Event-Driven AI: Supercharging ChatGPT with RAG and LangStream

Large Language Models like ChatGPT are fantastic for many NLP tasks but face challenges when it comes to real-time, up-to-date knowledge retrieval. Retrieval Augmented Generation (RAG) can effectively tackle this by pulling in external data for better, more context-aware responses.

This talk dives deep into using event-driven streaming through LangStream—an open-source library—to seamlessly integrate real-time data into generative AI applications like ChatGPT. Walk away with actionable insights on how to boost your GenAI applications using event streaming and RAG.

About Mary Grygleski

Mary is the VP of Global for the Western Hemisphere at the AI Collective, overseeing the health and growth of the community in North and Latin Americas.  She started her career in software engineering and has deep interest especially in distributed systems, which cover all spectrums in the computing world. She is also very passionate about tech advocacy and community work, and has been leading the Java users group in Chicago since 2015. She is recognized as a Java Champion and an Oracle ACE Associate.

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