RAG
Retrieval-Augmented Generation is a technique that enhances LLM responses by retrieving relevant information from a knowledge base before generating an answer. RAG grounds AI responses in specific, verifiable data.
Definition
Retrieval-Augmented Generation is a technique that enhances LLM responses by retrieving relevant information from a knowledge base before generating an answer. RAG grounds AI responses in specific, verifiable data.
Related Terms
LLM
A Large Language Model is an AI model trained on large amounts of text data to understand and generate human-like language. LLMs power chatbots, content generation, summarization, and other language-based applications.
Vector Database
A database optimized for storing and querying high-dimensional vectors (embeddings). Vector databases enable semantic search and are commonly used in AI applications for similarity matching and RAG systems.