Welcome + Opening Remarks
summary
Kubeflow claims to be a Kubernetes-native AI/ML platform that is portable to any certified Kubernetes distribution and already covers the full ML lifecycle with end-to-end pipelines and reusable components for data processing (Spark Operator), distributed training and fine‑tuning, model optimization, serving, notebooks and a new model registry. The ecosystem lists six projects under umbrella, emphasizes extensibility so teams take only needed pieces, runs weekly community calls, and is actively pursuing CNCF graduation plus proposals for a feature store, SDK integration and Helm‑based packaging.
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