Unverified60% confidenceFactExact time
A model's knowledge is frozen at its training cutoff date, and the model has no way of knowing what happened after training was completed
2
Sources
60%
Confidence
Long-term
Relevance
10/5/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedNative large models suffer from a knowledge cutoff problem and will produce hallucinations when answering questions about content after their training date.78% similarVerifiedThe knowledge of traditional language models comes entirely from training data, with a hard limitation of a knowledge cutoff date, making it impossible to perceive events that occurred after training was completed.77% similarUnverifiedAfter training is complete, a large model's knowledge is fixed at the training cutoff and it cannot perceive new information after that point; Function Calling allows the model to call external functions to obtain additional capabilities or real-time data.76% similarUnverifiedNative large models are trained on publicly available data, have no independent reasoning ability, can only perform probabilistic generation based on learned knowledge, and have a knowledge cutoff date.74% similarUnverifiedThe parameter count of traditional large language models is fixed once training is complete, and the model's knowledge is frozen in the weight matrices72% similar
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