Ray
Scaling AI Workloads on TPUs with Ray Engineering teams are increasingly using Ray to scale AI workloads across diverse hardware, including GPUs and Cloud TPUs. While Ray provides a robust scaling framework, developers have traditionally needed to address the unique architectural and programming models of TPUs — including their distinct networking
PyTorch
PyTorch Conference 2025 — Advancing Open & Scalable AI Infrastructure At the 2025 PyTorch Conference, the PyTorch Foundation announced several major initiatives to advance open, scalable AI infrastructure. Key highlights included: * Ray joining as a hosted project * Introduction of PyTorch Monarch for simplified multi-machine AI workloads * Showcasing open research efforts such
Ray
# Large Model Intelligence｜Sharing ## Introduction In **RL**, **distillation**, and other AI workflows, multiple models often need to **cooperate** — managing computation, data communication, and process control. For example, in **PPO** (and its derivatives), you may need to coordinate up to *five types of modules*: - **Actor** - **Rollout** - **Ref** -