NFT Creation Workflow With ML-Generated Rights Contracts
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Solution Overview
Problem
Existing NFT marketplaces and tools require technical expertise for minting and deploying NFTs, lack support for proving asset authenticity, and do not facilitate configurable royalty payment terms or rights management.
Innovation Solution
A system that creates an automated rights contract with a smart contract deployed to the blockchain, referencing an electronically signed natural language document contract, using machine learning to generate self-executing code that enforces terms and conditions without requiring technical expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users are required to have technical experience with smart contract programming language to mint NFTs, then the NFT creation process can be precisely controlled and secured, but only sophisticated users can use NFT tools and technologies
Solution Approach 1:
The patent introduces an intermediary system comprising a natural language processing module and a machine learning model that translates user-friendly natural language descriptions into smart contract code. This mediator layer allows users without programming expertise to define NFT rights and terms in plain language while maintaining the security and precision of blockchain-based smart contracts through automated code generation and deployment
Solution Approach 2:
The system enables self-service NFT creation by automatically generating, reviewing, and deploying smart contracts based on user inputs. The machine learning model autonomously translates natural language descriptions into executable contract code, and the system automatically manages the deployment process to the blockchain, eliminating the need for users to manually write or configure complex programming code
2Ease of operation
If automated machine learning models are used to generate smart contracts from natural language, then ease of operation is improved, but manufacturing precision (contract accuracy) may deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where the generated smart contract code is reviewed and validated through multiple layers: the machine learning model generates initial code, which then passes through validation checks against the original natural language description, and users can review and modify the generated code before deployment. This feedback loop ensures accuracy while maintaining ease of use
Solution Approach 2:
The system performs preliminary actions by pre-validating the natural language input against known contract templates and legal frameworks before code generation. The machine learning model is pre-trained on accurate contract patterns, and the system performs preliminary checks to ensure the generated code meets technical and legal requirements before final deployment
3Device complexity
If existing NFT tools are used without automated rights management, then device complexity is reduced, but the ability to prove asset authenticity and enforce rights deteriorates
Solution Approach 1:
The patent merges multiple functions into a unified system: the natural language processing module, machine learning code generator, electronic signature verification system, and blockchain deployment capabilities are combined into a single integrated platform. This consolidation provides comprehensive rights management and authenticity proof while presenting a simple user interface
Solution Approach 2:
The system provides multi-functionality by handling the entire NFT creation and rights management workflow within a single platform: users can input natural language descriptions, have contracts automatically generated and validated, sign documents electronically, and deploy to blockchain networks all through one unified system, eliminating the need for multiple separate tools
Data Source
AI summary
A digital content management system may include a set of one or more memory components and a set of one or more processing devices coupled to the set of one or more memory components. The set of one or more processing devices to perform operations comprising: obtaining one or more electronic signatures on a digital document to yield an electronically signed digital document, storing the electronically signed digital document at an off-chain address, using a trained machine learning model to create a smart contract, the smart contract comprising a reference to the off-chain address; and deploying the smart contract to a blockchain.