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Chronicles

The story behind the story

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OpenAI denies that its researchers or models saw Buckmaster and Alpöge's prompts and says it spent millions in compute after rumors of Anthropic making progress

Wired

Context & Ripple Effects

The dispute centers on provenance as much as mathematical performance. Buckmaster alleges OpenAI learned of work he and Levent Alpöge were conducting with Anthropic; OpenAI says it cannot fully exclude the possibility that de-identified product-use data contributed to model improvement, while denying that researchers or models saw their prompts.

The episode follows a period in which OpenAI and Anthropic have publicly contested boundaries around model use, including Anthropic's criticism of OpenAI's use of Claude Code before GPT-5. That makes the source and handling of research inputs a competitive issue rather than a narrow authorship dispute.

First-order effects

  • OpenAI's claimed result faces an immediate provenance test: its denial of access to Buckmaster and Alpöge's prompts sits alongside its stated inability to completely rule out de-identified data derived from their product use.
  • Buckmaster and Alpöge's work becomes central evidence in a public dispute over whether OpenAI's research process was independent of work associated with Anthropic.

Second-order effects

  • OpenAI's reported multimillion-dollar compute effort shows that even unconfirmed signals of a rival lab's progress can redirect expensive frontier-model research programs.
  • Anthropic and OpenAI face stronger incentives to document model access, user-data handling, and the separation between competitive research efforts as claims about independent discovery are scrutinized.

Third-order effects

  • If comparable disputes recur, frontier-lab advantage will be assessed not only by benchmark or research results but also by whether labs can establish credible provenance for the data and prompts behind them.
  • The expense cited by OpenAI reinforces a broader concentration dynamic: only well-capitalized labs can rapidly mount large compute-intensive responses to competitive intelligence.

The trend: Frontier AI competition is making research provenance and the cost of reacting to rival signals as consequential as the technical results themselves.

Discussion

  • @sama Sam Altman on x
    I spent much of the weekend talking with the team who did this work. Seb—and everyone else—acted with integrity and generosity throughout. Initially we believed the other team had also solved the problem. We wanted to collaborate and do a joint release. When we learned that they …
  • @kevinroose Kevin Roose on x
    OpenAI also acknowledging it did start working on Navier-Stokes after hearing rumors that Anthropic was getting close to a solution. (But implies they did not snoop on their work.) A math fight for the ages! https://x.com/...
  • @sebastienbubeck Sebastien Bubeck on x
    Some more technical points: (a) We began working on the Millennium problems due to viral twitter rumors that Anthropic had resolved 2 Millenium problems. Our aim was to see whether our system was also capable of this impressive feat, especially given our excitement regarding the …
  • @sebastienbubeck Sebastien Bubeck on x
    I would like to clarify a few things: 1) The screenshot is my reaching out to Levent to coordinate our releases. I hope it's clear from the message that we came in with the best possible intentions. 2) I never ever asked for Levent to be removed from authorship of his own work (a…
  • @polynoamial Noam Brown on x
    Yes, this result cost millions of dollars. But remember that when @OpenAI announced o3 it cost ~$500,000 to score 87.5% on ARC-AGI 1. Today, Astra scores higher for ~$20. In 2025 it took us and GDM an enormous amount of compute to achieve IMO gold. For the 2026 IMO, anyone with a…
  • @openai @openai on x
    We congratulate Levent Alpöge and Tristan Buckmaster on their remarkable mathematical work. 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 th…
  • @katie-drummond Katie Drummond on bluesky
    OpenAI and Anthropic are in a pissing contest about math now, and I'm honestly completely obsessed:
  • @krishnanrohit Rohit on x
    > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. Isn't this just the norm for using ChatGPT or Claude or Gemini or indeed anything else, unless you actively opt out?
  • @__alpoge__ Levent on x
    “we cannot rule out that de-identified data derived from their usage of our products helped improve our models.
  • @whodat35 Lee West on bluesky
    OpenAI Just Claimed a Huge Math Discovery.  Some Academics Are Crying Foul  —  A landmark announcement by the frontier AI lab has been overshadowed by accusations of impropriety.  WIRED  —  www.wired.com/story/openai...
  • @jetjocko Adam Rogers on bluesky
    Separate from the serious allegations of plagiarism in solving one of the most significant problems in math, you gotta wonder: Would spending millions of dollars on dozens of humans (and vast compute) have *also* worked?  —  www.wired.com/story/openai...
  • r/OpenAI r on reddit
    OpenAI Just Claimed a Huge Math Discovery.  Some Academics Are Crying Foul