Retrieval Augmented Generation (RAG) Explained: Understanding Key Concepts
Retrieval-augmented generation (RAG) is a technique that enhances text generation by retrieving and incorporating external knowledge.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
RAG, which stands for "Retrieval Augmented Generation," is a strategy in artificial intelligence where a large language model (LLM) retrieves relevant information from an external knowledge base (like a database or document collection) before generating a response to a user query, ensuring the response is more accurate and contextually relevant by ... See more
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Retrieval-Augmented Generation (RAG): A Technical AI Explainer
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You use state-of-the-art Retrieval Augmented Generation technology. How does that work?
Retrieval augmented generation (RAG) is an up and coming technique that addresses the pitfalls of large language models, particularly in the realm of AI hallucinations. It uses a mix of both good information retrieval and generative AI to generate answers which ... See more
Retrieval augmented generation (RAG) is an up and coming technique that addresses the pitfalls of large language models, particularly in the realm of AI hallucinations. It uses a mix of both good information retrieval and generative AI to generate answers which ... See more