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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
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  1. How iG3 Works
  2. iG3 Overall Architecture

Edge Node Layer

The Edge Node Layer forms the foundation of the iG3 network, composed of distributed devices that run AI workloads close to users. These devices process real-time interactions, reduce latency, and preserve privacy by minimizing cloud dependency.

Key Capabilities:

  • Real-time Audio I/O: Supports speech-to-text (STT) and text-to-speech (TTS) locally for instant voice interaction.

  • Local Inference: Runs lightweight AI models such as quantized LLMs, Whisper.cpp, and compact TTS engines directly on-device.

  • On-Device Task Execution: Handles specialized tasks like object detection, surveillance, and sensor data classification.

  • Local Identity Management: Manages decentralized identifiers (DIDs) for secure and verifiable identity.

  • Status Reporting: Periodically sends heartbeats, performance stats, and usage metrics to the AI Gateway.

Software Stack:

  • Dockerized Microservices: Modular services for LLMs, audio processing, and task handlers.

  • K3s (Lightweight Kubernetes): Orchestrates containerized services efficiently on resource-constrained hardware.

  • gRPC or WebSocket: Enables fast and secure real-time communication with the AI Gateway.

  • Edge Agent Daemon: A lightweight background service that handles device coordination, task reception, and model updates.

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Last updated 1 month ago

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