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We're Learning Backwards: LLMs build intelligence in reverse, and the Scaling Hypothesis is bounded
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We're Learning Backwards: LLMs build intelligence in reverse, and the Scaling Hypothesis is bounded

我們學習方向反了：大型語言模型以相反的方式構建智慧，擴展假說存在上限

A discussion exploring how large language models may develop intelligence through reverse processes, and questioning whether the scaling hypothesis—the idea that simply making models bigger leads to better performance—has fundamental limits that we're approaching.

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Keywords

large language modelsscaling hypothesisintelligence developmentreverse learningneural networks

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