Technology9

Tag: AI knowledge retrieval

  • Implementing RAG Chunking in AI Models

    RAG (Retrieval-Augmented Generation) Chunking is a sophisticated technique employed in AI systems to enhance their ability to retrieve and generate contextually relevant responses from large corpora of data. By combining retrieval mechanisms with generative capabilities, RAG models overcome the limitations of traditional language models that rely solely on internalized knowledge. Chunking further optimizes this process…

  • RAG in AI

    Retrieval-Augmented Generation (RAG) is a powerful technique in natural language processing (NLP) that combines the strengths of both retrieval-based and generation-based models. RAG enhances the capabilities of AI by retrieving relevant information from large external datasets or knowledge sources and using that information to generate more accurate and contextually relevant responses. This approach has seen…