Sage Union Whitepaper
  • Introduction
    • Project Overview
    • Problem Statement
    • Vision & Mission
  • Market Overview
    • Current Issues in the Information Ecosystem
    • Potential of Human-AI Collaboration
    • Competitor Analysis & Differentiation
  • SageUnion Solution
    • System Components
    • Human-AI Collaboration Model
    • Definition & Creation of High-Quality Information
  • Platform Architecture
    • Telegram Mini-App Structure
    • Data Collection & Processing Workflow
    • AI-Based Information Evaluation Mechanism
    • Reward Distribution Logic
  • Tokenomics
    • Token Overview (SAGU)
    • Token Utility & Rewards
    • Revenue Model & Sustainability
  • Governance & Community
    • User Participation Structure
    • Voting & Decision-Making Mechanism
    • Community Incentives
  • AI Learning & Quality Control
    • Data Collection Standards
    • AI Evaluation Logic
    • Continuous Learning Framework
  • Roadmap
    • Development Phases
    • Beta Launch & Official Release Timeline
    • Long-term Vision
  • Team & Partnerships
    • Team Introduction
    • Advisory Board & Partners
    • Strategic Partnerships Plan
  • Conclusion
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  1. SageUnion Solution

Definition & Creation of High-Quality Information

High-quality information within the SageUnion ecosystem is defined by the following key attributes:

  • Accuracy: The information must be factually correct, verifiable, and free of misinformation or bias.

  • Relevance: Contributions should directly address the weekly question and provide meaningful insight or knowledge.

  • Originality: Responses should demonstrate independent thought, critical analysis, or unique perspectives, rather than copied or generic content.

  • Depth: The information should include sufficient detail and context to enhance its value to other users.

The creation process of high-quality information in SageUnion is structured as follows:

  1. Strategic Question Design: Each weekly question is designed to elicit informative, well-reasoned responses from users.

  2. Community-Driven Contribution: Diverse perspectives and insights are gathered from a global community of participants.

  3. AI-Driven Evaluation: Advanced AI models analyze each response against predefined quality criteria.

  4. Transparent Reward System: Contributors are fairly compensated based on the verified quality of their input, encouraging continuous participation.

  5. Curation and Archiving: Verified, high-quality responses are stored in the SageUnion Information Database for future access and use.

Through this approach, SageUnion ensures the sustainable growth of a verified, trustworthy knowledge base.

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Last updated 1 month ago