retrieval-augmented generation
reh-TREE-vul AWG-men-ted JEN-uh-RAY-shun
rɪˈtriːvəl ˈɔːɡmɛntɪd ˌdʒɛnəˈreɪʃənListen
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Dictionary meaning
an AI architecture that combines a large language model's generative capabilities with a retrieval system that fetches relevant documents or passages from an external knowledge base at inference time, allowing the model to ground its responses in specific, up-to-date, or proprietary information rather than relying solely on knowledge encoded in its parameters during training; RAG significantly reduces hallucination rates for factual queries, enables LLMs to reference current events beyond their training cutoff, and allows organisations to deploy AI assistants over private document collections without the cost and risk of full fine-tuning
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