Sep 9–12, 2019

Philipp Moritz
UC Berkeley, University of California, Berkeley

Philipp Moritz is a PhD candidate in the Electrical Engineering and Computer Sciences (EECS) Department at the University of California, Berkeley, with broad interests in artificial intelligence, machine learning, and distributed systems. He’s a member of the Statistical AI Lab and the RISELab.

Sessions

1:30pm–5:00pm Tuesday, September 10, 2019

Location: 230 B

Building reinforcement learning models and AI applications with Ray

Implementing AI

Secondary topics: Machine Learning, Reinforcement Learning

Robert Nishihara (University of California, Berkeley), Philipp Moritz (University of California, Berkeley), Ion Stoica (University of California, Berkeley)

Building AI applications is hard, and building the next generation of AI applications, such as online and reinforcement learning (RL), is more challenging. Robert Nishihara, Philipp Moritz, and Ion Stoica lead a deep dive into Ray—a general-purpose framework for programming your cluster—its API, and system architecture and examine application examples, including state-of-the-art algorithms. Read more.