A method including receiving a spatial query on spatial data. The spatial query has a spatial query extent including a sub-portion of the spatial data. A projection type is selected for the spatial query. A framebuffer is created for the selected projection type. Vertex buffers are established to hold a geometry of the selected projection type. The vertex buffers are passed from a CPU to a GPU. A spatial geometry of the spatial query extent is rendered into the framebuffer by projecting feature vertex data for features that fall at least partly within the spatial query extent into the vertex buffers. Rendering generates rendered framebuffer pixel values. Pixel values of the rendered framebuffer are retrieved as bytes on the CPU. A spatial query result is processed that includes or uses the pixel values.

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for indicating location status. A computing device can receive a query from a user device, a current time, and a location for the user device. The computing device identifies results responsive to the query, including one or more business results that are each associated with a business location and operating hours. The computing device can select a subset of the business results as open results based on the operating hours of the business results, the current time, and travel times from the device location to the respective business locations. Data can be provided for a search engine results page that designates the subset of the business results as open results.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for indicating location status. A computing device can receive a query from a user device, a current time, and a location for the user device. The computing device identifies results responsive to the query, including one or more business results that are each associated with a business location and operating hours. The computing device can select a subset of the business results as open results based on the operating hours of the business results, the current time, and travel times from the device location to the respective business locations. Data can be provided for a search engine results page that designates the subset of the business results as open results.

A social media platform provides a map-based graphical user interface (GUI) with multiple geographically anchored icons that are selectable to trigger playback of respective galleries of ephemeral messages. Each of the plurality of location-based ephemeral galleries comprises media content contributed by multiple different users. The ephemeral galleries are compiled based on geotag data associated with respective ephemeral messages submitted by multiple users to be publicly viewable via the map-based GUI. Two or more different types of galleries are represented in the map-based GUI by different, visually distinct types of gallery icon.

A social media platform provides a map-based graphical user interface (GUI) with multiple geographically anchored icons that are selectable to trigger playback of respective galleries of ephemeral messages. Each of the plurality of location-based ephemeral galleries comprises media content contributed by multiple different users. The ephemeral galleries are compiled based on geotag data associated with respective ephemeral messages submitted by multiple users to be publicly viewable via the map-based GUI. Two or more different types of galleries are represented in the map-based GUI by different, visually distinct types of gallery icon.

System and methods enable vehicles to make ethical/empathetic driving decisions by using deep learning aided location intelligence. The systems and methods identify moral islands/complex driving scenarios where a complex ethical decision is required. A Generative Adversarial Network (GAN) is used to generate synthetic training data to capture varied ethically complex driving situations. Embodiments train a deep learning model (ETHNET) that is configured to output one or more driving decisions to be taken when a vehicle comes across an ethically complex driving situations in the real world.

System and methods enable vehicles to make ethical/empathetic driving decisions by using deep learning aided location intelligence. The systems and methods identify moral islands/complex driving scenarios where a complex ethical decision is required. A Generative Adversarial Network (GAN) is used to generate synthetic training data to capture varied ethically complex driving situations. Embodiments train a deep learning model (ETHNET) that is configured to output one or more driving decisions to be taken when a vehicle comes across an ethically complex driving situations in the real world.

A first stack running on a processor receives the transaction data, reference data, and context data. The reference data is independent of the transaction and of a user. The context data is associated with the user but is independent of the transaction. The first stack strips the transaction of derivable data to obtain stripped data. The derivable data includes data that can be derived from the stripped data, the context data, and the reference data. The derivable data can stream the stripped data to a global database available and redundant across multiple geographical regions. After the first stack fails, a second stack can resume the transaction by retrieving the stripped data from the global database, and retrieving the context data, and the reference data. The second stack can recreate the transaction data based on the stripped data, the context data, and the reference data, and can resume the transaction.