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LLMs learn backwards, and the scaling hypothesis is bounded
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LLMs learn backwards, and the scaling hypothesis is bounded

大型語言模型反向學習，擴展假說存在上限

Discussion about how large language models learn in reverse order and why simply scaling up models may have fundamental limits. The post questions whether bigger always means better when it comes to AI model development.

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Keywords

language modelslearning mechanismsscaling hypothesismodel training

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