Understanding Retrieval Augmented Generation (RAG)

This article explains how RAG enhances language models by retrieving relevant external documents at runtime. It outlines how separating the knowledge base from the model improves accuracy, adaptability, and enterprise applicability.

Key Insights

• Grounded Outputs: Combines retrieval with generation to produce fact-based responses.
• Updatable Knowledge: No need to retrain—just update the external data source.
• Scalable Design: Works with vector databases and is optimized for Intel hardware.
• Enterprise Focus: Suitable for real-world applications, especially where accuracy and efficiency matter.