Goal Progress Image Generation for Adaptive User Motivation
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Solution Overview
Problem
Existing systems fail to effectively visualize and enhance user engagement with personal or financial goals by generating unique, goal-based imagery that adapts to the user's progress and preferences.
Innovation Solution
A platform utilizing a generative artificial intelligence (GenAI) model to create custom imagery based on user inputs and progress towards goals, dynamically filling or modifying the image over time based on user achievements and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static goal visualization is provided to users, then the system complexity is low, but user engagement and motivation remain insufficient
Solution Approach 1:
The patent implements dynamic goal visualization where images progressively fill in or change as users achieve milestones. The system transitions from static to dynamic visual representations, automatically updating images based on user progress data to maintain engagement without requiring complex manual intervention
Solution Approach 2:
The system uses generative AI to create customized visual representations of user goals. Instead of using generic stock images, the system generates unique, personalized images that reflect individual user aspirations, making the visualization more meaningful and engaging
2Adaptability or versatility
If generic stock images are used for goal visualization, then the manufacturing cost is low, but user personalization and engagement are insufficient
Solution Approach 1:
The system changes key parameters of image generation by using generative AI models that can create unique images based on user-specific inputs. The AI generates customized visualizations by varying parameters such as subject matter, style, and content based on user preferences and goal characteristics, achieving high personalization without manual image selection
Solution Approach 2:
The system enables self-service personalization where users provide minimal input (e.g., goal description, preferences) and the generative AI automatically creates customized images. This eliminates the need for manual image curation while providing highly personalized visualizations that adapt to individual user needs
3Ease of operation
If the complete goal image is displayed immediately, then user motivation is high initially, but the user's sense of progression and achievement is reduced
Solution Approach 1:
The patent segments the goal visualization into progressive stages. Instead of displaying the complete goal image immediately, the system divides the image into portions that progressively fill in or become visible as users achieve milestones. This creates a visual representation of progress that maintains motivation while reinforcing the timeline of achievement
Solution Approach 2:
The system implements periodic updates to the goal visualization based on user progress. Images are updated at specific intervals or milestone achievements, creating a rhythm of revelation that maintains engagement. This periodic disclosure of visual progress aligns with the user's journey and prevents premature satisfaction
Data Source
AI summary
An example operation may include one or more of establishing a network connection between the computing system and a data source, iteratively performing a sequence of steps comprising collecting user data from the data source, executing a generative artificial intelligence (GenAI) model on the collected user data to generate a different image segment, and filling in a different subset of pixels of an image with the generated image segment and display the partially-filled in image on a user interface.