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Artificial Intelligence (AI) systems, particularly generative models like GPT-4, have transformed numerous industries. However, these models sometimes struggle with accuracy, especially when generating outputs based on limited or outdated training data. Retrieval-Augmented Generation (RAG) is an innovative approach designed to address these challenges, combining the generative strengths of AI with the precision of retrieval systems. […]

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