Multiple Network
  • Multiple Network
    • Intro
    • Problem
    • The Purpose
  • 🔥TESTNET
    • Testnet Timeline
    • Testnet Guide
      • For Windows Users
      • For Linux Users
      • For Chrome Users
  • 🚀Multple Product
    • Architectural Breakdown
      • Introducing De-WAN
      • AI Acceleration
      • AI Privacy
      • DeAI
    • Key Features & Edges
    • Potential Opportunities with Multiple Network
  • 🪙Multiple Tokenomics
    • MTP Token
    • Tokenomics
  • Resourse
    • FAQ
    • Roadmap
    • Investors
    • UPnP Enabling Guide
    • Referral Link
    • Social Media Links
    • Glossary
Powered by GitBook
On this page
  1. Multple Product
  2. Architectural Breakdown

AI Acceleration

Enhancing the speed of AI model training and inference, as well as network stability.

  • High Bandwidth and Low Latency: Through optimizations based on P2P and SD-WAN technologies, Multiple Network aggregates the bandwidth of distributed nodes to provide high-speed data transmission services. This feature enables AI models to acquire and transmit data at faster speeds during training and inference phases.

  • Stability Assurance: The dynamic routing optimization technology of SD-WAN can switch to the best path during network interruptions or high traffic, ensuring stable data flow and reducing fluctuations during transmission.

  • Cross-Regional Data Synchronization: Rapidly synchronizing distributed datasets globally to shorten training and inference times, particularly suitable for tasks requiring real-time responses, such as search engine interactions or large-scale data processing.

PreviousIntroducing De-WANNextAI Privacy

Last updated 29 days ago

🚀