As a federated learning researcher, I love to see articles introducing the public to the idea. But this article is really drawing a comparison between the fediverse and federated learning that doesn’t make sense (to me).
Beyond the fact that data and compute are stored on separate servers, they really aren’t similar. Federated learning avoids sharing data by sharing gradients or model updates with a central aggregator; raw data does not leave your device. The fediverse enables easy sharing of data between servers and avoids a central server.
Additionally, this article makes it seem like medical researchers were inspired by the fediverse, but the FedAvg paper was released in 2016—two years before ActivityPub was introduced in 2018.
As a federated learning researcher, I love to see articles introducing the public to the idea. But this article is really drawing a comparison between the fediverse and federated learning that doesn’t make sense (to me).
Beyond the fact that data and compute are stored on separate servers, they really aren’t similar. Federated learning avoids sharing data by sharing gradients or model updates with a central aggregator; raw data does not leave your device. The fediverse enables easy sharing of data between servers and avoids a central server.
Additionally, this article makes it seem like medical researchers were inspired by the fediverse, but the FedAvg paper was released in 2016—two years before ActivityPub was introduced in 2018.