Unverified50% confidenceFactExact time
LLMs are strictly speaking non-deterministic token generators; they do not understand causality, system boundaries or verification protocols.
1
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50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
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Related Claims
UnverifiedLLMs have no hard isolation mechanism between data and instructions and must rely on semantic understanding to distinguish the two, which is their vulnerability.76% similarUnverifiedLLM本质上是条件生成器，需要清晰的问题边界才能高效运作，不擅长发现值得解决的问题75% similarUnverifiedBecause LLM outputs are probabilistic, one cannot expect the model to proactively acknowledge errors; validation must have deterministic guarantees added at the system level.71% similarUnverifiedLLM本质上是无状态的文本预测系统，没有感知当前运行环境的原生能力70% similarUnverifiedThe model that generates code should not simultaneously serve as the validator of code security, because the systematic biases introduced by LLMs during the generation phase are equally present during the validation phase.69% similar
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