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
Powered by GitBook
On this page
  • Cortensor: A Decentralized AI Inference Platform
  • Core Features
  • Development Roadmap
  • Community and Ecosystem
  • Conclusion
  1. Abstract
  2. Whitepaper

Page5: Summary

Cortensor: A Decentralized AI Inference Platform

Introduction

Cortensor is pioneering the future of AI by developing a decentralized, community-driven AI inference platform. Built on a robust multi-layered blockchain architecture, Cortensor integrates advanced AI capabilities with blockchain technology, providing scalable and reliable AI services. This platform is designed to democratize AI, making it accessible to everyone, from individuals to enterprises, while ensuring high-quality performance and innovation.

Core Features

  1. Decentralized AI Inference:

    • Cortensor enables decentralized AI inference by leveraging community-operated nodes.

    • Nodes perform AI tasks, contributing to the network's overall computational power.

    • The platform supports a wide range of hardware, ensuring inclusivity and broad participation.

  2. Quantization for Inclusivity:

    • Cortensor uses LLM quantization to adapt AI models for various hardware types, from low-end CPUs to high-end GPUs.

    • Quantization allows more devices to participate, expanding the network's capabilities while maintaining cost efficiency.

    • Users can choose between quantized and non-quantized models based on their accuracy and performance needs.

  3. Proof of Inference (PoI) and Proof of Useful Work (PoUW):

    • These unique consensus mechanisms ensure the accuracy and usefulness of AI inference results.

    • PoI validates that nodes perform tasks correctly, while PoUW assesses the practical value of the output.

    • These processes are essential for maintaining the integrity and reliability of the network.

  4. Incentive Structure:

    • Cortensor's incentive system rewards nodes for contributing to the network, including tasks related to PoI, PoUW, and user requests.

    • Nodes earn $COR tokens through basic participation, task execution, and staking.

    • The platform encourages continuous improvement and high-quality contributions, with rewards scaling based on task complexity and node performance.

Development Roadmap

Cortensor’s development is structured across several key phases, each with specific goals and milestones:

  1. Q3 2024: Launch and Genesis

    • Begin staking for $COR tokens and engage the community.

    • Prepare for the closed alpha phase, focusing on mining and network validation.

  2. Q4 2024: Closed Alpha Testing

    • Test core functionalities with selected community members.

    • Focus on AI inference tasks, hardware compatibility, and network stability.

  3. Q1 2025: Open Alpha Launch

    • Expand testing to a broader audience.

    • Collect feedback and refine the platform for wider use.

  4. Q2 2025: User Request Testing (Layer 2)

    • Test user-facing functionalities and real-time task processing.

    • Offer incentives for participation and gather data for optimization.

  5. Q3 2025: Full Integration

    • Combine mining and user request functionalities for seamless operation.

    • Finalize airdrop strategies and reward early participants.

  6. Q4 2025 and Beyond: Testnet and Mainnet Launch

    • Transition from testing phases to a fully operational mainnet.

    • Focus on security, scalability, and real-world application.

Community and Ecosystem

Cortensor’s success hinges on the active participation and engagement of its community. The platform fosters an environment where contributors can collaborate, innovate, and earn rewards through various roles, including model development, validation, and governance participation. As the network evolves, Cortensor aims to establish a vibrant ecosystem of AI services, dApps, and enterprise solutions, with decentralized governance at its core.

Conclusion

Cortensor is not just another AI platform; it represents a paradigm shift in how AI is developed, deployed, and accessed. By combining the power of decentralized networks with cutting-edge AI technologies, Cortensor is paving the way for a more inclusive, efficient, and innovative future in AI. The journey is ambitious, but with the support of a dedicated community and a clear, structured roadmap, Cortensor is well-positioned to become a leader in decentralized AI inference.


Disclaimer: This page and the associated documents are currently a work in progress. The information provided may not be up to date and is subject to change at any time.

PreviousPage4: Development Roadmap and PhasesNextIntroduction

Last updated 9 months ago