<ul><li>Federated Learning (FL) flips the traditional data pipeline by pushing the model to where the data lives on user devices or systems.</li><li>FL reduces privacy risk, regulatory friction, and transmission costs in training models.</li><li>FedOps, similar to DevOps and MLOps, is emerging as a tooling and workflow to monitor, audit, and scale federated systems.</li><li>The future of learning might rely on FL: training smarter without storing everything, learning together without sacrificing autonomy, and building AI ecosystems respecting privacy.</li></ul>

The Orientation of Federated learning

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