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Knowledge cutoff

Knowledge cutoff (data di conoscenza)

The knowledge cutoff is the date beyond which a model has no information, because its training stopped there. It is like a printed encyclopedia: it holds everything known up to the day it went to press, but nothing that happened after. A model with an early-2024 cutoff will not know 2025 events, products or discoveries, even if it speaks about them confidently. It is not aging memory but a sharp boundary: past that threshold the model was simply never exposed to any data. It can still reason over what it knows, but it is no substitute for a fresh search.

Definition

The cutoff matters because it explains why an assistant errs on recent facts or invents plausible but false details. Techniques like RAG inject fresh information at request time to work around it.

Related terms

• RAG (Retrieval Augmented Generation)
• Grounding
• Retrieval
• Inference
• Context Window

More in AI Fundamentals

• LLM (Large Language Model)
• Token
• Context Window
• Temperature
• AI Hallucination
• Fine-tuning
• RAG (Retrieval Augmented Generation)
• Embedding

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