Storyboard GUI for Multimodal Video Generation Under Memory Limits

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Solution Overview

Problem

Existing AI tools face limitations in memory capacity, primarily affecting video and long-form text generation, and interfaces are nascent, with most prompts being text-based, lacking versatility for multi-modal inputs.

Innovation Solution

A visual media generative response engine utilizing a diffusion-transformer architecture that processes both image and text prompts, capable of generating high-quality videos with varied aspect ratios, resolutions, and lengths by breaking frames into spacetime patches and using a timeline interface for user input.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If AI tools use traditional text-based chat interfaces or APIs for prompting, then the interface implementation is simple, but the user input versatility is limited

Engineering Contradiction:
Improveuser input versatilityVSAvoidinterface complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The graphical user interface enables users to input prompts through multiple modalities including text boxes, image uploads, video uploads, and audio recordings, allowing a single interface to serve multiple input functions simultaneously. This multi-functional approach resolves the contradiction by expanding input versatility without requiring separate specialized interfaces for each input type.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The interface is divided into distinct functional components: a text box for text input, an image upload button for visual input, a video upload button for temporal visual input, and an audio recording button for auditory input. Each segment handles a specific input modality independently, allowing the system to process diverse input types through organized, manageable interface elements rather than a monolithic complex interface.

Inventive Principle:
Principle #1Segmentation

2Adaptability or versatility

If AI tools process video generation tasks, then creative capabilities are enhanced, but memory capacity limitations are exceeded

Engineering Contradiction:
Improvevideo generation capabilityVSAvoidmemory capacity
Core Design Contradiction:
Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The video generation process is divided into discrete frame processing steps, where the model generates one frame at a time rather than processing the entire video sequence simultaneously. This segmentation reduces the memory burden by breaking down the large-scale video generation task into smaller, manageable units that fit within available memory capacity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system employs iterative generation where the model produces video frames in periodic steps, generating a frame, evaluating it, then proceeding to the next frame. This periodic action allows memory to be released and reallocated between generation steps, enabling video generation capability while managing memory constraints through rhythmic processing cycles.

Inventive Principle:
Principle #19Periodic action

Data Source

PatentUS20250259361A1Storyboard graphical user interface to a visual media generative response engine
Publication Date: 2025.08.14 OPENAI OPCO LLC
  • US20250259361A1 patent drawing
  • US20250259361A1 patent drawing
  • US20250259361A1 patent drawing

AI summary

The present technology pertains to presenting a storyboard user interface that includes a visual media timeline and a representation of a first frame on the timeline along with a prompt to generate visual media. The input prompt is then sent to a visual media generative response engine, which generates output visual media in response to the input prompt.