In my presentation on Retrieval Augmented Generation (RAG), I will give a comprehensive overview of this key technology in the modern search landscape. RAG combines retrieval and generation models to deliver more accurate and contextualized search results. I'll explain the technical foundations, including vector representation, indexing, vector databases, and integration with large language models (LLMs).
I'll highlight recent advances in RAG-based search systems, such as intent detection, routing, and hallucination prevention. Using personal experiences, I'll show how RAG is used in different industries to optimize search processes and improve user experiences. I'll also discuss current challenges in implementing RAG systems and present innovative solutions.
Finally, I'll look at the future of RAG in search and potential developments that could revolutionize how we find and process information.

This is a brand new presentation. I am incorporating some of my own experience that I have gained in customer projects.