GenAI Goal Image Generation Platform

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Solution Overview

Problem

Existing technologies lack an effective method to visually depict and motivate users towards achieving their goals, as people tend to focus on the most visible or nearest goal while neglecting others.

Innovation Solution

A platform that utilizes a generative artificial intelligence (GenAI) model to create custom images of users' goals based on input prompts, allowing users to visualize their objectives and track progress dynamically.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If a platform uses GenAI to create custom images of user goals, then user motivation and goal achievement chances are enhanced, but the device complexity and computational resources required increase

Engineering Contradiction:

Improvegoal achievement probabilityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent introduces a platform as an intermediary between users and their goals, using GenAI models to generate visual representations. This intermediary handles the complex computational tasks of image generation from text prompts, user data, and goal attributes, while presenting simplified visual outputs to users that enhance motivation without requiring users to directly manage the underlying system complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system automatically collects user data from external sources (social media, calendars, to-do lists) and uses GenAI to generate goal images without requiring manual user input for each goal visualization. The platform self-manages the complex processes of data integration, prompt engineering, and image generation, reducing the operational burden on users while maintaining high motivation benefits

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If the system collects data from multiple external sources to personalize goal images, then the adaptability and personalization improve, but the loss of time for data collection and processing increases

Engineering Contradiction:

Improvepersonalization capabilityVSAvoiddata processing time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-collecting and storing user data from external sources (social media accounts, calendar events, to-do lists) before goal image generation is needed. This advance data gathering and processing allows the system to quickly generate personalized goal images when requested, reducing the perceived time delay for users while maintaining high personalization quality

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces manual user input mechanisms with automated data collection systems that programmatically extract information from external sources. This substitution of automated computational processes for manual user actions significantly reduces the time required to gather personalization data, enabling the system to adapt to individual users without requiring extensive user effort or time investment

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If the platform generates multiple custom images for different goals, then the visual motivation coverage increases, but the computational resources and processing time required increase

Engineering Contradiction:

Improvegoal coverageVSAvoidcomputational energy

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The system segments the goal image generation process by creating individual custom images for different goal categories (financial goals, personal goals, educational goals, health goals). Each goal receives its own specialized visual representation generated by the GenAI model, allowing comprehensive coverage of multiple user objectives while managing computational resources through targeted, focused image generation rather than attempting to create a single comprehensive image

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The platform implements partial action by generating goal images selectively based on user needs and priorities. The system can generate images for the most important or nearest goals first, providing immediate motivational benefit, while optionally generating additional images for other goals as computational resources allow. This approach ensures adequate goal coverage without requiring exhaustive generation of all possible goal images simultaneously, optimizing the balance between versatility and energy consumption

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20250078345A1Generating additional images from previously generated images

Publication Date: 2025.03.06 THE TORONTO DOMINION BANK

AI summary

An example operation may include one or more of training a generative artificial intelligence (GenAI) model to generate images based on user data using a dataset of images, executing the GenAI model based on input data from a user interface of a software application to generate an image corresponding to the input data, and displaying the image via a user interface of a software application, receiving feedback about the image via the user interface; andretraining the GenAI model based on the generated image and the received feedback about the image via the user interface.