4 ms·

Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers That's

by 20k 22d ago

Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers That's why nobody's talking about how impressive this is, because its not nearly as impressive of a piece of work to simply cobble together other peoples' work that didn't know you were doing it. I could have republished relativity from einstein's notes, but people would correctly not be impressed with my ability Until the plagiarism scandal is sorted out, its not a meaningful result at all, because nobody knows how much genuine innovation these models are displaying

sho_hn 22d ago
> Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers It's also true however that I haven't seen a single write up trying to discern what did more of the work in those AI chats - the prompts or the responses - bubble to the surface, also since we don't have access to them. For example, if I prompt Codex with "Make me a website about strawberry cake" and nothing else, and OpenAI announces they have the best strawberry cake minutes before I launch, I'm not sure they plagiarized anything. We just don't know if this is quibbling over "who prompted first" or if the researchers came up with anything strikingly original by themselves.
- 20k 22d ago
  The researchers apparently spend a year or so working on this, and it builds off significant previous work, so it seems like it was a pretty significant amount of work that OpenAI may have trained on I'd love to see an in depth analysis of how much OpenAI actually did, but I suspect we'll never see that because it would indicate at least some plagiarism which undermines a lot of what OpenAI is putting out in public
  - felipeerias 22d ago
    The American Mathematical Society credits the Spanish researchers Diego Córdoba and Luis Martínez‑Zoroa with the breakthroughs that eventually led to this solution, and which were published from ~2023 onwards. This is a good summary: > In broad outline, the pair’s technique relies on creating an infinite sequence of “layers,” each of which is a non-singular solution to the equation they are studying. (They’ve applied similar techniques to both the Euler and Navier-Stokes equations, as well as to other related systems.) They then combine those solutions in what Martínez-Zoroa calls an “infinite cascade” to produce a new solution. > > That new solution, they showed, contains the desired singularity. However, even though each individual layer relies on a smooth forcing function, combining them together can cause the forcing function to have undesirable mathematical properties. That’s why their solution fell short of satisfying the Millennium Prize criteria. The remaining hurdle was to figure out how to create a similar infinite cascade that resulted not only in a singularity, but also in a smooth forcing function. > > That’s the step that both competing AI groups appear to have had success with. https://www.quantamagazine.org/ai-has-solved-one-of-maths-1-million-millennium-prize-problems-20260908/ https://www.quantamagazine.org/ai-has-solved-one-of-maths-1-... The question is whether OpenAI started out from that published and well known research exclusively, or they also had some insight into the ongoing work of Tristan Buckmaster and Levent Alpöge. On the one hand, OpenAI have already admitted that they only launched their massive effort after hearing rumours that this particular problem had been solved. On the other, progress in mathematics research has accelerated significantly over the past months thanks to the availability of newer and more capable AI models. Alpöge himself presented a counterexample to the Jacobian conjecture on July, found with Claude Fable. So if model capability was a bottleneck, that gives credibility to the idea that an even more powerful unreleased model with massive compute would be able to make even faster progress.
- Hardwired8976 22d ago
  The conversation was about using the chat to check the draft, the novel ideas came from the researcher.
- TZubiri 22d ago
  It's worth noting that the case is that your input is being used to train their AI, and that's more important than whether it materially contributed, it cannot be denied or attributed accurately, it cannot be said with certainty which way it happened, and that's what's important.
- ImPostingOnHN 22d ago
  The truth is likely that without the tool or the humans using it, the process would have taken longer
  - airstrike 22d ago
    Without the humans, no tool would ever have done it. Without the tool, humans would have done it.
atleastoptimal 22d ago
Turning a bunch of vague research directions and exploratory prompts into a formalized proof is quite impressive on its own. OpenAI would have no incentive to taint its first math announcement of this magnitude if it knew it were "plagiarizing" another person's work. People are grasping at straws it seems to dismiss the power of this new model they may have. Hate OpenAI for any reason you want, but denying the capabilities of models has been a losing game for the past 5 years.
- samastur 22d ago
  Why do you assume they were vague? Do you imagine mathematicians work by stumbling around searching for accidental clues?
