Recent breakthroughs in large language model reasoning explain the 71% market-implied probability that an AI system secures an IMO gold medal in 2026. OpenAI’s experimental reasoning model and Google DeepMind’s Gemini Deep Think both reached the exact 35-out-of-42 gold cutoff at IMO 2025 by solving five of six problems under timed, closed-book conditions—advancing sharply from DeepMind’s 28-point silver-equivalent performance the prior year. Continued scaling, reinforcement learning on formal proofs, and benchmark convergence tracked in the Stanford AI Index support further gains before the July 2026 contest in Shanghai. Traders weigh the narrow historical margin against possible increases in problem difficulty or evaluation standards, yet view iterative releases from frontier labs as likely to clear the threshold.
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。 · 更新日はい
はい
The resolution source is the IMO Grand Challenge (https://imo-grand-challenge.github.io/) and the Artificial Intelligence Math Olympiad (AIMO, https://aimoprize.com/). If either source demonstrates that an AI has won the challenge/prize before the resolution date, this market will resolve to "Yes".
マーケット開始日: Nov 12, 2025, 5:08 PM ET
Resolver
0x65070BE91...The resolution source is the IMO Grand Challenge (https://imo-grand-challenge.github.io/) and the Artificial Intelligence Math Olympiad (AIMO, https://aimoprize.com/). If either source demonstrates that an AI has won the challenge/prize before the resolution date, this market will resolve to "Yes".
Resolver
0x65070BE91...Recent breakthroughs in large language model reasoning explain the 71% market-implied probability that an AI system secures an IMO gold medal in 2026. OpenAI’s experimental reasoning model and Google DeepMind’s Gemini Deep Think both reached the exact 35-out-of-42 gold cutoff at IMO 2025 by solving five of six problems under timed, closed-book conditions—advancing sharply from DeepMind’s 28-point silver-equivalent performance the prior year. Continued scaling, reinforcement learning on formal proofs, and benchmark convergence tracked in the Stanford AI Index support further gains before the July 2026 contest in Shanghai. Traders weigh the narrow historical margin against possible increases in problem difficulty or evaluation standards, yet view iterative releases from frontier labs as likely to clear the threshold.
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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