Tristan Buckmaster is a mathematician at NYU who works on problems in fluid mechanics. In recent coverage he raised concerns about OpenAI's use of his Codex data and joined other mathematicians in demanding proof that the company did not rely on unpublished research. A Guardian editorial and a Deccan Herald commentary cited his objections while questioning claims that AI solved Navier-Stokes and formalised Fermat's Last Theorem.
Mathematicians' Dispute Fuels Fears AI Could Undermine ScienceOpenAI said its AI agents solved a Navier–Stokes-related math problem in 88 hours, but NYU mathematician Tristan Buckmaster raised concerns beforehand that drafts stored in Codex might have fed OpenAI's work; OpenAI denied that anyone there saw the other team's work.
Commentary questions meaning of OpenAI, Anthropic automated proofsA Deccan Herald commentary pushes back on OpenAI's claim that AI solved the Navier-Stokes equations and Anthropic's claim that AI formalised Fermat's Last Theorem, noting both build on human work and employ mathematicians with little transparency about where human effort ends and AI begins. NYU mathematician Tristan Buckmaster told The New York Times he doubts due diligence was done given the volume of results released at once.
Guardian: mathematicians still vital, but AI firms won't see itA Guardian editorial criticises OpenAI's claim that its AI agents solved the Navier-Stokes problem, arguing LLM results rely on prior human mathematical work without adequate credit or compensation. Mathematician Tristan Buckmaster raised concerns about OpenAI's use of his Codex data; OpenAI denied directly accessing it but could not rule out the data helping improve its model.
Mathematicians question OpenAI's data useSeveral mathematicians, including Andreas Thom, Gábor Kun, and Tristan Buckmaster, have demanded proof that OpenAI did not use unpublished research and accused the company of lacking transparency. OpenAI acknowledged heavily drawing on Thom and Kun’s work for a non-sofic groups result and quietly amended its writeup; Thom says he emailed researchers including Sébastien Bubeck.
OpenAI trained on user sessions, raising privacy concernsA post highlights that OpenAI trains on uploaded user data and sessions, meaning internal models may leverage others' prompts to appear more autonomous, raising privacy and attribution concerns.
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