RESEARCH

Open-source hardware and software for evaluating reinforcement learning algorithms on physical Atari consoles.

Presented at Upper Bound 2025, this talk explores an alternative path toward artificial general intelligence centered on reinforcement learning, online adaptation, and learning from streams of experience rather than static datasets.

Topics include Physical Atari, continual learning, catastrophic forgetting, transfer learning, latency, embodiment, exploration, function approximation, and the challenges of building agents that learn efficiently over long time horizons.