Verified65% confidenceFactExact time
Large language models generate content based on predicting the next most likely token word by word, rather than retrieving answers from a factual database.
3
Sources
65%
Confidence
Long-term
Relevance
7/15/2026
First Seen
Sources
AI欺骗行为：为何无需意识同样危险
Related Claims
VerifiedThe training objective of large language models is to predict the next most likely token, not to judge the truthfulness of information.82% similarVerifiedWhen generating each token, large language models perform probabilistic sampling over all possible next words in the vocabulary, rather than deterministically selecting a unique answer.82% similarUnverifiedLarge language models such as ChatGPT work by making probabilistic predictions based on massive text data, essentially predicting the next most likely word rather than truly understanding causal relationships.78% similarVerifiedThe essence of large language models is learning the conditional probability distribution of what the next word is given the preceding text78% similar
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