Generative AI is powerful, but it hallucinates. To ground it in your enterprise data, you generally have two paths: Retrieval Augmented Generation (RAG) or Fine-Tuning.
The Case for RAG
For 90% of business use cases, RAG is the answer. It is cheaper, faster to implement, and allows for real-time data updates. Fine-tuning should be reserved for changing the *behavior* or *voice* of the model, not for teaching it new facts.
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#LLM#RAG#Architecture