Beginner · NLP

Knowledge Cutoff

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. The specific date or point in time beyond which an LLM's training data does not contain information, limiting its understanding of recent events.

Technical Definition

The specific date or point in time beyond which an LLM's training data does not contain information, limiting its understanding of recent events.

How it works

The knowledge cutoff defines the temporal boundary of an LLM's understanding of the world. Information or events occurring after this date will not be directly known by the model, potentially leading to outdated or incorrect responses. Techniques like Retrieval Augmented Generation (RAG) are used to overcome this limitation by feeding current, external information to the model.

Related Concepts

• Retrieval-Augmented Generation (RAG) — A technique that enhances LLM responses by retrieving relevant documents from an external knowledge base before generating an answer.
• Hallucination — When an AI model generates confident, plausible-sounding content that is factually incorrect or fabricated.
• Prompt Engineering — The art of crafting effective input instructions to guide LLM behavior without changing model weights.