RAG is a technique that combines the power of large language models (LLMs) with information retrieval to provide more accurate and context-aware responses. It works by retrieving relevant information from a knowledge base and using it to generate a response, rather than relying solely on the LLM's internal knowledge. This makes RAG particularly useful for tasks that require access to specific or up-to-date information, such as question answering, chatbots, and content generation.
🗓 Date: 8 APRIL 2026
