Virtual Canvas AI Interface for Remote Collaboration
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Solution Overview
Problem
Current technologies lack an efficient method for collaborating between remote computers to utilize an artificial intelligence engine within a virtual canvas, particularly for refining image outputs based on user input, and for facilitating seamless interaction and refinement of AI-generated images across multiple displays.
Innovation Solution
Establishing a peer-to-peer connection between computers running virtual canvas software, allowing a shared virtual canvas for real-time data exchange and manipulation, and incorporating an AI icon that enables users to input prompts, generate and rank multiple image outputs, and refine selections using gestures and ranking metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a virtual canvas is shared between remote computers, then collaboration capability is improved, but connection stability and data synchronization complexity increase
Solution Approach 1:
The patent introduces a cloud-based server as an intermediary to facilitate peer-to-peer connections between remote computers. The server acts as a mediator that receives virtual canvas data from one computer and transmits it to another, enabling stable remote collaboration without direct peer-to-peer connection complexity. This intermediary approach improves connection stability while maintaining collaboration capability.
2Adaptability or versatility
If multiple AI-generated image windows are displayed, then selection options are improved, but interface complexity and visual clutter increase
Solution Approach 1:
The patent segments the display interface into multiple functional tabs (Prompt tab, Notes tab, Media tab) that can be selectively activated. Each tab handles specific types of AI-generated content separately, allowing users to organize multiple image windows in a structured manner. This segmentation reduces visual clutter and interface complexity while maintaining comprehensive selection options.
Solution Approach 2:
The patent introduces a hierarchical organization structure where AI-generated images are arranged in multiple dimensions: prompt-level organization, note-level organization, and media-level organization. Users can navigate through these dimensional layers to access and select images systematically, reducing the perceived complexity while expanding selection capabilities.
3Productivity
If real-time AI image generation is implemented, then productivity is improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary actions by pre-defining prompt categories (Prompt tab, Notes tab, Media tab) and pre-establishing the AI engine connection. Users can select from pre-organized prompt types rather than creating new prompts from scratch, reducing processing time. The system also pre-loads AI model capabilities and maintains ready-state connections for rapid image generation.
Solution Approach 2:
The patent allows users to generate a limited number of AI images per prompt initially, with the option to generate more if needed. This partial action approach prevents excessive computational resources from being consumed in a single operation while maintaining productivity. Users can iterate through multiple prompts efficiently without overwhelming the system.
Data Source
AI summary
A method of using an artificial intelligence engine in a virtual canvas running on a computer associated with a display, the method including starting a virtual canvas on the computer, in response to an artificial intelligence icon being selected in an icon window of the virtual canvas, open a prompt tab to receive a prompt input, and in response to the prompt input and activation of a button, generate a response from an artificial intelligence engine in the prompt tab or in a new window on the canvas.