Distributed Ledger Token Incentive for Model Providers
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Solution Overview
Problem
Existing information processing methods using distributed ledger technology do not provide incentives to providers of trained models, despite allowing sharing and usage of these models by others.
Innovation Solution
An information processing method that includes receiving a use request for a trained model registered in a distributed ledger, issuing a token to the provider's wallet upon receipt of the request, and granting a non-transferable token based on the cumulative amount of tokens issued.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is registered in a distributed ledger to enable sharing among multiple persons, then accessibility and collaboration are improved, but incentive mechanisms for data providers are lost
Solution Approach 1:
The system implements a feedback mechanism where token rewards are automatically issued to providers when their models are accessed or used. This creates a closed-loop incentive system where the value provided by the provider is directly rewarded through token issuance, maintaining motivation while enabling open access.
Solution Approach 2:
Tokens serve as an intermediary medium between the provider and the user. Instead of direct monetary payment or traditional incentive mechanisms, the system uses tokens as a intermediary value carrier that can be issued, transferred, and accumulated, enabling decentralized incentive distribution without centralized control.
2Reliability
If tokens are issued to reward providers, then incentive motivation is improved, but system complexity increases
Solution Approach 1:
The token system serves multiple functions simultaneously: it acts as a reward mechanism, a value storage medium, a transferable incentive, and a cumulative achievement tracker. By making the token multi-functional, the system reduces the need for separate mechanisms for each function, thereby managing complexity through consolidation.
Solution Approach 2:
The system enables self-service through automated token issuance based on predefined conditions (model access or use events). The smart contract or automated system handles the incentive distribution without requiring manual intervention, reducing operational complexity while maintaining reliable incentive delivery.
3Reliability
If non-transferable tokens are granted based on cumulative amounts, then achievement recognition is improved, but flexibility for providers is reduced
Solution Approach 1:
The system applies different token characteristics to different purposes: transferable tokens for general rewards and accumulation, and non-transferable tokens for achievement recognition and ranking. This local differentiation allows each token type to optimize for its specific function while maintaining overall system flexibility.
Solution Approach 2:
The token system is dynamic in nature, allowing providers to accumulate transferable tokens that can be converted or exchanged, while non-transferable tokens provide permanent achievement recognition. The system adapts the token behavior based on the cumulative amount and purpose, balancing flexibility and recognition.
Data Source
AI summary
The information processing method includes a receiving step of receiving a use request of one learned model registered in the distributed ledger, a issuing step of issuing a token to a wallet of a provider of one learned model when the use request is received, and a granting step of granting a non-transferable token to the wallet based on the cumulative amount of the token issued to the wallet.