RAG (Retrieval-Augmented Generation) is a technique that combines a large language models (LLMs) with a knowledge base (like a database or document collection) to provide more accurate and
relevant responses.
Analogy: A student using both their own knowledge and a textbook to answer a question.
Why It Matters: It addresses the limitations of LLMs by providing access to external information and improves the accuracy of their responses.