Machine Learning Blog

The effectiveness and cost efficiency of safety islands are improved when the components interoperate effectively, while retaining freedom of IP choice and subsystem design. Arm and NetSpeed have partnered…

Over the last few years, there’s been a terrific amount of interest in artificial intelligence, and specifically the branch of machine learning known as 'deep learning'. This post provides a brief overview…

This tutorial is for embedded software developers who want to apply Machine Learning on Arm Cortex-M with CMSIS-NN.

Join Arm at Google Next '18 conference to see the latest secure client platforms, along with low-power machine learning at the edge.

Arm recently invested in SWIM.AI’s Series B to accelerate developers in creating the apps that will define the edge computing era.

This blog shares our experience developing our AR and ML demo using Google ARCore and Arm NN in Unity. Throughout this guide I'll point out the most important steps.

Deploying advanced deep learning algorithms on edge devices, especially for computer vision applications like autonomous vehicles and IoT, requires special capabilities.

Designers looking for an open HP cache-coherent chip to chip accelerator interface with an easy migration path from today’s PCIe should consider CCIX for their next SoC.

A number of technological challenges are posed by Augmented Reality (AR) on mobile devices. This blog reviews these, and presents a paper from Arm Research ML Group that seeks to address these challenges…

Rob Aitken is an Arm Research Fellow. Here, he shares his thoughts and key takeaways from the Future Chips Forum, held last December in Beijing.

We are proud to announce the release of two new Mali GPUs, Mali-G52 and Mali-G31, to our Mainstream and Ultra Efficient roadmaps.

Neural Network accelerators as an essential part of bringing ML to life on your device – and whilst it’s true that they have a significant role to play, they’re just one part of the story.

We're excited to announce some of our recent collaborations in mobile and camera tech, some of which we will be showcased at the MWC 2018.

We are launching Project Trillium to kickstart a new wave of invention in the world of artificial intelligence (AI), of which machine learning is a key part.

Arm NN SDK, a key piece of technology that makes it much, much easier to build and run ML applications on power-efficient, Arm-based platforms.

The Arm ML processor is a brand new design for the mobile and adjacent markets - such as smart cameras, AR/VR, drones, medical, consumer electronics

What would you do with a Cortex-M4, a neural network, some Lego and cable ties? Sebastian Förster built a small, four-legged robot and taught it to walk.

Develop your Convolutional Neural Networks using just the Compute Library and a Raspberry Pi with this step-by-step guide.