Trader consensus currently assigns the highest implied probability to the Hodge Conjecture, driven by OpenAI’s September 2026 resolution of the Navier-Stokes equations using large-scale AI agent systems and formal verification in Lean, alongside credible reports of the same internal model targeting algebraic geometry challenges next. Birch and Swinnerton-Dyer follows closely, reflecting ongoing machine-learning explorations of elliptic-curve L-functions and number-theoretic patterns that align with recent LLM strengths in structured reasoning. The 27% chance of no further solution by December 2027 captures realistic timelines for peer review, potential delays in capability scaling, and the inherent difficulty of formalizing proofs across remaining problems like Yang-Mills or P versus NP. These market-implied odds aggregate trader assessments of competitive lab efforts and verifiable AI math benchmarks rather than guarantees.
基于Polymarket数据的AI实验性摘要。这不是交易建议,也不影响该市场的结算方式。 · 更新于霍奇猜想 40%
伯奇-斯温纳顿-戴尔 29%
2027年12月31日前无解 27%
杨-米尔斯 2.5%
$127,580 交易量
$127,580 交易量
霍奇猜想
40%
伯奇-斯温纳顿-戴尔
29%
2027年12月31日前无解
27%
杨-米尔斯
2%
P与NP
1%
黎曼猜想
<1%
霍奇猜想 40%
伯奇-斯温纳顿-戴尔 29%
2027年12月31日前无解 27%
杨-米尔斯 2.5%
$127,580 交易量
$127,580 交易量
霍奇猜想
40%
伯奇-斯温纳顿-戴尔
29%
2027年12月31日前无解
27%
杨-米尔斯
2%
P与NP
1%
黎曼猜想
<1%
If no eligible AI lab announces a solution to a qualifying problem by December 31, 2027, 11:59 PM ET, this market will resolve to "No solution by Dec 31, 2027". If solutions to two or more qualifying problems are announced on the same calendar day (ET), this market will resolve to the problem whose name, as listed below, comes first in alphabetical order.
The qualifying problems are, in alphabetical order, the Birch and Swinnerton-Dyer Conjecture, the Hodge Conjecture, P versus NP, the Riemann Hypothesis, and the Yang-Mills existence and mass gap problem (https://www.claymath.org/millennium-problems/). Announcements concerning the Navier-Stokes existence and smoothness problem will not qualify.
A qualifying announcement must be made by an eligible AI lab or an official representative of the lab, and 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 lab, 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 lab's models, compute, or research credits, will not qualify. No further confirmation from Clay Math Institute or any other organization is required.
The eligible AI labs are Anthropic, Google, SpaceXAI, Alibaba, OpenAI, Baidu, Z.ai, Xiaomi, Moonshot, Meta, Nvidia, DeepSeek, MiniMax, Meituan, Amazon, ByteDance, Mistral, Tencent, StepFun, Microsoft, Harmonic, Axiom Math, Math Inc, Safe Superintelligence, Thinking Machines Lab, Reflection AI, Periodic Labs, Apple, IBM, Huawei, Samsung, Oracle, Salesforce, Cohere, AI21 Labs, Reka, Sakana AI, Poolside, Magic, Perplexity, Anysphere, Kuaishou, SenseTime, iFlytek, Baichuan, and 01.AI, together with their subsidiaries and research divisions, and any other company with a model listed on the MMLU-pro leaderboard (https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro) at the time of the announcement. Announcements by any other company, organization, or individual will not qualify.
The primary resolution source for this market will be official information from the eligible AI labs and/or their official representatives; however, a consensus of credible reporting may also be used.
市场开放时间: Sep 9, 2026, 3:43 PM ET
If no eligible AI lab announces a solution to a qualifying problem by December 31, 2027, 11:59 PM ET, this market will resolve to "No solution by Dec 31, 2027". If solutions to two or more qualifying problems are announced on the same calendar day (ET), this market will resolve to the problem whose name, as listed below, comes first in alphabetical order.
The qualifying problems are, in alphabetical order, the Birch and Swinnerton-Dyer Conjecture, the Hodge Conjecture, P versus NP, the Riemann Hypothesis, and the Yang-Mills existence and mass gap problem (https://www.claymath.org/millennium-problems/). Announcements concerning the Navier-Stokes existence and smoothness problem will not qualify.
A qualifying announcement must be made by an eligible AI lab or an official representative of the lab, and 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 lab, 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 lab's models, compute, or research credits, will not qualify. No further confirmation from Clay Math Institute or any other organization is required.
The eligible AI labs are Anthropic, Google, SpaceXAI, Alibaba, OpenAI, Baidu, Z.ai, Xiaomi, Moonshot, Meta, Nvidia, DeepSeek, MiniMax, Meituan, Amazon, ByteDance, Mistral, Tencent, StepFun, Microsoft, Harmonic, Axiom Math, Math Inc, Safe Superintelligence, Thinking Machines Lab, Reflection AI, Periodic Labs, Apple, IBM, Huawei, Samsung, Oracle, Salesforce, Cohere, AI21 Labs, Reka, Sakana AI, Poolside, Magic, Perplexity, Anysphere, Kuaishou, SenseTime, iFlytek, Baichuan, and 01.AI, together with their subsidiaries and research divisions, and any other company with a model listed on the MMLU-pro leaderboard (https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro) at the time of the announcement. Announcements by any other company, organization, or individual will not qualify.
The primary resolution source for this market will be official information from the eligible AI labs and/or their official representatives; however, a consensus of credible reporting may also be used.
Trader consensus currently assigns the highest implied probability to the Hodge Conjecture, driven by OpenAI’s September 2026 resolution of the Navier-Stokes equations using large-scale AI agent systems and formal verification in Lean, alongside credible reports of the same internal model targeting algebraic geometry challenges next. Birch and Swinnerton-Dyer follows closely, reflecting ongoing machine-learning explorations of elliptic-curve L-functions and number-theoretic patterns that align with recent LLM strengths in structured reasoning. The 27% chance of no further solution by December 2027 captures realistic timelines for peer review, potential delays in capability scaling, and the inherent difficulty of formalizing proofs across remaining problems like Yang-Mills or P versus NP. These market-implied odds aggregate trader assessments of competitive lab efforts and verifiable AI math benchmarks rather than guarantees.
基于Polymarket数据的AI实验性摘要。这不是交易建议,也不影响该市场的结算方式。 · 更新于


警惕外部链接哦。
警惕外部链接哦。
常见问题