Dynamic generation of goals and images
An example operation may include one or more of establishing a network connection between a computing system and one or more external sources over a computer network, receiving a request from a user via a software application on a user device, collecting data about the user from the one or more external sources via the established network connection, executing a machine learning model on the collected data about the user to determine a goal of the user, and displaying an image of the goal via a user interface of the software application.
1 . A computing system comprising:
a memory; and
at least one processor coupled to the memory, the at least one processor configured to:
receive an input data total submitted from a user interface of a software application on a source device associated with a parent data structure,
collect data associated with the source device from at least one external source via a network connection,
execute an artificial intelligence (AI) model on the collected data and the input data total to determine a goal and to generate an image of the goal,
generate a dependent data structure exclusively for the goal, the dependent data structure depending from the parent data structure,
detect a ratio of progress towards the input data total based on a distribution of data from the parent data structure to the dependent data structure, and
fill-in a corresponding ratio of pixels of the image on the user interface based on execution of the AI model on the ratio of progress towards the input data total.
2 . The computing system of claim 1 , wherein the at least one processor is further configured to establish a secure connection with an external data source prior to collecting the data from the external data source.
3 . The computing system of claim 1 , wherein the at least one processor is configured to execute a generative artificial intelligence (GenAI) model on the goal to generate a customized image of the goal and incrementally display the customized image of the goal via the user interface.
4 . The computing system of claim 3 , wherein the at least one processor is further configured to train the GenAI model to generate the customized image of the goal based on a plurality of goal-based images, prior to receiving the input data total.
5 . The computing system of claim 1 , wherein the at least one processor is configured to collect historical data associated with the source device from the at least one external source, and build a profile based on attributes included in the historical data.
6 . The computing system of claim 5 , wherein the at least one processor is further configured to convert content from the profile into a vector, and input the vector to the AI model to determine the goal.
7 . The computing system of claim 1 , wherein the at least one processor is further configured to display at least one prompt via the user interface, receive a response to the at least one prompt on the user interface, and execute the AI model on the response and the at least one prompt to determine the goal.
8 . The computing system of claim 1 , wherein the image of goal comprises a set of pixels displayed therein, and the at least one processor is configured to fill-in a different subset of pixels among the set of pixels in response to a respective increment of progress towards the goal.
9 . The computing system of claim 1 , wherein the at least one processor is further configured to detect the input data total becoming farther away and remove pixels of the image based on the input data total becoming farther away.
10 . The computing system of claim 1 , wherein the at least one processor is configured to train the AI model to generate partial images that correspond to different subsets of pixels by executing the AI model on images and segments of the images.
11 . A method comprising:
receiving an input data total submitted from a user interface of a software application on a source device associated with a parent data structure;
collecting data associated with the source device from at least one external source via a network connection;
executing an artificial intelligence (AI) model on the collected data and the input data total to determine a goal and to generate an image of the goal;
generating a dependent data structure exclusively for the goal, the dependent data structure depending from the parent data structure,
detecting a ratio of progress towards the input data total based on a distribution of data from the parent data structure to the dependent data structure; and
filling-in a corresponding ratio of pixels of the image on the user interface based on execution of the AI model on the ratio of progress towards the input data total.
12 . The method of claim 11 , wherein the establishing comprises establishing a secure connection with an external data source prior to collecting the data from the external data source.
13 . The method of claim 11 , wherein the executing comprises executing a generative artificial intelligence (GenAI) model on the goal to generate a customized image of the goal and the incrementally filling-in comprises incrementally displaying the customized image of the goal via the user interface.
14 . The method of claim 13 , wherein the method further comprises training the GenAI model to generate the customized image of the goal based on a plurality of goal-based images, prior to receiving the input data total.
15 . The method of claim 13 , wherein the customized image of the goal comprises at least one of a hologram, a digital image, a video, and a cartoon.
16 . The method of claim 11 , wherein the collecting comprises collecting historical data associated with the source device from the at least one external source, and building a profile based on attributes included in the historical data.
17 . The method of claim 16 , wherein the method further comprises converting content from the profile into a vector, and inputting the vector to the AI model to determine the goal.
18 . The method of claim 11 , wherein the method further comprises displaying at least one prompt via the user interface, receiving a response to the at least one prompt on the user interface, and executing the AI model on the response and the at least one prompt to determine the goal.
19 . A non-transitory computer-readable medium comprising instructions stored therein which when executed by a processor cause the processor to perform:
receiving an input data total submitted from a user interface of a software application on a source device associated with a parent data structure;
collecting data associated with the source device from at least one external data source via a network connection;
executing an artificial intelligence (AI) model on the collected data and the input data total to determine a goal and generate an image of the goal;
generating a dependent data structure exclusively for the goal, the dependent data structure depending from the parent data structure,
detecting a ratio of progress towards the input data total based on a distribution of data from the parent data structure to the dependent data structure; and
filling-in a corresponding ratio of pixels of the image on the user interface based on execution of the AI model on the ratio of progress towards the input data total.
20 . The non-transitory computer-readable medium of claim 19 , wherein the executing comprises executing a generative artificial intelligence (GenAI) model on the goal to generate a customized image of the goal and the incrementally filling-in comprises incrementally displaying the customized image of the goal via the user interface of the software application.