RAG (Retrieval-Augmented Generation)

Retrieval-Augmented Generation (RAG) is an AI technique that combines language models with information retrieval systems. When a user asks a question, the system first retrieves relevant documents or data, then uses that retrieved information to generate a more accurate, up-to-date response. RAG is used by systems like Perplexity to provide current information beyond the model's training data. For GEO, understanding RAG explains how AI systems access and cite external sources, highlighting the importance of having authoritative, accessible content.