Jack Parker-Holder recently joined DeepMind after his Ph.D. with Stephen Roberts at Oxford. Jack is interested in using reinforcement learning to train generally capable agents, especially via an open-ended learning process where environments can adapt to constantly challenge the agent's capabilities. Before doing his Ph.D., Jack worked for 7 years in finance at JP Morgan. In this episode, we chat about open-endedness, evolving agents and environments, online adaptation, offline learning with world models, and much more.
