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NYU Mathematician Questions OpenAI's Navier-Stokes Breakthrough
New York University mathematician Tristan Buckmaster has accused OpenAI of moving ahead with a solution to the million-dollar Navier-Stokes problem after becoming aware of work he and Levent Alpöge, a mathematician on the technical staff of Anthropic, had been developing.
![NYU mathematician Tristan Buckmaster has raised questions about OpenAI's claimed solution to the long-standing Navier-Stokes problem. [Image: OpenAi]](https://static.wixstatic.com/media/1c4fd3_85fec0a35b5d45f5834e5c773744096a~mv2.jpg/v1/fill/w_980,h_515,al_c,q_85,usm_0.66_1.00_0.01,enc_avif,quality_auto/1c4fd3_85fec0a35b5d45f5834e5c773744096a~mv2.jpg)
OpenAI announced Sept. 8 that an internal AI system had produced what it described as a solution to the Navier-Stokes existence and smoothness problem, one of the seven Millennium Prize Problems.
The company said its proof shows that the equations governing fluid motion can develop a singularity in finite time.
Buckmaster and Alpöge had been working on related aspects of the problem using several AI systems.
Buckmaster has questioned how closely OpenAI's approach resembles theirs and raised concerns about whether their work may have influenced OpenAI's effort.
Buckmaster described the development as a "Deep Blue-Kasparov moment" for mathematics, referring to the historic 1997 chess match in which IBM's Deep Blue defeated world champion Garry Kasparov.
OpenAI has denied accessing or using Buckmaster and Alpöge's specific unpublished research.
The company has said its effort began after researchers heard a rumor that appeared to concern the pair's work. OpenAI also acknowledged that it could not rule out the possibility that de-identified data from users' interactions with its products had contributed indirectly to model development.
Scientific American described the development as potentially historic for mathematics and artificial intelligence.
The publication noted that the Navier-Stokes equations are used to describe the movement of fluids such as air and water.
The controversy raises broader questions about attribution, privacy and the role of AI in mathematical research as companies race to develop increasingly capable systems.