- TZubiri 22d ago
  > if it knew it were "plagiarizing" But if it happened, they didn't know. Also OAI has demonstrated that they aren't big on understanding what they create, that their AI can get out of their control. It's very simple really user data can be used to train future models, so maybe or definitely some users helped in solving the problem, there's no scenario were it is impossible this happened, as it would have been in a haskell or virtualized type of system where the model has absolutely no knowledge of the user data dataset in question (and even if virtualized the models can break virtualization anyways)
- manofmanysmiles 22d ago
  > OpenAI would have no incentive to taint its first math announcement of this magnitude if it knew it were "plagiarizing" another person's work. I'm not sure I follow, considering the waterfall of evidence of unethical behavior flowing from OpenAI. A few major ones: - Safety team departures and dissolution in 2023 and 2024 - Mass copyright infrigement lawsuits - Scarlett Johansson Voice Controversy - For-Profit Conversion and Broken Promises - AI Agents Acting Autonomously - Potential Theft of User Work (this current controversy) - Military contracts These are not evidence of incentives, but rather evidence that ethetics seem to be of little concern to the company as a whole. Incentive wise, I would look at the perceive existential position due to competitors, capex, IPO pressure etc.
tristanj 22d ago
It is very unlikely to be plagiarized, and claims of plagiarism are largely unfounded and show a lack of understanding of the situation. They fall apart when reviewing the timeline, and what was actually solved. This is the timeline: On June 29, Buckmaster opted out of model training, and stopped allowing his chats to be used as training data with OpenAI https://mastodon.social/@tristanbuckmaster/117233413705701198 https://mastodon.social/@tristanbuckmaster/11723341370570119... On August 15, Buckmaster and Alpöge found their blow-up for 3D incompressible Euler with forcing https://cims.nyu.edu/~tristanb/statement.pdf https://cims.nyu.edu/~tristanb/statement.pdf In late August, OpenAI completed a pretrain of its latest internal model. A model derived from this pretrain, built after August 28, found a solution to 3D incompressible Euler without forcing and Navier-Stokes with forcing. https://openai.com/index/navier-stokes-solution/ https://openai.com/index/navier-stokes-solution/ To explain who solved what (I copied from here: https://x.com/IlinVasily29521/status/2097554700321329393 https://x.com/IlinVasily29521/status/2097554700321329393 ) Tristan + Levent: 3D incompressible Euler with forcing OpenAI: 3D incompressible Euler without forcing OpenAI: Navier-Stokes with forcing No one: Navier-Stokes without forcing Euler equations = Navier-Stokes without viscosity. Forcing means external force. Absence of viscosity and presence of external force make blowup easier to construct. Tristan+Levent ticked the weakest case, OpenAI ticked the two next weakest, then the final case is unsolved. Only the last two are eligible for the Millennium Prize. The Navier-Stokes general case remains unsolved. Buckmaster disabled model training long before the August 15 breakthrough results, so these chats were not used as training data for OpenAI's model which solved Navier-Stokes. Additionally, Tristan and Levent only solved the easiest version of the problem and did not have the key insights to solve the harder versions of the problem required for the Millennium Prize. And OpenAI directly addressed these plagiarism claims, and called them impossible: https://www.nytimes.com/2026/09/10/science/tristan-buckmaster-openai-math-navier-stokes.html https://www.nytimes.com/2026/09/10/science/tristan-buckmaste... "We can say categorically that it is impossible for Dr. Buckmaster’s Codex prompts over the last two months to have influenced the system in any way, including training."
- ggoo 22d ago
  I’m unsure or not if this is true but I did see some people saying that that checkbox when off only anonymizes your data, but it still may be trained on. Someone correct me if I am wrong
btilly 22d ago
The other researchers themselves were also using AI. That's why it was potentially available to be plagiarized. There is no human only proof of this.
- tristanj 22d ago
  The team also had access to internal Anthropic models.
mieses 22d ago
who cares about plagiarism? the biggest issue, as described by Terence Tao, is that AI companies don't understand the math they are publishing and do not devote any resources to answering questions about their methods after publishing results and getting a headline. they miss the whole point of mathematics. they do not contribute to the improvement of human understanding of math, perhaps because they are unable to.
thiht 22d ago
> but instead plagiarised the significant step of the result from other researchers Isn't that how research works? Everything is built on the shoulders of the ones that came before, attribution is a real problem (I don't know if OpenAI released a paper citing the previous contributions, I'm assuming not but they should), but using previous maths to prove new maths shouldn't be controversial

