Machine Learning Blog

As more people use their mobile devices for a range of everyday online tasks, from shopping to banking, the security threat to smartphones and other connected devices is only likely to increase.

Facebook Artificial Intelligence and Arm Compute Library are working together to enable optimal machine learning applications.

Being over four months into my new job at Arm, I'm still learning about the company and all the many areas of technology that we're involved in. One of these areas is machine learning (ML).

This guide shows you how to set up client-server speech transcription deployed as a service running on cloud-hosted Arm servers for just $3.

Arm TechCon 2018 is coming. One highlight is a hands-on workshop with Cortex-A CPU and Mali Graphics technology: Accelerating and Optimizing Machine Learning on Arm Cortex-A, on October 17.

Arm is donating the Arm NN inference engine and software developer kit to Linaro’s Machine Intelligence Initiative, and opening it to external contributions.

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.

The uptake and advancement of new use cases in the smartphone market means previous generation devices eventually won’t be able to run the advanced workloads and use-cases that are becoming increasingly…

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.