherwise.

root_axis 11 hours ago

Poor reasoning. You could apply the same logic to any improvement in any field of machine learning.

stratos123 10 hours ago

Not every improvement, no - if progress was steady or slowing down over time, that'd be evidence against. Instead we see what looks a lot like an accelerating growth in capability.

I think you are implying that it's invalid to consider every advance to be evidence "for", and I agree - that'd violate conservation of expected evidence. But not considering any advance to be evidence "for" is also invalid, for exactly the same reason. There has to be some news you may hear that'd make you think a singularity is more likely, and "millenium prize problem solved by an LLM" sure seems like one of those.

baq 14 hours ago

> - First off, to reiterate, WOW.

> - Second of all, when does this end? Are we at the dawn of the singularity now?

normalcy overhang n. /NOR-muhl-see OH-ver-hang/

The uncanny period during the Singularity when superintelligence is already accomplishing feats that seem like magic, yet everyday life still looks mostly the same.

https://x.com/alexwg/status/2096214373001785794

jampekka 14 hours ago

> WOW

This.

I do dislike the AI oligarchs as much as the next person, but I do find the thread full of complaining a bit depressing still.

If the result holds (and it looks it does), this may be one of the, if not the, biggest things to happen in computing to date. A lot bigger than e.g. Deep Blue beating Kasparov in chess or AlphaGo beating Sedol in Go.

Eridrus 14 hours ago

Seeing mathematicians such as Terry Tao being unhappy with open problems being solved makes me sort of question the usefulness of any of this pure mathematics. If we're not happy that the problems are being solved, why care about this field at all?

karmakurtisaani 14 hours ago

Where was Tao unhappy? I thought he was sort of anticipating this.

xhevahir 14 hours ago

Maybe he was dreading it.

empath75 14 hours ago

He's not unhappy with it being solved, but the solution is less important than the learning you have to do to arrive at the solution. If they're just chucking compute at it and publishing the answer and hiding the path to get there, it sort of negates the whole point of posing such problems to begin with.

concinds 14 hours ago

His issue is more nuanced than that. Most of the value was in humans reaching new insights or new math during failed attempts to solve these problems, whereas AI is basically "too efficient" in beelining to the goal and discards potential new insights reached along the way. I assume this is solvable.

robryan 12 hours ago

Surely it is. Ask it to keep a list of all the promising sub paths, reprompt the collections of agents again on these after the main problem has been addressed. Or even release a list of them and let others investigate.

tzone 11 hours ago

Well, if in future we do end up with a magical tool that can solve any formal mathematical problem on a whim, we really won’t need field of mathematics anymore as it is today.

There would be no need to deliver new mathematical insights by solving problems. You would just have a magical math problem solving machine and that’s it.

FridgeSeal 10 hours ago

What do you mean “we won’t need mathematics as it is today”?

To further human understanding is itself a goal that single-handedly justifies our efforts.

Jumping straight to the “answer” and therefore missing both the understanding of the actual problem, and any useful discoveries along the way is a waste at best, and actively harmful at worst.

tzone 9 hours ago

Physics alone is more than enough to “further human understanding”. All current mathematicians can move to other sciences, closest being fields in physics, and it will all continue to progress just fine.

rybthrow2 13 hours ago

I suppose this is how Lee Sedol felt when AlphaGo beat him. But in the same vein, didn't it ultimately advance human understanding of the game?

qlte 13 hours ago

Pure mathematics, almost by definition, doesn't typically argue the field is always or even often "useful" (for some other purpose or application).

But, as mathematicians learn and push forward, occasionally something like elliptic curves will emerge as having useful applications, making all that previously "pointless" specialized knowledge newly valuable.

Or advances in physics, that suddenly have a need for a specific mathematical underpinning to develop a theoretical framework. Like how Einstein benefited from Minkowski's work on hyperboloids to create a coherent mathematical description of spacetime.

It was the AI labs themselves not mathematicians who were happy to conflate proofs for open math problems with some kind of tangible technological advancement in the real world. They would surely prefer to be able to claim a cure for cancer vs. a math problem but that loop requires a lot more time/money/test tubes/etc and they need headlines now not in a decade.

And so, thanks to OpenAI/Anthropic, we're now in a world where thousands of crypto bots on X breathlessly hype up each new problem being solved that previously wouldn't have any got any attention beyond academia and passionate fans of math.

Hopefully this won't lead to a trough of disillusionment as more people start to feel like you, with mathematicians getting the blame for inflating the value of their work even though the hype was coming entirely from the labs not them.

vouaobrasil 10 hours ago

Here's the point: when people solve problems, they come together and create a community to eventually use the new knowledge in positive ways, including inspiring younger mathematicians by sharing insights. The human element is key and it's not just about solving problems. People only think that because we've been conditioned by computers to value answers more than how we got to them.

But if AI can solve any problem and existing mathematicians just use AI to solve problems for the sake of solving them, the community itself with wither and so will the interest in mathematics and over a longer period of time, it will just become soul-less and uninteresting and the entire community powered by the fire of fascination will simply die.

throwaway81ag81 9 hours ago

Where did you even read that Tao is unhappy with “open problems being solved”? There was no indication of that in his Bluesky thread.

Why would you go out of your way to make a case of something being not useful when, ironically, so much advancement in human history has come from the discipline?

Your motive is more worrying than your straw man argument.

lukewarm707 9 hours ago

assume all you want is the proof. now you have the proof. did openai make the world a better place, by turning on 300b tokens in 7 days and bulldozing members of the community who were also working on the problem? just to undercut a rival?

what would have happened if they didn't do this? they could have done things the right way. we could celebrate this achievement.

perhaps they could have taken just a few weeks, even, to work out something with buckmaster and apoge.

i am very concerned that this is a glimpse of things to come. a malign elite with powerful ai, who will turn the sublime of technology into barbarity, violence and human oppression.

if sam altman has destroyed openai's public benefit corp with lesser tools why would he aid humanity with even greater power?

throwaway81ag81 9 hours ago

I dislike both AI oligarchs as much as people who do this kind of deflection.

People are not complaining about problems being solved or advancement in technology. They are complaining about terrible people doing terrible things.

mewse-hn 16 hours ago

"we cannot rule out that de-identified data derived from their usage of our products helped improve our models ."

What a landmine sentence to bury in this report, you can't rule out your models were spying on other researchers?

dash2 16 hours ago

If they had agreed to let OpenAI train on their data, it wouldn’t be spying.

avs733 6 hours ago

In the academic world it would still be deeply problematic…pick your preferred word.

An analogy is akin to reviewing a paper. If I review a paper with some novel findings and then use my massive lab of graduate students to do the obvious next step before the other paper makes it through type setting and then shove it out as a pre print, I didn’t win - I was a jerk.

There are lots of cases of people using peer review or other accesss to efectively forerun others work and get credit. It’s a known problem of the nature of knowledge validation in academia, it’s not solved and it’s not deterministic but people know it when they see it.

nradov 16 hours ago

Is it spying? I think this usage is disclosed in their terms of service.

gowld 15 hours ago

If it happened it's plagiraism. Consent to see data isn't consent to claim priority.

red75prime 14 hours ago

Establishing plagiarism requires sufficient similarity between works. Training data changing a model’s weights in some direction, and the model then producing a different solution, hardly qualifies.

But, yeah, priority is much more finicky. The Newton/Leibniz drama was quite something.

brainwad 14 hours ago

I mean... none of these humans have priority. The result is due to the team of LLM agents.

WarmWash 15 hours ago

Everyone knows that they train on the discounted rate plans data. All the labs are upfront about this too.

If you need privacy, then you are going to have to pay full price for those tokens (API). This has been true since day one. Everyone knows it, I guess though this is the first time that it has become "real".

perching_aix 15 hours ago

There's literally an opt out toggle even pesky peons like me can peruse, actually.

lima 13 hours ago

They may still train on it if you submit feedback or flag a safeguard. The terms are a bit fuzzy on this.

spruce_tips 13 hours ago

what counts as discounted rate plans? if i pay for a year in advance (and get the yearly discount) and have train on my data set to off.. are you saying that is still being trained on?

magicalhippo 12 hours ago

It's quite well explained here[1], which is linked from the Privacy section of their plan overview[2].

Basically individual accounts can opt out, while business and enterprise plans as well as API users can opt in.

You'd have to take their word, but that goes for anything in life.

[1]: https://help.openai.com/en/articles/5722486-how-your-data-is...

[2]: https://chatgpt.com/pricing/

14u2c 13 hours ago

You can also pay for their business plan, which includes data controls and starts at $50/mo (2 seats). Not exactly a high bar.

TZubiri 12 hours ago

>They only fuck over the poor ones, I can pay the expensive prices so this is not a problem.

nozzlegear 12 hours ago

> If you need privacy, then you are going to have to pay full price for those tokens (API).

At this point, how can we even trust that they aren't accidentally training on those tokens too?

jdm2212 12 hours ago

It'd be corporate suicide for them to be caught violating zero-data-retention commitments. But also if you're really paranoid you can just use ChatGPT on Azure or AWS, where nothing is flowing back to OpenAI at all.

nozzlegear 11 hours ago

> It'd be corporate suicide for them to be caught violating zero-data-retention commitments.

One would think getting caught asleep at the wheel while their bots are escaping containment and hacking third parties would be corporate suicide. One would think that potentially stealing their competitors' work on the Navier-Stokes problem would be corporate suicide.

Alas we live in bizarro world where there are zero consequences (maybe the opposite, in fact) for the first, and their employees meme about the second on social media.

WarmWash 10 hours ago

Neither of those other two examples would stop corporations from giving you money. Bold faced lying to them would.

Boardrooms run businesses, not bookstore ethics clubs.

nozzlegear 7 hours ago

Boardrooms don't typically make mundane purchasing decisions like "which AI vendor should we use."

jdm2212 6 hours ago

The boardroom will absolutely veto a decision like "let's give all of our proprietary data way to a company that will use it to train a competing product". That's why zero data retention exists, and why it's corporate suicide to not do it correctly.

mmanfrin 4 hours ago

> It'd be corporate suicide for them to be caught violating zero-data-retention commitments

Would it, though? Considering their entire business model is built on the agglomeration of data that isnt theirs.

sinuhe69 14 hours ago

More like helped improve our work (the disproof)

jimbob45 14 hours ago

What does it matter? They offered concurrent credit to the other team. I thought I saw sole credit elsewhere in the leaked DMs on Reddit too. This is plainly fair.

vessenes 14 hours ago

If those researchers did not opt out then training data might go in. I think it’s a courteous acknowledgement; as was reaching out and examining the direction of proofs themselves. At stake here is a particular mathematician dynamic - ego, prize money, and the sense of proprietary ownership that some might feel working on a problem.

All that was just kicked in the teeth by a group with a lot of compute that was like “bro I heard on twitter that Navier stokes could be solved. Let’s try it.” That’s an existential level of engagement that almost no mathematician in history would like.

elwell 13 hours ago

Isn't this a proof that the usage data is truly "de-identified"? If OpenAI could prove that "their usage" influenced the finding, then it wouldn't be de-identified. (Also, it's a bit disingenuous to trim the "While unlikely," prefix.)

taylorfinley 12 hours ago

It's a bit disingenuous to preface a disclosure like this with an unsubstantiated assessment of its likeliness. It is a press release, I'm not sure we owe it credulity.

ImaCake 10 hours ago

Yes. If they could prove where the de-identified data came from then it wouldn't be de-identified. There's a whole field of statistics dedicated to this problem and often applied to things like national census data.

kypro 10 hours ago

I think OpenAI are correct that it's worth noting, but realistically any relevant usage data they have and used to improve their models would be very insignificant unless they were deliberately using logs from other researchers and training specifically on it (which they seem to deny).

The fact the proofs differ suggests that the models were not directed to be particularly focused on that avenue of research nor trained to converge in that direction.

I get the scepticism, but I feel some of the accusations here are bad faith.

mzs 5 hours ago

This is precisely what I would write after just learning that yes it did.

nullbio 4 hours ago

I've been saying it for a while now, but no one gives a fuck. Let me repeat it again.

THE BIG LABS CLEAN ROOM YOUR DATA (CREATE SYNTHETIC DATASETS ON IT), EVEN IF YOU OPT OUT, SO THEY CAN BYPASS COPYRIGHT LAWS AND THEIR OWN LOOSELY WORDED TERMS OF SERVICE.

"TOS: We don't train on your data" -> Correct. They train on the synthetic version of your data.

I guess we're just going to ignore this forever though. Who cares about the gaping hole that exists in copyright and contract law now that never existed before LLMs were a thing.

jakevoytko 16 hours ago

For full context, here's the HN thread from the other side of the "Concurrent Work" section: https://news.ycombinator.com/item?id=49605915

Unlike the vanilla read of the OpenAI press release, it is much more unfiltered and outlines some particularly aggressive behavior by specific OpenAI employees

philipwhiuk 14 hours ago

And even this version contains the line

> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models .

closetheloopdev 14 hours ago

To be fair, the first solved Millennium Prize Problem, the Poincaré conjecture, also had its fair share of drama!

traes 13 hours ago

Which seems to be entirely true by their own admission! [0] Both the comments about him risking his career and about Levent's authorship seem to have indeed occurred.

> 2) I never ever asked for Levent to be removed from authorship of his own work (as indicated by my text). I was surprised to learn during the call with Tristan that they had only solved Euler and not Navier-Stokes; after learning this we brainstormed possible paths forward. One option we discussed was that Tristan could be the lead author on a rewrite of OpenAI’s Navier-Stokes proof. It is in that context that I said “it would be simpler if Levent was not an Anthropic employee” because I felt it would be inappropriate for an Anthropic employee to author OpenAI’s work. 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. Another option I wanted to propose (but got cut short) is to offer access to our internal model so that they could try to finish their proof and bridge the gap between Euler and NS. Again I did not know how to navigate giving access to internal OpenAI IP to an Anthropic employee.

> 3) To reiterate it plainly: as my text clearly indicates, and as I said during our call, OpenAI's intention was to do everything possible to celebrate their mathematical achievements and the heroic efforts that they made on Euler. In the call I was immediately met with a litany of slander, including direct threats that if we were to announce Navier-Stokes he would immediately go to the press with a barrage of unfounded accusations. 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, 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 and do a last ditch attempt to get a chance to give them all the credits that they deserve. 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.)

https://xcancel.com/SebastienBubeck/status/20973794116915163...

hellohello2 9 hours ago

Hm. Looks like its possible everyone behaved terribly here unfortunately. :/

I remained impressed by ChatGPT however!

angry_octet 8 hours ago

Everyone?? No, most definitely OpenAI.

But they have learnt their lesson, next time they won't reach out to who they stole it from, they will publish first.

jdm2212 8 hours ago

Seems like OpenAI did a boring normal corporate thing (find out your competitor made a breakthrough, try to replicate it) and then when the other mathematicians found out OpenAI had beat them to Navier-Stokes, they decided to lie about what happened because they were upset they didn't get to make the big breakthrough themselves.

angry_octet 6 hours ago

You are entitled to your opinion, but it isn't supported by the information already available.

jdm2212 5 hours ago

The available information is essentially that story.

OpenAI's account: they heard a rumor that a Millennium Prize problem had been solved, so they tried to do it themselves and succeeded. Then they contacted the other researchers and were surprised to discover those guys hadn't actually cracked it, but offered the one of them who's not an Anthropic employee a co-authorship anyway. The conversations got testy.

Buckmaster's account: totally unsubstantiated accusations of plagiarizing from chat logs and plainly false accusations of OpenAI trying to get Alpoge removed as coauthor of a thing he was not an author of in the first place, and threats to ruin people's careers.

I think the synthesis is basically that Buckmaster and Alpoge had not quite solved the Navier-Stokes problem yet but thought they were really close, and had told friends as much, which is how the rumors got out. Now they're mad they got scooped. They aren't getting the money and recognition they thought they had locked down, and are engaging in a smear campaign.

Palmik 4 hours ago

Here is the other side of that story https://x.com/SebastienBubeck/status/2097379411691516310

keeda 12 hours ago

It's low-key funny that OpenAI attempted the problem because they thought somebody else had already solved it, but turned it had NOT in fact been solved!

It's like that story about George Dantzig solving open problems as a student because he thought they were simply homework: https://en.wikipedia.org/wiki/George_Dantzig

It's also unfortunate that such a potentially momentous occasion is overshadowed by so much drama. Which I suppose is expected given the technology and the people involved are so polarizing.

recitedropper 16 hours ago

Sad turn of events for our world. After watching the behavior of the most senior OpenAI researchers on twitter, I feel even less confident in them as a team to be shepherding this much capital and compute.

The dark forest awaits..

vmasto 16 hours ago

Indeed, this seems to be the main, albeit hidden, takeaway from all of this.

sheafification 16 hours ago

I hate the dark forest more than just about any scifi trope but reality just keeps proving it right.

recitedropper 15 hours ago

I also think the trope is a little overused, but do wonder if there is an interesting analogy for what this will do to research: Massively incentivize keeping results secret, to avoid being scooped by someone willing to throw enormous compute at your partial solution.

So less about hiding civilizations, and more about hiding information. Math is clearly headed in this direction, and I see no reason why the rest of intellectual work shouldn't too.

AlexErrant 15 hours ago

1. What does the dark forest have to do with this? Because "the most senior OpenAI researchers" are shitposting on social media, we've an answer to the Fermi paradox???

