The Rising Compute Costs of Reinforcement Learning Environments

The author argues that the most expensive part of reinforcement learning data is running tasks rather than writing them. Recent industry data shows that RL runs require thousands of GPUs over days, involve long rollouts taking hours, and consume hundreds of millions of tokens per attempt. Consequently, building an RL environment has evolved into a recurring compute expense for AI labs rather than a one-time dataset creation. Open article →