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Unverified80% confidenceOpinionExact time

LLMs do not understand knowledge the way humans do, but capture complex probability distributions in text through billions or trillions of parameters

1

Sources

80%

Confidence

Long-term

Relevance

8/2/2026

First Seen

Sources

From Medieval Grimoires to AI: Humanity's Thousand-Year Quest for Instant Knowledge

Related Entities

Large Language Modelsconcept

Related Claims

UnverifiedLLM的知识以分布式方式编码于数十亿参数的权重矩阵中，而非以符号化的逻辑规则存储73% similar VerifiedLLM本质上是基于海量文本训练的概率分布系统，每次输出都是对下一个最可能词元的采样，而非基于真实世界知识的检索与推理73% similar UnverifiedWhen LLMs are scaled to tens of billions or even trillions of parameters, emergent abilities such as reasoning, translation, and code generation arise.70% similar VerifiedLLM的生成机制是基于概率的文本预测，而非真正'理解'代码语义69% similar Verified大模型的核心原理是概率文字接龙，输出结果是概率采样而非确定性输出65% similar

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