Unverified50% confidenceFactExact time
The core working principle of large language models such as ChatGPT and Claude is next-token prediction based on massive training data.
1
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50%
Confidence
Long-term
Relevance
9/1/2026
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Related Claims
VerifiedLarge language models (LLMs) such as GPT and Claude are essentially probabilistic prediction systems trained on massive amounts of text data.80% 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.79% similarUnverifiedCurrent mainstream code generation models (including GPT-4, Claude, etc.) are essentially probabilistic models trained on code corpora, with a training objective of predicting the conditional probability of the next token rather than performing logical execution validation.73% similarVerifiedThe training objective of large language models is to predict the next most likely token, not to judge the truthfulness of information.72% similarUnverifiedBERT uses Masked Language Modeling as its pre-training task, while GPT uses Causal Language Modeling (predicting the next word) as its pre-training task.71% similar
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