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OpenAI announces a Navier–Stokes blowup construction
Tracks OpenAI's announced forced Navier–Stokes result, its multiagent workflow, mathematical scope and disputes over priority and research-data use.
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Overview
OpenAI announced that an internal model had produced a construction showing blowup in the forced Navier–Stokes equations, with a Lean formalization, and matched it to conditions C and D of the Millennium Prize formulation. Moonshots discussed a reported workflow of 10,000 agents over 88 hours and estimated the inference cost at 6.5 million dollars. The panel saw a breakthrough in automated research, and it passed on disputed accounts of authorship and worries that researchers could be scooped by their own model provider. The announcement says OpenAI will not claim the prize and that its investigation ruled out any influence from Buckmaster's recent Codex prompts. In a Diary of a CEO debate, the safety-focused side used the result as a warning sign about AI-driven AI research. A skeptic called that a leap, and the debaters gave the run's length as 11 days. On the Dwarkesh Podcast, OpenAI researcher Noam Brown, who works on multi-agent systems, gave an insider's account. He said multi-agent techniques deserve less than 10 per cent of the credit and that the core reason for the result was a very strong general-purpose model. OpenAI has not run a single-agent baseline, so the benefit of 10,000 agents is unmeasured. He said the same internal model, which is not available outside OpenAI, has produced solutions to other unsolved problems, and he called this an unfair advantage that OpenAI has no good answer for. None of these discussions counts as independent mathematical validation.
What changed
Dates show when each podcast discussion was published.
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Interpretation
On The Diary of a CEO, Nate Soares's side used the Navier–Stokes claim to argue that AI-driven research on better AI architectures could arrive sooner than expected. He described the run as 10,000 OpenAI agents over 11 days, which differs from the reported 88 hours, and said OpenAI had raced human researchers who were close to a solution. A skeptic called the inference a leap. He said it was unconfirmed how much OpenAI relied on human scientists' work and that the AI had not worked alone. Speakers also mentioned unverified rumors of other Millennium claims.
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New information
On the Dwarkesh Podcast, OpenAI researcher Noam Brown said he would not give multi-agent techniques even 10 per cent of the credit for the result. In his account, the main reason was a very strong general-purpose model that can run over long horizons and think in parallel. He said OpenAI has not tested how long a single agent would take, so the run is one data point, and it is possible that 10,000 humans currently coordinate better than 10,000 agents. He said the internal model is not available to outsiders and has produced solutions to other unsolved problems as well. He called this an unfair advantage with trade-offs he does not know how to weigh. He said that about two weeks before the result, a frontier-lab researcher bet him 1,000 dollars that it would take until after 2027, and he took the bet. The interviewer described the 130 billion tokens as roughly 4,000 years of full-time human thinking.
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New information
The panel interprets the announced result as evidence that generalist agents can tackle major mathematical problems. It discusses compute costs, concurrent Euler work, disputed credit negotiations and possible training contamination, leaving the latter as a concern rather than an established finding.
Podcast discussions
- Dwarkesh Podcast Noam Brown – Agent swarms, alignment, & recursive self-improvementSep 17, 2026
- The Diary of a CEO AI Debate Ed Zitron, Andrew McAfee, Nate Soares, Roman YampolskiySep 17, 2026
- Moonshots with Peter Diamandis Why Jensen Huang Believes We’ve Reached AGI and Inside OpenAI’s German Website Hijack | #287Sep 9, 2026
Sources
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Version history
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Sep 29, 2026 · Version 3
On the Dwarkesh Podcast, OpenAI researcher Noam Brown said he would not give multi-agent techniques even 10 per cent of the credit for the result. In his account, the main reason was a very strong general-purpose model that can run over long horizons and think in parallel. He said OpenAI has not tested how long a single agent would take, so the run is one data point, and it is possible that 10,000 humans currently coordinate better than 10,000 agents. He said the internal model is not available to outsiders and has produced solutions to other unsolved problems as well. He called this an unfair advantage with trade-offs he does not know how to weigh. He said that about two weeks before the result, a frontier-lab researcher bet him 1,000 dollars that it would take until after 2027, and he took the bet. The interviewer described the 130 billion tokens as roughly 4,000 years of full-time human thinking.
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Sep 25, 2026 · Version 2
On The Diary of a CEO, Nate Soares's side used the Navier–Stokes claim to argue that AI-driven research on better AI architectures could arrive sooner than expected. He described the run as 10,000 OpenAI agents over 11 days, which differs from the reported 88 hours, and said OpenAI had raced human researchers who were close to a solution. A skeptic called the inference a leap. He said it was unconfirmed how much OpenAI relied on human scientists' work and that the AI had not worked alone. Speakers also mentioned unverified rumors of other Millennium claims.