Unverified60% confidenceFactExact time
Large models have a knowledge cutoff date during training and cannot retain a company's internal private data.
2
Sources
60%
Confidence
Long-term
Relevance
9/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedFor pure generative models that rely on training data, brand information updates lag significantly due to the existence of a knowledge cutoff date, and recent content may not have been incorporated into training.78% similarVerifiedLarge language models have an inherent limitation of a knowledge cutoff date, meaning the model only contains information up to the cutoff date of its training data.78% similarUnverifiedLarge model training cycles span months to years, and researchers or test users often encounter early versions before the official release, giving rise to the phenomenon of unofficial information leaking out in advance.71% similarUnverifiedLarge model training cycles last from several months to over a year, with costs starting in the millions of dollars, and once training is complete the knowledge base is fixed and cannot be updated in real time.71% similarVerifiedThe knowledge cutoff of mainstream models often lags behind their release date by half a year to more than a year, because training data collection and cleaning takes several months.71% similar
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