Dynamic GenAI Image for NFT Progress Tracking
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Solution Overview
Problem
Current technologies lack effective methods to visualize and achieve goals, particularly in the context of non-fungible tokens (NFTs), where users need interactive and dynamic representations to track progress and manage ownership.
Innovation Solution
A generative artificial intelligence (GenAI) model generates and modifies NFTs based on user interactions and account activity, allowing for dynamic evolution of images and transfer of image segments on a blockchain ledger, enabling users to visualize goal progress and manage ownership through smart contracts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static visual representation is used to represent goals, then the system is simple to implement, but it cannot effectively track progress or reflect user activity
Solution Approach 1:
The patent transforms static goal representations into dynamic visualizations that automatically update based on user activity and progress tracking. The system generates evolving images that reflect real-time account activity, feature activation, and goal achievement status, allowing the visual representation to adapt and change over time without requiring complex manual intervention
2Ease of operation
If NFT functionality is added to enable ownership management, then user engagement improves, but the system complexity increases
Solution Approach 1:
The patent introduces NFTs as intermediary digital assets that bridge user interaction and goal tracking. These NFT-containing images serve as mediators that encapsulate ownership information, progress data, and visual representations in a single transferable unit, simplifying user engagement while managing complexity through standardized blockchain-based ownership protocols
3Productivity
If the image is updated dynamically based on user activity, then goal tracking becomes effective, but processing requirements increase
Solution Approach 1:
The patent implements periodic updates of the visual representation based on triggered events such as goal milestone achievements, feature activations, or scheduled progress checks. Rather than continuous processing, the system updates images at meaningful intervals or upon specific triggers, reducing overall processing energy while maintaining effective goal tracking through timely visual feedback
Data Source
AI summary
An example operation may include one or more of generating an image of an object based on execution of a generative artificial intelligence (GenAI) model and displaying the image via a user interface of a software application, receiving inputs via the user interface, determining that a new feature of the software application has been activated by a user account of the software application based on the received inputs, and in response to the activation of the new feature, adding additional content to the image of the object based on execution of the GenAI model on information associated with the new feature and refreshing a display of the image of the object within the user interface of the software application.