Verified75% confidenceOpinionExact time
Large language models are optimized to make code look correct rather than to meet current-stage requirements; they are fundamentally probability-statistical machines that predict the next most likely token and excel at reproducing high-frequency patterns from training data.
3
Sources
75%
Confidence
Long-term
Relevance
7/10/2026
First Seen
Sources
Related Claims
Unverified大语言模型的训练目标是最大化下一个Token的预测概率而非最大化代码安全性，这两个目标在数学上不等价80% similarUnverifiedLarge language models default to optimizing for plausibility rather than discriminability when generating options, because the training objective is to predict plausible words.79% similarVerifiedWhen input information is incomplete, large language models complete it based on the most common patterns in their training data, which is statistically called maximum likelihood estimation.79% similar
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