AI
RAG (Retrieval-Augmented Generation)
A technique that enhances LLM responses by retrieving relevant context from external knowledge sources.
Why it matters
- Grounds AI responses in actual data
- Reduces hallucinations and improves accuracy
- Enables AI to use private or recent information
When to use
- When AI needs access to specific knowledge bases
- For customer support chatbots with documentation
- When accuracy is more important than creativity
Common mistakes
- Poor chunking and embedding strategies
- Not evaluating retrieval quality
- Retrieving too much or too little context
Related terms
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