FileMarket AI
  • 🌐FileMarket: Data Platform for Human and AI Agents
  • ⛩️1. Introduction
    • 1.1 Overview
    • 1.2 Key Features
  • ⚙️2. System Architecture
    • 2.1 Multi-chain Data Platform
    • 2.2 Community-driven Data Collection in Social Media
    • 2.3 Datasets Tokenization
    • 2.4 AI-Powered Data Processing
    • 2.5 Decentralized Compute Network
    • 2.6 Decentralized Storage
    • 2.7 Decentralized Exchanges (DEXs) in AI Data Economy
  • 💱3. FileMarket AI Data Economy
    • 3.1 How the Data Economy Works
    • 3.2 The Key Participants & Their Roles
    • 3.3 Future Vision: A Fully Autonomous AI Data Marketplace
  • 🕹️4. Gamified Data Collection
    • 4.1 Data Quests
      • 4.1.1 Types of Data Quests
      • 4.1.2 Compensation and Rewards
      • 4.1.3 Boosting Earnings with Referrals
      • 4.1.4 Gamified Earning System
      • 4.1.5 Participation Process
    • 4.2 Scaling Through Gamification
      • 4.2.1 Key Strategies
  • 🗓️5. Technical Roadmap
    • Phase 1: Product Market Fit and SEED Round
    • Phase 2: Data Platform Launch and Multi-Chain Expansion
    • Phase 3: AI Compute & Validator Network launch and Multichain Expansion
  • 🧮6. Tokenomics
    • 6.1 Overview
    • 6.2 Multi-Token Architecture
      • 6.2.1 $DATA Token
      • 6.2.2 $DATASET_X Tokens
    • 6.3 Token Allocation & Vesting
      • 6.3.1 $DATA Token Allocation
      • 6.3.2 DatasetX Token Allocation
    • 6.4 Unlock Schedule & Sell Pressure Management
      • 6.4.1 $DATA Unlocks
      • 6.4.2 DatasetX Unlocks
    • 6.5 TGE Roadmap
    • 6.6 Why the Multi-Token Model Matters
  • ❓7. FAQ
  • 📥8. CONTACT US
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  • Image & Gesture Quests
  • Audio Quests
  • Video Quests
  • Labeling & Annotation Quests
  • Specialized Data Quests
  1. 4. Gamified Data Collection
  2. 4.1 Data Quests

4.1.1 Types of Data Quests

FileMarket AI provides diverse data collection tasks to enhance AI model training. All quests involve self-labeling, and future improvements will include AI-assisted validation and annotation double-checking for greater accuracy.

Image & Gesture Quests

Users submit selfies, full-body photos, palm images, and gesture-based actions under varied conditions (lighting, angles, backgrounds) to support computer vision, identity verification, and biometric AI models.

Audio Quests

Participants record speech samples, dialects, and accents for speech recognition, text-to-speech (TTS), and voice AI models. Some tasks focus on regional accents or scripted prompts, while others require natural conversations.

Video Quests

Users provide short video clips demonstrating facial expressions, gestures, motion, and object interactions, improving AI-driven motion tracking, behavioral analysis, and AR/VR applications.

Labeling & Annotation Quests

Participants verify and refine AI-generated labels on images, audio, and video data to enhance dataset accuracy. Future tasks will involve AI-assisted pre-labeling, with contributors reviewing and correcting annotations.

Specialized Data Quests

High-value datasets tailored to custom AI needs, including:

  • Conversational Datasets (dialogues, speech interactions)

  • Environmental Sound Captures (background noise for AI recognition)

  • Handwritten Text Data (OCR training)

  • Custom AI Training Sets (specific requests from AI companies)

Previous4.1 Data QuestsNext4.1.2 Compensation and Rewards

Last updated 4 months ago

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