feat(physical-ai/cosmos3): add Cosmos3 data flywheel reference architecture#76
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…ecture End-to-end CKS reference for NVIDIA Cosmos3: synthetic robotics-manipulation data generation -> SFT fine-tuning -> DCP->HF export -> Ray Serve -> marimo. Packaged as a small Helm chart (Chart.yaml, values.yaml, 4 templates) so every pipeline step is a single value entry. Default values.yaml renders to a no-op; enable steps individually with `--set steps.<name>.enabled=true` or via an overrides file. Replaces what would otherwise be ~23 nearly- identical Job manifests with one templated definition + per-step bash. Validated single-node on 8x RTX Pro 6000 Blackwell with VAST CSI. Includes the nine upstream workarounds the CKS path required (UPSTREAM_BUGS.md) as candidate PRs back to NVIDIA. A multi-node H100 SXM variant via cw-mpijob is in development on a separate branch. Lives under physical-ai/ so future Cosmos / robotics / world-foundation-model reference architectures can sit alongside. Signed-off-by: Nisha Nadkarni <nnadkarni@coreweave.com>
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Summary
End-to-end CKS reference architecture for NVIDIA Cosmos3: synthetic data gen → SFT → DCP→HF export → Ray Serve → marimo notebook.
Lives at
physical-ai/cosmos3/, packaged as a Helm chart. Every pipeline step is a singlevalues.yamlentry; enable the ones you want andhelm template . | kubectl apply -f -. Seephysical-ai/cosmos3/README.mdfor the walkthrough andUPSTREAM_BUGS.mdfor the nine upstream patches applied.Apply pattern
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