viralmind.ai
  • Viralmind's Mission
  • The $VIRAL Token
  • Roadmap
  • What Sets Viralmind Apart?
  • Join Our Communities
  • The Team
  • Understanding Computer Use Agents
    • ❓What is a Computer Use Agent?
    • πŸ–₯️Real World Examples and Use Cases
  • The Forge
    • ℹ️Introduction
    • πŸŒ€Training Pools
  • Training Gym
    • ℹ️Introduction
    • πŸ”„How It Works
    • πŸͺ§Demonstrations
    • πŸ“ŠDemonstration Data
  • Inference API
    • πŸ€–Deploy Agentic AI with $VIRAL
  • Frequently Asked Questions
    • ❓General FAQs
    • ❓Technical FAQs
    • ❓Token and Ecosystem FAQs
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On this page
  • How Training Pools Work
  • 1. Funding the Pool
  • 2. Dynamic Payouts Based on Demonstration Quality
  • 3. Bidding System for Worker Participation
  • 4. Reputation-Based Incentives
  • Why Training Pools Matter
  • Example Training Pool Funding Scenarios
  • Web2 Enterprise Example
  • Web3 Startup Example
  • The Role of Training Pools in AI Growth
  1. The Forge

Training Pools

The Training Pool is the core funding mechanism within The Forge, enabling AI training environments (Gyms) to distribute rewards to contributors. Gym creators fund a pool using $VIRAL, USDC, or their own native tokens, ensuring a steady flow of incentives to attract high-quality AI training demonstrations.

Training Pools enable dynamic, competitive AI training, where contributors earn based on the quality of their demonstrations, and Gym owners can scale their AI models efficiently.


How Training Pools Work

1. Funding the Pool

  • Gym creators deposit $VIRAL, USDC, or their own token to finance AI training. A 20% platform fee is taken from each deposit.

  • The pool is used to pay workers who submit high-quality demonstrations.

  • Web3 startups can stake $VIRAL to unlock the ability to use their own token.

2. Dynamic Payouts Based on Demonstration Quality

  • Workers record demonstrations, which are then scored by ViralMind’s data quality agent.

  • Higher-quality submissions receive larger payouts, ensuring AI models learn from the best data.

  • Example: A $0.20 bid per demonstration means:

    • 85% quality submission: Worker receives $0.17, and $0.03 is refunded to the pool.

    • Submissions below 50% quality: No payout, and the full amount is refunded to the training pool.

3. Bidding System for Worker Participation

  • Gym owners adjust pricing based on demand.

  • If a Gym sets $0.20 per demonstration but receives few submissions, it can raise the bid to $0.30 to attract more workers.

  • This creates an organic marketplace, ensuring that AI models are trained efficiently without overspending.

4. Reputation-Based Incentives

  • ViralMind implements a Worker Reputation System, rewarding consistent, high-quality contributors.

  • Workers with strong track records gain priority access to higher-paying tasks, improving training efficiency.


Why Training Pools Matter

πŸ”Ή Incentive-Driven AI Training – High-quality demonstrations are rewarded fairly, ensuring AI agents learn from the best data sources.

πŸ”Ή Scalable and Competitive Marketplace – The bidding system allows Gym owners to dynamically control costs and training speed.

πŸ”Ή Tokenized AI Training Economy – The system creates constant demand for $VIRAL, as businesses must acquire and fund pools to train AI models.

πŸ”Ή Reputation and Quality Control – Workers are ranked by performance, ensuring AI agents improve efficiently without low-quality data slowing progress.


Example Training Pool Funding Scenarios

Web2 Enterprise Example

  • Company Funds: $20,000 USDC

  • Flat Setup Fee: $250

  • 20% Platform Fee: $4,000

  • Remaining Worker Pool: $15,750

  • Demonstration Price: $0.20 per task

  • Total Demonstrations Funded: 78,750

Web3 Startup Example

  • Project Funds: $20,000 USDC equivalent in $VIRAL

  • Flat Setup Fee: 1 SOL (~$100)

  • 20% Platform Fee: $4,000

  • Remaining Worker Pool: $16,000

  • Demonstration Price: $0.20 per task

  • Total Demonstrations Funded: 80,000

These funding mechanisms scale AI training based on demand, ensuring sustainable growth while keeping contributors incentivized.


The Role of Training Pools in AI Growth

Training Pools are the economic backbone of The Forge, ensuring AI models are trained, improved, and monetized in an open, decentralized way.

By aligning funding, quality control, and incentives, ViralMind enables:

βœ… Enterprise-grade AI development without centralized control

βœ… A sustainable AI training workforce where contributors are fairly rewarded

βœ… Continuous demand for $VIRAL, reinforcing the AI training economy

With Training Pools, The Forge transforms AI training into a scalable, self-sustaining system, where Gym creators and AI trainers both benefit from continuous innovation.

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Last updated 2 months ago

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