edge-ai · GitHub Topics · GitHub
Skip to content
#

edge-ai

Edge Computing and Artificial Intelligence of Things (AIoT) involve performing localized data processing directly on edge devices rather than relying entirely on centralized cloud servers. This architectural approach combines Internet of Things (IoT) hardware with optimized, lightweight machine learning models to enable real-time decision-making, drastically reduce network latency, and improve overall data privacy and bandwidth efficiency.

Here are 3,124 public repositories matching this topic...

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

  • Updated Oct 28, 2025
  • Python
OGAM

The Swiss Army Knife of Offline AI. Chat, see, speak, and generate images on your phone or Mac — GGUF LLMs, vision, Whisper speech-to-text, Stable Diffusion, tool calling, and local-network servers. Runs on your CPU, GPU, or NPU. No account, no API key, zero data leaves your device.

  • Updated Sep 6, 2026
  • TypeScript
Biodiversity

Microsoft AI for Good Lab — Biodiversity research hub. Open-source AI models, edge devices, and tools for biodiversity monitoring and conservation. Your source for MegaDetector, SPARROW, PytorchWildlife, Bioacoustics, and more.

  • Updated Aug 25, 2026
  • Python

Real-time voice assistant — WebRTC streaming, faster-whisper ASR, local LLM, Vui Nano (300M) TTS. OpenAI Realtime API compatible. Voice cloning, barge-in, ~9× realtime on a 4090. Apache 2.0.

  • Updated Sep 2, 2026
  • Python
Followers
106 followers
Website
github.com/topics/edge-computing
Wikipedia
Wikipedia