Artificial Intelligence Conference San Francisco 99/114
Ion Stoica
Professor, UC Berkeley
Ion Stoica is a professor in the EECS Department at the University of California, Berkeley, where he does research on cloud computing and networked computer systems. Ion’s previous work includ es dynamic packet state, chord DHT, internet indirection infrastructure (i3), declarative networks, and large-scale systems, including Apache Spark, Apache Mesos, and Alluxio. He is the cofounder of Databricks—a startup to commercialize Apache Spark—and Conviva—a startup to commercialize technologies for large-scale video distribution. Ion is an ACM fellow and has received numerous awards, including inclusion in the SIGOPS Hall of Fame (2015), the SIGCOMM Test of Time Award (2011), and the ACM doctoral dissertation award (2001).
Sessions
1:30pm–5:00pm Monday, September 18, 2017
Building reinforcement learning applications with Ray
Implementing AI
Location: Yosemite BC
Location: Yosemite BC
Level: Intermediate
Secondary topics: Algorithms, Open source, Transportation and autonomous vehicles
Ion Stoica (UC Berkeley), Robert Nishihara (UC Berkeley), Philipp Moritz (UC Berkeley)
Ion Stoica, Robert Nishihara, and Philipp Moritz lead a deep dive into Ray, a new distributed execution framework for reinforcement learning applications, walking you through Ray’s API and system architecture and sharing application examples, including several state-of-the art RL algorithms.
11:55am–12:35pm Tuesday, September 19, 2017
Ray: A distributed execution framework for reinforcement learning applications
Implementing AI
Location: Yosemite BC
Location: Yosemite BC
Level: Intermediate
Secondary topics: Data science and AI, Tools and frameworks
Ion Stoica (UC Berkeley)
Ion Stoica offers an overview of Ray, a new distributed execution framework for reinforcement learning applications, walking you through Ray’s API and system architecture and sharing application examples, including several state-of-the art RL algorithms.