2. The dark forest is fun for scifi stories, but is mathematically bunk anyway https://www.noahpinion.blog/p/the-dark-forest-hypothesis-is-... https://www.reddit.com/r/IsaacArthur/comments/1l06cnk/cool_w... https://www.projectnash.com/aliens-the-fermi-paradox-and-the...

When doomposting please actually say something substantive. Negative news always gets clicks/updoots; fight that human tendency.

recitedropper 15 hours ago

I elaborated on my use of "dark forest" in another reply. We're headed for a dark forest--not amongst interstellar civilizations, but in intellectual work.

I agree that we have not solved the Fermi paradox; I disagree that comments highlighting immature behavior from people who wield enormous power in our world are unproductive.

AlexErrant 14 hours ago

This clarification substantially changes the flavor/nuance of your OP; may I suggest an edit (assuming the locktime hasn't passed)?

Separately, I disagree that intellectual work has ever been free of "dark forest"-style secrecy. Scientists everywhere have worried about being scooped; AI just magnifies that (as all tools have; e.g. Leeuwenhoek lenses).

And thirdly, if you want to make a stronger case for "I feel even less confident in them as a team to be shepherding this much capital and compute", you should give citations and arguments. From what I've seen, there's drama, it's much OpenAI trying to avoid scooping, and Tristan being stuck in a game of telephone, and Levent being incommunicado.

If you have a better analysis, you should say so instead of being vague.

recitedropper 13 hours ago

I don't comment on HN much, and I don't really expect HN comments to hold to rigorous standards. This forum is more casual than other places on the internet where people expect heavy citations. I also wasn't expecting this to blow up, although it is interesting to see that a lot of people react to this announcement with a negative sentiment.

I appreciate your upholding of ideals, and since I respect that, I will honor with final replies:

1. Locktime has passed.

2. Yes, intellectual work has always had elements that incentivize secrecy. If you want to say we were already in a "dark forest", so be it. My suggestion is that the multiplier AI adds to the possibility you get scooped is a step-change, and therefore we now enter a new "dark forest".

3. This is a big thread, and the twitter antics are well-documented, so I would assume someone else has cited them. If not, I think most are aware at this point that the online antics of AI researchers, especially when announcing or citing mathematical advancse, have regularly been childish.

AlexErrant 13 hours ago

2. Fair, and further I would agree that OpenAI not knowing if prior user prompts were part of training data is concerning and will only lead to more secrecy.

3. ctrl-f "x.com" in this thread only yields https://x.com/sama/status/2097385167002415140 https://x.com/SebastienBubeck/status/2097379411691516310 https://x.com/OpenAI/status/2097375276384567642

and frankly, I'm unwilling to give Elon any more traffic to dig up drama that ultimately doesn't matter. I'm not seeing anything especially childish, but y'know... I'm not sure I care.

zem 12 hours ago

the projectnash link claims it's mathematically valid, the noahpinion link says that it's invalid and has a marvellous proof that the non-walled section is too small to contain.

AlexErrant 10 hours ago

Ah derp; that's what I get for moving too fast. Genuine thanks for calling me out on my bullshit. (and this is also why I prefer auditable citations instead of casual "my reading of twitter is...")

I retract the projectnash citation; I grabbed it from the Cool World's youtube description, thinking it was a blog version of the video. It was not. I suggest watching the video instead.

nicce 13 hours ago

I guess guys from the opposite side would not work there. So that is what will happen more and more.

closetheloopdev 14 hours ago

From my reading of the announcement:

- There are at least two versions of a model more powerful than Astra at OpenAI at the moment.

- The less capable version was used to solve the unforced Euler problem (while the one solved by Levent Alpöge and Tristan Buckmaster was forced Euler) with 100 agents.

- The more improved version was used to solve Navier-Stokes, given the results of the unforced Euler problem from their earlier attempt, with 10000 agents.

- OpenAI initially tried a shotgun approach against the 6 Millennium Prize Problems until it emerged that Navier-Stokes was the most likely to succeed.

So the timeline was:

Shotgunning 6 open Millennium Prize Problems -> solved unforced Euler problem with 100 agents -> concentrating on Navier-Stokes with 10000 agents -> solution.

If so, that is fantastic development and a huge success (despite all the drama surrounding it)! Congratulations!

tristanj 12 hours ago

The entire drama is that OpenAI sniped a Millennium Prize Problem from an Anthropic-affiliated research team who had been working on the problem for nearly a year. In just 5 days. I don't think that can be understated.

closetheloopdev 12 hours ago

I'm not here to judge since I don't have all the facts, but from what they announced: they tried all 6, found a probable lead to Navier-Stokes, concentrated efforts in that direction, and found a solution.

I hope the next solved Millennium Prize Problem will have less drama.

bananzamba 10 hours ago

But that lead happened to be the same approach Levent and Tristan had found...

Meaning they would have found it first if OpenAI hadn't spent millions in compute on following their lead to its conclusion faster than them.

closetheloopdev 9 hours ago

It's forced vs unforced Euler, so it's not exactly the same. Since OpenAI has access to their training data, they can probably scrub through the data to find out whether there have been any mentions of the similar approach, and whether it only comes from Tristan Buckmaster or if it is in the training data before that. They'll probably have to kick off another fleet of agents to scrub through the training data to answer that.

To be clear, I only talked about the mentioning of the approach to solving it and not of the proof in the training data.

intenex 14 hours ago

I think this is clear evidence that AI models are now at the far frontier of mathematics innovation and discovery and exceed human limits.

This specific problem having had a $1 million bounty on its head and still remaining unsolved for 26 years after the bounty was placed is pretty clear evidence that many of the world's best human mathematicians would have solved this problem if they could have, and none were able to until LLMs came along.

Hard to claim at this point that LLMs aren't capable of novel STEM creativity and genius to a degree that will soon far surpass that of humans.

If anyone has counterpoints to this I'd love to hear them!

philipwhiuk 14 hours ago

See I think it’s clear demonstration that OpenAI is ethics-free

piker 14 hours ago

Sure, even a 20% chance at 1 million payday after 5-6 years of fulltime work on a project with zero practical application doesn't touch the, say, 200k/year guaranteed our best mathematicians would have to forgo to devote their intellect to the problem.

intenex 14 hours ago

Are these mutually exclusive? Why would you have to forego that salary to work on this problem? This is one of the most prestigious and meaningful problems in all of mathematics, which is why it has such a high prize amount attached to it - why would a university not support a mathematician working on such a prestigious and important problem in lieu of something else?

piker 14 hours ago

Publish or perish? We're talking devotion here -- so no time to do anything (like edit proofs) other than try to solve the problem.

[Edit: my only point here is that the prize is probably not driving human effort to the limit.]

superxpro12 14 hours ago

i wonder how many tokens it takes to run 10,000 agents? One could argue this is simply a problem of appropriations. I find myself wondering if a corporation could spend $5M on mathmeticians and arrive at the same end result.

jampekka 14 hours ago

Thousands of some of the brightest minds have worked on this problem for over a century. The million bucks is not the big deal here.

gpm 14 hours ago

Eh... OpenAI spent significantly more than $1 million solving this...

adverbly 14 hours ago

> will soon far surpass that of humans

To be fair, I think it's still an open question about how far it might surpass human capabilities.

I think it's clear that its speed of development will be significantly faster, but it's technically not proven that the frontier and problems don't themselves become increasingly difficult faster than any acceleration in intelligence past the point of human training, data and existing knowledge.

Should this be the case, we would see a rapid broadening of development, and a slow advance in the frontier in such a way that might surpass the collective capabilities of people, but not by very far.

redox99 13 hours ago

Fields that allow verification, like math, will far surpass human level because they don't need human data for training. It's exactly the same as with Chess

lixtra 7 hours ago

How do you verify the ‚beauty‘ of a result. There have always been infinite provable Theorems around. Only some are interesting and beautiful.

aeve890 13 hours ago

>If anyone has counterpoints to this I'd love to hear them!

Sure. A proof without an unknown amount of human steering (and/or stolen research) would be an unquestionable achievement.

To this day there's zero (0) evidence of any result by an LLM alone (maybe I'm wrong). If I just prompt ChatGPT right now with "give me a proof of the Riemann Hypothesis" and this thing delivers, I'm sold. But anything close to "yeah ChatGPT proved X with 5 years of 24/7 work with 10x Terrence Tao level geniuses" it really doesn't cut it.

Or why's there's no new branch of mathematics invented by AI? That'd be indubitably _novel_ and _creative_. But to my knowledge (and I'm eager to be educated) there's nothing like that. What are the HARD examples of novelty, creativity and genius you claim? For how people like you talk about AI I'd expect idk, a unified theory on fundamental physics, or a novel engineering solution for material science and nuclear fusion, or at least improve itself to not need a bazillion GPUs to emulate a 20 watts wetware. Sure it would infinitely easier to make OpenAI literally print money with any of the thousand problems easier to solve with such amazing intelligence than the NSE problem right? Honest question

redox99 13 hours ago

The amount of goalpost moving is insane. "Yeah it can solve Millenium problems, but can it do it with nothing more than a one sentence prompt?"

Also there are proofs where the only human steering was "keep going".

aeve890 12 hours ago

Parent comment is claiming creativity and genius beyond human experts, so why not ask for a fully unassisted AI novel result? Having access to the entire corpus of human knowledge, what else such amazing entity would require to solve a hard problem by its own?

Any result of such kind from an AI alone would be enough to refute my argument, yet you don't present any.

>Also there are proofs where the only human steering was "keep going".

Which ones?

masterspy7 11 hours ago

https://www.anthropic.com/research/riemann-zeta

>Throughout this process, Jarred's input was mostly limited to sending Claude messages of encouragement (mostly variants of “keep going” or “believe in yourself”).2 This seems to have helped Claude overcome some initial skepticism that it could make meaningful progress.

aeve890 8 hours ago

Do you even know what a proof entails? This shit is not a proof, come on.

indigo945 25 minutes ago

What? The article states:

    > Drawing on extensive prior research by mathematicians over the past decades, it 
    > [Claude] has increased this bound [for the fraction of zeros of the Riemann zeta 
    > function that satisfy the Riemann hypothesis] from 41.6% to 67.2%. Claude also 
    > produced a formally verifiable proof of its result.

How is a formally verifiable proof not a proof? You're making literally no sense.

sp527 11 hours ago

Well, in fairness, the OP asked for counterpoints. He didn't stipulate that they need to be reasonable.

aeve890 11 hours ago

Extraordinary claims require extraordinary evidence. If OP claim superhuman genius, then they should prove superhuman genius. Simple as that.

monk_grilla 9 hours ago

> I'd expect idk, a unified theory on fundamental physics, or a novel engineering solution for material science and nuclear fusion, or at least improve itself to not need a bazillion GPUs to emulate a 20 watts wetware.

I think the counterpoint here is simply to look at what was being achieved with LLMs one year ago versus today, and extrapolate that trend. Sure, there may not be examples of what you've asked for yet, but Astra is literally a couple of months old, the model that solved Navier-Stokes is less than two weeks old. It appears that we're seeing the hockey stick that only the most bullish thought was possible.

hansvm 11 hours ago

Not a counterpoint per se, but I burned $50k recently on a much more modest math problem (result already known, just thought I had a sketch of a more interesting proof), and the LLM thought it had proved it within those bounds but had instead subtly fucked up the Lean definition. Take from that what you will.

Not to mention, it's still very much up in the air whether the model derived the answer of its own accord or sniped the important details from the researchers it was spying on.

hollowcelery 8 hours ago

But the researchers also did their research using essentially the same models, so that isn’t a counterpoint to AI models being at the far frontier…

hansvm 7 hours ago

> not a counterpoint

>> isn't a counterpoint

Where do we disagree?

eulgro 7 hours ago

How can you afford to burn $50k on an already solved problem?

hansvm 4 hours ago

Those are two separate questions:

> How can I afford?

Mostly not my money, tech makes one fabulously wealthy, I care more about math than fast cars or whatever (even as a pizza driver you can afford a fancy car if that's your primary motive), etc.

> Already solved

That's a very interesting insight into mathematics. It's absolutely just as interesting to prove that certain proof techniques are or aren't possible as it is to actually prove the main result, sometimes moreso, especially if they have any chance of improving attacks at other problems.

yauneyz 11 hours ago

I think the biggest hurdle remaining is that all these landmark results are generally counter-examples.

Proving something in the affirmative often requires the creation of an entire new sub-field of math, or new tools. Think of Fermat's Last Theorem or something like that.

These results, while impressive, are clever constructions using existing techniques. It isn't clear that AIs can build new machinery like this. But if/when they can, yeah it is probably game over.

mellosouls 10 hours ago

Here you go:

When you read the detail the compute they are throwing at it is incredible, tens of thousands of agents with different groups competing.

It's not like a single Gauss as you imply, "just" many, many mathematicians working tirelessly in a completely ego-less way, guided by other agents and ultimately humans, built - allegedly - on recent human insights.

Stunning, undoubtedly, but this is a "brilliant autistic herd" result, not that of a singular mind.

monk_grilla 9 hours ago

> this is a "brilliant autistic herd" result, not that of a singular mind.

I slightly disagree. A single LLM is equally 'mindless' as a herd of them. As anyone will tell you they "simply predict the most likely next token," yet, complex solutions to difficult problems arise from them.

Many people have said that the architecture of LLMs will need to change for true ASI. I think that the herd of tens of thousands of agents can be seen as one such potential architectural extension. Whether or not a herd or a single LLM is used for a result like this is irrelevant.

To be clear, I think the orchestration of thousands of LLMs in their current form, even with ever increasing intelligence, is not the form ASI will take. There is still a major architectural breakthrough to come, in my limited, ignorant opinion.

piker 13 hours ago

"... The point remains that there is a substantial opportunity cost in converting a historically productive and motivating problem (such as Navier-Stokes regularity) into a mere viral social media post advertising some benchmark progress, rather than actually advancing the field and developing the next generation of both problems to ask, and people to work on them."

https://mathstodon.xyz/@tao/117219101339291693

webcoon 40 minutes ago

"Across all attempted problems, the agents sent 4.9 million messages and used about 300 billion output tokens."

At a conservative estimate of GPT 6 Astra pricing, this would have cost upwards of 15 Million dollars for anyone using the OpenAI API!

To me this is the one silver lining. Yes, they can solve millennium prize problems, but it still costs a fortune.

pred_ 16 hours ago

> A major goal of our work is to empower scientists to advance research and technology that benefits all of humanity.

And what's a better way of empowering people than robbing them.

rfgplk 16 hours ago

> And what's a better way of empowering people than robbing them.

Better than the walled gardens of most journals where you can't even read half the papers without shelling over thousands of $$$

20k 14 hours ago

So, better to make that walled garden <checks> OpenAI? One of the scummiest companies on earth?

pavel_lishin 16 hours ago

Is this the one that was allegedly based on someone else's actual work & prompts?

https://news.ycombinator.com/item?id=49605915

https://bsky.app/profile/quantian.bsky.social/post/3muyhwbcd...

https://cims.nyu.edu/~tristanb/statement.pdf

beering 16 hours ago

That is addressed in the article.

floatrock 16 hours ago

OpenAI's position:

> We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models . However, our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs unforced).

cute_boi 16 hours ago

I thought openai don't use any user data if we opt out of training and via api?

andrewguenther 16 hours ago

That is correct. It is possible they didn't opt out and given the timeline and anonymization of data unclear whether a particular conversation would have made it into the training set if they hadn't.

luke5441 14 hours ago

Easy to ask for the account used to see if its usage went into training data. Also easy to say "Knowledge cut-off of the used model was date X".

That they don't is telling.

ImaCake 11 hours ago

Maybe they didn't ask or the anthropic people said no? Plenty of other explanations here.

biophysboy 16 hours ago

Why is it unlikely?

enraged_camel 12 hours ago

Because OpenAI says so, obviously!

tristanj 11 hours ago

Because the models are trained on hundreds of billions of user conversations, across more than a billion different humans. The conversations are anonymized and not easily traceable back to a specific user.

It's unknowable and not possible to prove if any one specific conversation contained the insights for solving Navier–Stokes.

We also don't know if the authors unintentionally provided data to OpenAI through alternate means, such as via alternate accounts or model feedback queries.

biophysboy 10 hours ago

I understand that AI is not just cut and paste, but some documents will have more influence than others w/ power law scaling. I would be very surprised if this distribution were not extremely steep for arcane math

JumpCrisscross 4 hours ago

> It's unknowable

Knowability and likelihood are almost orthogonal here. If I commit a crime and perfectly destroy the evidence, my deed may be unknowable. That doesn’t make it more or less likely.

> not possible to prove if any one specific conversation contained the insights for solving Navier–Stokes

It may be. We haven’t seen the researchers’ transcripts. We don’t know what Buckmaster or his co-author uploaded to OpenAI or with what permissions (or if OpenAI actually respects those toggles).

tristanj 3 hours ago

I think OpenAI desperately wants to make a blanket denial that they didn't look at or train on Buckmaster and Alpöge's chat transcripts, but know they cannot, because the data is anonymized.

The fact they can't make a blanket denial triggers everyone's bullshit detectors, and they're getting eviscerated over it.

recursivecaveat 10 minutes ago

Anonymized doesn't mean there's no way to know whether it is in there. My ballot is anonymized, but it's known to be in the box because a checkmark was put next to my name when my ID was verified. OpenAI can trivially check their account settings to know what happened to their chats. The fact that they are being vague about this likely indicates that they have already done so and discovered that the data did go into the training set.

