AI-Generated Visual Programming Modules for Mixed Reality
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Solution Overview
Problem
Creating software modules for mixed reality experiences using visual programming interfaces is time-consuming and error-prone for developers, requiring knowledge of programming languages and algorithms, and existing visual programming interfaces do not eliminate the need for manual coding.
Innovation Solution
A facility that generates visual programming modules using artificial intelligence, retrieving directive templates, receiving natural language input, and employing generative AI models to produce executable directives, which are then integrated into a visual programming interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If developers manually create software modules using visual programming interfaces, then the modules can be assembled in a graphical user interface, but the process remains time-consuming and requires programming knowledge
Solution Approach 1:
The system enables self-service by allowing the AI model to automatically generate visual programming modules based on natural language descriptions, eliminating the need for developers to manually code or configure modules while reducing time consumption
Solution Approach 2:
The patent replaces the mechanical process of manual module creation with an intelligent system that uses natural language processing and code generation, substituting human programming efforts with AI-driven automatic module synthesis
2Reliability
If developers manually code software modules, then functionality can be implemented, but errors result from failure to adhere to programming language requirements
Solution Approach 1:
The AI model acts as an intermediary between natural language descriptions and executable code, translating user intent into syntactically correct visual programming modules while ensuring adherence to programming language requirements, thereby reducing errors and the need for deep programming knowledge
Solution Approach 2:
The system uses template-based code generation where pre-defined module structures and patterns are copied and adapted based on natural language input, ensuring that generated code follows established patterns and reduces errors from manual coding
3Productivity
If more powerful hardware is used to run visual programming interfaces, then module creation speed improves, but resource consumption increases
Solution Approach 1:
The AI-powered system performs automatic module generation locally or through efficient cloud processing, reducing the need for high-end local hardware while maintaining productivity through intelligent automation that optimizes resource usage
Data Source
AI summary
A directive template that includes sample directive code for a directive to be generated and natural language annotation is retrieved. Then, a natural language statement specifying a functionality for the directive in a mixed reality experience is received from a user. A prompt is generated based on the directive template and the statement and is submitted to an artificial intelligence model. A response from the artificial intelligence model is received that includes a proposed directive providing the specified functionality. An attempt to translate the proposed directive into machine code is made. If the translation is successful, the proposed directive is added to a source code directory accessible for execution in a visual programming interface for mixed reality experiences. An indication of the directive is displayed in the visual programming interface for mixed reality experiences, enabling the directive to be incorporated into MR experiences.