Exploring Retrieval-Augmented Generation and Its Business Benefits
One of the challenges of generative AI is that a model may not always possess the latest information or have access to private organizational documents. Retrieval-Augmented Generation, commonly known as RAG, addresses this challenge by connecting a language model to external information sources. Rather than relying entirely on information learned during training, a RAG-based system searches...
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