Unverified50% confidenceFactExact time
GPT-series models are optimized during training to maximize prediction accuracy (i.e., minimize perplexity), so their outputs tend toward high-probability word combinations.
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Long-term
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10/12/2026
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VerifiedThe GPT series adopts the autoregressive training objective of "predicting the next word".80% similarUnverifiedGPT 系列、Llama 等模型的核心能力绝大部分来自预训练而非后续微调阶段78% similarUnverifiedCurrent mainstream generative AI models (such as the GPT series, Claude, etc.) are essentially probabilistic prediction systems trained on massive amounts of text, and their output is a sampling of the most likely language sequences in the training distribution76% similarUnverifiedMainstream LLMs such as the GPT series use a decoder-only autoregressive architecture that generates text by predicting the probability distribution of the next token, with a training objective of minimizing cross-entropy loss.75% similar
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