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That's true, but the data is only approximately represented in the weights.

Maybe it's better to have the AI only "reason", and somehow instantly access precise data.



Is this Retrieval Augmented Generation, or something different?


Yes, RAG, but have the model specifically optimzied for RAG.


What use cases will gain from this architecture?


Data processing, tool calling, agentic use. Those are also the main use-cases outside "chatting".




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