Popular GitHub Repositories for Analog Devices

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba. Full multimodal LLM Android App:[MNN-LLM-Android](./apps/Android/MnnLlmChat/README.md)

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

An open source AI wearable device that captures what you say and hear in the real world and then transcribes and stores it on your own server. You can then chat with Adeus using the app, and it will have all the right context about what you want to talk about - a truly personalized, personal AI.

A Curated list of IoT Security Resources

Enabling PyTorch on XLA Devices (e.g. Google TPU)

Connect home devices into a powerful cluster to accelerate LLM inference. More devices means faster inference.

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

Deep learning gateway on Raspberry Pi and other edge devices

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

RL research on Android devices.

Realtime AI speech with OpenAI Realtime API on Arduino ESP32 with Secure Websockets and Deno edge functions with >10min uninterrupted conversations globally for AI toys, AI companions, AI devices and more

EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]

Fast Multimodal LLM on Mobile Devices

Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019

The open-source iOS app that's making quality voice transcription more accessible on mobile devices.

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory

The World's Leading Cross Platform AI Engine for Edge Devices

The Qualcomm? AI Hub Models are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm? devices.