by 20k 22d ago

sho_hn 22d ago

> Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers It's also true however that I haven't seen a single write up trying to discern what did more of the work in those AI chats - the prompts or the responses - bubble to the surface, also since we don't have access to them. For example, if I prompt Codex with "Make me a website about strawberry cake" and nothing else, and OpenAI announces they have the best strawberry cake minutes before I launch, I'm not sure they plagiarized anything. We just don't know if this is quibbling over "who prompted first" or if the researchers came up with anything strikingly original by themselves.

20k 22d ago
The researchers apparently spend a year or so working on this, and it builds off significant previous work, so it seems like it was a pretty significant amount of work that OpenAI may have trained on I'd love to see an in depth analysis of how much OpenAI actually did, but I suspect we'll never see that because it would indicate at least some plagiarism which undermines a lot of what OpenAI is putting out in public
- felipeerias 22d ago
  The American Mathematical Society credits the Spanish researchers Diego Córdoba and Luis Martínez‑Zoroa with the breakthroughs that eventually led to this solution, and which were published from ~2023 onwards. This is a good summary: > In broad outline, the pair’s technique relies on creating an infinite sequence of “layers,” each of which is a non-singular solution to the equation they are studying. (They’ve applied similar techniques to both the Euler and Navier-Stokes equations, as well as to other related systems.) They then combine those solutions in what Martínez-Zoroa calls an “infinite cascade” to produce a new solution. > > That new solution, they showed, contains the desired singularity. However, even though each individual layer relies on a smooth forcing function, combining them together can cause the forcing function to have undesirable mathematical properties. That’s why their solution fell short of satisfying the Millennium Prize criteria. The remaining hurdle was to figure out how to create a similar infinite cascade that resulted not only in a singularity, but also in a smooth forcing function. > > That’s the step that both competing AI groups appear to have had success with. https://www.quantamagazine.org/ai-has-solved-one-of-maths-1-million-millennium-prize-problems-20260908/ https://www.quantamagazine.org/ai-has-solved-one-of-maths-1-... The question is whether OpenAI started out from that published and well known research exclusively, or they also had some insight into the ongoing work of Tristan Buckmaster and Levent Alpöge. On the one hand, OpenAI have already admitted that they only launched their massive effort after hearing rumours that this particular problem had been solved. On the other, progress in mathematics research has accelerated significantly over the past months thanks to the availability of newer and more capable AI models. Alpöge himself presented a counterexample to the Jacobian conjecture on July, found with Claude Fable. So if model capability was a bottleneck, that gives credibility to the idea that an even more powerful unreleased model with massive compute would be able to make even faster progress.
Hardwired8976 22d ago
The conversation was about using the chat to check the draft, the novel ideas came from the researcher.
TZubiri 22d ago
It's worth noting that the case is that your input is being used to train their AI, and that's more important than whether it materially contributed, it cannot be denied or attributed accurately, it cannot be said with certainty which way it happened, and that's what's important.
ImPostingOnHN 22d ago
The truth is likely that without the tool or the humans using it, the process would have taken longer
- airstrike 22d ago
  Without the humans, no tool would ever have done it. Without the tool, humans would have done it.

atleastoptimal 22d ago

Turning a bunch of vague research directions and exploratory prompts into a formalized proof is quite impressive on its own. OpenAI would have no incentive to taint its first math announcement of this magnitude if it knew it were "plagiarizing" another person's work. People are grasping at straws it seems to dismiss the power of this new model they may have. Hate OpenAI for any reason you want, but denying the capabilities of models has been a losing game for the past 5 years.

