Cassie, developed by engineers at Oregon State University is the first bipedal robot to use machine learning to control a running gait on outdoor terrain. It completed the five-kilometers run untethered around the campus in just over 53 minutes on a single charge. This includes 6.5 minutes of resets following 2 falls, which are due to overheated computer and being asked to execute a turn at too high a speed. It is the first time a robot has learned to walk and run, and successfully do that outside over human terrain. Since Cassie’s introduction in 2017, engineers and students have been exploring machine learning options for the robot. Cassie has knees that bend like an ostrich’s, and it can teach itself to run with a deep reinforcement learning algorithm. Running requires dynamic balancing – the ability to maintain balance while switching positions or otherwise being in motion – and Cassie has learned to make infinite subtle adjustments to stay upright while moving. In a related project, Cassie has become adept at walking up and down stairs. As for potential application, bipedal robots with intelligence have capabilities to help people in more scenarios beyond logistics work.