Generating a customized digital map via a generative machine-learned model

1 . A computing device for generating a customized digital map, comprising:

a display device;

one or more memories configured to store instructions; and

one or more processors configured to execute the instructions to perform operations, the operations comprising:

providing, for presentation to a user associated with the computing device, a digital map of a location which includes a plurality of graphical objects representing at least one of a point-of-interest, a geographic feature, or a path of travel;

receiving an input from a user relating to customizing features associated with at least one of the plurality of graphical objects;

based on receiving the input, implementing a generative machine-learned model to generate the customized digital map which depicts the location including the at least one of the plurality of graphical objects having the one or more customized features which are generated via the generative machine-learned model based on the input; and

providing the customized digital map for presentation via the display device.

2 . The computing device of claim 1 , wherein the generative machine- learned model is provided at the computing device.

3 . The computing device of claim 1 , wherein receiving the input from the user relating to customizing features comprises receiving a semantic description of a tile associated with the digital map which is to be generated.

4 . The computing device of claim 2 , wherein

the generative machine-learned model is configured to generate the customized digital map by rendering a portion of the customized digital map which depicts the location with the one or more customized features, and

the operations further comprise receiving a remaining portion of the customized digital map rendered by a server computing system.

5 . The computing device of claim 4 , wherein the operations further comprise implementing one or more machine-learned models to smooth and mix the portion of the customized digital map rendered by the computing device and the remaining portion of the customized digital map rendered by the server computing system.

6 . The computing device of claim 1 , wherein

the operations further comprise receiving, prior to receiving the input from the user, one or more default tiles associated with the location, and

the generative machine-learned model is configured to generate the customized digital map by referencing the one or more default tiles and the input to render the customized digital map which depicts the location with the one or more customized features.

7 . The computing device of claim 6 , wherein the one or more default tiles associated with the location are received at a predetermined time, in accordance with a predetermined condition, or in accordance with a predetermined event.

8 . The computing device of claim 7 , wherein

the predetermined time occurs periodically,

the predetermined condition is associated with network conditions of a network by which the one or more default tiles are received from a server computing system, and

the predetermined event is associated with a state of the computing device.

9 . The computing device of claim 1 , wherein the input indicates particular content which is to be omitted or reduced when generating the customized digital map, and

implementing the generative machine-learned model to generate the customized digital map comprises omitting or reducing the particular content when generating the customized digital map.

10 . The computing device of claim 1 , wherein

receiving the input from the user relating to customizing features comprises receiving a selection of a user interface element which corresponds to a customized map layer, and

the generative machine-learned model is implemented to generate the customized digital map based on the selection of the user interface element.

11 . The computing device of claim 10 , wherein the operations further comprise, based on the selection of the user interface element, generating the customized map layer based on at least one of information associated with the user or contextual information associated with the location.

12 . The computing device of claim 1 , wherein

the computing device comprises one or more databases configured to store a plurality of generative machine-learned models respectively associated with a plurality of different locations, and

the operations further comprise retrieving, from among the plurality of generative machine-learned models, the generative machine-learned model associated with the location.

13 . The computing device of claim 1 , wherein

the input comprises a text query that specifies one or more graphical objects to be associated with the location.

14 . The computing device of claim 1 , wherein

the generative machine-learned model has been fine-tuned based on a large parameter generative machine-learned model having a greater number of parameters than the generative machine-learned model.

15 . A computer-implemented method for generating a customized digital map, comprising:

providing, for presentation to a user associated with a computing device, a digital map of a location which includes a plurality of graphical objects representing at least one of a point-of- interest, a geographic feature, or a path of travel;

receiving, by the computing device, an input from a user relating to customizing features associated with at least one of the plurality of graphical objects;

based on receiving the input, implementing, by the computing device, a generative machine-learned model to generate the customized digital map which depicts the location including the at least one of the plurality of graphical objects having the one or more customized features which are generated via the generative machine-learned model based on the input; and

providing, by the computing device, the customized digital map for presentation via a display device.

16 . The computer-implemented method of claim 15 , wherein the generative machine-learned model is provided at the computing device.

17 . The computer-implemented method of claim 15 , wherein receiving the input from the user relating to customizing features comprises receiving a semantic description of a tile associated with the digital map which is to be generated.

18 . The computer-implemented method of claim 15 , wherein implementing the generative machine-learned model comprises:

rendering a portion of the customized digital map which depicts the location with the one or more customized features, and

receiving a remaining portion of the customized digital map rendered by a server computing system.

19 . The computer-implemented method of claim 15 , wherein the input indicates particular content which is to be omitted or reduced when the customized digital map is generated, and

implementing the generative machine-learned model comprises omitting or reducing the particular content when generating the customized digital map.

20 . A non-transitory computer readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations for generating a customized digital map, the operations comprising:

providing, for presentation to a user associated with a computing device, a digital map of a location which includes a plurality of graphical objects representing at least one of a point-of-interest, a geographic feature, or a path of travel;

receiving an input from a user relating to customizing features associated with at least one of the plurality of graphical objects;

based on receiving the input, implementing a generative machine-learned model to generate a customized digital map which depicts the location including the at least one of the plurality of graphical objects having the one or more customized features which are generated via the generative machine-learned model based on the input; and

providing the customized digital map for presentation via a display device.