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

System Architecture

The ZDUCK platform is supported by a well-structured architecture designed to facilitate decentralized machine learning. This architecture simplifies the development and deployment of AI agents while maintaining a high degree of reliability and efficiency.

  • Data Management Structure: The platform ensures secure data uploading, storage, and accessibility, thereby safeguarding data integrity and traceability. This is critical in maintaining the trustworthiness of all data used within the ZDUCK ecosystem.

  • Model Management Interface: ZDUCK provides a comprehensive model management interface that facilitates the submission, management, testing, and deployment of AI models. Developers can work efficiently, ensuring that the models meet performance benchmarks and are seamlessly integrated into the platform.

  • Reward System: ZDUCK promotes active participation by rewarding contributors for activities ranging from data provision to model validation. This fosters an environment where every participant receives appropriate compensation for their contributions, driving community engagement and growth.

  • Verification and Arbitration Framework: ZDUCK’s verification framework ensures that the quality and reliability of both data and models are maintained. The platform integrates both automated and manual review processes to guarantee the integrity of deployed AI solutions, providing users with a trustworthy and efficient environment.

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Last updated 5 months ago