Scalable AI and reinforcement learning with Ray
February 18, 2020
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 Rays API and system architecture and sharing application examples, including several state-of-the-art distributed training, hyperparameter search, and RL algorithms.
