Distributed in-browser deep learning for predictive pre-fetching
Abstract:
Techniques for distributed processing and pre-fetching content using an in-browser neural network model are disclosed herein. In some embodiments, a server transmits a neural network model to a client device, where the neural network model is stored a persistent store of a browser on the client device, and, during a networking session in which the browser on the client device is accessing a page of an online service, the client device predicts at least one link from a plurality of links on the page using the stored neural network model. The client device then fetches content associated with the predicted link(s) from a server of the online service prior to any selection of the predicted link(s) during the networking session.
Public/Granted literature
Information query
Patent Agency Ranking
0/0