Abstract: 
Large AI Models demonstrate promising capabilities and open numerous possibilities for innovative applications. What are future AI applications like and how do we empower every developer to build them? AutoGen is a pioneering attempt to address this question as a generic multi-agent conversation framework. This talk will explore the core functionalities and key concepts of AutoGen, explain how it can be used to simplify and unify the implementation of complex AI workflows with integration of models, tools, and human inputs, and illustrate how it is applied across a broad spectrum of tasks and industries, paving the way for next-generation AI applications.
 

Bio:
Chi Wang is a principal researcher in Microsoft Research. He has worked on large language model and AI frameworks, automated machine learning, machine learning for systems, scalable solutions for data science and data analytics, and knowledge mining from text data and graph data (with a SIGKDD Data Science/Data Mining PhD Dissertation Award). Chi is the creator of AutoGen, a popular and rapidly growing open-source framework for enabling next-gen AI applications. Chi is the creator of FLAML, a fast open-source library for AutoML & tuning used widely inside and outside Microsoft. Chi has a PhD in Computer Science from University of Illinois at Urbana-Champaign, and a BS in Computer Science from Tsinghua University.