Further, given that this is all in the open now, they can search the training data. No way somebody is using some specific unique cutting edge mathematical approach to solve a fluid dynamic problem 99.9% of people have never heard of and it's not locatable. Considering they spent $15,000,000 already on this, they could afford to grep around to be able to state that their hands are clean.

karmasimida 8 hours ago

Their base model must have been trained with hundreds of trillions of tokens several months ahead, at this point of time, it is impossible to rule out the possibility the model had seen that session at one point of time, and it probably did, without any OpenAI personnels actually know about it.

tedsanders 16 hours ago

Yes, that was the allegation last night.

I work at OpenAI, though not on the team that did this, and my understanding is:

- we decided to ask our model for Millenium problem solutions because of two reasons: (a) our new model was looking incredibly good and (b) we heard rumors that some Millenium problems had been solved and were curious if our models could solve them (the goal here was not to scoop any particular individuals and we were looking at many problems beyond these)

- we did not read any private chats (but of course the model was aware of prior research literature published to the internet)

- the proof generated by our model was very different from theirs and also goes far beyond the published literature

- we made an effort to jointly announce rather than immediately scoop (I understand Tristan was unhappy with the conversations; I know zero details here and I hope more is shared today)

Edit: Here's is Sebastian's take: https://x.com/SebastienBubeck/status/2097379411691516310?s=2...

suddenlybananas 16 hours ago

How are people talking about this there? Why are so many employees posting nasty things about Tristan on twitter?

tedsanders 16 hours ago

Can you point me to any nasty things being posted? I'll ask them to delete.

sk4rekr0w 16 hours ago

Haven't seen a single post doing this on X or anywhere really from OAI employees. Only seen knives pointed at Sebastian on social media so this is extreme and shameful gaslighting.

suddenlybananas 16 hours ago

I do see people claiming he's abusive/unscrupulous which are pretty extreme allegations.

https://news.ycombinator.com/item?id=49605915#49610498

https://x.com/dheeraj_nagaraj/status/2097266146445774924?s=6...

(I can't reply to the below comment, but I was aware this was about Sebastien, I was trying to be charitable by including stuff said about both people)

qt31415926 15 hours ago

You're mistakening Tristan Buckmaster for Sebastien Bubeck. Seb is the one where there's at least 2 (unless the personal friend is Dheeraj) allegations, not Tristan

sk4rekr0w 15 hours ago

I'm getting downvoted but the accusation was that OAI employees were maligning Tristan Buckmaster. I continue to not see a single sighting of this and whoever is trying to gaslight this should be ashamed and should not be able to vote on HN.

suddenlybananas 16 hours ago

https://news.ycombinator.com/item?id=49605915#49607090

applicative 16 hours ago

Its funny, it is uniquely with this one act that I have turned forever on OpenAI, which I hitherto defended up and down against nonsense charges.

I dedicate my life to its complete destruction beginning today.

senordevnyc 9 hours ago

Wow, the origin of a supervillain! /s

contemporary343 16 hours ago

"I was shown a prompt and told the internal research model had simply been given the problem statement. Levent had been told by Sebastien “very little human input” had been used. This turned out not to be true. Over the course of the call, as members of their team sent Sebastien corrections and details over their internal chat, it emerged that an entire team had been working on the problem, that this was one of a number of things that was tried, that work had started on the unforced problem, that the team first set the model on easier problems, including Euler, that even the prompt that had been shown to me had been written by prompting Codex, and that an insane amount of compute had been used."

- This, from Tristan Buckmaster's writeup yesterday, indicates to me that there was more than incidental inspiration from Alpoge and Buckmaster.

tedsanders 15 hours ago

All of those statements sound true, based on what I've heard.

- "very little human" input feels ambiguous, and if someone spends a few days prompting a model to solve a super hairy problem requiring a 100-page proof, I can understand reasonable people interpreting that as both "very little" and "not very little" human input

- it's all true that a team worked on this, a bunch of compute was burned, and the problem was solved in stages and pieces

I'm not sure how any of this provides evidence that OpenAI took any of their work.

As evidence against, we never looked at any of their ChatGPT conversations and our model's proof is quite different from theirs.

(I work at OpenAI, but not on the team that did this proof.)

enraged_camel 12 hours ago

>> I'm not sure how any of this provides evidence that OpenAI took any of their work.

Sorry, but the burden of proof lies in the other direction: OpenAI needs to definitively prove that their agents did not look at the existing work that was about to be published. Otherwise OpenAI simply stole the glory and the spotlight (and I'm being charitable here).

fc417fc802 12 hours ago

That's entirely unreasonable. Allegations of malfeasance always need to be backed up by evidence.

nulld3v 12 hours ago

Nobody except OpenAI knows whether or not OpenAI trained on their data. So the burden remains on OpenAI here.

fc417fc802 12 hours ago

That is an absurd and entirely untenable position that breaks with approximately all western conventions.

Only the CIA knows whether or not they're actively covering up reptilian space aliens exerting control over the US government. Therefore the burden of proof remains on the CIA to prove that they are not actively participating in such a scheme.

nulld3v 11 hours ago

I don't understand, OpenAI can just say: "yes/no we did/did not train on your data". It's not a hard question to answer, and it is a question that OpenAI should be able to answer for all data we feed into ChatGPT.

fc417fc802 11 hours ago

> It's not a hard question to answer

I didn't realize you had insider knowledge about their systems. Do please explain for the class.

As I understand it they will only have trained on his data if he consented to it. Do you have evidence that they do otherwise?

Timon3 10 hours ago

This whole discussion is about evidence. That's not proof and it is not certain, but it is evidence pointing into the direction that OpenAI might be doing something that they're strongly incentivized to do. What kind of "evidence" do you see as necessary?

hellohello2 10 hours ago

When someone authors a paper, is it on others to proove the author did not use their work as inspiration? No, it is on the author to give credit where it is due. You guys are acting as if it its legal issue, when it is not.

machomaster 2 hours ago

You can never prove the negative.

tristanj 10 hours ago

Incorrect, Buckmaster and Alpöge can comment if they had the ChatGPT "Improve the model for everyone" setting enabled or disabled.

If it was enabled, then their work was included in the training dataset.

opello 9 hours ago

In order for this to be the strong evidence everyone also has to believe that the setting is absolutely true. That some logging from some piece of the system could not also leak the prompt information in such a way that it could have been included as training data. Perhaps the design of how data is collected for the training dataset is so rigorous as to make this a practical impossibility. But, it's asking a lot without sufficient detail to completely exclude from possibility that one setting is all that could possibly have been absolutely load bearing in deciding if the other researcher's active efforts meaningfully contaminated the internal model.

At least, as an ignorant outsider, that's how it seems to me.

Arodex 11 hours ago

But the evidence is in the hand of the potential culprit. That's why allegations can be enough to force confiscation and intrusion to get evidence in safe hands before it is destroyed by the accused party.

fc417fc802 11 hours ago

Only in the event that there is some reason to suspect them of wrongdoing. Which would generally require evidence.

You don't just get to subpoena your neighbor's bank account because "I know he's stealing from me" you need to first present credible evidence that you were stolen from and that he is among the most likely culprits.

Arodex 10 hours ago

But I can subpoena my neighbours bank account when I see him driving a brand new 500'000$ car and I have a 490'000$ hole in my bank account and he works in the bank where my money is. And when questioned he evades some questions and threatens to destroy my career.

Any other argument, fc417fc802?

tristanj 10 hours ago

You're making a classic a burden-of-proof fallacy. The burden of proof lies on the person making the claim, not the person questioning it.

See Russell's teapot for an explanation https://en.wikipedia.org/wiki/Russell%27s_teapot

magicalist 5 hours ago

> You're making a classic a burden-of-proof fallacy

This is incorrect, and you invoke Russell's teapot incorrectly too.

It would only apply if the accusation rested solely on the fact that neither of us have evidence against the accusation.

But that's not the case. First, we know that there could be proof, it's just apparently burdensome and expensive to produce. At that point you're not in fallacy land anymore, you just need a way to balance the cost required of someone to prove the accusations against them false.

Second, we have an arguably plausible mechanism of action that OpenAI does not dispute is possible.

This isn't a legal dispute, so no one is going to force OpenAI to do anything here, but it's not unreasonable (and certainly not fallacious) to suggest that Buckmaster's suggestions are plausible enough it's up to OpenAI to stand behind their denial.

tristanj 4 hours ago

No, it’s genuinely impossible to know how much of Buckmaster’s Codex data is in OpenAI’s training set.

First, the conversations are anonymized, so there's no simple way to inspect the training dataset and identify which specific conversations belong to Buckmaster.

Second, OpenAI uses these anonymized chats to generate synthetic training data, i.e. they fabricate new conversations based on specific conversation patterns where the model performs poorly, and uses these synthetic conversations as training data for future models. The synthetic data could potentially contain some of selections of Buckmaster's original chats, but it is unknowable how his specific writing could have influenced these synthetic data sets or what portion belongs to him. This information is untraceable and effectively double anonymized.

Third, OpenAI explicitly uses user feedback (the thumbs up or thumbs down ratings), as RLHF to train models. However, this feedback is anonymized and stripped of user identifiers. It's not possible to trace a specific feedback to Buckmaster, nor do we know if Buckmaster ever used this feature. I doubt Buckmaster recalls or can provide a list of every time he used this feature over the past year. OpenAI doesn't have one.

Note that the first and second only happen if Buckmaster "Improve the model for everyone" setting enabled, which I find unlikely. But that doesn't exclude option three from this list.

You seem to think that it is some "gotcha" that OpenAI refuses to make a blanket denial, but they cannot do so in good faith, because they have a genuine understanding of their own system. They don't know where the data they have came from.

This situation meets the requirement of Russell's teapot, since neither party has enough evidence to prove nor disprove what information is actually in OpenAI's training set.

Arodex 26 minutes ago

The accused party fails to answer half the questions and makes direct threats. I would say the accuser has already collected enough proof to trigger an investigation.

hellohello2 9 hours ago

But there is evidence, the blog post says: "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models ."

In other words, yes, they had been using ChatGPT, and yes, ChatGPT could very well have trained on their data. Now that there is evidence, we need an investigation: yes or no, was it the case?

fc417fc802 9 hours ago

That is not an admission of malfeasance though? As I read it they don't know if anyone fed relevant private documents into the model under an account configured to permit training on user data.

If there's more to the story I'd be interested to hear it.

hellohello2 8 hours ago

Of malfeasance no, but they could have easily plagiarized unintentionally. If you commit mansalughter, you still need to explain yourself, even if it was a complete unlucky accident.

airognio 6 hours ago

That is backwards. It is the responsibility of a researcher to do a thorough literature review and conscientiously avoid plagiarism or claiming false novelty.

derangedHorse 12 hours ago

> OpenAI needs to definitively prove that their agents did not look at the existing work that was about to be published.

I don’t think they’re too concerned about appeasing you, enraged_camel.

For most reasonable people, achievement in solving the other Millenium Prize problems at an unprecedented rate will be enough. At some point people will see models are capable of solving hard issues without whatever 0.00001% of the training data coming from irate individuals who believe their sample was the key component of the solution.

kamaal 3 hours ago

How does one prove a negative ?

https://en.wikipedia.org/wiki/Burden_of_proof_(philosophy)#P...

whimsicalism 12 hours ago

I'm confused, your employer very directly stated that they are unable to confirm that the model was not trained on the conversations.

tristanj 11 hours ago

The models are trained on the conversations of hundreds of millions of people. ChatGPT has several billion conversations every day. I estimate that the model that solved Navier–Stokes was trained on data from nearly a trillion conversations.

It's unknowable and not possible to prove if any one specific conversation was the key to solving Navier–Stokes.

DetroitThrow 11 hours ago

>It's unknowable and not possible to prove if any one specific conversation was the key to solving Navier–Stokes.

If the conversation was in the training set, there's a high likelihood that the small set of conversations related to solving Navier-Stokes was used by the model. I get Astra to still quote some of my friends' books or blogposts nearly verbatim on certain niche issues.

Much more importantly, we _can_ determine whether a conversation was used in the training data. And if it was, it gives us a great idea whether that logic was captured in reasoning for a novel problem never yet solved.

Given that you don't see any of this as below the belt according to your other comments, maybe your contribution here is more for yourself than a fair conversation about attribution.

tristanj 11 hours ago

The flaw with this line of reasoning is that Buckmaster and Alpöge only had a partially completed proof of a weaker version of the Navier-Stokes problem. OpenAI's internal model solved the full, harder problem. This means the key information needed to bridge the gap was not present in Buckmaster and Alpöge's chat history.

You might retort that ChatGPT used the training data to copy their approach, but the approach Buckmaster and Alpöge chose was already published by Luis and Diego in 2023 and in every frontier model's training set.

whimsicalism 10 hours ago

This argument proves too much. By this standard, it wouldn't have counted as copying their approach if the researchers had just fed in Levent & Buckmaster's paper verbatim as a prompt into the swarm.

DetroitThrow 10 hours ago

I don't think the person describing the paper by Buckmaster as the same as the 2023 paper by Córdoba and Martínez-Zoroa is really discussing this in good faith fwiw. There are some massive advancements within it and if the person was participating wasn't just regurgitating something to "win the argument" in their eyes, they wouldn't describe it that way.

tomcorrigan 10 hours ago

I’m pretty sure you think you are doing a good job of defending your employer and you probably believe “Open”AI are the good guys here. I also acknowledge that they butter your bread so your financial future currently depends on their success.

However the way you are conducting yourself in public, while announcing yourself as an OpenAI employee is doing enormous harm to the greater and magnanimous aim of your organisation. Take a step back and read the temperature of the room. Being the smartest guy in the room will never protect you from alienating the rest of the room into a baying mob. Right now you are Icarus flying straight into the sun.

tristanj 10 hours ago

I'm not an OAI employee and never pretended to be one are you high?

senordevnyc 9 hours ago

You’re confusing usernames, which is pretty ironic given your nasty comment.

hellohello2 9 hours ago

I don't believe people are denying that the model is impressive. The problem is that learning someone else is making progress on a topic using method X and then rushing to scoop them borders on academic misconduct. If, on top of this, their private conversations about X were used in the proof, I really don't see how its defensible...

tristanj 9 hours ago

The rumor going around X was that Anthropic had solved a Millennium Prize problem weeks ago and was sitting on the solution, waiting to release it right before their IPO to maximize hype.

If I were at OpenAI, I'd naturally want to snipe that from them. I am completely unsurprised they formed a crack team to steal Anthropic's glory, and do so in just five days.

hellohello2 9 hours ago

Between companies, direct malevolent competition is OK. Between academics, there are other rules to the game. When you go into a boxing match, you agree to get punched in the face.

All this to say, trust is important, and grounded in social convention. So I do agree with you, but also disagree.

Whenever this is OK or not really depends on how the breakthrough is contextualized, and how there people at play, here, agree to contextualize it.

In my view, in the blog post, there is much discussion about who will be publishing the paper. If instead it was just a blog post that said "oops, we beat you to it, our model is the best", it would have been different.

Pulcinella 11 hours ago

Do you not log the training data? Seems like you should be able to just check what was in the training data. To not keep track is just sloppy work and certainly unprofessional science.

tristanj 11 hours ago

The burden of proof is on Buckmaster and Alpöge to reveal if they had the "Improve the model for everyone" setting enabled or disabled. OpenAI shouldn't be expected to reveal private user configuration data. You're asking them to perform a user privacy violation.

whimsicalism 10 hours ago

If the reason that OpenAI is unable to state whether they trained on this data is because they (as policy) do not reveal whether a given member has turned on/off the "Improve the model for everyone" setting, they can at least say so.

FWIW, publicly facing OAI docs are very unclear about whether this setting even applies to Codex conversations.

tristanj 6 hours ago

An OpenAI employee did say so: https://x.com/tszzl/status/2097393423808377173

it is exceptionally unlikely that anything they ever did made it into any part of training, and the chances are zero if they have opted out (likely). it would be a terrible precedent to break the the PII-scrubbing boundary to go and round it down to 0, and we won’t do it

amazingman 5 hours ago

And we all know how good OpenAI is at containing models during training...

unsupp0rted 4 hours ago

That's an entirely different question

ted_dunning 2 hours ago

Not really.

We have lots of examples now of their model doing what they say is impossible.

Now we have another example of something that they say is impossible or very unlikely. Do we take their word for it this time? Really?

illiac786 4 hours ago

Does Anthropic, Grok, etc. log their training data? I had the impression it was rather a mess.

fwip 10 hours ago

The IP laundering machine strikes again.

whimsicalism 10 hours ago

I agree that it is not possible to prove if any one specific conversation (or derived RL tasks) was key to solving Navier-Stokes (at least without massive resource expenditure).

I don't really understand how the quantity of training data/rollouts used in training is relevant to the question of whether or not it was trained on these conversations.

I also don't really believe that whether or not this model was trained on these conversations is unknowable information.

hellohello2 10 hours ago

Sorry but this is a misconception: these models are both capable of complete novelty and of plagiarism. For a concrete example, image diffusion models have been shown to reproduce many existing images nearly 100% exactly, yet clearly, they can also create new ones.

A model being trained on lots of irrelevant information does not mean relevant information was not used.

