多年来，人工智能工程中普遍存在的假设是，更大的模型本质上更优越。这一观点正受到挑战，表明“为特定目的而设计”的方法可能比仅仅扩大模型规模更有效。 AI
影响 暗示了人工智能开发重点可能从单纯的模型规模转向更定制化、更高效的架构。
排序理由 该条目呈现了一篇讨论人工智能工程理念转变的观点文章。
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AI工程转变焦点：模型开发中的“适配优于蛮力”
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- 该条目呈现了一篇讨论人工智能工程理念转变的观点文章。
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报道来源 [1]
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过去几年，人工智能工程一直遵循一个出奇简单的假设：更大的模型就是更好的模型。https://hackernoon.com/the-slm-rev
For the last few years, AI engineering has operated under a surprisingly simple assumption: Bigger models are better models. https:// hackernoon.com/the-slm-revolut ion-taking-a-look-at-why-fit-beats-force # ai