Abstract: Methods, non-transitory machine-readable mediums, and system to provide historical positioning information are described. In an embodiment, a device detects one or more conditions in user contextual data that trigger collection of a set of historical positions for a lookback window, the device receives at least one historical position from the set of historical positions for the lookback window, the device classifies the at least one historical position based on one or more features as a candidate location for a backtrack route, and the device determines to provide the at least one historical position as part of the lookback window based on the classification.

Abstract: Embodiments described herein provide for a system, a non-transitory machine-readable medium, and methods to provide location services. In an embodiment, a method provides receiving a request to display at least one waypoint user interface object on an electronic device user interface, sending a request to duty cycle waypoint information requests for the at least one waypoint user interface object, wherein the duty cycle has a first time period based on a motion classification, and where a waypoint information request comprises at least one of a positioning request or a bearing request, upon expiration of the first time period, performing at least one of determining not to wake an application processor based on receipt of waypoint information from another application during the time period, or coalescing the waypoint information request with other process requests, and receiving the waypoint information and displaying the received waypoint information on the electronic device user interface.

Abstract: One embodiment provides for an electronic device, comprising a non-transitory machine-readable medium to store instructions, one or more processors to execute the instructions, and a memory coupled to the one or more processors. The memory can be configured to store a set of synchronization data associated with interaction between the electronic device and one or more applications and instructions which, when executed by the one or more processors, configure the one or more processors to retrieve a set of synchronization data to be transmitted from the electronic device to select a transport channel from one of a peer-to-peer channel or a network-based channel and transmit the set of synchronization data from the electronic device to one or more remote devices via the selected transport channel.

Abstract: One embodiment provides for an electronic device, comprising a non-transitory machine-readable medium to store instructions, one or more processors to execute the instructions, and a memory coupled to the one or more processors. The memory can be configured to store a set of synchronization data associated with interaction between the electronic device and one or more applications and instructions which, when executed by the one or more processors, configure the one or more processors to retrieve a set of synchronization data to be transmitted from the electronic device to select a transport channel from one of a peer-to-peer channel or a network-based channel and transmit the set of synchronization data from the electronic device to one or more remote devices via the selected transport channel.

Abstract: A system for determining relevant information based on user interactions may include a processor configured to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more application including applications local to the device that are stored in the memory and applications external to the device. The processor may be further configured to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features. The processor may be further configured to sort one or more UI elements based on a ranking of the relevance scores. The processor may be further configured to provide, as output, the one or more UI elements based at least in part on the ranking.

Abstract: A system for determining relevant information based on user interactions may include a processor configured to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more application including applications local to the device that are stored in the memory and applications external to the device. The processor may be further configured to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features. The processor may be further configured to sort one or more UI elements based on a ranking of the relevance scores. The processor may be further configured to provide, as output, the one or more UI elements based at least in part on the ranking.

Abstract: One embodiment provides for an electronic device, comprising a non-transitory machine-readable medium to store instructions, one or more processors to execute the instructions, and a memory coupled to the one or more processors. The memory can be configured to store a set of synchronization data associated with interaction between the electronic device and one or more applications and instructions which, when executed by the one or more processors, configure the one or more processors to retrieve a set of synchronization data to be transmitted from the electronic device to select a transport channel from one of a peer-to-peer channel or a network-based channel and transmit the set of synchronization data from the electronic device to one or more remote devices via the selected transport channel.

Abstract: A system for determining relevant information based on user interactions may include a processor configured to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more application including applications local to the device that are stored in the memory and applications external to the device. The processor may be further configured to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features. The processor may be further configured to sort one or more UI elements based on a ranking of the relevance scores. The processor may be further configured to provide, as output, the one or more UI elements based at least in part on the ranking.