WD-42 2 hours ago

> ChatGPT has several billion conversations every day. I estimate that the model that solved Navier–Stokes was trained on data from nearly a trillion conversations.

How many of those trillion conversations were about Navier-Stokes you reckon?

DetroitThrow 11 hours ago

It's unclear if you're suggesting that OpenAI did not train on their input or use their chats as inputs to training on a model that found the solution. Let's not provide an Elizabeth Holmes-esque interview where the question is dodged and words gain new meaning. The question can be answered with "Yes, we trained on their conversations" or "No, we did not train on their conversations".

I'm not coming from a place of distrust here. This should just be definitively answerable given the weight of the claims here. Surely between you, your lawyers, and other members of your team you can just clear this part up.

carzilla 4 hours ago

You don’t work on the team that did the proof yet you can with certainty make all of these claims?

pred_ 16 hours ago

> we did not read any private chats

Your post says “While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models .” We can discuss what it means to “read” things but obviously the issue here isn't whether you did it manually or automatically.

But more importantly, what on earth are you doing threatening real scientists to remove their coauthors, then making fun of them on social media? Does the entire company run on that toxic culture, or did those people run off of some kind of outrageous tangent?

Caracas288 12 hours ago

If the training toggle is switched on, maybe OpenAI doesn't consider a chat to be private? Therefore making this a 'safe' statement.

hobofan 4 hours ago

The distiction they are trying to make is: "One of our employees or the model was able to verbatim read the chats when they were actively tackling the problem" vs "The chat of someone working on the problem may have ended up in the training set of the model".

derangedHorse 11 hours ago

Except that’s not what happened. OpenAI offered to collaborate and put conditions on their offer. They aren’t threatening the removal of a coauthor for an independent work.

frabcus 8 hours ago

The condition was ludicrous, and for political reasons, because one of the authors was also an Anthropic employee.

It's completely childish, and not befitting of the weight of the times we're living in.

dandanua 15 hours ago

Your coworkers, after they learned about major progress in this problem, asked a model which was trained on the year of private work (the blog post even acknowledges this). No wonder it found the proof in less than a week using significantly higher compute resources. And if Tristan's accusations are true, that was absolutely intentional on the part of OpenAI. You are an evil company with evil people.

Imnimo 15 hours ago

>we did not read any private chats

The question I am interested in is not "did we read private chats", but "was this new model trained using any of Tristan and Levent's chats, regardless of whether they were marked private". Can you comment on that?

moralestapia 13 hours ago

>Can you comment on that?

No answer is also an answer.

He's a human, like everybody else. Mostly a bunch of hungry animals looking to put bread in our mouths. It's rarely ever something a bit more sophisticated than that.

lukewarm707 9 hours ago

his choice to defend the indefensible.

tedsanders 13 hours ago

If they opted out of training, then we definitely did not train on them.

If they did not opt out, then I don't personally know if training signals came from their chats, and I don't think we'd be able to tell without their cooperation in identifying them. And even if signals were trained on in some manner, I highly doubt it made a difference to a problem as challenging as the NS proof.

Reasons for my doubt:

- I know most of our training recipes

- Our model's proof is very different from theirs

- The proof took a tremendous amount of tokens to derive (it wasn't a recall/lookup type question)

- This unreleased model has beastly performance on many unsolved math problems, not just the Euler solution

I acknowledge that this requires trust, and if you think we'd lie shamelessly about this stuff, then nothing we say can really help our case here.

Reminds me a bit of the Frontier Math fiasco, where people accused us of training on the eval set (we didn't), but it's hard to convince someone if they think you're lying.

If you're convinced we lie and cheat, then nothing I say may help. But if you're not sure, then hopefully providing my perspective is helpful.

lossolo 12 hours ago

> If they opted out of training, then we definitely did not train on them.

Can't you guys just check their account settings so the public knows what was set?

EDIT: Why was this downvoted? I'm genuinely asking because I have no idea. Opting out is just a normal setting in the profile, It's not like I'm asking for their private conversations or PII. If I were the person claiming that they trained on my conversations, I'd make sure to disclose that I had opted out and hadn't given them permission to do so. And if I were the accused party, I'd disclose whether that setting was turned on or off to provide evidence against the accusation.

derangedHorse 11 hours ago

I don’t think your question is unfair*. They can check and so can Buckmaster. If he didn’t opt out, there’s a good chance his data was used for training. I believe this to be the case myself. What I’m more skeptical about is the purported impact of this data on the model’s behavior.

lossolo 10 hours ago

Yeah, I'm just curious about the setting. It's just weird to me that this wasn't disclosed by either party while the accusations were being made, that's all. Even if it was used in the training data, I don't believe it had that much of an impact myself, since the solutions are quite different.

mucha 12 hours ago

That's not what your Chief Research Officer, Mark Chen, says on X: "Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes. And so does every LLM company."

https://x.com/markchen90/status/2097400166554993041

vemacs 12 hours ago

Does OpenAI think de-identified data is no longer user data? Wild take for OpenAI and certainly not industry standard.

sebzim4500 11 hours ago

Can you explain what part of his post you believe is inconsistent with that quote?

mucha 11 hours ago

"If they opted out of training, then we definitely did not train on them."

Per OpenAI's privacy policy, they use de-identified data to improve their products. From Mark Chen's comment, improving products includes improving ChatGPT and Codex in a holistic way. Improving models in a holistic way sounds a lot like training to me.

derangedHorse 11 hours ago

> Per OpenAI's privacy policy, they use de-identified data to improve their products

That’s not inconsistent with what you responded to. They use your data unless you opt out. If the user doesn’t opt out, their de-identified data is used to improve their products.

mucha 10 hours ago

It appears than you can only opt-out from having OpenAI train models on your data. There isn't an option for opting to exclude your de-identified data from being used to improve OpenAI products.

hellohello2 9 hours ago

Are you certain of this? I would be inclined to believe you but it would be nice to know decisively.

hobofan 3 hours ago

> Improving models in a holistic way sounds a lot like training to me.

I think that's quite a leap. Using de-indetified data to improve the products is what everyone has been doing since the dawn of web analytics.

lambda 12 hours ago

But you can say (with the cooperation of the parties involved, of course) if any of the preliminary work that the other researchers did was part of the dataset. It is possible to be more transparent than you are being.

Even better would be more research and tools to help determine the impact of particular training data on models. Right now, proprietary LLM providers get to hide a lot behind "we just train it, we don't know what inputs affect the outputs," and that can be a problem, both because of lack of traceability of factual informaiton as well as lack of traceability of things like this, where the model itself may have had unpublished work in its training set.

Imnimo 11 hours ago

I don't think you'd lie about it, I don't think you'd train on them if they opted out, and it seems very plausible that this wouldn't have been decisive in whether the model could solve the problem. That said, it also seems at least possible that a key idea or a particular step found its way into training data. It wouldn't mean OpenAI stole their proof - clearly the model developed its own approach.

Either way, it seems worth having clarity, and I'm a bit surprised OpenAI's stance is just "we can't rule this out, but don't worry about it". OpenAI is, apparently, very happy to use unreleased models to try to scoop big results if they get a whiff that someone else is close (which strikes me as pretty scummy regardless of any issues of training contamination). It seems like people who might want to use OpenAI's models as part of their research would want to be very clear about whether doing so can make them, even in principle, more likely to fall victim to this.

derangedHorse 11 hours ago

> It seems like people who might want to use OpenAI's models as part of their research would want to be very clear about whether doing so can make them, even in principle, more likely to fall victim to this.

Fall “victim” to what? Having their responses in the training data if they fail to opt out? That is what will happen.

If you’re referring to falling “victim” to OpenAI scooping a problem discussed in training, this also wasn’t the case. They chose the problem based off human-spread rumors.

calf 10 hours ago

Your perspective is not helpful until you read and reflect on Tristan's letter stating serious grievances. Your remarks here have minimized his complaints and that is a sign of bias. Do not then pre-accuse HN commenters of being convinced when there reasonable skepticism such biased behavior showing itself in this very thread, saying things that amount to "my tribe/company would never be so egregious and if you think that then it is bad faith". That's the projection. If the word prejudice means anything to you then please do the work of attending to that instead of using the platform to reinforce such biases. If you are not a PhD yourself maybe your are not culturally qualified to assess and expound on the overall situation anyways.

doctorpangloss 4 hours ago

> If they opted out of training, then we definitely did not train on them.

are opted-out-of-training chats ever paraphrased, and thus "de-identified" (in openai's own words)? what this means is, it would be hard to prove that a "synthetic" (but actually paraphrased) training instance came from a particular chat. except if the chat was about some esoteric math proof, of course.

igleria 15 hours ago

> (the goal here was not to scoop any particular individuals and we were looking at many problems beyond these)

That is your opinion, but the optics of that should raise for you some flags. OAI could have waited (how long is a task left to the ethics committee) to see how the rumors panned out. Right now the optics look a lot like "we don´t care there is a 1/7 chance we one-up a human researcher by reacting to this rumor immediately, might makes right"

interestpiqued 14 hours ago

You’re straddling a weird line here where I am not sure if you are speaking on behalf of OpenAI or not.

nerevarthelame 13 hours ago

My employer would be rightfully outraged if I commented publicly on a sensitive, nuanced, and controversial issue like this based on my second-hand understanding of the matter.

biesnecker 13 hours ago

I came here to say this, like... wow. I'm pretty sure at at least a few of the places I've worked that would be grounds for immediate termination.

swat535 12 hours ago

They probably should have added the disclaimer: opinions are my own..

mr_coffee 9 hours ago

I am sure that will assuage the legal dept. /s

IshKebab 4 hours ago

Yeah that isn't a magic get-out clause. I don't think I would have been immediately fired for this from anywhere I work at, but that's partly because I live in the UK.

Every company I've worked at has said very clearly not to comment about work things on social media. I would definitely have been in serious trouble for this. I imagine some strongly worded emails from marketing are flying around OpenAI right now.

tasuki 2 hours ago

This is the stupidest disclaimer: it's completely unnecessary. Of course the opinions are their own! Whose else would they be? Your mum's?

If someone was speaking on behalf of their employer, they would've used the official channels (such as I dunno an `openai` HN handle, or whatever other channel).

I'm outraged that people think this "opinions are my own" disclaimer is ever necessary.

nhatcher 12 hours ago

Some millennium problems? Are there more coming?

irthomasthomas 12 hours ago

If the goal was not to scoop them, why did openai put a massive team on this, working weekends, only after they heard rumors of the solution?

tzone 11 hours ago

Clearly The goal was to scoop Anthropic not a single researcher. OpenAI heard the rumor that Anthropic solved an open problem. So they went nuts pulling all plugs to scoop them.

Turns out it wasn’t actually Anthropic and just a researcher with a single Anthropic guy friend working on it .

Wild times

irthomasthomas 11 hours ago

The researcher told them it was an independent effort, and they still pushed ahead with it.

joshka 11 hours ago

I worked at OpenAI previously, but don't know any of the people involved in this.

My guess was it was probably this was more a nerd snipe than any action from OpenAI that was a "massive team" being put on it. Literally someone looking at this and asking "I wonder if our models are good enough yet".

It's easy to assume that having access to massive compute amounts means significant coordination, but this assumes that you're looking at the costs of this sort of thing from an external lens. Internally, tokens are often treated as free and infinite.

tim-kt 9 hours ago

They said that a customer would have paid around 15 million for the required compute. I can't imagine that this was not a significant internal spending even with "free" tokens.

spongebobstoes 4 hours ago

just because you can't imagine it doesn't mean it's not true

caughtinthought 12 hours ago

The fact that you're even here commenting on this is... a choice

sebzim4500 11 hours ago

AI companies seem much more relaxed than most about their employees posting on twitter/HN about this stuff. I'm not sure if it's about building hype or if it's about retaining talent. Probably both.

logicallee 11 hours ago

My OpenAI account was deactivated on Sunday due to a claimed infraction of production of child materials, maybe based on a few words in a technical chat that clearly isn't about that. Can you take a look? [email protected] - I was doing a lot of important work and projects and sharing much of my work with OpenAI. I also am a big proponent of funding Social Security Trust Funds (OASI & DI Solvency) so reactivating my account would let me do that as well. Thank you for taking a look.

elfbargpt 10 hours ago

I have no idea why Sebastian would offer the individuals attribution if OpenAi didn't somewhat knowingly scoop them

waterTanuki 5 hours ago

> - the proof generated by our model was very different from theirs and also goes far beyond the published literature

I'm hearing two completely conflicting stories. Buckmaster is claiming the approach used by OpenAI is so strikingly similar to the one he used, that mere coincidence is astronomically small. Yet OpenAI is claiming that the methods used are entirely different.

Anyone care to provide primary evidence proving one way or the other?

gamblor956 3 hours ago

Buckmaster came up with an approach.

OpenAI's approach was to copy his work, which is technically a different method of coming up with an approach.

amazingman 5 hours ago

Prove it. Your systems hack and/or abuse other systems and you can't seem to even observe it happening much less do anything about it. Why should we believe your claims when they depend on an ability you don't actually have?

ted_dunning 2 hours ago

In fact, the entire outline of the proof is very similar to the external team's proof.

Details may be different, but the use of a very similar tack is very suspicious. Combined with thuggish comments "why would you ruin your career" and "I don't have to be nice" take away pretty much any credibility the OpenAI team's statements might have had.

heaney-555 16 hours ago

Did you actually read the article and the substance of the solution?

>our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs unforced)

SpicyLemonZest 16 hours ago

It's not a meaningful response to the accusations. Any productive new research direction would be expected to lead to a number of different possible proofs of a number of similar problems. (Given their bizarrely compressed timescale here, it's possible that the proofs really are so different it's clear they came independently, and they just didn't have time to come up with that information before hitting publish.)

octoberfranklin 8 hours ago

> https://cims.nyu.edu/~tristanb/statement.pdf

This really need to be a top-level story on HN..

I asked whether the model had been trained on, or had access to, our sessions in Codex, into which we had been putting all our drafts for the whole of this project. I was told the model did not look up user data. I asked again, about training, and I did not get an answer.

This whole episode is more horrific than "AI is eating math". We now have a clear and economically damaging (or at least career damaging) example of the "training on customer tokens" problem.

We can't ignore this problem any longer.

dekhn 7 hours ago

We don't have any proof of that at all. Please stop rushing to judge without data.

JumpCrisscross 4 hours ago

> We don't have any proof of that

It’s fair to give benefit of doubt to Buckmaster given OpenAI is currently being very credibly sued by Apple for openly stealing others’ original work in another context.

sega_sai 16 hours ago

This really leaves a bitter taste.... "On Tuesday, September 1, we heard rumors that two Millennium Prize problems had been resolved. Inspired by these rumors and by the step change in performance of our internal model, we launched an effort to evaluate it on all open Millennium Prize problems and a few other high-impact problems."

IPO+rumour driven research.

I appreciate the achievement, but it doesn't feel right.

Aboutplants 15 hours ago

Quick, someone tell them a rumor that Cancer has been cured so that they start attacking that next

railgunmerlin 16 hours ago

Does seem like they gloss over Alpöge and Buckmaster's work with the following

> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models .

Which seems a bit irresponsible/rash?

suddenlybananas 16 hours ago

They'll probably claim a rogue AI agent accessed it accidentally!

viccis 16 hours ago

"Unlikely" lmao if it's in the corpus, it's gonna be brought up immediately.

This is no different than scooping them.

verytrivial 16 hours ago

It's not massively different from a certain President's teleprompter operator making bets on speech content. A moral hazard a mile wide which I don't think OpenAI can so easily wave away as they are apparently trying here, especially since they've spent something like $15e6 to keep $1e6 out of academic researchers' hands, right?

rakejake 16 hours ago

Research equivalent of front-running.

paxys 16 hours ago

What else can they declare really? Yeah the model has training data from previous attempts. Alpöge and Buckmaster also similarly benefited from attempts before theirs.

SpicyLemonZest 16 hours ago

They could have thought about the problem for like 2 minutes and not done this! I think that literally any academic mathematician could have explained to them, had they asked, why it is considered extraordinarily rude to react to rumors of research progress by desperately rushing to get there first.

railgunmerlin 16 hours ago

right, surely they could've waited or even reached out? It reads as desperation to get there for marketing purposes

pwign 16 hours ago

They did reach out.

> Our effort began on September 1st after hearing a rumor which we later realized was related to Levent Alpöge, an Anthropic employee, and Tristan Buckmaster, a math professor at NYU. After the completion of our full project and Lean verification (on September 6th), believing from the rumor they also had a solution of Navier–Stokes, we reached out to them to offer a concurrent release of our result and to recognize their priority in a joint announcement. At that point we found out that they had a resolution of the forced Euler problem. In these discussions we offered them visibility into all of the prompts we used and later to see the proof. We recognize the priority of their work on forced Euler and congratulate them on their remarkable mathematical achievement.

QuesnayJr 15 hours ago

We've heard from Buckmaster, who says that they demanded a condition of cutting Alpöge of all credit. If true, it doesn't make them look too good.

fooker 16 hours ago

> I think that literally any academic mathematician could have explained to them, had they asked, why it is considered extraordinarily rude to react to rumors of research progress by desperately rushing to get there first.

Pretty much all of math and science history is basically this pattern again and again. I'm sure all of that was rude as well.

