title: "生成AIの新たな可能性を開くRetrieval Augmented Generation (RAG)"

Retrieval-Augmented Generation (RAG) is a key technology for enabling generative AI within enterprises. It works by combining the generative capabilities of large language models with a retrieval component that pulls relevant, up-to-date information from a company's internal knowledge base. This process grounds the AI's responses in factual, specific context, overcoming the limitations of static training data and reducing the risk of hallucinations. By integrating information retrieval with content generation, RAG dramatically improves the accuracy and reliability of AI for business applications.