Machine learning (ML) is no longer the new kid on the block. We’re almost all familiar with the concept of personal assistants, connected homes and a seemingly limitless torrent of gadgets that can improve our lives – as long as we have a data connection…

You’ve got 20 bright teenagers, a classful of robots running on Raspberry Pi Zero and an interest in neural networks (NNs). What do you do next? You dig into an Arm machine learning tutorial and use object detection to control the robots’ behaviour…

This article is part of the Arm Innovator Program, a series created to highlight the work of key technical leaders who are pushing the boundaries of how Arm architecture can enable next-generation solutions.

Meet Ibrahim Abdalkader, an embedded systems…

Overview

This blog is for embedded software developers who want to apply Machine Learning (ML) on Arm Cortex-M. We will show you how to deploy a trained Neural Network (NN) model (using Caffe as an example) on those constrained platforms with the Arm…

Deploying advanced deep learning algorithms on edge devices – especially for computer vision applications like autonomous vehicles and IoT – requires special capabilities. At Brodmann17, our mission is to create practical, neural-network based…

Augmented reality (AR) is a technology where virtual content is overlaid on top of the real world. If you’ve ever played with Snapchat “Lenses” on your mobile phone, to transform a selfie with a cartoon monocle or dog ears, you will…

原文地址：https://community.arm.com/tools/b/blog/posts/arm-nn-sdk

最近，我们宣布推出神经网络机器学习(ML) 软件 Arm NN，这是一项关键技术，可在基于 Arm 的高能效平台上轻松构建和运行机器学习应用程序。

实质上，该软件桥接了现有神经网络框架（例如 TensorFlow 或 Caffe）与在嵌入式 Linux 平台上运行的底层处理硬件（例如 CPU、GPU 或新型 Arm 机器学习处理器）。这样，开发人员能够继续使用他们首选的框架和工具…

Imagine you’re 30 meters down, diving above a reef surrounded by amazing-looking creatures and wondering what species the little yellow fish with the silver stripes is. You could fumble around for a fish chart, if you have one, but what you really want…

It would be really amazing to have a personal assistant in my hands that is actually smart, truly understands my words and responds intelligently to resolve day-to-day tasks. The recent advancements in Machine Learning (ML) make me optimistic that such…

Recently, we announced our neural network machine learning (ML) software, Arm NN, a key piece of technology that makes it much, much easier to build and run ML applications on power-efficient, Arm-based platforms.

In essence, the software provides a bridge…

What would you do with a Cortex-M4, a motor or two, some lego and a few cable ties? Well, if you’re Sebastian Förster, an embedded systems developer based in Germany, the answer is a small, four-legged robot that you’d teach to walk using neural networks…

Artificial intelligence (AI) is a technology that is already impacting our lives, from recognizing who’s in our photos on social media to spotting patterns in medical data, defining the evolution of self-driving cars and running real-time fraud detection…

Neural Networks are becoming increasingly popular in always-on IoT edge devices performing data analytics right at the source, reducing latency as well as energy consumption for data communication. CMSIS-NN is a collection of efficient neural network…

It IS possible to optimize neural network architectures to fit within the memory and compute constraints of microcontrollers – without sacrificing accuracy. We explain how, and explore the potential of depthwise separable convolutional neural networks…

Machine Learning (ML) is moving to edge no doubt. A lot of embedded devices want to have edge computing capability to provide more advanced services, like voice recognition for smart speaker and face detection on surveillance camera. Constructing a solid…

The launch of Arm support for the Android Neural Networks API (NNAPI) sees the release of open-source, optimized neural network operators that deliver significant performance uplift across CPUs and GPUs.

Back in May at Google I/O, we heard the first public…

This year’s High Performance Graphics event takes place in LA 28th-30th July 2017. It brings together the very best of the graphics industry’s researchers, engineers, and innovators to examine the latest innovations in graphics algorithms, architectures…