Abstract: The present disclosure relates to processing operations configured for intelligent management of a synchronization interval usable to synchronize data for an application/service between local data storage and distributed data storage. A classification prediction for a synchronization interval may be generated that is used as prediction for modifying the synchronization interval when a plurality of computing devices, linked to one or more user accounts, are used to access content. For instance, a suggestion is made as to whether a synchronization interval should be made faster, slower or even remain unchanged when a user account is accessing content. This may occur based on analysis of contextual factors described herein, thereby enabling a synchronization prediction component to make a best possible prediction for setting a synchronization interval. Artificial intelligence processing may be trained to generate the classification prediction for a synchronization interval.

Abstract: The present disclosure relates to processing operations configured for intelligent management of a synchronization interval usable to synchronize data for an application/service between local data storage and distributed data storage. A classification prediction for a synchronization interval may be generated that is used as prediction for modifying the synchronization interval when a plurality of computing devices, linked to one or more user accounts, are used to access content. For instance, a suggestion is made as to whether a synchronization interval should be made faster, slower or even remain unchanged when a user account is accessing content. This may occur based on analysis of contextual factors described herein, thereby enabling a synchronization prediction component to make a best possible prediction for setting a synchronization interval. Artificial intelligence processing may be trained to generate the classification prediction for a synchronization interval.