Incognito mode for personalized machine-learned models

Abstract

The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a mode controller that allows a user to provide data input indicating whether to operate one or more applications on the device in a first collection mode (e.g., permission mode) for storing training examples or a second collection mode for (e.g., incognito mode) for not storing training examples. The training examples can be generated based on user interaction with the one or more applications and used to personalize one or more machine-learned models used by the application(s) by retraining the models using the user-specific training examples.