English(EN) Poolside’s Laguna S 2.1 shows that smaller models can outperform larger ones by revising their work and persisting during long tasks. It solved a 49-year-old ma

小型 AI 模型 Laguna S 2.1 通过修改其工作超越大型竞争对手

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-23 14:30

Poolside 的 Laguna S 2.1 是一款较小的 AI 模型，已证明其能够超越大型模型。这是通过其在复杂、长期任务中进行自我修正和坚持的能力实现的。值得注意的是，该模型以不到十分之一美元的成本成功解决了一个 49 年的数学问题。 AI

影响证明了通过自我修正等先进技术，更小、更高效的模型可以实现最先进的性能。

排序理由 Frontier-lab 模型发布，系统卡 [lever_c 从 frontier_release 降级：ic=1 ai=1.0]

在 Mastodon — fosstodon.org 阅读 →

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Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] · 2026-07-23 14:30

Poolside’s Laguna S 2.1 shows that smaller models can outperform larger ones by revising their work and persisting during long tasks. It solved a 49-year-old ma

Poolside’s Laguna S 2.1 shows that smaller models can outperform larger ones by revising their work and persisting during long tasks. It solved a 49-year-old math problem for under 10 cents. # AI # Automation Source: The Decoder AI https:// the-decoder.com/poolsides-lagu na-s-2-1…

链接 the-decoder.com/poolsides-laguna-s-2-1-is…

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Poolside’s Laguna S 2.1 shows that smaller models can outperform larger ones by revising their work and persisting during long tasks. It solved a 49-year-old ma

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