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Miles, Slime, and Ray: Orchestrating the Post-Training Loop

2026-09-17

A practical architecture guide to the post-training loop, Ray as the control plane, and engineering weight synchronization.​​

Megatron LLM Post-Training Reinforcement Learning Ray SGLang
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  • Miles, Slime, and Ray: Orchestrating the Post-Training Loop
  • Hands on DSH
  • Dive into the Agent Loop
  • How uv Works: Python Environments, Dependency Resolution, and Caching
  • Cross-Attention in Multimodal AI: When One Stream Needs to Read Another
  • LFT and Topology Exports in InfiniBand: Diagnose the Fabric Without Expanding the Attack Surface
  • The Decision Engine Behind Fused Attention: How Transformer Engine Orchestrates cuDNN on Blackwell
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