Procedural XR Environment Generation via Few-Shot Model

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Solution Overview

Problem

Existing digital object generation techniques, such as procedural generation, often produce repetitive or near-repetitive outputs due to reliance on preset components, failing to create unique and personalized digital content that human viewers appreciate as unique.

Innovation Solution

A system that utilizes user-specific parameters and one-way functions to generate unique digital objects, incorporating features like few-shot models and cryptographic protocols, allowing for personalized and varied outputs by validating and randomizing user inputs, and employing blockchain-based smart contracts for token generation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If preset components are used for procedural generation, then generation speed is improved, but uniqueness of output deteriorates

Engineering Contradiction:

Improvegeneration speedVSAvoiduniqueness of output

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The system changes the parameters of procedural generation by incorporating user-specific inputs (device identifiers, location data, time stamps, biometric data) into the generation process. These parameter changes ensure that even though preset components are used, the combination and transformation of these parameters with user-specific data produces unique outputs for each user, resolving the contradiction between generation speed and output uniqueness.

Inventive Principle:

Principle #35Parameter changes

2Manufacturing precision

If random elements are used for generation, then uniqueness of output is improved, but human appreciation deteriorates

Engineering Contradiction:

Improveuniqueness of outputVSAvoidhuman appreciation

Core Design Contradiction:

Manufacturing precisionVSEase of operation

Solution Approach 1:

The system incorporates feedback mechanisms where user interactions, preferences, and behavioral data are collected and used to refine and personalize the generated content. This feedback loop ensures that while random elements provide uniqueness, the content is continuously adapted to match user preferences and expectations, thereby maintaining human appreciation while preserving uniqueness.

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If user-specific parameters are incorporated, then personalization is improved, but system complexity deteriorates

Engineering Contradiction:

ImprovepersonalizationVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the complexity by dividing user-specific data collection and processing into separate modules: device identifier extraction, location data acquisition, time stamp generation, and biometric data processing. Each module handles a specific aspect of personalization independently, which reduces overall system complexity while maintaining high personalization capabilities. This modular segmentation allows the system to manage multiple user-specific parameters without becoming unmanageably complex.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS12198128B2Method and system for unique, procedurally generated extended reality environment via few-shot model

Publication Date: 2025.01.14 EMOJI ID LLC

AI summary

Disclosed herein is digital object generator that makes uses a one-way function to generate unique extended reality environments based on the user specific input. Features of the input are first extracted via a few-shot convolutional neural network model, then evaluated weight and integrated fit. The resulting digital object includes a user decipherable output such as a visual representation, an audio representation, or a multimedia representation that includes recognizable elements from the user specific input.