Tagger Documentation
  • About Tagger
    • 🛸 Our Vision
    • 🔌 What We Do
  • Challenges in the Current Data Economy
    • 🌏 Chaotic Data Authentication
    • 📂 Difficulty in Data Acquisition
    • 📌 Quality of Labeled Data
    • 🪝 Data Silos
    • 🛡️ Privacy and Ethical Issues
    • 🧳 The Need for Continuous Maintenance
  • Our Solutions
    • 📃 Data Authentication Protocol
    • 🌲 A Full-Stack Decentralized AI Data Solutions Platform
      • Web 3 Crowdsourcing
      • Simple Onboarding, Instant Global Payments
      • DePIN-Based Data Collection and Sharing
      • AI Copilot Labeling Tool
      • Permissionless AI Marketplace
      • Data Developer Community
      • Human-In-The-Loop
  • Tagger Features
    • Data Authentication Protocol
    • Decentralized AI Data Collection
    • Decentralized AI Data Labeling
    • Data Evaluation, Cleaning, and Processing
    • Data Trading and Management
    • HITL Telegram Mini App
  • Hardware
    • ⌚ Health Monitoring Wristband
  • Tokenomics
    • ☑️ $TAG
    • 🪙 Token Distribution
    • 💡 Task Reward Calculation
      • AI Copilot Labeling
      • Manual Labeling
      • Data Review and Staking
      • 👥 Daily Task Bonus
  • Smart Contract and Audit
    • 📄 Audits
    • 🖼️ NFT Smart Contract
    • 🪙 Token Smart Contract
  • Roadmap
  • Team
  • Contact Us
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  1. Challenges in the Current Data Economy

🧳 The Need for Continuous Maintenance

In the context of AI applications, data needs to be continuously updated to adapt to new challenges. This requires the establishment of effective data management mechanisms for collecting, updating, and maintenance of datasets to ensure sustained performance improvement of AI models. Automating data update processes and conducting regular data quality assessments are keys to addressing this issue.

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Last updated 8 months ago