Cortensor
  • Home
  • Abstract
    • Value Proposition
    • Whitepaper
      • Page 1: Introduction and Vision
      • Page 2: Architecture and Technical Overview
      • Page 3: Incentive Structure and Tokenomics
      • Page4: Development Roadmap and Phases
      • Page5: Summary
  • Introduction
    • What is Cortensor?
    • Key Features & Benefits
    • Vision & Mission
    • Team
  • Getting Started
    • Quick Start Guide
    • System Requirements
    • Installation & Setup
      • Getting Test ETH
      • Setup Own RPC Endpoint
      • Router Node Setup
        • Router API Reference
  • Core Concepts
    • Decentralized AI Inference
      • Community-Powered Network
      • Gamification and Quality Control
      • Incentive Structure
    • Universal AI Accessibility
    • Multi-layer Blockchain Architecture
  • Technical Architecture
    • Design Principles
    • Node Roles
    • Node Lifecycle
      • Ephemeral Node State
    • Node Reputation
    • Network & Flow
    • Type of Services
    • Coordination & Orchestration
      • Multi-Oracle Node Reliability & Leadership Rotation
    • AI Inference
      • Open Source Models
        • Centralized vs Decentralized Models
      • Quantization
      • Performance and Scalability
    • Consensus & Validation
      • Proof of Inference (PoI) & Proof of Useful Work (PoUW
      • aka Mining
      • Proof of Useful Work (PoUW)
      • Proof of Useful Work (PoUW) State Machine
        • Miner & Oracle Nodes in PoUW State Machine
      • Sampling in Large Distributed Systems
      • Parallel Processing
      • Embedding Vector Distance
    • Multi-Layered Blockchain Architecture
    • Modular Architecture and Smart Contract Interactions
      • Session Queue
      • Node Pool
      • Session Payment
    • Mining Overview
    • User Interaction & Node Communication
      • Session, Session Queue, Router, and Miner in Cortensor
    • Data Management
      • IPFS Integration
    • Security & Privacy
    • Dashboard
    • Development Previews
      • Multiple Miners Collaboration with Oracle Node
      • Web3 SDK Client & Session/Session Queue Interaction
    • Technical Threads
      • AI Agents and Cortensor's Decentralized AI Inference
    • Infographic Archive
  • Community & Ecosystem
    • Tokenomics
      • Network Incentive Allocation
      • Token Allocations & Safe Wallet Management
    • Staking Pool Overview
    • Contributing to Cortensor
    • Incentives & Reward System
    • Governance & Compliance
    • Safety Measures and Restricted Addresses
    • Buyback Program
    • Liquidity Additions
    • Partnerships
      • Partnership Offering for Demand-Side Partnerships
    • Community Testing
      • Closed Alpha Testing Phase #1
        • Closed Alpha Testing Phase #1 Contest: Closing & Winners Announcement
      • Closed Alpha Testing Phase #2
      • Closed Alpha Testing Phase #3
      • Discord Roles & Mainnet Privileges
      • DevNet Mapping
      • DevNet Modules & Parameters
    • Jobs
      • Technical Writer
      • Communication & Social Media Manager
      • Web3 Frontend Developer
      • Distributed Systems Engineer
  • Integration Guide
    • Web2
      • REST API
      • WebSocket
      • Client SDK
    • Web3
      • Web3 SDK
  • Use Cases
  • Roadmap
    • Technical Roadmap: Launch to Next 365 Days Breakdown
    • Long-term Vision: Beyond Inference
  • Glossary
  • Legal
    • Terms of Use
    • Privacy Policy
    • Disclaimer
    • Agreement for Sale of Tokens
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On this page
  • Key Differentiators
  • 1. Gamified Supply-Side Quality Control
  • 2. Dynamic Node Capability Assessment
  • 3. Balanced Supply and Demand Approach
  • 4. Incentivized Participation
  • 5. Flexible Consumer Subscription Model
  • 6. Potential for Synthetic Data Generation
  • Addressing Adaptation and Supply Problems
  • Gamification as a Solution
  • Token Economics
  1. Abstract

Value Proposition

Cortensor offers a decentralized AI inference platform that combines gamified quality control, dynamic node capability assessment, and flexible privacy options through a Layer 2/3 blockchain architecture. This results in a scalable, efficient, and reliable AI inference service addressing supply and demand challenges, while incentivizing participation and maintaining high-quality standards.

Key Differentiators

1. Gamified Supply-Side Quality Control

  • First Layer (Supply Building): Nodes participate in periodic, randomized "games" answering questions on various topics, allowing continuous quality assessment and capability categorization. This ensures a high-quality, well-categorized supply of inference nodes.

  • Second Layer (Demand Matching): Consumers subscribe to inference services, and tasks are matched to nodes based on their capabilities, effectively managing both supply and demand.

2. Dynamic Node Capability Assessment

  • The gamification process allows Cortensor to maintain an up-to-date understanding of each node's capabilities, enabling precise matching of tasks to nodes. This improves efficiency and performance compared to static classifications.

3. Balanced Supply and Demand Approach

  • Cortensor comprehensively addresses both supply and demand. The first layer builds a quality-controlled supply, while the second layer efficiently matches this supply to consumer demand.

4. Incentivized Participation

  • Gamification serves as a quality control mechanism and incentivizes node operators to continuously maintain and improve their performance, fostering a more engaged and competitive supply-side ecosystem.

5. Flexible Consumer Subscription Model

  • Consumers can subscribe to inference services based on specific needs, offering more flexibility than fixed-tier systems used by competitors.

6. Potential for Synthetic Data Generation

  • The gamification process generates valuable question-answer data for training and improving AI models, offering an additional value stream.

Addressing Adaptation and Supply Problems

Gamification as a Solution

  • Engagement and Community Building: Increases engagement and fosters a sense of community among participants.

  • Quality Control: Ensures continuous quality control and categorization of nodes, maintaining a high standard of service for consumers.

  • Incentives: Rewards participants, creating a competitive environment similar to Bitcoin mining, incentivizing node operators to join and stay active.

Token Economics

  • Token Incentives:

    • Base Rewards: Tokens for basic network participation and liveness checks.

    • Performance-Based Rewards: Additional tokens for high performance in the gamified evaluation process and successful completion of inference tasks.

  • Staking Mechanism: Allows node operators to stake tokens for participation in higher-value tasks, ensuring vested interest in network quality.

  • Dynamic Token Pricing: Adjusts token rewards based on network demand and supply, ensuring tokens remain valuable and attractive for participants.

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Last updated 4 months ago