An FAQ on Reinforcement Learning Environments
Summary
An in-depth interview-based FAQ on reinforcement learning environments, outlining what RL environments and tasks are, how labs use them (RL, benchmarking, supervised fine-tuning), and the economics of the space. It highlights growth in enterprise workflows, concerns about reward hacking, and the bottlenecks of scaling task creation while maintaining quality. The piece also maps the landscape of startups, neolabs, and product-company partnerships shaping RL environment ecosystems.