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Reinforcement learning (RL) post-training is becoming a standard step in building capable language model agents. Models learn to reason and act across sequences of steps by generating trajectories, receiving rewards, and updating their policy based on outcomes. Running this at scale, across multiple nodes with hundreds of GPU-hours of rollouts per training run, requires persistent…

The flagship AirPods Pro 3 are still $50 off and the new AirPods 5 are now available, but Amazon is now offering a clearance deal on the now previous base model AirPods 4 down at $89 shipped. You will also find AirPods 4 with ANC down at $119 (just keep in mind you can get…

When you post-train a Mixture-of-Experts (MoE) model with Reinforcement Learning from Human Feedback (RLHF) or Group Relative Policy Optimization (GRPO) at scale, three simultaneous challenges emerge. The first requires coordinating heterogeneous compute for rollout generation and policy training. Second, sustaining high-throughput communication across hundreds of accelerators. And third, dynamically orchestrating every subsystem to keep them…