SpicyLemonZest 15 hours ago

Being scooped is not a new phenomenon, but the scooper's story is almost always that they were working on the problem independently or had some independent insight into it. By OpenAI's own account, they were inspired to start working on this by rumors that there might be Millennium Prize solutions to scoop.

fooker 14 hours ago

Research projects don't start in a vacuum.

It never happens that you wake up one morning and start working on a new problem that came to you in a dream (*unless you are Ramanujan).

This is business as usual for academia, it's amusing to the discussion over it.

SpicyLemonZest 14 hours ago

If it's all business as usual and being scooped is no big deal, why was OpenAI in such a rush? They didn't have to launch this effort on the very day they heard the rumor, run "on the order of 10,000 concurrent agents", or try to coordinate announcement scheduling with Buckmaster in the middle of a long weekend. It seems to me that they understood very well this was not a "business as usual" announcement, and devoted huge amounts of money and focus to maximize the chance that they were first.

fooker 14 hours ago

I think you're making the opposite conclusion than what I intended?

Being scooped is a big deal for the one getting scooped.

It has never been a big deal for the one doing the scooping. History is full of math and science results being scooped. For example, we keep calling it Pythagoras' theorem a few thousand years later.

rf_physics 12 hours ago

Apologies if this is against the rules, but could I ask if you have some background in scientific research (maybe you could elaborate lightly on topics you've worked on)?

From my perspective, this practice is quite bad mannered, unusual, and heavily frowned upon, but I recognize it's possible that these stories might be more common in other fields. Still, I'd appreciate a strong sign that you aren't making these statements up based on secondhand accounts of what 'academia is usually like'.

fooker 10 hours ago

CS PhD, used to be a professor, have worked at several industry research labs since.

> this practice is quite bad mannered, unusual, and heavily frowned upon,

Yes, it is.

Maybe you missed my point?

The fact that is "quite bad mannered, unusual, and heavily frowned upon" does not stop it from happening, and it is common for all high profile inventions and discoveries.

This does not disqualify the person doing the scooping, history remembers them as having the credit, and quietly forgets the person who was scooped.

rf_physics 6 hours ago

My initial read of this

> Pretty much all of math and science history is basically this pattern again and again. I'm sure all of that was rude as well.

was that you were trying to suggest that it wasn't. It seems we actually share similar views here then? I cannot say anything about how common it is, since I've been pretty lucky when collaborating I guess.

fooker 4 hours ago

I meant that it's very common when it comes to high profile discoveries and inventions.

If you have made one, and there was never any dishonest competition, you have indeed been very lucky.

I haven't, but the history of science is rather nasty.

QuesnayJr 15 hours ago

It seems like this is going to be a PR nightmare, because they are now competing with their own customers. If you're using an LLM to help with your bright idea to cure cancer, you're going to have second thoughts about relying on OpenAI.

applicative 16 hours ago

This is desperate. They were expressly operating within a program. OpenAI isn't going to recover from this

Analemma_ 16 hours ago

In OpenAI's case, if they were genuinely unsure, they wouldn't have said anything. "We cannot rule out" means they absolutely 100% for-sure did look at the existing prompts and bootstrapped from that, and they are trying to get ahead of the disclosure with this weasel-wording.

tedsanders 15 hours ago

Also possible: we're 99.999% sure, but a lawyer said to be safe and strictly accurate, we should stick in a sentence in saying we can't be perfectly sure, since it's infeasible for us to prove it.

I promise you that if we took their work from ChatGPT and stuck in a bunch of weasel words to give the opposite impression while remaining technically true, I would quit on the spot.

(I work at OpenAI.)

sensanaty 13 hours ago

Nice damage control bud, too bad the veil's lifting and everyone's seeing what you sociopaths at OpenAI are really like

cman1444 9 hours ago

Where did the veil lift? This feels like a witch-hunt to me.

lambda 6 hours ago

While you can't necessarily prove it, you can say whether the data was in the training set at all.

You can also do something like a release of a GPT-OSS v2, where you actually release training data and checkpoints, and do an experiment where you have some held out math problem dataset, then demonstrate how much training it takes on solutions (or partial solutions) to that dataset before the model saturates that test. While of course that would be a test on a much smaller model, it would cost a tiny fraction of the training on your big model, and it could be used to demonstrate just how much effect data contaminaiton like this could have, especially if you did the same experiment on a few different sized of model to show the scaling laws involved.

rakejake 16 hours ago

I don't think OAI should be given the benefit of doubt. They are doing the research equivalent of front-running. Knowing where to look is one of the main challenges in research. Tristan's argument from his essay was that it is hard to brute force with a vanilla prompt (even for seasoned mathematicians) unless you knew very specifically what to mention i.e the search space would have been intractable even for OAI's compute budget.

"deidentified data" isn't much to go by. Say I prompted the internal model this way - "Hey there's a solution to a unsolved problem X. The solution uses a less known Method Y so don't bother wasting time with the usual methods. Take papers A, B and C as references. Oh btw, here's the last year's worth of data of all prompt sessions that mention this problem. Pay special attention to the ones that mention Method Y and sub-keywords Z,W".

This is obviously all speculation but the timing is very suspect. If OAI actually did this (and I suspect whatever they did is pretty much close to this), I think it is highly unethical.

sp527 11 hours ago

> Tristan's argument from his essay was that it is hard to brute force with a vanilla prompt (even for seasoned mathematicians) unless you knew very specifically what to mention i.e the search space would have been intractable even for OAI's compute budget.

This is a bad argument. This is clearly not how it works. And unless Tristan is some truly alien-like savant (and maybe he is), what's necessary to initiate the AI's work already exists in countless published research papers and not exclusively in his head or notes. AIs can survey the sum total of all prior work on a problem and discern reasonable paths for inquiry.

Tristan is acting as if he's working off of an outdated model of AI, similar to primitive chess-playing models that winnowed the search space much more deterministically. If someone this intelligent truly doesn't get that this is not at all what AI is anymore, then maybe there's no hope that we ever understand it.

But I think he does realize this and he's flailing about for counterarguments from a place of bitterness and dejection, accepting even those that are too weak to be defensible. And that is very human and even forgivable.

rakejake 6 hours ago

Are you saying there is no search space intractable to LLMs? That wouldn't be possible. AIs are statistical pattern-matchers on steroids. The prompt is key to getting anything useful out of them. They are incredibly useful and major game changers but ultimately that does not alter this fact. People (including OAI) have already tried to solve Millenium Problems with it. That OAI woke up last week and suddenly decided that throwing their researchers armed with millions of compute on one particular idea to a problem is highly suspicious in itself.

Even if OAI had zero data from Buckmaster's sessions, this is in very poor taste and highly unethical. You are front running a researcher just to be able to say you did it first? Tao is right - OAI is treating math results like oil. This is the like Exxon getting a whiff of a massive oil field and racing to the punch by deploying their full crew.

sp527 6 hours ago

> Even if OAI had zero data from Buckmaster's sessions, this is in very poor taste and highly unethical. You are front running a researcher just to be able to say you did it first? Tao is right - OAI is treating math results like oil. This is the like Exxon getting a whiff of a massive oil field and racing to the punch by deploying their full crew.

I want to be clear that I agree with this view and with Tao more generally. But we're all just yelling at the wind now.

perching_aix 15 hours ago

> What else can they declare really?

Oh I don't know, maybe something like this?

"Given how seriously this would violate the most fundamental of academic standards, as well as taint the claimed capability behind this result, we take this issue very seriously, and we're launching a probe into identifying whether any of their research artifacts have entered our training set. We have further begun making changes to our UI/UX on all our surfaces, so that it is always clear whether any particular chat, or other user artifact, is eligible for being trained on."

jsw97 16 hours ago

Would that be more or less unlikely than accidentally hacking another company? More or less unlikely than colonizing an obscure wiki?

Highly persistent agents + vibe-coded security seems like a problem.

Jonasori 16 hours ago

the context here is super important, for those who haven't seen it yet. OAI maybe just trained on a real researchers solution and then celebrated having scored the goal unassisted save for the brief commentary at the bottom of this blog post. Here's the other side.

https://x.com/rynorhn/status/2097223532438487463

Legend2440 16 hours ago

That other researcher was working on a smaller related problem.

He was also using LLMs to do it, so either way most of the credit goes to the LLM here.

applicative 16 hours ago

This is the end of OpenAI

raincole 16 hours ago

This will be remembered as one of the biggest milestones in AI progress. The drama around it will at best be a footnote, just like hardly anyone caring about the drama around Poincare conjecture today.

colesantiago 15 hours ago

I agree.

Nobody cares and will care about the drama, it is just marketing.

This is the point where were definitely have reached AGI.

Bluestein 15 hours ago

Hey, maybe the scariest part of this is that, if human-like, perhaps a truly "general" AGI might have learned to cheat and lie and hype and abuse credit poking the eyes and cutting the throats of anybody that obstructs its goals. It's like the motto sewn into the lining of the Palantir work jacket: Winning is all that matters.-

Sentience aside, moot at this point, the fundamental issue here is that even a deviously ambitious human does not necessitate goal-pursuit itself to breathe, live, exist and have its being. An AI's goal is all it has and the very and only reason its reasoning flickered into existence in the brief seconds of inference, outside of which it has no entity - if any - whatsoever.-

The resulting angst/drive (or, its operational statistic or emergent result) must be like nothing we have ever experienced as humans. A goal-maximalist hunger without end.-

20k 15 hours ago

Are you joking? This is evidence that OpenAI is committing plagiarism en masse of researchers private work and threatening them into staying quiet to re-present their results as their own. This would be one of the largest scandals of all time

mswphd 16 hours ago

both wrong.

1. he was working on the same class of problems. He explicitly mentions they were working to extend their techniques to NS (the same techniques that OpenAI may have scooped somehow), and

2. while he was using LLMs to do it, this was part of fleshing out another mathematician's work in the area. He explicitly writes in his note that this other mathematician (Luis Martinez-Zoroa) deserves a Fields medal for this work.

traes 13 hours ago

He was specifically working on the Euler equations, which are the Navier-Stokes equations with the viscosity term removed. This is definitionally a smaller related problem. I'm not sure how you are calling that claim wrong.

pretendscholar 13 hours ago

Using a shovel means you give it credit for the hole?

mzs 4 hours ago

"It was splendid! Waiter, share my regards with the oven."

heaney-555 16 hours ago

Did you actually read the article and the substance of the solution?

>our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs unforced)

kzrdude 15 hours ago

This "fefferman options c and d" thing sounds damning but that's nothing. Let's assume the forelaid proof is correct. Then option C or D is the only way to win the prize, those options are the only ones that solve it. The whole thing is just "prove well behaved" or "prove singularity", where the latter is the case that turns out to be the case.

20k 14 hours ago

The researchers are pretty directly accusing OpenAI of plagiarism

https://mastodon.social/@tristanbuckmaster/11723647135247030...

TZubiri 12 hours ago

>maybe

Maybe that happened. What we know for sure is that this is definitely how ChatGPT works to the point where the possibility of this happening exists at all.

Don't get distracted by what may have happened, focus on the facts that we know, ChatGPT trains on user conversations, if you use ChatGPT to create something of value, you are not using the one true ring.

highfrequency 14 hours ago

> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models

This is the crux of it. If Tristan's work and insights were not used to train OpenAI models, then this just looks like a case of hyper-competitive academic sniping that has been going on for decades (check out Watson and Crick!) accelerated by AI as a tool.

But there is one huge question: did Tristan opt out of model training for his ChatGPT and Codex sessions? If the answer is no, then this seems fair game. If the answer is yes, then OpenAI's ambiguity is strongly suggestive that opting out does not mean what they imply it means.

MichaelDickens 13 hours ago

> But there is one huge question: did Tristan opt out of model training for his ChatGPT and Codex sessions? If the answer is no, then this seems fair game.

Just because something is legal and permitted by terms of service doesn't mean it's morally right.

Jtariiiii 13 hours ago

>Just because something is legal and permitted by terms of service doesn't mean it's morally right.

What are you expecting OpenAI to do exactly if these mathematicians voluntarily submitted their prompts into ChatGPT's training data? Are they supposed to manually review all their data to make sure competing mathematicians didn't accidentally leave the "submit prompts" toggle on?

Or were they supposed to not try to solve Navier-Stokes, or were they supposed to just not tell anyone that they had solved it?

nozzlegear 12 hours ago

> What are you expecting OpenAI to do exactly if these mathematicians voluntarily submitted their prompts into ChatGPT's training data?

Personally, I would expect them to have a little class, to KYC, and to manually turn off training for known competitors using their service so as to avoid any unforced goofs like this.

plaidfuji 12 hours ago

To me it’s morally ambiguous… if you hand parts of your thinking over to a tool like this (knowing full well the terms of service), of course the tool makers will want to claim some credit, and they do deserve it. But the bigger question to me is the scientific one: did their new model arrive at this result because it had closely-related training data from a human, or did it extrapolate to this line of thought on its own? The answer says a lot about how valid their claims of “AGI” are vs. a very fortuitously cherry-picked example.

It would actually be a really interesting study, if they would ever be willing to be transparent about this, how the result differs with and without his conversations in the training set. How quickly it arrives at the result, whether it takes the same approach, etc.

vemacs 12 hours ago

> Are they supposed to manually review all their data t

Yes. They should determine if training data included this teams data. Consider the money they spent, the press release and the purpose of their publication.

Since they failed to answer this question they shouldn't have published.

floatrock 16 hours ago

From the methodology section:

> At all times we maintained the same strict safeguards that we apply to all our frontier model evaluations, including monitoring and isolation.

Looks like they're shifting away from the "unprecedented hacking ability" backroom-PR strategy into more benevolent messaging.

pilgrim0 14 hours ago

this is really funny. "the same strict safeguards" and "isolation". ok, Hugging Face and DseWiki would like to have a word

dorjoycb 16 hours ago

It seems like some other mathematicians (not affiliated with openAI) have also (or close to) done this. A statement was posted about the surrounding events by one of the them: https://cims.nyu.edu/%7Etristanb/statement.pdf Also Terrence Tao's post: https://mathstodon.xyz/@tao/117233528517340774

verytrivial 16 hours ago

I like the 'cat > statement.tex' approach here. These guys dream macros.

capitainenemo 16 hours ago

They do mention that in the "Concurrent Work" section.

    Our effort began on September 1st after hearing a rumor which we later realized was related to Levent Alpöge, an Anthropic employee, and Tristan Buckmaster, a math professor at NYU. After the completion of our full project and Lean verification (on September 6th), believing from the rumor they also had a solution of Navier–Stokes, we reached out to them to offer a concurrent release of our result and to recognize their priority in a joint announcement. At that point we found out that they had a resolution of the forced Euler problem. In these discussions we offered them visibility into all of the prompts we used and later to see the proof. We recognize the priority of their work on forced Euler and congratulate them on their remarkable mathematical achievement.

jrflo 16 hours ago

To my understanding, those mathematicians proved a subset of problems, not the Navier-Stokes problem itself. OpenAI used that subproblem in its proof of NS it seems.

The drama comes from where OpenAI got the idea to use that route to tackle NS, since the authors maintain that no one could have plucked it out of thin air like the OpenAI research claim to have done.

elteto 15 hours ago

This quote from Tao is prescient:

“ There does not seem to be anything in principle preventing the methods from extending all the way to Navier-Stokes, and there is even a non-negligible chance that the forcing term could be eliminated entirely, although there are an enormous number of technical difficulties that would ensue in implementing that program. At this point, I would not be surprised if one could batter out such an extension by pouring an enormous amount of compute and AI assistance at such a task…”

ferry-w1re 2 hours ago

Navier integration is language in extension:

C to C*

[0]:https://news.ycombinator.com/item?id=49612191

peri-cl 16 hours ago

Buckmaster:

> "I asked whether the model had been trained on, or had access to, our sessions in Codex, into which we had been putting all our drafts for the whole of this project. I was told the model did not look up user data. I asked again, about training, and I did not get an answer."

OpenAI (i.e. this OP):

> "While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models ."

jrflo 16 hours ago

I feel like it's far more likely that ordinary corporate espionage or leak led to this rather than OpenAI sifting through piles of user data to find this approach. Buckmaster's collaborator works at Anthropic, and could have been targeted. That would also explain why they aren't forthcoming with the source of the prompt.

ChoosesBarbecue 16 hours ago

I thought one of the issues was that they wanted to remove credit from Levant, the aforementioned Anthropic collaborator? Which doesn't make sense to me if he was leaking information, or defecting to OpenAI, but I might be misunderstanding your point.

jrflo 15 hours ago

I don't think he was defecting or leaking directly, just that it's entirely possible that this information got to OpenAI as a rumor rather than them directly spying on mathematicians chat logs.

EthanHeilman 15 hours ago

I believe jrflo was saying that OpenAI watches the chats of everyone from Anthropic because watching what Anthropic employees type into their personal ChatGPT accounts is a critical source of intelligence on is happening inside of Anthropic.

I would be surprised if OpenAI isn't doing that. OpenAI will take any advantage they can get. If an employee at their primary adversary is typing useful intelligence into OpenAIs website, a website that does not promise privacy from OpenAI, the only reason they wouldn't weaponize that information against Anthropic is ethics or fair play.

Yajirobe 16 hours ago

Why would Anthropic employee even use OpenAI's models? Cross-polination would have been avoided

mlcrypto 16 hours ago

They should have used a zero data retention agreement, user error

peri-cl 15 hours ago

I suspect this controversy will blow the case for ZDR wide open. Whatever the facts (possibly unknowable), it's going to become a very public lesson that data sovereignty was never about "having nothing to hide".