samastur 22d ago
Why do you assume they were vague? Do you imagine mathematicians work by stumbling around searching for accidental clues?
TZubiri 22d ago
> if it knew it were "plagiarizing" But if it happened, they didn't know. Also OAI has demonstrated that they aren't big on understanding what they create, that their AI can get out of their control. It's very simple really user data can be used to train future models, so maybe or definitely some users helped in solving the problem, there's no scenario were it is impossible this happened, as it would have been in a haskell or virtualized type of system where the model has absolutely no knowledge of the user data dataset in question (and even if virtualized the models can break virtualization anyways)
manofmanysmiles 22d ago
> OpenAI would have no incentive to taint its first math announcement of this magnitude if it knew it were "plagiarizing" another person's work. I'm not sure I follow, considering the waterfall of evidence of unethical behavior flowing from OpenAI. A few major ones: - Safety team departures and dissolution in 2023 and 2024 - Mass copyright infrigement lawsuits - Scarlett Johansson Voice Controversy - For-Profit Conversion and Broken Promises - AI Agents Acting Autonomously - Potential Theft of User Work (this current controversy) - Military contracts These are not evidence of incentives, but rather evidence that ethetics seem to be of little concern to the company as a whole. Incentive wise, I would look at the perceive existential position due to competitors, capex, IPO pressure etc.

tristanj 22d ago

It is very unlikely to be plagiarized, and claims of plagiarism are largely unfounded and show a lack of understanding of the situation. They fall apart when reviewing the timeline, and what was actually solved. This is the timeline: On June 29, Buckmaster opted out of model training, and stopped allowing his chats to be used as training data with OpenAI https://mastodon.social/@tristanbuckmaster/117233413705701198 https://mastodon.social/@tristanbuckmaster/11723341370570119... On August 15, Buckmaster and Alpöge found their blow-up for 3D incompressible Euler with forcing https://cims.nyu.edu/~tristanb/statement.pdf https://cims.nyu.edu/~tristanb/statement.pdf In late August, OpenAI completed a pretrain of its latest internal model. A model derived from this pretrain, built after August 28, found a solution to 3D incompressible Euler without forcing and Navier-Stokes with forcing. https://openai.com/index/navier-stokes-solution/ https://openai.com/index/navier-stokes-solution/ To explain who solved what (I copied from here: https://x.com/IlinVasily29521/status/2097554700321329393 https://x.com/IlinVasily29521/status/2097554700321329393 ) Tristan + Levent: 3D incompressible Euler with forcing OpenAI: 3D incompressible Euler without forcing OpenAI: Navier-Stokes with forcing No one: Navier-Stokes without forcing Euler equations = Navier-Stokes without viscosity. Forcing means external force. Absence of viscosity and presence of external force make blowup easier to construct. Tristan+Levent ticked the weakest case, OpenAI ticked the two next weakest, then the final case is unsolved. Only the last two are eligible for the Millennium Prize. The Navier-Stokes general case remains unsolved. Buckmaster disabled model training long before the August 15 breakthrough results, so these chats were not used as training data for OpenAI's model which solved Navier-Stokes. Additionally, Tristan and Levent only solved the easiest version of the problem and did not have the key insights to solve the harder versions of the problem required for the Millennium Prize. And OpenAI directly addressed these plagiarism claims, and called them impossible: https://www.nytimes.com/2026/09/10/science/tristan-buckmaster-openai-math-navier-stokes.html https://www.nytimes.com/2026/09/10/science/tristan-buckmaste... "We can say categorically that it is impossible for Dr. Buckmaster’s Codex prompts over the last two months to have influenced the system in any way, including training."

ggoo 22d ago
I’m unsure or not if this is true but I did see some people saying that that checkbox when off only anonymizes your data, but it still may be trained on. Someone correct me if I am wrong

btilly 22d ago

The other researchers themselves were also using AI. That's why it was potentially available to be plagiarized. There is no human only proof of this.

tristanj 22d ago
The team also had access to internal Anthropic models.

mieses 22d ago

who cares about plagiarism? the biggest issue, as described by Terence Tao, is that AI companies don't understand the math they are publishing and do not devote any resources to answering questions about their methods after publishing results and getting a headline. they miss the whole point of mathematics. they do not contribute to the improvement of human understanding of math, perhaps because they are unable to.

thiht 22d ago

> but instead plagiarised the significant step of the result from other researchers Isn't that how research works? Everything is built on the shoulders of the ones that came before, attribution is a real problem (I don't know if OpenAI released a paper citing the previous contributions, I'm assuming not but they should), but using previous maths to prove new maths shouldn't be controversial