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NVIDIA's open-sourcing of OSMO addresses a critical fragmentation challenge in physical AI by unifying training, simulation, and hardware-in-the-loop testing into a single Kubernetes-native workflow. This tool enables robotics teams to define complex pipelines via YAML, allowing seamless routing of tasks across diverse compute tiers—from GB200 clusters to edge devices like Jetson AGX Thor—without custom infrastructure glue code. By standardizing the orchestration layer for this three-tier architecture, OSMO lowers the barrier to scaling robust physical AI models from data centers to real-world robots.
NVIDIA Open-Sources OSMO: One YAML Orchestrates Physical AI Training, Simulation, and Robot Testing
NVIDIA has open-sourced OSMO, the Kubernetes-native workflow orchestrator it uses internally for Project GR00T, Isaac Lab, and Isaac Sim. OSMO lets robotics teams define training, simulation, and hardware-in-the-loop tasks in a single YAML file and routes each one to the right compute tier, from GB200 clusters to Jetson AGX Thor devices, without infrastructure code. Apache-2.0 licensed, latest release 6.3.1. The post NVIDIA Open-Sources OSMO: One YAML Orchestrates Physical AI Training, Simulation, and Robot Testing appeared first on MarkTechPost.
Robot developers do not have one compute problem. They have 3. A policy is trained on GB200 or H100 clusters, tested in Isaac Sim on RTX GPUs, then validated on a Jetson mounted inside a real robot. Each tier has its own cluster, its own scheduler, and its own glue scripts. NVIDIA OSMO is NVIDIA’s answer to that fragmentation: an…
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