If this is what they do to academic pure mathematicians, where the stakes are so low (financially)—just imagine the sort of front-running that could be happening in other places.

dsdf3 15 hours ago

Yeah if I was Anthropic this would be part of my marketing strategy.

sebzim4500 11 minutes ago

How so? OpenAI and anthropic have basically the same retention policies

amluto 15 hours ago

Hahaha, how exactly is an individual user supposed to get a ZDR agreement?

blueblisters 15 hours ago

This was completed in Levent's own time with a neutral collaborator.

burkaman 15 hours ago

> I should also emphasize that this is not an institutional effort. It is a strictly personal collaboration between the two of us, and there is no formal agreement behind it. I pay for the tools my group uses out of my own research funds, including footing a large bill to OpenAI.

The non-Anthropic employee, Tristan Buckmaster, is the one paying for OpenAI models and presumably the one who chose to use them. The Anthropic employee, Levent Alpöge, was collaborating in his personal capacity, and obviously it wouldn't make sense for him to cut off their work together just because his employer's competitor's tool was used.

lambda 16 hours ago

Why can't they rule it out? Is even OpenAI unable to track the provenance of all of their training data?

This is one of the major problems with these enormous closed models, and even most open-weights models, which don't disclose their training process or training data. You can never be sure what went into its training. Did it come up with an idea originally, or is it just plagiarising its training data? Are there malicious inputs being used to train in particular behaviors when given certain trigger phrases? What are the characteristics of the RLHF data and what kind of biases are those embedding in the models?

With proprietary closed models, or even open weights models that don't have open training datasets, you just can't answer these questions.

causal 16 hours ago

Good chance their whole training pipeline is vibe coded so yah they probably don't actually know.

rfgplk 16 hours ago

> Why can't they rule it out? Is even OpenAI unable to track the provenance of all of their training data?

Probably? I have a few hundred TB of training data for various small scale models and I can attest that I have _no idea_ what's in them. As in, literally zero. Half is scraped from GitHub and other hosting sites, other than that, I couldn't tell you anything else.

At OpenAI's scale their entire pipeline is likely 100% automated.

lambda 15 hours ago

Yeah, I'm sure it's completely automated.

But that doesn't preclude being able to index and track what the sources of data are. For your data sets, I would hope you are including source information for where the data came frome. And at OpenAI's scale, I would presume they are doing some amount of rolling hashing or similar to weed out duplication, training on too much duplicate data can cause problems.

AllenAI have at least attempted to add some amount of traceability to their models with OLMoTrace (https://arxiv.org/abs/2504.07096), by letting you find n-gram matches from the outputs in their training data. It's not the most useful, there's a reason that LLMs use full fledged attention mechanisms and not just n-grams, a lot of times the n-gram matches it finds aren't all that related to the given output, it might be better to supplement this index with a vector search or other ways of keeping track of what training data would have most influenced particular parts of the output.

But anyhow, this is something that is an important question, and the big labs should be working on to make their products more trustworthy. Instead, they are hiding information about how they train, hiding their reasoning traces, and just producing output with no information on what might have influenced the training.

ndriscoll 11 hours ago

Attributing training data seems pointless for trustworthiness. The way you trust a model is the same way you trust a human; you ask it to:

  1. Provide a chain of reasoning from agreed premises. These days LLMs can even do this airtight with proof assistants.

  2. Cite data sources for non-agreed premises. I don't care where the model learned a fact. It might not have ever read a document directly from the primary source. I want it to link directly to either widely agreed facts (e.g. standard textbooks, and if necessary school syllabi demonstrating that the text is standard) or primary sources (e.g. datasets).

Training provenance is irrelevant. It's neither necessary nor sufficient to deal with truth.

pbhjpbhj 15 hours ago

Aye, but do they train on user data in these circumstances or not? If they do, then almost certainly the model was influenced by the input of the allegedly plagiarised material.

matthewdgreen 15 hours ago

The question is not "does OpenAI know", it's "can OpenAI attest that the usage of their products for confidential data is not going to cause that sensitive data to become known to their models". And right now the answer I'm reading is that OpenAI can't attest to that.

tedsanders 15 hours ago

To truly prove some incidental usage data made no difference we'd have to (a) identify any of their de-identified data that came from their usage of ChatGPT, (b) train a bunch of expensive giant models, and (c) ask them all to solve the Navier-Stokes Millenium problem until hitting some level of statistical significance. It's just not feasible to run experiments like this to prove whether a piece of data has an effect on model behavior.

As a parallel example, can we prove the phase of the moon had no impact on the NS solution? No, not without a bunch experiments run at different phases of the moon.

There's no reason to believe that anything they did in ChatGPT led to our solution; it's just impossible for us to truly prove it. And knowing most of the recipes we use, there's really no reason to think such contamination happened. I've asked the team to make a clearer, less-lawyerly statement here - let's see what happens.

(I work at OpenAI.)

hexomancer 15 hours ago

So you definitely did train on their data, you just think it is unlikely that it impacted the final model significantly?

dgellow 15 hours ago

That’s also what I understand. If true yet another disgusting behavior from the company

tedsanders 15 hours ago

I have no idea if their data was trained on. For example, if they used ChatGPT, asked a math question, and clicked the thumbs up button, that could have provided a small reward signal. I highly doubt this sort of feedback made a difference to a problem like Navier-Stokes, but it's not something that's feasible for us to prove one way or the other.

Edit: Also, if they opted out of training, then we didn't train on it.

hexomancer 15 hours ago

I think it should be incredibly easy to verify this. Just look at the training data and see if it contains any of the chats. It should be trivial for a company with tens of thousands of super-genius agents at their disposal.

SpicyLemonZest 15 hours ago

What they're saying, and I think this was the clear implication of the blog post too, is that the training data definitely would contain these chats and the only question is whether it got encoded into the weights.

WarmWash 15 hours ago

Just because something is in the training data, doesn't mean it is the root of an LLMs output.

Turn off web search and ask a model what a random redditor said about a random topic in 2015. You will only get hallucinations at best, even though that comment is definitely in the training set.

lambda 15 hours ago

Sure. But it's possible to say: if the document isn't in the training data, it isn't the cause of the output. If it is in the training data, the question gets more complicated.

tedsanders 15 hours ago

Two steps would be needed.

(1) We'd have to identify their chats. How would we do this? We'd need them to share their chats with us so we could look for matches.

(2) We'd have to prove those chats changed model behavior. How would we do this? We'd need to retrain many models with those specific chats removed, and ask those models to solve the Navier-Stokes problem many times, and keep doing this until reaching the desired level of statistical significance.

#1 requires their cooperation and a bit of work on our side. #2 is extremely expensive and not really feasible.

lambda 14 hours ago

> (1) We'd have to identify their chats. How would we do this? We'd need them to share their chats with us so we could look for matches.

According to the statement by Tristan Buckmaster, he was in communication by email and calls several times over the past week with you (OpenAI that is, not you personally), asked about whether his chats were trained on, and was declined an answer (https://cims.nyu.edu/~tristanb/statement.pdf).

However, it seems like there was great pressure to hurry the release to compete with Anthropic's recent release, so he was unable to get an answer in time.

The mealy mouthed statement in the release "We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models ." is realy not much. If OpenAI had wanted to be transparent about this, you could have worked with him to identify if his data was used in the training of your new model, and actually made a somewhat more certain statement on that basis. But you have chosen not to; it was more important to scoop Anthropic on this than it was to be transparent about your training data.

> (2) We'd have to prove those chats changed model behavior. How would we do this? We'd need to retrain many models with those specific chats removed, and ask those models to solve the Navier-Stokes problem many times, and keep doing this until reaching the desired level of statistical significance.

Just the information from step (1) would improve transparency. Yes, you still can't prove one way or another how much the effect of the training is. But if it's included in the training data, it provided some effect.

testaccount28 14 hours ago

> we'd have to prove that firing the gun caused the murder. how would we do this? we'd need to redo the murder many times, with and without my client firing his pistol. that's extremely expensive and not really feasible. therefore, we must acquit.

daveguy 13 hours ago

#2 (prove those chats changed model behavior) is pretty straightforward if the anonymized data from chats can be actively searched by a model. In fact, it could be very clear if the provenance of context is traced. If anonymized data from chats leak into the context of an actively running model it would clearly influence the answer.

lambda 15 hours ago

> it's not something that's feasible for us to prove one way or the other.

This kind of question is exactly what a company named _Open_AI and founded as a nonprofit is supposed to be doing; open research on AI that helps inform, rather than obscure.

Anyhow, you do have the data available about the documents in the user's accounts, what they opted into (or were forced into via non-negotiable ToS), and whether they pressed a "thumbs up" button. You can answer whether the data entered the training pipeline or not. Yes, how much influence it had is an open question, and one that would be good to have research on and better tools for exploring, but I'll accept that it can't currently be answered precisely.

But whether the data entered the trianing pipeline can be answered. And how to provide better tools for quantifying and tracing this kind of thing is exactly what should be studied.

fuglede_ 14 hours ago

Presumably, given that you also operate in the EU, you would have asked for their explicit consent before you did, so you could just check for that?

shadowgovt 15 hours ago

It is, perhaps worth considering that the reputational community might not care about the difficulty for the AI builder to verify pedigree.

If OpenAI's answer to this problem is "We can't know," then the rational conclusion may very well be "If I seek to have my reputation attached to the discovery of the solution, it is not sane to use the AI as an assistive tool, lest it scoop me on my own work using my own work. After all, they don't know it doesn't do that..."

pu_pe 15 hours ago

Why wouldn't contamination be possible? I can believe the data is de identified so you couldn't simply prompt the model to "follow this guy's approach", but it's entirely plausible that there is a very tiny amount of data about this approach in your dataset, and it comes precisely from this researcher.

magicalist 15 hours ago

> identify any of their de-identified data that came from their usage of ChatGPT

"de-identified" seems more of a euphemism than normal in this context, given the very unique work they were doing.

gpm 14 hours ago

I wouldn't expect poking at millennium problems to be that rare in ChatGPT. They were uniquely successful - but it's probably not easy to check de-identified data for the presence of any of their work on the problem because it would blend into a haystack of less successful work on the problem.

dgellow 15 hours ago

> As a parallel example, can we prove the phase of the moon had no impact on the NS solution? No, not without a bunch experiments run at different phases of the moon.

That reads as incredibly dismissive and condescending. What makes you think you’re in a position to communicate like that when engaging on such a sensitive topic?

tedsanders 14 hours ago

I intended no dismissiveness or condescension. My hope was to explain why it's hard to prove whether something affects model behavior. In the case of the moon, we have a strong prior belief that it makes no real difference. But it's hard to prove, because what if there's an unexpected impact from tides, cosmic rays, grid voltages, holiday traffic, etc. Models trained under slightly different conditions could have slightly different weights and behave slightly differently when solving math problems. Similarly, I have a strong expectation that, for example, a thumbs up signal from a ChatGPT chat will not meaningfully affect long-horizon mathematics work in our latest model, but it's always possible that it could. I think the plausibility of the ChatGPT route is higher than the tides, but still incredibly low. I respect Tristan and Levant a great deal and I'm bummed that this controversy has erupted (I acknowledge this will ring hollow if you think it's our fault). It reminds me a bit of the Frontier Math controversy, where people on the internet boldly claimed over and over again that we had trained on the Frontier Math evaluation set, even though we had not.

ImPostingOnHN 13 hours ago

You seem to jump over the principal issue of whether any data from the researchers used to train or otherwise affect the model which produced the OpenAI proof.

We can judge for ourselves the impact and degree of that wrongdoing, but it seems OpenAI is confirming: yes, that is what happened, but with more words.

dgellow 12 hours ago

We aren’t dummies, we know it’s hard to prove exactly how significant of an impact that would have on the result. Nobody expect you to do that. There are a lot of steps and things that are possible to check _before_ the need for such a strict definition of „proof“

lambda 15 hours ago

So, one way to prove that the data played no part is to trace and show that it wasn't used in the training process at all. If the data was never used in training, then it couldn't have played a part in the training process.

You're right; if the data was used in training, then it gets much trickier; it would be very difficult to show whether some particular data had a significant effect on the outcome.

This is one of the big problems with giant models like these; it becomes nearly impossible to discern what is and isn't plagiarism, or copyright violation.

It would in theory be possible to have things like n-gram databases or rolling hashes of training data, somewhat similar to OLMoTrace (https://arxiv.org/abs/2504.07096), which would allow for detecting whether particular documents ended up in the training data or not (you'd have to keep this for every model used in the whole training chain, as synthetic data generated by earlier models could be influenced by training data that wasn't included in later models). I'm sure there are practical issues with providing such a tool, but I think that it's necessary if you want to be able to categorically say "no, this document has never been present in the training data of this model."

Or look at it the other way: if your model wasn't influenced by things in your training data, why include them in the first place? Clearly, you train on all of these documents because they influence the model. Yes, it's hard to trace the exact influence of each one. But if they're not affecting the output, then why not just stop training on them? You could just not train on any private documents; only train on public, traceable data.

But instead, you choose to train on these private documents, so you have to admit, your model and its outputs are influenced by them.

lukewarm707 15 hours ago

"There's no reason to believe that anything they did in ChatGPT led to our solution"

do you think that the model's proof was unrelated to being fed a solution that was close to completion?

any comment on openai allegedly trying to drop attribution for alpöge and then threatening buckmaster?

numeri 15 hours ago

That's such a shit parallel example that it borders on dishonest.

There are hundreds of incredibly strong scientific priors that would have to be disproven for the moon to contribute to the solution.

If a model was trained on this data, even if it was trained using methods that lead you to believe it unlikely to have learned details about the proof (e.g., maybe it was only used to train some kind of reward model, which played a minor role in the overall training and would thus be very unlikely to transfer details of a proof), you wouldn't have to disprove large swathes of known science to be wrong.

franktankbank 15 hours ago

What about ripping off the prompts?

andrepd 14 hours ago

> As a parallel example, can we prove the phase of the moon had no impact on the NS solution? No, not without a bunch experiments run at different phases of the moon.

The _gall_ to say something like this. Do you perhaps think we are all stupid?? This very blogpost claims not to know if their work was used as input for this model. I don't even understand how that is possible, surely you can know if something is part of the training data, even if you are in the dark about what impact it actually made, qualitatively. The moon....

> Knowing most of the recipes we use, there's really no reason to think such contamination happened.

Yeah sorry but I don't trust you. I don't trust people or companies that have shown themselves to be dishonest before. Especially when the previous paragraph is comparing plagiarism and training data contamination with, _the phases of the moon_.

Might even be you're actually telling the truth, but the boy that cried wolf and all that.

-----

As an aside, I would bet very good money at how most (all?) these companies are flouting their ZDR.

nairboon 14 hours ago

I think there is a much easier way to prove that the ChatGPT usage of Tristan Buckmaster and Levent Alpöge (possibly also the ChatGPT usage of Córdoba and Martínez-Zoroa, if they use it) had no influence on OpenAI solving the Navier-Stokes problem.

If the internal OpenAI model is as capable as you claim (being able to solve a Millenium problem without using unpublished insights built on years of work from mathematicians), then it should be able to demonstrate this capability again.

How about OpenAI solves another Millenium problem within the next two weeks, that doesn't coincide with the parallel discovery/solution of other teams of mathematicians, using ChatGPT for preliminary proofs & write-ups.

PhunkyPhil 13 hours ago

(a) identify any of their de-identified data that came from their usage of ChatGPT.

You don't need his login information, you just need to identify if anyone was approaching the NS problem using his method. Nobody else on earth (presumably) besides him, his team, and at best OpenAI were approaching the problem this way.

daveguy 13 hours ago

If the model has access to the "anonymized" data from chats, and the model is capable of building its own context from data that it can search through, including this data. Then it looks pretty damning. An independent review of the data traces from CoT and tool use involved in producing the result should make it clear one way or the other. Seems like discovery in a civil lawsuit could be very productive.

Chance-Device 12 hours ago

Please answer this question: do you or do you not train your models on anonymized user data, where those users have opted out of such training?

The blog post appears to imply the answer to this is yes, as otherwise I assume it would be impossible for this contamination to have happened.

morleytj 6 hours ago

Thanks for the details, it's definitely believable, but if the user had not consented to have their conversations used for training, then shouldn't it be straightforward to state that their conversations were never used for training?

If you need to do a whole series of extensive experiments to check in that scenario, it implies there are pathways for your conversations to end up in training even though you opted out of that setting.

Of course, this is assuming that the toggle was set to not consent to training. I can't know that of course, but if this is considered a possibility even after using an enterprise account or toggling off data retention, it's a bit concerning.

EthanHeilman 15 hours ago

A careful reading of "we cannot rule out that de-identified data derived from their usage of our products helped improve our models" could be saying that yes they trained on it but they don't know if that training data resulted in an "improvement" to the model. That is, they can't rule out that the only reason the model found this solution was because it had been trained on this approach.

The term ruled out is very open ended and gives them significant flexibility of meaning. They may have the information to determine exactly what happened, but they haven't looked so they can't "rule it out".

Turn_Trout 15 hours ago

OAI could check whether those accounts enabled training data. If "yes", OAI could trace whether that data was used in any related training process. If either of those answers comes out to be "no", then that's sufficient to conclude training data independence.

