Abstract: 

In this demo-centric session, we'll start by showing you a generative AI app that brings our own data to an LLM, using Retrieval-Augmented Generation (RAG). We’ll then show you a systematic approach for developing, measuring, and improving generative AI applications, using Microsoft's PromptFlow. We'll evaluate the quality of our current application according to different metrics, we'll make changes to our logic accordingly, and we'll re-evaluate our changes to quantify the improvements made.

Bio: 

Bea Stollnitz is a developer advocate at Microsoft, focusing on the Azure Open AI Service, Azure ML and other AI/ML technologies. She has a background in scientific machine learning, applied math, and software engineering. She loves to share her machine learning knowledge with others on Medium and on her blog.