What is Retrieval-Augmented Generation (RAG), and how do I use it in my company?

This week, we take a closer look at Retrieval-Augmented Generation (RAG), an AI architecture that combines generative AI models with external knowledge bases. RAG improves accuracy, scalability and cost efficiency by providing access to up-to-date, domain-specific data. This reduces the risk of misinformation (“hallucinations”) and increases user confidence. We explain the components of a RAG system (knowledge base, retriever, integration and generator layer), its process and how it can be used in companies and organizations—a must-read for leaders interested in AI.

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