What Is Retrieval-Augmented Generation (RAG) in AI?
Learn what Retrieval-Augmented Generation (RAG) is: an AI technique that breaks documents into chunks and retrieves relevant data to give LLMs accurate context.
Question
What is Retrieval Augmented Generation (RAG)?
A. A system for generating random text outputs
B. A technique that breaks large documents into chunks and retrieves only relevant pieces when answering questions
C. A way to increase the processing speed of AI models
D. A method for training large language models from scratch
Answer
B. A technique that breaks large documents into chunks and retrieves only relevant pieces when answering questions
Explanation
Retrieval-Augmented Generation (RAG) is an AI framework that enhances Large Language Models (LLMs) by connecting them to external knowledge bases. Instead of relying solely on static training data, a RAG system processes large external documents by breaking them into smaller chunks, storing them in a vector database, and retrieving only the most semantically relevant pieces of information to provide context to the LLM when answering a specific user query.