What Is Retrieval-Augmented Generation, aka RAG?
Retrieval-Augmented Generation (RAG) is a technique that combines retrieval and generation to enhance the performance of AI models in producing relevant and accurate responses. By leveraging external information sources, RAG improves the contextual understanding of generated content, making it particularly useful for applications requiring up-to-date information. This approach represents a significant advancement in the capabilities of AI systems in handling complex queries.
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