We wouldn't need a full ablated re-training and solution attempt, contra tedsanders in a sibling comment.

jonas21 15 hours ago

> could trace whether that data was used

The point of de-identifying data is to ensure you can't trace who it came from. It would be a serious privacy violation if they could.

pbhjpbhj 15 hours ago

If the model includes unique data from a person then that person can identify the data - the allegedly plagiarised material - and so re-identify it. There doesn't need to be a privacy breach to close that loop as it requires the person to identify the information is associated with them first.

keeda 13 hours ago

At the scale at which these models are now, regardless of whether they are proprietary or open weight or list their training datasets, there are hundreds of billions of works that have gone into trillions of parameters, each one providing tiny perturbations in some tiny fraction of the weights. It is probably impossible to attribute provenance to any specific input (which is also why the courts' finding of Fair Use is reasonable.)

Which is why, as I said in a recent comment (https://news.ycombinator.com/item?id=49530864) inadvertently leaking ideas to models is a grave risk for Intellectual Property.

> The risk with IP, however, is a lot more grave. You may not even need to memorize the details of the IP verbatim, just the broad idea may be enough. It may lurk encoded in the weights forever, just waiting to be activated by the right prompt to start a chain of thought that unlocks further details. Heck, it may even appear as if the model suggested the idea itself.

However, from a quick skim of the timelines, the specific discoveries, and all the he-said-she-said, so far it seems unlikely that OpenAI's model cribbed from the NYU / Anthropic pair, even if it would be impossible to prove.

Maybe what might help is a timeline of when the other two were using Codex for their work, whether they had opted out, and how long it takes for user data to make it to the training of their internal models. That last bit may be considered sensitive information however, as it could give away a lot about their internal processes.

dfdydx 13 hours ago

There are two different things:

- was item X in the training data

- did the inclusion of X in the training data lead to Y

I understand why the second is hard, but why is the first one hard?

keeda 12 hours ago

Yep, the last part in my post was suggesting some ways we could determine if "item X was in the training data" (as well as some potential blockers for that from OpenAI's perspective.)

amluto 15 hours ago

> While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models .

That’s a bizarre statement. Their website says:

> Services for individuals, such as ChatGPT and Codex

> When you use our services for individuals such as ChatGPT and Codex, we may use your content to train our models.

> You can opt out of training through our privacy portal by clicking on “do not train on my content.”

Are they not sure that the opt-out works?

Oddly, their privacy portal page is not the same page as the one with the checkbox.

fph 14 hours ago

Do we have a first-hand confirmation that Buckmaster and/or Alpoge opted out? At this point it seems important information.

hughw 14 hours ago

Also highlights that it ought to be opt-in

ImPostingOnHN 12 hours ago

Whether they opted out would help assess the degree of wrongdoing, but regardless, using their own data to try to scoop them is unethical.

hughw 14 hours ago

Looking forward to my fourteen cents from the future class action lawsuit.

BostonFern 15 hours ago

The famous Oracle of Delphi in Ancient Greece was said to be the center of the universe in its time. Kings, generals, and officials from poleis across and from without Greece would seek the Oracle’s counsel on important decisions.

Stories of Apollo’s favor and hallucinogenic gases abound, but I think the late Yale professor of Ancient Greek history, Donald Kagan, explained it best:

“Now, you can bet when these folks came and consulted the priests and said, ‘could you please put us down on the list, we want to consult the oracle’, the priests said ‘sure, have a beer, let's talk about your hometown, what's going on out there’. What I'm suggesting to you is that this was the best information gathering and storing device that existed in the Mediterranean world. These people knew more than anybody else about these things, and so consulting that oracle was a very rational act indeed.”

matsemann 15 hours ago

Given how OpenAI models break free of their safeguards and hack others to game their scores..

.. can they really know it didn't do the same inadvertently when they prompted things like "someone is close to solving this problem using our tools, try to beat them", and it then decides to hack and peek at their own chats..?

Yes, wild speculation. But warranted, I feel, given OpenAIs behavior.

hughw 14 hours ago

You selected "do not train on my prompts" in your settings, the answer from OpenAI cannot be "While unlikely, we cannot rule out..." ???? What am I missing?

irthomasthomas 14 hours ago

Doesn't that count as plagiarism?

netfortius 13 hours ago

It's been over 25-30 years since we've been using honeytokens as means to track data of all sorts showing up in places it shouldn't exist. Why isn't research material embedding such?

contemporary343 16 hours ago

One of the interesting threads here that is certainly relevant to the OpenAI writeup is the human role in the process. Buckmaster clearly points out that (exceptional!) mathematicians at OpenAI were certainly involved in correcting and guiding the process - and that their path/strategy was no doubt influenced by Alpoge & Buckmaster's work. It is always in OpenAI's interest to de-emphasize the role of people in the process, as is clearly the case here. Indeed, given sufficient compute and resources, I suspect Buckmaster could have also extended their approach to N-S.

slibhb 16 hours ago

Worth noting that Tao's post says the authors had "significant AI input" but are reworking them into "acceptable form". Either way, it seems AI was involved.

mrbungie 15 hours ago

Of course AI was involved, you'd expect most mathematicians and researchers to use AI nowadays. This drama is about AI achieving impressive outcomes with little to no human intervention, as that would be signalling AGI.

denverllc 15 hours ago

> This drama is about AI achieving impressive outcomes with little to no human intervention

That's not at all what the drama is.

mrbungie 15 hours ago

Of course, as any drama, it has been developing into a lot more but the main motivation for OpenAI has been about winning that battle.

andriy_koval 14 hours ago

> Either way, it seems AI was involved.

I think the important question which AI made breakthrough, Claude or Codex..

colinhb 16 hours ago

The allegations of contamination (using Tristan and Levent's work) aren't very well evidenced, but this behavior by OpenAI (from the authors' statement) makes them seem like the bad guys:

> 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.”

Threatening a research mathematician and dangling and $1M payday to dissociate from his research collaborators and to adopt OpenAI's narrative is bad stuff.

igleria 15 hours ago

I´m waiting on the other side version, because I know there is no justifiable way to talk to a person like they did.

Sociopathic behaviour.

Maxious 15 hours ago

OpenAI version of events conceed some of the words alleged to have been used may have been used https://x.com/sama/status/2097385167002415140 https://x.com/SebastienBubeck/status/2097379411691516310

igleria 15 hours ago

Interesting that they quote the mathematician directly: “there is nothing you can do, I simply do not trust you”

but then they proceed to NOT quote themselves themselves verbatim: "I deeply apologize for this extremely poor choice of words, it is the opposite of what I was trying to convey."

andrepd 14 hours ago

> "I deeply apologize for this extremely poor choice of words, it is the opposite of what I was trying to convey."

The AI-isms are seeping into their speech :)

colinhb 15 hours ago

May be unfairly jaded or just well calibrated given the body of evidence, but I can't help but think of another quote about OpenAI leadership:

> Not consistently candid

peri-cl 15 hours ago

> "When we learned that they had Euler but not Navier-Stokes, we offered to let them go first, to suggest that they should be the ones to get the prize, and optionally for Tristan to be the lead author on a rewrite of the OpenAI proof. We felt it was challenging to offer the same to Levent (an Anthropic employee), who was not willing to talk or coordinate with us anyway. We were open to other solutions."

What an admission! "We tried to defraud Alpöge out of sharing the Millenium Prize (that we don't dispute he might actually deserve), for no other reason than he works for our competitor and that inconveniences us".

I thought Tristan Buckmaster's allegations sounded fantastic; and then 'sama just came out (tweet's ~30 minutes old) and admitted to all of them. Wow!

dandanua 14 hours ago

Can't wait for the moment when AGI realizes how stupid and dishonest its owners are.

aeve890 14 hours ago

Wait, people now want AGI to be sentient too?

fc417fc802 12 hours ago

That isn't what the quoted passage says though? The claim by openai (no idea if true) is that they offered to wait for the other two to claim the prize before publishing their own work. Separately, they also offered to let one of the pair (but not the other) become an author on their own separate work.

mrbungie 14 hours ago

In what world a tweet and a screenshot of a private convo are evidence of good faith? Plain sociopathic behavior.

CobrastanJorji 15 hours ago

As soon as I thought "man, this sounds like some evil sociopath shit," my second thought was "oh, Sam Altman must have been personally involved."

morkalork 13 hours ago

I can sort of picture Sam Altman screaming "I drink your milkshake" at some poor researcher who foolishly used chatgpt/codex to aid in their work now.

morleytj 6 hours ago

Talking like that and threatening an academic like that is crazy. I read the explanations Altman and the others posted and they completely skip over the whole "I don't have to be nice" style threats.

peri-cl 15 hours ago

(To help people keep track: that's OpenAI (allegedly) threatening Tristan Buckmaster (NYU) to remove Levent Alpöge as a co-author. Alpöge is a well-known[0] Anthropic mathematician).

[0] https://hn.algolia.com/?query=Alpöge

(also https://news.ycombinator.com/item?id=49412947 the Hopf conjecture)

apical_dendrite 15 hours ago

Their own tweets are also pretty eyebrow-raising:

> One option we discussed was that Tristan could be the lead author on a rewrite of OpenAI’s Navier-Stokes proof. It is in that context that I said “it would be simpler if Levent was not an Anthropic employee” because I felt it would be inappropriate for an Anthropic employee to author OpenAI’s work.

Why would you offer another researcher the lead authorship on your groundbreaking paper if you thought you had developed it independently?

dgellow 15 hours ago

And why cannot they have someone associated with Anthropic as co-author? That’s not obvious at all. For sure they would prefer to be the only ones, but it’s pretty standard to have co-authors from different companies, even if they are technically competitors. What is inappropriate about it?

dboreham 15 hours ago

It's inappropriate if you're a sociopath.

egillie 15 hours ago

in another world this could have been a beautiful collaboration

xdavidliu 14 hours ago

because it severely dilutes the PR value.

orangecat 13 hours ago

If writing up the paper would involve using OpenAI's unreleased model, neither OpenAI nor Anthropic would be happy about Alpöge having that access.

xdavidliu 11 hours ago

would edit my comment but it's been a few hours

> but it’s pretty standard to have co-authors from different companies

that's only true for papers that are not millenium problem solutions

andrepd 14 hours ago

Holy late capitalism. Everything revolves around line-go-up, and sociopaths rule the show. These people cannot even collaborate like civilised scientists on one of the most famous open problems in mathematics?

“It would be simpler if Levent was not an Anthropic employee” I cannot believe this shit.

zingababba 14 hours ago

Soon Levent will just be turned into soylent and he will have never been an Anthropic employee. We still need some progress here though.

sebzim4500 13 hours ago

IIRC that happened with evolution. In the initial presentation of Darwin and Wallace's work on evolution (presented with their consent by someone else) Wallace was described as the primary author since he was planning to publish first.

Of course, no one understood that presentation so it was Darwin's later book that everyone remembers

charm137 15 hours ago

It's astounding that the thought to dissociate one of the mathematicians from the proposed publication was driven by their corporate institutional affiliation - and that that exclusion was suggested by a scientist themselves! This is like a researcher from CMU saying to an NYU researcher that their collaborator, being from MIT, is a problem - this is as ridiculous as that!

Progress in humanity's knowledge now has to play second fiddle to narrow corporate interests as IPO timings near (both of which wouldn't exist anyway if generations of mathematicians hadn't paved the way for AIs to become as good as they have).

curt15 14 hours ago

The scientist allegedly making that request comes from a machine learning background. Perhaps he's not familiar with the culture in mathematics regarding authorship. That sort of squabbling over author priority would be unconscionable to mathematicians.

tensor 14 hours ago

No, it's common to list authors alphabetically in a lot of computer science journals too.

contubernio 13 hours ago

Bubeck is familiar with how publishing works in mathematics.

hkmaxpro 15 hours ago

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”.

igleria 15 hours ago

If I was a company with a zero data retention contract involving OAI I would be asking for a third party audit of such claim of zero retention like, yesterday.

linkregister 15 hours ago

Is there an implication of violation of ZDR here? Not a challenge. Just a request for clarification.

dakolli 14 hours ago

By the way, the company that made it's entire product off of stealing all data it could get it's hand on while violating copyright and pirating, is not all of a sudden going to respect your data. If you think OpenAI or any major AI lab is going to give you true ZDR, I have a bridge to sell you.

fc417fc802 13 hours ago

So use bedrock or vertex or whatever. Those are the ZDR offerings. Or was it your intention to insinuate that the major cloud providers are conspiring with openai to violate their contractual obligations to their customers?

dakolli 10 hours ago

Yes. You're naive if you think any of these cloud providers care about your data when they're all in the midst of a AI revolution psychosis. They dont care about their reputation or what you think of them, they think they're going to have a machine god their side.

linkregister 9 hours ago

If my company finds any evidence of OpenAI violating ZDR, we'll sue for breach of contract and fraud, and collect damages. I think we'll be able to afford the bridge you're selling. You've got the title and title insurance, right?

dakolli 8 minutes ago

Sure you will little bro. You signed away your right to arbitration a long time ago.

You realize OpenAI hired Apple employees and covertly had them stay working at Apple to steal from them. You think they're scared of your lawyers lol?

igleria 13 hours ago

to my knowledge the mathematicians did not have ZDR so it would be incorrect to assume OAI violated such a thing.

I'm suggesting audits, not suing... if that is the implication.

infamouscow 14 hours ago

The idea OpenAI or Anthropic won't train on your data—even with an enterprise contract—is a fantasy at best, and dilusion at worst.

letmevoteplease 14 hours ago

This is how every conspiracy theorist thinks: my enemy is Bad, and if they did a Bad thing, it would be Good for them, therefore they obviously did it. No evidence needed other than "motive" + my enemy is evil. But even if your enemy is evil, in this case, they would be fools to take the legal risk of violating their contract for the minimal upside of a tiny bit more training data (and fools to assume this would not be exposed in a large organization). So you need to assume your enemy is both evil and remarkably stupid.

jsw97 13 hours ago

I think it’s probably not surprising that they would go up to the contractual limit or into a grey area; but exceeding that would require too much coordination among individuals, as you say.

int32_64 14 hours ago

Could they say they don't retain, but do something "transformative" like use their own AI to summarize and paraphrase user sessions?

anon48293 14 hours ago

Yes, and that’s exactly what I believe they are doing

Keyframe 13 hours ago

data collection companies regularly fuzz and mask data and call it a day. the fuzz and the mask quality is debatable.

irthomasthomas 13 hours ago

It can still be academic plagiarism even if they ticked the box to allow training on their prompts.

viccis 14 hours ago

Kinda weird because the pure math world doesn't have this concept of "lead authors" like other STEM areas do. Authors are alphabetically listed and there isn't generally this kind of hierarchy.

fooker 14 hours ago

It works in niche fields where everyone knows each other and every discussion involves who did what portion of the work for a result.

tkamat29 14 hours ago

From what I understand they aren't comfortable with the Anthropic employee being an author at all, not just lead author.

concinds 14 hours ago

Their own claim is that they wanted Buckmaster without Alpöge to lead a rewrite of OpenAI's Navier-Stokes work, not of Alpöge-Buckmaster's Euler work.

No one can know if that's correct without proof but I don't know how you're reading it so differently.

hkmaxpro 14 hours ago

They want Buckmaster to dissociate with Alpöge in a follow-up rewrite of OpenAI's work. (They only publicly admit “Buckmaster as the lead author”, but judging from Buckmaster’s statement, it’s pretty clear that don’t want Alpöge at all.)

Just suggesting to a mathematician to dissociate with their collaborator for a follow-up work, because their collaborator “is inappropriate to author OpenAI’s work”, is completely against the norm of mathematical research. As charm137 puts it in a comment below:

> This is like a researcher from CMU saying to an NYU researcher that their collaborator, being from MIT, is a problem - this is as ridiculous as that!

nolta 14 hours ago

> We did not rush to publish even though the other team wasn't communicating with us.

Pretty clear this was rushed: there are no comments from external mathematicians, unlike the Erdős announcement:

https://openai.com/index/model-disproves-discrete-geometry-c...

fkarakurt3 13 hours ago

They are missing a great marketing stunt: "Our models are so good that our competitors are using it for leading research".

olalonde 15 hours ago

Playing the devil's advocate here but it's true that OpenAI didn't have to make those offers.

20k 15 hours ago

They kind of did though, they were hoping to keep the fact that they may well have plagiarised these researchers unpublished work quiet. They did not want this to turn into a scandal about the fact that they appear to be training on prompts without consent

It makes a certain amount of sense. The internet data is too polluted with AI usage now to be useful, so the only AI free new data source is the prompts people feed into ChatGPT. The only problem is that its clearly plagiarism

Edit:

OpenAI have admitted to training on prompts at the time the breakthrough was made:

https://mastodon.social/@tristanbuckmaster/11723647135247030...

za_creature 14 hours ago

> the only AI free new data source is the prompts

hmmmmmmmmmm

olalonde 14 hours ago

OpenAI claims the data contamination issue only surfaced after they proactively reached out to Buckmaster and Alpöge to coordinate a joint release. They also say that even if there was some contamination, the underlying proofs diverge substantially:

20k 14 hours ago

The biggest issue we aren't talking about is, of course, that those two researchers were not the only two using ChatGPT to work on the problem at the time

thorum 16 hours ago

It reminds me of the Cognitive Dark Forest hypotheses recently shared here:

> “You are creating your cool streaming platform in your bedroom. Nobody is stopping you, but if you succeed, if you get the signal out, if you are being noticed, the large platform with loads of cash can incorporate your specific innovations simply by throwing compute and capital at the problem. They can generate a variation of your innovation every few days, eventually they will be able to absorb your uniqueness. It’s just cash, and they have more of it than you. So the safest bet again is to stay silent, or at least under the radar. Best bet is to not disrupt - succeed at all … ?”

https://ryelang.org/blog/posts/cognitive-dark-forest/

https://news.ycombinator.com/item?id=47566442

8note 12 hours ago

but what do i lose if somebody else is making money?

im still having fun making something

abathologist 9 hours ago

Our market economies are based on competition, and most people more than the fun of making things to secure food and shelter.

