RAG

RAG stands for Retrieval-Augmented Generation, a machine learning (ML) approach that combines two key components: retrieval of relevant information/data from external sources and generation of natural language responses based on that data, typically through a language model like GPT. RAG is particularly useful for enhancing the capabilities of generative models by allowing them to access up-to-date, large-scale, and domain-specific information that's either beyond their training data or more detailed.

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