Federated Learning: Training Models Without Moving the Data
For most of the last decade, the ML playbook was simple: collect data, ship it to a central server, train, deploy. It worked, but it came with baggage — transfer costs, latency, and a compliance headache every time “personal data” and “cloud” showed up in the same sentence. Federated Learning (FL) flips the pipeline. Instead… Read more
