Matrix Layer Protocol
  • I. Project overview
  • II. The Contradiction between Terminal Devices and Centralized Networks
    • 1. Data Control and Privacy Issues
    • 2. Decentralization Needs and Hardware Bottlenecks
    • 3. Market Monopoly of Centralized Platforms
    • 4. High Costs and Low Efficiency of Decentralized Networks
    • 5. The Contradiction of Terminal Devices as Data Entry Points
    • Trends in Solutions
  • III. Technical Solution: AI-Driven Terminal Device Network Communication Method
    • 1. AI-Driven Intelligent Routing and Peer-to-Peer Data Transmission
    • 2. AI Applications in Decentralized Networks
    • 3. AI Computing Power Management for Terminal Devices
    • 4. Data Privacy and Security Protection
    • 5. Adaptive Network Communication Protocol
  • IV. Technical Advantages and Protocol Value of MLP
    • 1. Technical Advantages
    • 2.Protocol Value
  • V. MLPhone: Application Product Based on MLP
    • 1. Decentralized Communication and Data Management
    • 2. Decentralized Finance (DeFi) and UBI Identity Verification
    • 3. Smart IoT Device Management and Integration
    • 4. Access to Metaverse and Web3 Applications Leveraging
    • 5. AI and Automated Device Management
  • VI. AI Ecosystem Platform Overview
    • 1. AI Ecosystem Platform - AICIAR Platform Introduction
    • 2. Introduction to AI Investment Advisor
    • 3. Introduction to other AI components
  • VII. The Ecological Application Development of MLP and MLPhone
    • 1. Expansion of Decentralized Device Network
    • 2. Ecological Development of Digital Identity and Data Autonomy
    • 3. Decentralized Finance Ecological (DeFi)
    • 4. Support for Web3 and the Metaverse Ecological
    • 5. Development and Ecological Prosperity of Decentralized Applications (DApp)
  • VIII. Token Economic Model and Mechanism
    • 1. Token Allocation
    • 2. Basic Pool Mining (PoW)
    • 3. NFT Series
    • 4. Accelerated Pool Staking (PoS)
    • 5. Promotion Incentive
  • IX. MLP and MLPhone Project Development Roadmap
  • X. Token Investment Risk Notice
    • 1. Market Volatility Risk
    • 2. Technical Risk
    • 3. Privacy and Data Security Risk
    • 4. Regulatory and Legal Risk
    • 5. User Operation Risk
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  1. III. Technical Solution: AI-Driven Terminal Device Network Communication Method

3. AI Computing Power Management for Terminal Devices

MLP has fully considered the computing power and power consumption issues of terminal devices in its design. Through AI algorithms, the protocol can intelligently manage the computing power resources of terminal devices, ensuring that computing resources are optimally allocated during data transmission or network interaction. This not only effectively reduces the power consumption of devices but also enhances the long-term participation ability of devices in decentralized networks.

In specific application scenarios, smart devices like MLPhone achieve intelligent management of device computing power through MLP. AI can determine when to perform full-power computing and when to hand off some tasks to other nodes, thereby reducing the computational load of the device. This distributed computing power management mechanism allows terminal devices to maintain efficient power management even when participating in a large number of computational tasks in decentralized networks.

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Last updated 6 months ago