14–17 Oct 2019

Peter Schafhalter
Researcher, UC Berkeley RISELab

Peter Schafhalter is a first-year PhD student at UC Berkeley’s RISELab. His focus is AI systems, which involves writing software that makes AI run quickly, securely, explainably, and in a way that’s resilient to failures. He’s building an operating system for self-driving cars based on Ray.

Sessions

9:00–12:30 Tuesday, 15 October 2019

Location: Blenheim Room - Palace Suite

Scalable AI and reinforcement learning with Ray

Secondary topics: Machine Learning, Machine Learning tools, Reinforcement Learning

Edward Oakes (UC Berkeley Electrical Engineering & Computer Sciences), Peter Schafhalter (UC Berkeley RISELab), Kristian Hartikainen (University of Oxford)

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Edward Oakes, Peter Schafhalter, and Kristian Hartikainen take a deep dive into Ray, a new distributed execution framework for distributed AI applications developed by machine learning and systems researchers at RISELab, and explore Ray’s API and system architecture and sharing application examples, including several state-of-the-art distributed training, hyperparameter search, and RL algorithms. Read more.