BOINC AI White paper
  • 🌍Abstract
  • 🌍1. BOINC AI Background
    • 1.1 Introduction to BOINC AI
    • 1.2 Introduction to BOINC AI Technology
    • 1.3 Supported AI Projects
  • 🌍2. BOBchain
    • 🌍2.1 BOBchain background
      • 2.1.1 AI development is proportional to arithmetic demand
      • 2.1.2 There is a paradox of sequencing between industry landing and technology diffusion
      • 2.1.3 Uneven Distribution of Arithmetic Power, and Lack of a Firm Community Base
      • 2.1.4 Lack of Mechanisms to Achieve Economic Circularity;
    • 2.2 Overview
    • 🌍2.3 Technical Features
      • 2.3.1 L1 Layer Network
      • 2.3.2 L2 Layer 2 Network
      • 2.3.3 PoVC Arithmetic Contribution Value Consensus
      • 2.3.4 Decentralized Distributed Storage of Encrypted Data;
      • 2.3.5 Proof of Zero Knowledge
      • 2.3.6 Blockchain Standardization for AI
  • 🌍3. BOINC AI Miner
    • 3.1 Hardware Binding and Verification
      • 3.1.1 Binding the Miner to the Chain
      • 3.1.2 Zero proof of knowledge is used for miner registration
      • 3.1.3 Mining Group Network Validation
      • 3.1.4 Compatible Smart Contracts
    • 3.2 Node Client
      • 3.2.1 Initialization of the Mining System
      • 3.2.2 Miner Hardware Identifier
      • 3.2.3 Proof of zero knowledge of the miner is submitted for validation
    • 3.3 AI Training and Validation
      • 3.3.1 Data Hashing
      • 3.3.2 Random Sampling
      • 3.3.3 Validating the AI Model
  • 🌍4. Data Privacy and Security
    • 4.1 Model Confirmation and Training Data Privacy and Security
    • 4.2 Distributed Cryptographic Storage
    • 4.3 Zero-knowledge proof protects user privacy
  • 🌍5. Artificial Intelligence Ecology
    • 5.1 BOINC AI Miner Community
    • 5.2 Web3 Standards for AI Ecology
    • 5.3 Decentralised Model Rental and Trading Marketplace
    • 🌍5.4 BOINC AI Foundation
      • 5.4.1 Overview
      • 5.4.2 Strategic Decision Committee
      • 5.4.3 Committee on Technology Development
      • 5.4.4 Public Relations Committee
      • 5.4.5 Secretariat
      • 5.4.6 Token economy model
    • 5.5 BOINC AI Team
    • 5.6 BOINC AI Development Roadmap
  • 🌍6. Super AI and AI Company
    • 6.1 Super AI Backgroud
    • 6.2 What can AI company do on the platform
    • 6.3 How does AI company issue STO tokens
    • 6.4 How to invest in AI companies in the miners
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  1. 4. Data Privacy and Security

4.2 Distributed Cryptographic Storage

The AI training model and data are stored in multiple nodes in a decentralized manner through encryption algorithms. Only those who hold the key can access it, preventing illegal access and tampering during transmission and storage. Meanwhile, in distributed encrypted storage, the data is first split into multiple segments, then encrypted separately, and then stored separately on different nodes. Zero knowledge is required to prove, decrypt, restore, and combine in order to restore the complete data.

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Last updated 1 year ago

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