Goal-Based Image Generation With Adaptive Progress Visualization
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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, attributes, and progress towards goals, dynamically filling or modifying the image over time, and allowing user feedback for retraining.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a system generates custom imagery based on user goals using GenAI, then user engagement and motivation are enhanced, but system complexity and computational resources increase
Solution Approach 1:
The patent introduces an intermediary system that bridges user goals and visual representation through GenAI technology. This intermediary layer processes user input, manages the complex image generation process, and delivers simplified visual outputs, thereby enhancing user engagement while containing system complexity within a dedicated processing layer
Solution Approach 2:
The patent replaces traditional mechanical or manual methods of goal tracking and visualization with generative AI-based image synthesis. This substitution enables dynamic, adaptive visual representations that automatically update based on user progress, significantly improving ease of operation and user engagement compared to static or manually updated systems
2Adaptability or versatility
If the system dynamically fills or modifies images based on user progress, then the visual representation becomes more adaptive and motivating, but processing time and computational energy increase
Solution Approach 1:
The system implements partial action by selectively updating only the portions of images that correspond to changes in user progress, rather than regenerating entire images. This approach maintains image adaptability while significantly reducing computational energy requirements by focusing processing resources on specific modified regions
Solution Approach 2:
The system performs preliminary actions by pre-generating base image templates and pre-defining progress thresholds. This allows the system to quickly adapt images by overlaying or modifying predefined elements rather than performing complete image generation from scratch, thereby reducing real-time computational energy consumption while maintaining adaptability
3Ease of operation
If the system uses GenAI to create unique goal imagery, then user motivation increases, but the time required to generate and process images increases
Solution Approach 1:
The system performs preliminary actions by pre-training the GenAI model on goal-related imagery and pre-generating template images for common goal types. This preliminary preparation significantly reduces the time required to generate unique goal imagery during actual use, as the system can leverage pre-processed resources rather than creating everything from scratch
Solution Approach 2:
The system applies local quality by generating or modifying only the specific portions of images that are relevant to user goals and progress, rather than generating complete high-resolution images. This approach maintains motivational impact through targeted visual elements while reducing overall image generation time through selective processing
Data Source
AI summary
An example operation may include one or more of storing a generative artificial intelligence (GenAI) model configured to create images, displaying a plurality of prompts on a user interface of a software application, receiving an identifier of a goal of the user and attributes of the goal via the plurality of prompts on the user interface, executing the GenAI model on the identifier of the goal of the user and the attributes of the goal to generate a custom image of the goal for the user, and displaying the custom image of the goal via the user interface of the software application.