Verified65% confidenceFactExact time
The GPT series of models are trained on trillion-scale text data through a self-supervised task of predicting the next token.
3
Sources
65%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
不禁用AI：师生共建课堂契约的教学实验与启示
hackernewshackernews7/3/2026
Related Claims
UnverifiedSelf-supervised learning is the training foundation of the GPT series of models, which learn by predicting the next masked word in text.84% similarVerifiedThe GPT series adopts the autoregressive training objective of "predicting the next word".81% similarUnverifiedGPT系列底层架构基于自回归语言模型，通过逐Token预测的方式生成文本81% similarUnverifiedGPT-type models use billions of parameters to memorize the statistical patterns of the entire corpus of internet text.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 distribution78% similar
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