Generative AI GUI Mapping for Dynamic Content Placement

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Solution Overview

Problem

Existing wealth management systems lack the ability to dynamically adapt to user preferences and integrate external data sources effectively, leading to suboptimal user interface experiences and missed opportunities for personalized content display.

Innovation Solution

Implementing a generative artificial intelligence (GenAI) model that learns user interface preferences and connects user profiles across platforms, allowing for dynamic content placement and recommendation of missing features based on user similarity and external data integration.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If user profiles are connected across multiple platforms using AI models, then user interface adaptability and personalized content display are improved, but system complexity and data integration requirements increase

Engineering Contradiction:

Improveuser interface adaptabilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent employs an AI model as an intermediary component that processes and analyzes profile features from multiple platforms. This mediator extracts relevant features, determines new profile characteristics, and generates personalized content recommendations, thereby managing the complexity of cross-platform data integration while enhancing UI adaptability

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments the complex profile integration task into distinct components: extracting profile features from external platforms, processing these features through an AI model, determining new profile characteristics, and generating personalized content. This segmentation allows each component to handle specific aspects of the integration challenge independently

Inventive Principle:

Principle #1Segmentation

2Loss of information

If external data sources are integrated to identify missing profile features, then personalized content recommendations are improved, but data security and privacy management challenges increase

Engineering Contradiction:

Improveprofile feature completenessVSAvoiddata security risks

Core Design Contradiction:

Loss of informationVSObject-affected harmful factors

Solution Approach 1:

The system extracts only the necessary profile features from external data sources rather than importing complete datasets. The AI model processes these extracted features to identify missing profile characteristics, thereby obtaining complete profile information while minimizing exposure of sensitive user data

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system implements a feedback mechanism where the AI model continuously learns from user interactions and profile completions. This feedback loop allows the system to improve its understanding of user preferences and identify missing features more accurately over time, reducing the need for extensive initial data collection from external sources

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250231774A1Memorializing a graphical user interface with generative artificial intelligence

Publication Date: 2025.07.17 THE TORONTO DOMINION BANK

AI summary

An example operation includes one or more of rendering a graphical user interface within a software application including a plurality of elements, modifying locations of the plurality of elements within the graphical user interface based on user inputs on the graphical user interface, generating a dynamic mapping of the graphical user interface including the modified locations of the plurality of elements based on an execution of an artificial intelligence (AI) model on the rendered graphical user interface, and storing the dynamic mapping of the graphical user interface within a storage.