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M-RAG: Retrieval Augmented Generation Goes Global
- Capstanlqc 3y agoI have been reading opinion pieces in which the key message was that Retrieval Augmented Generation (RAG) is a dead end. I was not convinced. The combination of RAG, knowledge graphs and large language models (LLMs) is powerful and promising. And it is work. I think that is what scares many of my peers and colleagues: it is hard to convince management that leveraging AI means investing a lot of time and resources in building a specialist LLM that does a specific task well. So I am more supportive of approaches that take complexity into account and address the legwork that is required to fine-tune the models and embed principled design in them.