Verified80% confidenceFactTime unknown
Large language models are essentially stateless functions whose weights are fixed at inference time and do not learn over time.
8
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80%
Confidence
Long-term
Relevance
6/2/2026
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Unverified大语言模型本身是无状态的，其所有知识编码在训练后固定不变的神经网络权重中，单次推理完成后中间状态归零81% similarUnverifiedThe operation of large language models does not involve symbolic reasoning, world model construction, or goal-directed intent — only probability distributions encoded in weight matrices.79% similarUnverifiedLarge language models are responsible for thinking and decision-making but never directly execute actions themselves; the code outside the model is what actually executes the actions.79% similarUnverified大语言模型（LLM）在架构层面是无状态系统，每次推理调用是一次独立的前向传播计算，模型权重在推理阶段完全冻结79% similarVerifiedThe inference speed of large language models is constrained by the nature of autoregressive generation, which can only produce one token at a time and depends on all preceding tokens, making true parallelization impossible.78% similar
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