AGILE-The Blockchain for AGI
  • Introduction
  • Motivation
  • Core Principles
  • On-Chain AGI Registry
    • On-Chain Decentralized GPU Node Registry
    • On-Chain AI Model Registry
    • On-Chain AI Agent Registry
    • On-Chain AGI Training Data Registry
    • On-Chain Model Creation & Decentralized Training
  • On-Chain GPU Bidding Marketplace
  • AGI Council and Governance Framework
    • AGI Council and Transparent Governance
    • AGILedger Governance: Empowering Transparent & Inclusive AGI Innovation
    • AGI Council: Driving Inclusive and Responsible AGI Governance
    • Robust Security and Compliance
    • Adaptive and Scalable Governance
  • Core Components
    • Blockchain Layer
    • Storage Layer
    • Compute Layer
    • Interface Layer
  • User Experience Flows
  • Architecture
    • Layer-1 Blockchain Foundation
    • Smart Contracts & Protocol Modules
    • Oracles & Layer-2 Extensions
    • Advanced Security & Privacy Measures
  • Use Cases
    • Decentralized AGI Marketplace
    • On-Chain Federated Learning
    • Open-Source Model Collaboration
    • Data-Sharing Platform
    • Incentivized Knowledge Graphs
  • Tokenomics
    • Phase 1: Community Rewards Token
    • Phase 2: $AGILE — The Native Utility Token
  • Conclusion
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  1. Architecture

Advanced Security & Privacy Measures

AGILedger ensures ironclad security through advanced cryptographic protections and multi-layered consensus-driven safeguards:

  • Consensus-Driven Security: Leveraging Byzantine Fault-Tolerance and robust PoS mechanisms to guarantee blockchain finality and resilience against attacks.

  • End-to-End Data Encryption: Secure off-chain data storage, cryptographically linked to immutable on-chain references, accessible exclusively by authorized nodes.

  • Zero-Knowledge Proofs (ZKP): Implementing cutting-edge ZKP technology, enabling secure validation of AI training data without disclosing sensitive details, maintaining confidentiality and trust.

Immutable Model Integrity: Digital signatures and on-chain verification processes protect and verify the authenticity and integrity of published and updated AI models, ensuring tamper-proof reliability.

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