OpenAI’s September 8 announcement that an unreleased internal model used thousands of AI agents to produce a Lean-verified proof of finite-time singularity in the Navier-Stokes equations has intensified competition, yet the market remains near even because the effort was triggered by rumors of related work by Anthropic researcher Levent Alpöge and NYU mathematician Tristan Buckmaster on Euler and Boussinesq stepping-stone problems. Traders view both labs as comparably positioned: OpenAI demonstrated superior scale and agentic workflows, while Anthropic benefits from direct talent overlap and ongoing model improvements. Key swing factors include independent verification of the proof, potential joint credit disputes, and whichever lab next releases a comparably capable system or tackles remaining Millennium problems such as Yang-Mills or Riemann.
Polymarketデータを参照したAI生成の実験的な要約。これは取引アドバイスではなく、このマーケットの解決方法には一切関係ありません。 · 更新日OpenAI
OpenAI
If neither company makes a qualifying announcement by December 31, 2027, 11:59 PM ET, or if both make qualifying announcements on the same calendar day, this market will resolve 50-50. A qualifying announcement by any other company does not end the race or affect resolution.
The qualifying problems are the Riemann Hypothesis, P versus NP, the Yang-Mills existence and mass gap problem, the Hodge Conjecture, and the Birch and Swinnerton-Dyer Conjecture (https://www.claymath.org/millennium-problems/). Announcements concerning the Navier-Stokes existence and smoothness problem will not qualify.
A qualifying announcement must express that the problem has been solved; announcements of partial results or progress toward a solution will not qualify. The announcement must present the solution as the work of the company, its researchers, or its models, alone or jointly with outside researchers. An announcement that only credits or congratulates outside researchers, including researchers who used the company's models, compute, or research credits, will not qualify. No further confirmation from Clay Math Institute or any other organization is required.
The primary resolution source for this market will be official information from OpenAI and Anthropic and/or their official representatives; however, a consensus of credible reporting may also be used.
マーケット開始日: Sep 9, 2026, 3:42 PM ET
リゾルバー
0x65070BE91...If neither company makes a qualifying announcement by December 31, 2027, 11:59 PM ET, or if both make qualifying announcements on the same calendar day, this market will resolve 50-50. A qualifying announcement by any other company does not end the race or affect resolution.
The qualifying problems are the Riemann Hypothesis, P versus NP, the Yang-Mills existence and mass gap problem, the Hodge Conjecture, and the Birch and Swinnerton-Dyer Conjecture (https://www.claymath.org/millennium-problems/). Announcements concerning the Navier-Stokes existence and smoothness problem will not qualify.
A qualifying announcement must express that the problem has been solved; announcements of partial results or progress toward a solution will not qualify. The announcement must present the solution as the work of the company, its researchers, or its models, alone or jointly with outside researchers. An announcement that only credits or congratulates outside researchers, including researchers who used the company's models, compute, or research credits, will not qualify. No further confirmation from Clay Math Institute or any other organization is required.
The primary resolution source for this market will be official information from OpenAI and Anthropic and/or their official representatives; however, a consensus of credible reporting may also be used.
リゾルバー
0x65070BE91...OpenAI’s September 8 announcement that an unreleased internal model used thousands of AI agents to produce a Lean-verified proof of finite-time singularity in the Navier-Stokes equations has intensified competition, yet the market remains near even because the effort was triggered by rumors of related work by Anthropic researcher Levent Alpöge and NYU mathematician Tristan Buckmaster on Euler and Boussinesq stepping-stone problems. Traders view both labs as comparably positioned: OpenAI demonstrated superior scale and agentic workflows, while Anthropic benefits from direct talent overlap and ongoing model improvements. Key swing factors include independent verification of the proof, potential joint credit disputes, and whichever lab next releases a comparably capable system or tackles remaining Millennium problems such as Yang-Mills or Riemann.
Polymarketデータを参照したAI生成の実験的な要約。これは取引アドバイスではなく、このマーケットの解決方法には一切関係ありません。 · 更新日



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