Tuesday, August 23
11:30 AM - 12:00 PM
Ray AI Runtime (AIR) is an open-source toolkit for building end-to-end machine learning applications. By leveraging Ray and its library ecosystem, Ray AIR brings scalability and programmability to ML platforms. In this session, we'll be exploring Ray AIR functionality and features, along with some benchmarks demonstrating its utility.
Richard Liaw is an engineering manager at Anyscale, where he leads a team in building open source libraries on top of Ray. He is on leave from the PhD program at UC Berkeley, where he worked at the RISELab advised by Ion Stoica, Joseph Gonzalez, and Ken Goldberg. In his time in the PhD program, he was part of the Ray team, building scalable ML libraries on top of Ray.
Eric Liang is a PhD candidate at UC Berkeley studying the intersection of systems and machine learning. Before grad school, he spent several years working on distributed systems at Google and Databricks. He currently leads Ray Core and RLlib development at Anyscale.
Come connect with the global community of thinkers and disruptors who are building and deploying the next generation of AI and ML applications.Save your spot