Unverified50% confidenceFactExact time
A model trained on two weeks of dry-season data degraded to near-random performance within one month of the wet season starting.
1
Sources
50%
Confidence
Long-term
Relevance
10/17/2026
First Seen
Sources
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Related Claims
VerifiedThe 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.70% similarUnverifiedAnthropic's peak compute consumption during model pre-training is under 200 megawatts, with a duration of approximately two months.67% similarUnverifiedFine-tuned models are based on existing open-source base models and use small domain-specific datasets, with training time typically ranging from hours to days.64% similarUnverifiedNewly disclosed vulnerabilities typically require a 6–18 month data collection and cleaning cycle before entering training data.64% similar
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