AI Skill Tracking With NFT Credentials for Gameplay Validation
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Solution Overview
Problem
Existing online learning and gaming platforms fail to track and validate user skills acquired through gameplay or AI agents, and there is no platform to connect individual game developers with large-sized developers to showcase and utilize their skills effectively.
Innovation Solution
A system utilizing AI models to evaluate and track user skills through non-fungible tokens (NFTs) on a blockchain, enabling skill representation and connection between individual and large-sized game developers for skill utilization and game enhancement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If skills are acquired through gameplay or AI agents in online environments, then users can learn and acquire skills, but the skills are neither tracked nor validated
Solution Approach 1:
The patent introduces an intermediary validation system that acts as a mediator between skill acquisition activities and skill recognition. This system uses AI models to evaluate and validate skills, and blockchain technology to record validated skills as NFTs, creating a trusted bridge that connects unvalidated gameplay/learning activities to recognized skill credentials.
Solution Approach 2:
The patent implements a feedback mechanism where AI models continuously evaluate user actions during gameplay or learning activities, provide validation feedback, and update skill status. The system monitors user behavior, compares it against skill criteria, and provides real-time or post-action validation feedback that confirms or refutes skill acquisition.
2Productivity
If large-sized game developers lack bandwidth to fulfil evolving user needs, then they can maintain core game development, but they cannot create custom skins and avatars for gaming characters
Solution Approach 1:
The patent segments the game development ecosystem into core development functions (handled by large-sized developers) and custom content creation functions (handled by individual developers). This segmentation allows large developers to focus on maintaining core game development productivity while individual developers specialize in creating custom skins, avatars, and other user-specific content.
Solution Approach 2:
The patent creates a universal platform that serves multiple functions: it validates skills from various sources, connects individual developers with large developers, manages NFT-based skill credentials, and enables diverse custom content creation. This multi-functional platform resolves the contradiction by providing a single ecosystem that handles both core development needs and custom content requirements.
3Adaptability or versatility
If individual game developers want to showcase and employ their skills, then they can contribute to the game ecosystem, but there is no platform to connect them with large-sized game developers
Solution Approach 1:
The patent introduces a platform intermediary that connects individual developers with large-sized developers. This platform uses blockchain technology to create visible, verifiable skill profiles and NFT credentials that individual developers can showcase, and large developers can discover and utilize. The intermediary resolves the information loss by making skills visible, trackable, and connectable across the ecosystem.
4Ease of operation
If skills are not tracked or validated, then users can freely acquire skills through gameplay, but there is no way to identify the uniqueness of skills acquired by users
Solution Approach 1:
The patent introduces an AI-based intermediary validation system that freely evaluates skills without restricting acquisition methods. This system uses machine learning models to assess skill uniqueness, compare it against existing skill databases, and assign distinctive credentials. The intermediary maintains ease of operation by not blocking skill acquisition while simultaneously providing precise measurement of skill uniqueness through AI evaluation and blockchain verification.
Data Source
AI summary
A system and method for artificial intelligence (AI) based skill tracking and non-fungible token (NFT) based skill/behavior representation are provided. The system acquires information associated with a non-tangible asset of a user in an online environment, apply an artificial intelligence (AI) model on the acquired information, wherein the AI model is trained to evaluate the non-tangible asset and track a progress of acquisition of the non-tangible asset in the online environment. The system determines a proficiency level of a plurality of proficiency levels of the non-tangible asset of the user based on the application of the AI model on the acquired information. The system assigns, based on the determined proficiency level of the non-tangible asset of the user, a value to a digital token associated with the user. The digital token may include a non-transferable part unique to the user and a fungible part that may be exchangeable across platforms.