iAgent whitepaper
iAgent whitepaper
  • Introduction
  • Philosophy
    • Problem & Solution
    • Vision & Mission
  • Product and Ecosystem
    • Visual Learning Model (VLM)
    • ERC-AI Agent Standard
    • AI Agent Marketplace
    • Data Collection & Labeling
    • iAgent Dev Hub
  • Visual Learning Model Explained
  • iAgent Protocol Explained
  • Protocol Governance
    • Governance Framework
    • Governance Core
    • Privacy and Security
  • Protocol Nodes
    • Node Deployment
    • Video Tutorial
    • FAQs
    • Key Aspects
    • Consensus Algorithms
    • Reward Calculation
    • How to KYC
    • Purchase and Sale Agreement
  • $AGNT
    • $AGNT Tokenomics
    • $AGNT Solo Staking
    • $AGNT Liquid Staking
  • Roadmap
  • Conclusion
  • Official Links
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  1. Product and Ecosystem

Data Collection & Labeling

PreviousAI Agent MarketplaceNextiAgent Dev Hub

Last updated 15 hours ago

Powering AI’s Next Evolution

AI thrives on high-quality, labeled data—and in gaming, data is the key to next-gen AI. The iAgent ecosystem builds a robust game data collection and labeling infrastructure, fueling AI-driven advancements in game strategy, automation, and generative content.

Key Components:

  • Decentralized Game Data Processing: iAgent & OORTech enable scalable AI data pipelines.

  • Incentivized Data Contributions: Players and developers earn $AGNT for providing game data.

  • Real-Time AI Model Training: AI models improve continuously with fresh labeled data.

  • Generative AI in Gaming: Labeled datasets power AI-generated assets, environments, and NPC interactions.

Why This Infrastructure is Critical:

  • Bridges raw gaming data with AI model training.

  • Powers adaptive AI for in-game automation and strategy optimization.

  • Enables decentralized AI research and innovation in gaming.

GameHub
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