NYU Professor Accuses OpenAI of Preempting AI Mathematical Breakthrough
NYU professor Tristan Buckmaster and Anthropic mathematician Levent Alpöge achieved key mathematical breakthroughs on fluid equations using AI models, only for OpenAI to subsequently claim a complete proof of the Navier-Stokes problem using an unreleased next-generation model. Buckmaster publicly questioned whether OpenAI preempted their work after learning of their progress and potentially leveraging Codex usage data. The Navier-Stokes existence and smoothness problem is one of the seven million-dollar Millennium Prize Problems, representing a foundational milestone in mathematical physics. This controversy highlights growing tensions surrounding academic ethics, computational scale in automated theorem proving, and the privacy of scientific research conducted via commercial AI models. OpenAI reported that its proof process consumed 300 billion output tokens worth roughly $22.5 million in compute over a single week, and stated it would decline the Clay Institute's $1 million prize. Although OpenAI claimed its proof was independent and did not access private user data, Buckmaster noted that OpenAI only began prompting its model after learning of their progress on a unique, rarely used mathematical strategy.
## BACKGROUND
The Navier-Stokes equations describe the motion of fluids, but whether smooth, non-breakdown solutions always exist in three dimensions remains an open problem. In 2000, the Clay Mathematics Institute named the Navier-Stokes problem one of seven Millennium Prize Problems, offering $1 million for a verified proof or counterexample. Modern mathematical breakthroughs increasingly combine domain-expert insights with AI models and formal proof checking tools like Lean.