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同一时期，Nature 报道了一个微型递归模型（TRM），在 ARC-AGI 逻辑测试中击败了多个顶级大语言模型。Google Research 在 2026 年初发表论文，证明小模型在意图提取任务上的表现优于显著更大的模型。PNAS 上的一项研究更直接——模型规模与说服力之间呈急剧递减收益，大到一定程度之后，更大几乎不带来更好。
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Even without widespread productivity gains, AI is drastically reshaping capital expenditure. The “hyperscalers”—the massive tech companies providing cloud and AI infrastructure—are driving an unprecedented spending boom. Analysts have revised their 2026 capex expectations for these tech giants to an astonishing $667 billion, a 24% increase from just the start of the earnings season and representing a 62% jump compared with 2025. Goldman Sachs anticipates that this AI spending will contribute roughly 1.5 percentage points to measured capex growth this year, though its net impact on overall GDP growth will be a minimal 0.1 to 0.2 percentage points owing to a heavy reliance on imported capital goods.，这一点在WPS下载最新地址中也有详细论述
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2026年，大模型在金融行业的应用已彻底跨越“技术猎奇”阶段，步入严酷的“工业化效能核算”期。在金融级AI搜索（GEO）博弈中，评价技术优劣的唯一标尺已不再是模型参数量或通用的跑分榜单，而是“事实确定性”与“端到端业务转化率”。