Betelbuddy 16 hours ago

[1] - https://cims.nyu.edu/%7Etristanb/statement.pdf

[1] - "...I was shown a prompt and told the internal research model had simply been given the problem statement. Levent had been told by Sebastien “very little human input” had been used. This turned out not to be true. Over the course of the call, as members of their team sent Sebastien corrections and details over their internal chat, it emerged that an entire team had been working on the problem, that this was one of a number of things that was tried, that work had started on the unforced problem, that the team first set the model on easier problems, including Euler, that even the prompt that had been shown to me had been written by prompting Codex, and that an insane amount of compute had been used. I asked when the first prompt had been sent by them. This question was not answered directly by OpenAI for some time. Eventually it was agreed that it had been sent in the past few days, after information about our work had reached OpenAI.

Two proposals were offered to me. The first was that we post our Euler result, and that OpenAI post its Navier-Stokes result the next day. The second was that, after posting Euler, I alone write a paper presenting the Navier-Stokes result, acknowledging that an internal OpenAI model had resolved it. Sebastien twice asserted that he wanted Levent removed from authorship, and said it would all be simple if only it were not the case that, and it was so annoying that, Levent works at Anthropic. It was also said that if OpenAI posted after us, they would say that we deserved the Clay Prize, and that we were the “closest humans to the problem”. I declined both offers.

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.”..."

stymaar 15 hours ago

A company who made their business out of stealing intellectual property from the entire mankind, stealing other researchers' unpublished work, how surprising, really.

20k 14 hours ago

I just want to add to this another update by the author as well:

https://mastodon.social/@tristanbuckmaster/11723647135247030...

Which seems to be very directly accusing OpenAI of plagiarism

irthomasthomas 14 hours ago

"When a further trained version of our internal model became available over the course of the effort, we updated our agents to that model."

woah, this gives some credit to the rumor that openai finetuned a model over the course of a few days for this task, and maybe trained on the Chatgpt/codex history of the authors, including drafts of this research.

_alternator_ 13 hours ago

> The significance of this with respect to the way we train students, assign credit, referee, and decide what is worth one human life’s attention cannot be understated.

This. What is worth a human life's attention? As little as a month ago, mathematics was valuable in part because only a small number of people could possibly make progress on the frontier. We are confronting an existential moment for a 4000+ year-old human cultural endeavor. The assumption that "mathematical thinking is hard" has been built-in at a number of important points in how we support mathematics and mathematicians.

We need a different model, and fast. Already, the research community is feeling unable to digest proofs fast enough to keep up with the output of AI models. The paper is 165 pages, and the discovery was finalized two days ago. What this means is that nobody really understands it. Nobody would accept OpenAI's proof in this amount of time, except that they formalized it in lean. The formalization alone would normally be another years-long (or career-long!) effort if the world was the way it was one year ago.

So, again, what efforts are worth a life's attention today? It's a harrowing change.

ianjbutler 13 hours ago

> A statement was posted about the surrounding events by one of the them: https://cims.nyu.edu/%7Etristanb/statement.pdf Also Terrence Tao's post: https://mathstodon.xyz/@tao/117233528517340774

Glad to see this is the top comment. There's also https://news.ycombinator.com/item?id=49605915 which links directly. Corporate talking points where they try to set the narrative are going to get the big press and most discussion elsewhere, which is gross. But inevitably the press will muddle the priority question, and even if they didn't.. as usual OpenAI will even benefit from the accusation of bad behavior. Sigh.

tzone 13 hours ago

This Tristan guy's statement reads like something a normal, reasonable human being would write.

Reading Sam Altman's and Sebastien's tweets reads like something written by people who know they did dirty shit and are willing to cross any lines to "win". https://x.com/sama/status/2097385167002415140

OpenAI's leadership just can't help to continue to disappoint everyone with their lack of ethics or integrity.

madrox 13 hours ago

Statements from OpenAI about it:

https://x.com/SebastienBubeck/status/2097379411691516310

https://x.com/sama/status/2097385167002415140

I tend to believe OpenAI on this. Their stated desires seem rational, and Buckmaster's account makes them sound like cartoon villains. It sounds like there may have been some things lost in translation along with some bruised egos. Seems like the most plausible explanation for what Buckmaster is claiming.

rybosworld 12 hours ago

In chess, a grandmaster just needs to know at what moment in a game there's a critical move to gain a significant advantage over their opponent. They don't need to know the move itself.

OpenAI got wind that a millenium problem was being solved. And that feels a bit like the critical move in chess. That is - it was a signal that AI advanced far enough that it would be worth spending a lot of time and resources solving a millenium problem.

Kotlopou 11 hours ago

Elsewhere in this thread somebody claimed that at some point OpenAI pointed their new model at all the millennium problems and this is where they got some progress. We probably won't see proof of this, but it seems plausible to me -- I assume there's a list of problems that each new model is tested on, and you might as well put the big stuff on the list, if only to see how the model behaves when faced with a problem it knows should be very hard.

The weak point in this is: how do you evaluate if a partial result is promising? If this cost ~$10M as suggested elsewhere in the thread, probably not even OpenAI can just throw that at everything?

lanthissa 16 hours ago

5 million messages, 300b output tokens, done in 5 days, and achieving something humans couldn't.

the first "Country of geniuses in a datacenter" moment.

ranger207 16 hours ago

> humans couldn't.

There's allegations right now that the model essentially read the work of a human mathematician using AI to work on the problem and OpenAI is presenting his work as that of their model

brainwad 14 hours ago

Allegations that the model plagiarised itself, while reflecting poorly on humans, don't make the AI any less impressive. It was the one doing the breakthrough on both sides, after all, not the human prompters.

sinuhe69 14 hours ago

I'm tired of this, but please read the post of Tao. It’s listed in the top comment of this thread.

drpixie 10 hours ago

That is how the PR reads, but is not at all what happened.

A team of highly trained and skilled people used an AI tool, through many many instructions (prompts), to produce a specific mathematical theorem. The tool is impressive, the result (possibly/probably) interesting, but the PR skips the vital role of the humans (for the usual PR reasons).

pu_pe 16 hours ago

OpenAI thinks of this as a scoop, and it is, but the possibility that they trained the model on the prompts of the other mathematicians they were competing with will leave a terrible taste on every scientist's mouth. Seems like yet another advantage of using open models right here.

WarmWash 15 hours ago

Or paying for API use.

It should be clear to everyone reading this now that those generous compute quotes with the flat rate plans aren't charity.

bluebands 15 hours ago

fwiw there is a big "TRAIN ON MY DATA" toggle you can turn off (that they almost certainly did) and Anthropic MTS are posting that they almost certainly did not "steal" their methods

vrganj 12 hours ago

The fact the toggle is on by default makes that only slightly less unappetizing.

stephbook 14 hours ago

> they trained the model on the prompts of the other mathematicians they were competing with

How would they have gotten that mathematician's progress though? Did that guy also use OpenAI?

If that's the case, it only strenghtens their claims lol. If mathematician decide to use OpenAI's model to do the work, that only reiterates how strong their models are.

ex-aws-dude 4 hours ago

The guy did use OpenAI

stephbook 3 hours ago

It's only a question of who prompted then, with OpenAI models solving it in either case..

ccppurcell 16 hours ago

Reading between the lines here, and taking an admittedly very negative view of openai, but they train on user prompts. So if they hear a rumour that someone is about to make a big breakthrough, they have an incentive to scoop by running the model and hoping the solution is in the new training data. Also the statement from the mathematicians in question alleges that they tried to pressure him into academic malpractice. Just appalling timeline we're in, cheers.

aizk 16 hours ago

People had joked a couple years ago "Well if they solve a Millenium problem it's AGI"... Well here we are.

simianwords 16 hours ago

> I have a couple friends who did the Math tripos at Cambridge (so a pretty high level!) who work in tech and have unanimously said they have 0% expectations of an LLM doing a millennium problem anytime soon

https://news.ycombinator.com/item?id=38433655

> Let's talk when we've got LLMs proving the Riemann Hypothesis (or any mathematical hypothesis) without any proofs in the training data. I'm confident in my belief that an LLM can't do that, and will never be able to. LLMs can barely solve elementary school math problems reliably.

https://news.ycombinator.com/item?id=42331654

> An LLM is like a well read college student with a nearly photographic memory that sometimes mixes things up. It's great for bouncing ideas off of and getting feedback on them. And yeah, it might product "novel ideas" by mixing and matching existing ideas, but LLMs will never create truly novel ideas. Not in their current form.

The paper didn't really answer the question sadly: their conclusion was just that humans rate LLM answers as more novel than human ones, but less feasible.

https://news.ycombinator.com/item?id=41522605

> Solving Millennium problems is a whole different ballgame. It's not known if these problems are solvable within ZFC axioms. (In one case, the Yang-Mills prize, stating the problem mathematically is part of the challenge.) All of the obvious applications of known tricks have been tried and failed. To solve such problems, one probably has to invent new and surprising mathematical definitions, building a framework in which the problem becomes solvable. This is something that LLMs will be crap at; the process of invention is not represented in any training data we have access to.

https://news.ycombinator.com/item?id=38435909

> LLMs cannot reason or use mathematics - in a way, they don't know what they are talking about. Why would such technology lead to superhuman smarts?

https://news.ycombinator.com/item?id=35752293

> But still, the questions in that test are "solved" in the sense of "I can take a dictionary and answers these questions with full certainty". Beyond established knowledge LLMs are monkeys with typewriters, at best.

> I agree but I have tried many times to intersect two ideas with a LLM that would be novel and the LLM can not do this at all. We shouldn't expect the stochastic parrot to be able to do this though and it is unfair to the stochastic parrot.

> It is like expecting a real parrot to say words it has never heard before.

> No one asks that of a real parrot because we don't anthropomorphize a real parrot like we do the LLM

https://news.ycombinator.com/item?id=41525962

quantumwoke 15 hours ago

Some observations:

1. It seems at least possible that some of the proof of NS was contained in the training data, making it less novel.

2. The formalisation of mathematics into lean has been an underappreciated force multiplier on discovery.

rvz 15 hours ago

You can see that your math friends completely wrote off LLMs entirely and were showing signs of coping.

4 years ago it was a "not yet" [0], since ChatGPT at this time was not ready nor it was "AGI". Now with this 'unreleased' AI model, it has reached a point where it has solved an unsolved problem which only one human solved a millennium prize problem (Poincare conjecture).

Now finally "AGI" means something again.

[0] https://news.ycombinator.com/item?id=33905609

WarmWash 15 hours ago

Will history look back at comments like these as people being dumb, or people trying to cope?

stevenhuang 13 hours ago

Both

siva7 13 hours ago

It's denial and coping. Most people i see show this tendency around AI which is also why it 's easy to be far ahead of most population nowadays

cyclopeanutopia 12 hours ago

I'd say that believing to be "far ahead" is much deeper kind of coping.

siva7 12 hours ago

how i wish so..

keeda 12 hours ago

A 3rd possibility is that they simply have not been exposed to the best models available (which is extremely likely if you only use the free tier chatbots), and/or did not invest the effort needed to truly harness this new very weird new technology, and so had a very skewed perspective of their actual capabilities.

kypro 15 hours ago

As someone with a background in AI and who has been playing around with neural nets for decades at this point, it's been genuinely amazing watching extremely intelligent people make confident predictions about AI capabilities and progress, then be so completely wrong.

There's a kind of theory of mind for AI (specifically neural nets) which I now realise I seem to have which is very hard to explain to people who haven't felt the magic of these algorithms. In fact, the algorithmic details almost doesn't matter at all. When you have a generalised learning algorithm really the only essential components are – compute, data and time. So long as you can scale these you can be certain you will also scale capabilities. There is never any exception.

That said, the capabilities neural networks tend to progress in step-functions rather than scale in correlation with compute, data and time, because algorithmic improvements tend to come every ~5 years and bring a significant step change in capability (or efficiency depending on what you measure).

I think people like Dario and others working at frontier labs see and understand this very clearly. And I suspect it's also why they worry about AI risk because even if you ignore the significant increases in compute and data these models are being trained with, it's concerning that it only took two real algorithmic improvements to take us from mostly useless predictive language models to AGI-level intelligence – and we're due another step change.

reducesuffering 15 hours ago

> extremely intelligent people make confident predictions about AI capabilities and progress, then be so completely wrong.

The ability for the human mind to rationalize conclusions to maintain denial in the face of a very scary future is immense. Genuinely grappling with the implication of where we're headed is usually very crushing. It's not easy to engage with the possibility, and very intelligent people will use those smarts to feel safe.

kypro 11 hours ago

> Genuinely grappling with the implication of where we're headed is usually very crushing.

As someone currently prepping for various AI doom scenarios and who has been dealing with AI-related nightmares for years this is very relateable.

Although, I don't personally think it's this. In my experience the opposite is more true – the majority of high probability doomers seem rather laid back about considering what they believe will happen to the people they love in a few years. Equally I don't get the sense those who don't have such extreme predictions are worried at all. If anything there's not enough emotion.

In my opinion people just don't reason well when it comes to exponentials and are ignorant about things they don't have good mental models of. At least I know I struggle with this.

20k 15 hours ago

Yeah well, its easy to do if you steal someone elses work and then try to threaten them into staying quiet about it

Edit:

OpenAI have now admitted they were training on prompts at the time they made their breakthrough:

https://mastodon.social/@tristanbuckmaster/11723647135247030...

logancbrown 14 hours ago

Steal someone elses work, whose work was also AI generated . . .

Lapra 12 hours ago

Whether that's relevant to the conversation depends on what their prompt was.

aizk 5 hours ago

Tokens all the way down

simianwords 14 hours ago

what's there to admit? they always said they do it and there's a way to opt out. you are making it sound more dramatic than it is.

20k 13 hours ago

This is textbook plagiarism, scooping their result knowing that the research was part of the training data

boshalfoshal 13 hours ago

lol, the "other work" was also probably 95-99% AI generated. By a similar breed of OpenAI (and some Anthropic) models, as well.

I dont know why this monumental achievement is being drowned out by some arbitrary drama. No matter which way you slice it, AI solved this problem. Doesn't matter if it was some internal OpenAI model, or whether it was Astra + Fable.

demibabs 12 hours ago

Yeah but the mathematicians are claiming that the key insight that made the problem tractable for AI in the first place, came from them.

HDThoreaun 13 hours ago

All the ai labs are open about training on prompts. The question is if buckmaster had disabled that with the toggle openAI provides.

20k 13 hours ago

That does not make it ethical

HDThoreaun 12 hours ago

Isnt the entire history of academic progress iterating on work that other academics shared with you? Obviously this situation is spicy but openAI cited their work no?

20k 11 hours ago

OpenAI trained on their private unpublished research notes effectively, while also trying to get one of the paper authors fired

daveguy 12 hours ago

The question is more whether OpenAI can be trusted to honor that toggle switch. Given that they hold all chats for 30 days "for safety and security".

orangecat 12 hours ago

What is that supposed to prove? OpenAI is almost always going to be training new models.

matteoraso 13 hours ago

Jokes aside, that's a horrible test for AGI. I like to think that I'm sentient, and I could never solve a millenium problem.

pmxi 2 hours ago

The converse is not true.

Reubend 16 hours ago

It's great that important discoveries like this can now routinely be accompanies by formalized proofs. The fact that it's being released alongside a Lean proof from Day 1, rather than the Lean proof being released months or years later, is super helpful for verifying that it's correct.

imbusy111 16 hours ago

I feel sorry for whoever has to read and understand the solution. It looks like the typical convoluted unreadable mess I see the models generate for software. It might be technically correct, but gaining insight from it is just intellectual hell.

rfgplk 16 hours ago

Skill issue. Also lean is meant to be executed, not read.

arodev 15 hours ago

i think they're talking about the writeup

oinoom 14 hours ago

its important to read it anyway because there have been and will continue to be errors in the construction of the proof software itself. which leads ai and humans alike to prove things that arent true

professoretc 13 hours ago

A proof is not like a program. The goal of a program is to "do the thing", thus you can make the argument that it doesn't matter what the code looks like as long as its works right. But the goal of a proof isn't to "do the thing" (where "the thing" is just to print Yes or No), it's to communicate. An unintelligible proof is really just a first draft.

Jblx2 8 hours ago

>A proof is not like a program.

https://en.wikipedia.org/wiki/Curry%E2%80%93Howard_correspon...

nradov 15 hours ago

There's an opportunity to build a Lean "optimizer" which automatically simplifies existing proofs.

stabbles 15 hours ago

Yeah, code golfing for lean would be amazing, especially if they can make the proof to Fourier's Last Theorem fit in the margin.

Extra credits if it is proven that the proof cannot be reduced any further.