I am also interested in designing large-scale distributed systems for training machine learning applications. To that end, I led the development of a massively large-scale distributed reinforcement learning system that scales to TPU Pod and efficiently manages thousands of actors to solve complex, real-world tasks. As a case study, our team demonstrates how using this highly scalable system enables reinforcement learning to accomplish chip placement in ~an hour instead of days or weeks by human effort.