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Ruvi AI
  • 📄Abstract
  • 🧭Introduction
  • 🚧Problem Statement
  • 💡The Solution: Ruvi
  • ⚙️Core Features
    • 🤖AI Tool Suite
  • 🧩Ready-Made Templates
  • 🧠User-Guided Model Training
  • 🪙Tokenomics
    • 🧾Token Utility
  • 📊Token Distribution
  • 🚀Presale Structure
  • 🎁Presale Bonuses
  • 🪐Ecosystem
    • 🏛️Ecosystem & Governance
  • 🖥️Technical Architecture
  • 🗺️Roadmap
  • 👨‍💼Team
  • 🔍Links
    • Website
    • Ruvi AI Public Beta
  • Telegram
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On this page
  • 🧠 How It Works
  • 💎 Token Rewards System
  • 🤝 Community-Led AI
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User-Guided Model Training

PreviousReady-Made TemplatesNextToken Utility

Last updated 1 month ago

Ruvi isn’t just a platform for using AI—it’s a platform for shaping it. Through a unique feature called User-Guided Model Training, Ruvi invites its community to play an active role in training and improving its native AI models. In return, users earn $RUVI tokens, reinforcing a circular, decentralized system where contributions are rewarded and innovation is community-driven.

This feature opens up a new layer of engagement and transparency rarely seen in traditional AI platforms.


🧠 How It Works

Ruvi integrates mechanisms that allow users to interact with AI outputs in ways that generate valuable training data. These include:

  • Rating & Feedback Users can rate AI outputs (e.g., “Was this answer helpful?”) and submit corrections or suggestions to improve future responses.

  • Data Annotation Tasks Users can opt in to label data—such as identifying objects in images, classifying content, or tagging sentiment in text.

  • Prompt Engineering Challenges Periodic challenges where users compete to create the best-performing prompts for specific tasks (e.g., best script for an ad), with top entries rewarded and used to improve the prompt-tuning layer of Ruvi’s models.

  • Content Contributions Verified users may contribute text, images, or other datasets for model fine-tuning, governed by community-approved standards.


💎 Token Rewards System

Every valid contribution is tracked and assigned a reward score based on:

  • Value to the training process

  • Uniqueness or quality of the input

  • Community validation (peer reviews, upvotes)

Participants are rewarded in $RUVI tokens, which can be used within the platform or staked for additional benefits.


🤝 Community-Led AI

Eventually, model updates and training priorities can be governed via a decentralized voting system. Token holders will be able to propose and vote on:

  • New datasets to integrate

  • Model fine-tuning directions

  • Ethical use policies

  • Which templates or models to prioritize

This transforms Ruvi into a living, evolving AI ecosystem that reflects the needs and values of its users—not just a central development team.

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