Retrieval-Augmented Generation (RAG)
RAG is a technique used by AI models to retrieve fresh, external data (from the web or a database) to augment their internal training data before generating an answer.
RAG is a technique used by AI models to retrieve fresh, external data (from the web or a database) to augment their internal training data before generating an answer.
The Context
Search engines like Perplexity and Bing Chat use RAG to provide real-time answers with citations, rather than relying solely on pre-trained knowledge.
Why It Matters for AI Search
Optimizing for RAG means ensuring your content is easily retrievable and formatted for extraction (e.g., using lists, tables, and direct answers).
Related Concepts
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