
As technology is developing rapidly companies always look for new ways to use AI tech to make better choices and work more. One new technology that’s grabbing attention in the tech world is Retrieval Augmented Generation (RAG). In this post, we’ll look at what RAG is, how people use it, and why it’s providing a new aspect for companies in many fields.
Retrieval Augmented Generation (RAG) addresses several critical challenges in AI and natural language processing:
1.
Hallucination and Accuracy: Traditional large language models can sometimes generate reasonable sounding but incorrect information, a term known as “hallucination.” RAG mitigates this by grounding responses in verified, external data sources, significantly improving accuracy.
2.
Hallucination and Accuracy: Traditional large language models can sometimes generate reasonable sounding but incorrect information, a term known as “hallucination.” RAG mitigates this by grounding responses in verified, external data sources, significantly improving accuracy.
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