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Core concept · AI Search Infrastructure

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Definition

A knowledge cutoff is the date beyond which a language model’s training data does not extend. Events, content, or developments that occurred after the cutoff are not part of the model’s base knowledge and must be supplied through retrieval-augmented generation or real-time search. Knowledge cutoffs create predictable gaps in AI representations of brands and industries. A company that launched after a model’s cutoff, or that made significant changes after it, may be absent or inaccurately represented in that model’s base knowledge. Understanding cutoffs helps explain why a brand appears differently across different AI platforms — and why real-time retrieval optimization matters alongside training corpus presence.

Training corpus

RAG

Foundation model

Pre-training

AI Search Ecosystem

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