Event-Driven AI: Supercharging ChatGPT with RAG and LangStream

Thursday, 11:00 AM MDT

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 Grygleski

Mary is a Java Champion, and the AI Practice Lead at Callibrity, a consulting firm based in Ohio. She started as an engineer in Unix/C, then transitioned to Java around 2000 and has never looked back since then. After 20+ years of being a software engineer and technical architect, she discovered her true passion in developer and customer advocacy. Most recently she has serviced companies of various sizes such as IBM, US Cellular, Bank of America, Chicago Mercantile Exchange, in topic areas that included Java, GenAI, Streaming systems, Open source, Cloud and Distributed messaging systems. She is also a very active tech community leader outside of her day job. She is the President of the Chicago Java Users Group (CJUG), and the Chicago Chapter Co-Lead for AICamp.

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