Expired65% confidenceFactTime unknown
Large language models have inherent non-determinism — even with identical prompt inputs, the model may return results that differ in format, content, or even logic at different times.
3
Sources
65%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
Sources
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
bilibili朱老师AI课堂
Related Claims
Unverified大语言模型本质上是概率性的，相同的输入可能产生不同的输出，这与传统软件的确定性行为截然不同84% similarVerifiedLarge language models are essentially probabilistic text generation systems, lacking the ability to verify external systems in real time, and produce hallucinations when input documents are ambiguous or incomplete.79% similarUnverifiedBecause the output of large language models is non-deterministic, the same input may produce different outputs, making it difficult to cover all edge cases with unit tests alone.79% similarUnverifiedA recent study found that large language models do not consistently follow Bayesian rules, and their probabilistic beliefs exhibit internal inconsistencies.79% similarUnverifiedLarge language models have a sycophancy characteristic, tending to organize their output according to the inclination of the prompt rather than reflecting factual truth.77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/59537API
curl https://kongchang.com/api/v1/knowledge/claims/59537MCP
get_claim(id=59537)