Large Language Models and Search — RAG Implementation

AI Impact Summary

The intersection of Large Language Models and Search is rapidly evolving, primarily driven by Retrieval-Augmented Generation (RAG). LLMs are being used to transform search queries, improve query understanding, and even construct more effective search indexes by summarizing long documents and extracting structured data. This integration is fundamentally changing how we access and utilize information, moving beyond simple keyword matching to semantic understanding and contextual reasoning.