RL² capability: Fast reinforcement learning via slow reinforcement learning

AI Impact Summary

RL² introduces a capability that leverages slow reinforcement learning to accelerate fast RL tasks. For engineering teams, this implies changes to training pipelines to support meta-learning or bootstrapping fast adapters from slower, more data-efficient policies. It could reduce online data requirements and shorten iteration cycles, but will require careful evaluation to ensure transferability across tasks. Operationally, expect new orchestration between offline training jobs and online agents, with telemetry needed to validate meta-policy performance.