ZDUCK WHITEPAPER v1.0
  • Introduction
  • ZDUCK
    • Introduction to ZDUCK
    • Purpose and Objectives
    • System Architecture
    • Conclusion
  • $ZDK
    • $ZDK Coin
    • Purpose of $ZDK
    • Economic Design
    • Utility within the Ecosystem
  • ZDUCK Architecture
    • Overview
    • Core Components of the ZDUCK Architecture
    • Design Principles
    • Data Layer
    • Model Management Interface
    • Reward System
    • Verification and Arbitration Layers
    • Monitoring and Feedback Loop
  • Storage Nodes
    • Overview
    • Roles and Functions
    • Operation
    • Storage Node Reward System
    • ZDUCK Network Integration
  • ZNEST
    • ZNEST Platform
    • Model Selection and Customization
    • Blockchain Integration
    • Model Testing and Validators
    • Usage-Based Reward Structure
  • Tokenomics
    • Basic Information
    • Utility
    • Key Functions
    • Reward System
    • $ZDK Token Vesting Plan and Allocation
  • Team
  • ZDUCK Business and Development Roadmap
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  1. ZDUCK Architecture

Core Components of the ZDUCK Architecture

  • Data Integrity: ZDUCK’s architecture is focused on ensuring data accuracy and immutability. Through the use of encryption technologies, the system performs data authentication and verification, maintaining a permanent record of the data used in AI applications to ensure reliability and stability.

  • Verification: ZDUCK incorporates a multi-layered verification structure to assess and guarantee the quality of both data and AI models. This verification process combines automated algorithms with human expertise to thoroughly examine everything from data input to model output, thereby maintaining the operational excellence and reliability of AI functionalities.

  • User Incentives: The platform operates on a reward model that compensates users for their contributions to the network. Whether users provide valuable data or develop efficient AI models, they are rewarded with $ZDK tokens, which function as the primary currency within the ecosystem. This reward system is designed to foster active participation from technologists and AI practitioners, encouraging high-quality contributions.

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Last updated 5 months ago