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Deep Dive into Retrieval-Augmented Generation (RAG)

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Retrieval-Augmented Generation (RAG) is a powerful technique that combines the strengths of large language models (LLMs) with external knowledge retrieval.

In this post, we’ll explore:

  1. What is RAG? - The core concepts and architecture.
  2. Why use RAG? - Addressing limitations of standard LLMs like hallucination and outdated knowledge.
  3. How it works: - Vector databases, embeddings, and prompt engineering.
  4. Application: - A look at how these principles were applied in the Medicare RAG project.

More details to come…
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