RAG: Enhancing AI with External Information Retrieval

Retrieval-Augmented Generation (RAG) is a method that enables AI systems to answer questions using information not included in their original training data. By retrieving relevant data from external sources like documents, databases, or knowledge bases, RAG provides this information as context to the AI model. This approach helps AI systems incorporate specialized or current information, reducing the likelihood of unsupported or fabricated answers.