What does RAG stand for in AI

What does RAG stand for in AI refers to Retrieval-Augmented Generation, an acronym that defines a fundamental artificial intelligence methodology combining external knowledge retrieval with generative language model capabilities. RAG stands for three interconnected components: Retrieval involves dynamically searching and accessing relevant information from external databases, documents, and knowledge repositories using semantic similarity algorithms; Augmented signifies enhancing the AI model’s context by incorporating retrieved information before response generation; Generation encompasses producing informed, accurate outputs based on both the model’s pre-trained knowledge and the retrieved external context. This acronym represents AI systems that overcome traditional limitations including knowledge cutoffs, hallucinations, and outdated information by grounding responses in current, verifiable sources. RAG stands for enhanced accuracy, improved factual precision, and access to real-time information through technical implementation involving vector embeddings, semantic search, and context integration mechanisms essential for enterprise AI applications.