Retrieval Augmented Generation (RAG) in Machine Learning Explained

Imagine that your company has access to a powerful AI tool that can process vast amounts of data and extract significant conclusions, identify key information, and effectively summarize it. Such capabilities could significantly enhance the efficiency of your employees' work, allowing them to focus on the most valuable aspects of their job, rather than on time-consuming data processing. In this context, Retrieval Augmented Generation (RAG) opens new perspectives. RAG allows for the integration of AI models with specific, internal data …

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