What is Retrieval-Augmented Generation (RAG) in AWS ML systems?

RAG combines search-based retrieval with generative models to improve accuracy.

RAG retrieves relevant documents from vector databases (like OpenSearch or Pinecone) and feeds them into a generative model (like Bedrock LLMs) to produce grounded responses.