Retrieval Augmented Generation (RAG)

What is RAG

RAG is a technique in natural language processing (NLP) that combines retrieval-based and generation-based methods.

• "reterival-based" means that, unlike purely generative models that create responses from scratch, retrieval-based systems rely on accessing existing data or knowledge to formulate their outputs
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Why RAG is needed

• LLM faces challenges
  • domain knowledge
  • hallucinations
  • training date cut off (outdated training set)
• These challenges maybe can be tackled by LLM Fine-tuning, but it's expensive to train the LLM