Google tests a collaborative approach to machine learning - SiliconANGLE

Google Inc. is plotting to speed up machine learning with a new "federated learning" approach that sees training data spread across millions of individual Android devices. The approach is different from traditional machine learning techniques, where datasets are distributed across multiple cloud servers. It enables machine learning models to be trained from actual users' interactions with their Android devices, Google researchers Daniel Ramage and Brendan McMahan said in the company's research blog. The method also allows models to be trained faster, and with less power consumption than traditional methods. In addition, users can benefit immediately from any improvements made to the machine learning models.