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
        • Dedicated Ephemeral Node Setup
        • Reverse Proxy Setup
  • 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
    • Developer Ecosystem
    • 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
      • Closed Alpha Testing Phase #4
      • 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
  • Overview
  • Key Use Cases
  • Benefits of Using IPFS
  • Summary
  1. Technical Architecture
  2. Data Management

IPFS Integration

Cortensor leverages the InterPlanetary File System (IPFS) to enable decentralized, content-addressable storage and distribution of data. This integration supports Cortensor’s core mission to deliver scalable, verifiable, and censorship-resistant AI services without relying on centralized infrastructure.

Overview

IPFS is a peer-to-peer distributed file system that allows files to be stored and accessed using content hashes rather than traditional URLs. In Cortensor, IPFS plays a crucial role in ensuring integrity, traceability, and decentralization across various stages of the AI inference workflow.

Key Use Cases

1. Inference Input & Output Storage

When users submit large input files (e.g., datasets, documents, media) or receive output files from inference tasks, Cortensor stores these files on IPFS.

  • Ensures tamper-proof and immutable storage.

  • Files are retrieved using content hashes, enabling verifiable access.

  • Keeps heavy data off-chain while maintaining transparency and accessibility.

2. Synthetic Dataset Generation & Distribution

Cortensor’s synthetic data engine generates datasets used for training and fine-tuning AI models. These are distributed using IPFS to ensure open, reproducible access.

  • Datasets are versioned, content-addressed, and publicly auditable.

  • Enables decentralized data sharing for AI researchers and developers.

  • Reduces reliance on centralized hosting services.

3. Cross-Node Task Data Sharing

In distributed AI inference, miners require access to task-related data such as prompts, configurations, and session metadata. Cortensor uses IPFS to:

  • Provide reliable access to shared data across geographically distributed nodes.

  • Facilitate coordination between session queue, session module, and miners.

  • Eliminate bottlenecks caused by centralized APIs.

4. Oracle Proof & Audit Trail

Cortensor’s oracle and validation modules may reference inference results or proof artifacts stored on IPFS:

  • Content hashes are written to the blockchain for lightweight verification.

  • Enables decentralized audit trails for AI outputs and session behavior.

Benefits of Using IPFS

Feature
Benefit

Decentralization

Eliminates reliance on centralized storage providers.

Content Addressing

Ensures integrity and immutability of input/output data.

Scalability

Offloads storage-heavy operations from on-chain systems.

Interoperability

Easily integrated with Web3 clients, smart contracts, and developer SDKs.

Censorship Resistance

Promotes open and resilient AI infrastructure.

Summary

The integration of IPFS within Cortensor reinforces the network’s commitment to openness, trust, and verifiability. Whether serving input/output for inference, sharing synthetic datasets, or providing audit trails for oracle validation, IPFS plays a foundational role in supporting Cortensor's decentralized AI ecosystem.

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Last updated 2 months ago