RL² capability adds fast reinforcement learning via slow RL meta-learning

AI Impact Summary

The new RL² capability introduces a meta-learning-based approach that enables fast reinforcement learning by leveraging insights from slow RL runs. This can reduce sample and wall-clock time for adapting policies to new tasks, improving experimentation throughput and time-to-value. Teams should plan for updated training pipelines to support cross-task transfer initialization, new metrics to monitor transfer quality, and potential shifts in compute patterns due to the mix of offline meta-learning and online fine-tuning.