The 77.5% market-implied probability favoring "No" stems from the substantial gap between today's frontier large language models and the extreme difficulty of FrontierMath, which features competition-level and research-grade mathematics problems far beyond standard benchmarks. Leading systems such as OpenAI's o1 series and Google's latest Gemini models currently achieve scores in the 30-50% range on comparable advanced math evaluations, with incremental gains driven primarily by scaling compute and reasoning techniques rather than transformative breakthroughs. Traders see limited evidence of the rapid capability jumps needed to reach 90% before 2027, given typical product cycles, data constraints, and the benchmark's focus on unsolved problems. Key upcoming catalysts include the next wave of model releases and any disclosed internal benchmarks from major AI labs that could shift this consensus.
Экспериментальная сводка, созданная ИИ на основе данных Polymarket. Это не является торговой рекомендацией и не влияет на то, как разрешается этот рынок. · ОбновленоМодель ИИ набирает ≥ 90% по FrontierMath Benchmark до 2027 года?
Да
$66,298 Объем
$66,298 Объем
Да
$66,298 Объем
$66,298 Объем
The primary resolution source will be information from EpochAI however a consensus of credible reporting may also be used.
Открытие рынка: Nov 12, 2025, 5:15 PM ET
Resolver
0x65070BE91...The primary resolution source will be information from EpochAI however a consensus of credible reporting may also be used.
Resolver
0x65070BE91...The 77.5% market-implied probability favoring "No" stems from the substantial gap between today's frontier large language models and the extreme difficulty of FrontierMath, which features competition-level and research-grade mathematics problems far beyond standard benchmarks. Leading systems such as OpenAI's o1 series and Google's latest Gemini models currently achieve scores in the 30-50% range on comparable advanced math evaluations, with incremental gains driven primarily by scaling compute and reasoning techniques rather than transformative breakthroughs. Traders see limited evidence of the rapid capability jumps needed to reach 90% before 2027, given typical product cycles, data constraints, and the benchmark's focus on unsolved problems. Key upcoming catalysts include the next wave of model releases and any disclosed internal benchmarks from major AI labs that could shift this consensus.
Экспериментальная сводка, созданная ИИ на основе данных Polymarket. Это не является торговой рекомендацией и не влияет на то, как разрешается этот рынок. · Обновлено
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