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The use of AI RAG could help organizations develop better AI applications by combining language models with outside knowledge sources. First of all, the RAG model will have an opportunity to get current or specific information without relying solely on information used for training the model initially. Additionally, it allows businesses to connect AI applications with their internal sources of information, such as documents, databases, knowledge bases, etc. An additional benefit of using such a method is its flexibility since organizations will be able to update the knowledge source without having to retrain the whole language model. Thus, it can be used in creating applications like document-based question answering, customer service assistants, researching tools, and other types of internal knowledge sources.

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