Endpoint device peer ecosystem for federated learning

Abstract

Aspects of the present disclosure relate to an endpoint device peer ecosystem for federated learning. Lower capability endpoint devices within the peer ecosystem (e.g., within a networked household or office) can collect data, such as user data, usage data, environmental data, etc., while being in communication with a local central device (e.g., a laptop). The local central device can receive a trained machine learning model from a remote computing system, and can either A) receive data collected by the lower capability endpoint devices, aggregate it, and retrain the model, or B) provide the model to the lower capability endpoint devices that individually retrain the model, with the local central device aggregating the retrained models. The local central device can then send the retrained and/or aggregated model back to the remote computing system, without exposing the data collected by the peer ecosystem.