What is Retrieval-Augmented Generation (RAG)?

Retrieval-Augmented Generation (RAG) is a method that combines retrieval-based and generative models to enhance the capabilities of AI agents. In this approach, the agent retrieves relevant information from the KB and uses it to generate more accurate and informative responses. RAG leverages the strengths of both retrieval and generation, ensuring that the agent can provide precise and contextually appropriate answers.

Learn more: https://arxiv.org/abs/2005.11401