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Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK
Richard Liaw

Richard Liaw
Graduate student, UC Berkeley RISELab

Richard Liaw is a PhD student in the Berkeley Artificial Intelligence Research (BAIR) Lab and RISELab at UC Berkeley working with Joseph Gonzalez, Ion Stoica, and Ken Goldberg. He’s worked on a variety of different areas, ranging from robotics to reinforcement learning to distributed systems. He’s working on Ray, a distributed execution engine for AI applications; RLlib, a scalable reinforcement learning library; and Tune, a distributed framework for model training.

Sessions

13:30–17:00 Tuesday, 9 October 2018
Building reinforcement learning applications with Ray
Location: Blenheim Room - Palace Suite
Secondary topics:  Reinforcement Learning, Text, Language, and Speech
Richard Liaw (UC Berkeley RISELab), Eric Liang (University of California, Berkeley, RISELab)
Ion Stoica, Robert Nishihara, Richard Liaw, Eric Liang, 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. Read more.