Chi Wang
Principal Researcher
Nouvelles
Introducing AutoGen Studio: A low-code interface for building multi-agent workflows
| Victor Dibia, Gagan Bansal, Jingya Chen, Suff Syed, Adam Fourney, Erkang (Eric) Zhu, Chi Wang, and Saleema Amershi
AutoGen Studio, built on Microsoft’s flexible open-source AutoGen framework for orchestrating AI agents, provides an intuitive user-friendly interface that enables developers to rapidly build, test, customize, and share multi-agent AI solutions—with little or no coding.
Research Focus: Week of June 10, 2024
In this issue: RELEVANCE automatically evaluates creative LLM responses; Recyclable vitrimer-based printed circuit boards; Lean Attention: Hardware-aware scalable attention mechanism; WaveCoder: a fine-tuned code LLM; New AutoGen training course.
Dans les actualités | Wired
Chatbot teamwork makes the AI dream work
Dans les actualités | Foundation Capital
The Promise of Multi-Agent AI
In this post, I share learnings from my conversation with Chi Wang, a principal researcher at Microsoft and the creator of AutoGen. Agents have been a cornerstone of human-computer interaction for decades, from the friendly Clippy of Microsoft Office fame…
Research Forum Episode 2: Transforming health care and the natural sciences, AI and society, and the evolution of foundational AI technologies
Research advances are driving real-world impact faster than ever. Episode 2 of Microsoft Research Forum explores how AI is transforming health care and the natural sciences, the intersection of AI and society, and the evolution of foundational AI technologies.
Dans les actualités | Anyscale Blog
Fast AutoML with FLAML + Ray Tune
FLAML is a lightweight Python library from Microsoft Research that finds accurate machine learning models in an efficient and economical way using cutting edge algorithms designed to be resource-efficient and easily parallelizable. FLAML can also utilize Ray Tune for distributed…
Dans les actualités | Aminer
2016 AMiner Most Influential Scholar Award in Data Mining
The AI 2000 Most Influential Scholar Annual List will name 2,000 of the world's top-cited research scholars from the fields of artificial intelligence over the next ten years (2020 - 2029).
Dans les actualités | Yelp
Grand Prize in Yelp Dataset Challenge
His 'Mining Quality Phrases from Massive Text Corpora' research was a Round Four winner.
Dans les actualités | ACM SIGKDD
SIGKDD Data Science/Data Mining PhD Dissertation Award Winner
ACM SIGKDD dissertation awards recognize outstanding work done by graduate students in the areas of data science, machine learning and data mining.