Intelligent Self-Growing Avatar for Metaverse Adaptation

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Solution Overview

Problem

Current metaverse technologies lack the ability to create avatars that can learn and adapt to the personal characteristics and activities of real individuals, limiting their ability to evolve and interact realistically in virtual environments.

Innovation Solution

The development of an intelligent self-growing avatar (ISGA) system that utilizes an ISGA server and client to collect personal characteristics and activities from the real world, create avatars with these traits, train them to recognize and respond to real-world activities, and adjust their behavior and personality over time to ensure continuous growth and evolution in the metaverse.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional avatar systems are used in the metaverse, then the system structure is simple, but the avatar cannot learn and adapt to personal characteristics and activities of real individuals

Engineering Contradiction:

Improveavatar learning and adaptation capabilityVSAvoidsystem structure complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system is divided into distinct functional modules: data collection module that gathers personal characteristics and activities, avatar creation module that generates virtual representations, and continuous learning module that updates avatar behavior. This segmentation allows complex learning capabilities to be implemented through manageable, independent components that can be developed and maintained separately.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

A machine learning model acts as an intermediary between real-world user data and the virtual avatar representation. This intermediary processes raw data about personal characteristics and activities, transforming it into actionable insights that shape avatar behavior and appearance, thereby enabling adaptation without direct complex connections between all system elements.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If avatars are created with detailed personal characteristics from real individuals, then the realism and engagement of interactions improve, but the data collection and processing requirements increase

Engineering Contradiction:

Improveinteraction realismVSAvoiddata collection volume

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The system extracts only the most relevant personal characteristics and activities from extensive user data, rather than processing all available information. By identifying and isolating key traits that define individual behavior patterns, the system achieves realistic avatar representation while minimizing the volume of data that needs to be collected and processed continuously.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Different levels of detail are applied to different aspects of avatar representation based on their importance. Critical personal characteristics that fundamentally define user identity receive detailed processing and continuous refinement, while less significant attributes are represented with appropriate but reduced detail, optimizing the balance between realism and data requirements.

Inventive Principle:

Principle #3Local quality

3Duration of action of stationary object

If avatars continuously evolve based on real-world activities, then the avatar grows and adapts over time, but the computational resources and processing time increase

Engineering Contradiction:

Improveavatar evolution durationVSAvoidcomputational resource consumption

Core Design Contradiction:

Duration of action of stationary objectVSUse of energy by moving object

Solution Approach 1:

Instead of continuously processing and updating avatar characteristics in real-time, the system implements periodic learning cycles where avatar evolution occurs at scheduled intervals. During these periodic updates, accumulated user data is processed to refine avatar behavior and characteristics, while between updates the avatar maintains its current state with minimal computational overhead, thereby reducing overall energy consumption while still enabling long-term evolution.

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS20250053773A1Intelligent self-growing avatar

Publication Date: 2025.02.13 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A method for maintaining an intelligent self-growing avatar (ISGA) in a metaverse is presented including supporting the ISGA with an ISGA server communicating with an ISGA client, collecting, via an ISGA data structure, personal characteristics and activities of a person in a real world, creating, via an avatar creator, an avatar having the personal characteristics of the person in the real world, training, via an ISGA trainer, the avatar to recognize and respond to the activities and relationships of the real person, and changing, via an ISGA adjuster, a behavior and personality of the avatar based on the activities and relationships of the real person in the real world to allow the avatar to continuously grow and evolve in the metaverse.