AI Design Template Generation System
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Solution Overview
Problem
The limited size of a template library in design applications restricts the ability to present proposed designs that fully satisfy user preferences.
Innovation Solution
A data processing system that utilizes a Large Language Model (LLM) and a text-to-image model to generate new design templates, expanding the template library by producing designs based on user-defined design purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a manual process is used to create design templates, then the quality and relevance of templates can be maintained, but the scale and comprehensiveness of the template library are limited
Solution Approach 1:
The patent replaces manual design processes with an automated AI-based system that uses text-to-image models and Large Language Models to generate design templates. This substitution of mechanical (manual) processes with automated intelligent systems enables massive scaling of template library size while maintaining quality through AI-driven generation rather than human craftsmanship
Solution Approach 2:
The system enables self-service template generation where the AI model automatically creates templates based on user inputs and design purposes without requiring manual intervention for each template creation. The text-to-image model generates images, the LLM processes requirements, and the system automatically assembles templates, allowing the system to serve itself in the template creation process
2Adaptability or versatility
If the template library is expanded with more distinct templates, then the ability to satisfy user preferences improves, but the complexity of managing and curating the library increases
Solution Approach 1:
The system incorporates feedback mechanisms where user interactions and preferences are analyzed to refine future template generation. The LLM processes user inputs and design purposes to generate appropriate templates, creating a feedback loop where user needs directly shape template creation, thereby expanding versatility without manual curation complexity
Solution Approach 2:
The system changes the parameters of template generation by using AI models that can create templates based on text descriptions, design purposes, and user inputs rather than requiring manual creation. This parameter change from manual to automated generation enables unlimited template variety while simplifying management through algorithmic organization
3Quantity of substance
If automated AI models are used to generate templates, then the scale and comprehensiveness of the library increase, but the text accuracy and editability of generated templates may be compromised
Solution Approach 1:
The patent introduces an intermediary process where the LLM acts as a mediator between the text-to-image model and the final template output. The LLM processes text requirements, generates appropriate prompts, and refines the output to ensure text accuracy and editability, thereby maintaining precision while enabling automated scaling
Solution Approach 2:
The system performs preliminary actions by using the LLM to process and validate text requirements before they are used to generate images. This preliminary text processing and prompt generation ensures that the text elements in the final templates are accurate and properly formatted, preventing text accuracy issues from arising in the first place
Data Source
AI summary
A data processing system includes a processor, and a memory storing executable instructions which, when executed by the processor, cause the processor alone or in combination with other processors to perform the following functions: based on a list of design purposes, generate prompts requesting a Large Language Model (LLM) to produce corresponding prompts for input to a text-to-image model to generate a proposed design corresponding to each design purpose; submit the prompts from the LLM to the text-to-image model; receive the proposed designs from the text-to-image model; and increase a design template library by adding a design based on the proposed designs output by the text-to-image model.