What's New in AutoGen?
TL;DR
- AutoGen has received tremendous interest and recognition.
- AutoGen has many exciting new features and ongoing research.
Five months have passed since the initial spinoff of AutoGen from FLAML. What have we learned since then? What are the milestones achieved? What's next?
Background
AutoGen was motivated by two big questions:
- What are future AI applications like?
- How do we empower every developer to build them?
Last year, I worked with my colleagues and collaborators from Penn State University and University of Washington, on a new multi-agent framework, to enable the next generation of applications powered by large language models. We have been building AutoGen, as a programming framework for agentic AI, just like PyTorch for deep learning. We developed AutoGen in an open source project FLAML: a fast library for AutoML and tuning. After a few studies like EcoOptiGen and MathChat, in August, we published a technical report about the multi-agent framework. In October, we moved AutoGen from FLAML to a standalone repo on GitHub, and published an updated technical report.