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  • 🚄iG3: The Edge Network for Real-Time AI Interaction
    • ✍️Problem
    • 💡iG3 Solution
  • How iG3 Works
    • 🏗️iG3 Overall Architecture
      • Gateway Layer
      • Edge Node Layer
        • Node Architecture Overview
      • Decentralized Layer
  • 🧠iG3 Tokenomics
    • General Information
    • Utility
    • Conversion Process
  • 💰Reward Mechanism
    • Regional Fairness
  • Products
    • 💻iG3 Edge Devices
      • M1 Agent Device
        • Key Features of the M1 Edge Device
        • Hardware Specifications
        • Power Consumption
        • M1 Agent Device Sales
  • 📘User Guides
    • M1 Setup Guide
    • How to Check Token Balance
  • ❓Frequently Asked Questions (FAQs)
    • Devices
  • Growth & Plan
    • ⛳Roadmap
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  • The Latency Gap in Cloud AI
  • Centralization Risks
  • Scalability and Cost
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  1. iG3: The Edge Network for Real-Time AI Interaction

Problem

The Latency Gap in Cloud AI

Cloud inference platforms often take several seconds to respond to voice or video prompts. In use cases like language tutoring, customer service, or gaming, this latency breaks immersion and utility.

Centralization Risks

The centralized nature of today’s AI platforms poses risks around control, surveillance, and censorship. Users must trust that their data is handled ethically.

Scalability and Cost

Hosting LLMs at scale in cloud infrastructure becomes economically unsustainable when applied to millions of daily users or devices.

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Last updated 1 month ago

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