Federated Learning - a podcast by Ben Jaffe and Katie Malone

As machine learning makes its way into more and more mobile devices, an interesting question presents itself: how can we have an algorithm learn from training data that's being supplied as users interact with the algorithm? In other words, how do we do machine learning when the training dataset is distributed across many devices, imbalanced, and the usage associated with any one user needs to be obscured somewhat to protect the privacy of that user? Enter Federated Learning, a set of related algorithms from Google that are designed to help out in exactly this scenario. If you've used keyboard shortcuts or autocomplete on an Android phone, chances are you've encountered Federated Learning even if you didn't know it.

Further episodes of Linear Digressions

Further podcasts by Ben Jaffe and Katie Malone

Website of Ben Jaffe and Katie Malone