Machine Learning Blog

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.

This tutorial shows how to use Streamline on the AlexNet example application from the Compute Library which was demonstrated in the article, Running AlexNet on Raspberry Pi with Compute Library.

We are very excited to be able to announce some of our recent collaborations in mobile and camera technologies, some of which we will be showcased at the Mobile Word Congress 2018 in Barcelona

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.

If you’d like to develop your Convolutional Neural Networks using just the Compute Library and a Raspberry Pi, this step-by-step guide will show you how…

In this blog, I will try to use a sample Convolutional Neural Network (CNN) as an example to descript how to use Arm development solutions to enable Machine Learning (ML) on device.

Arm now supports Android Neural Networks API (NNAPI) with open-source, optimized NN operators that deliver serious performance uplift across CPUs and GPUs

Artificial Intelligence is still in the early stages of adoption, but it is clear that Machine Learning will move to the edge of the network to enable new use cases and drive innovation.

CMSIS-NN is a library of neural network kernels that maximizes the performance & efficiency of DNNs on Cortex-M-based platforms for smart IoT edge devices.

It IS possible to optimize neural network architectures to fit within the memory and compute constraints of microcontrollers without sacrificing accuracy.

Our predictions about how the key themes of AI and Machine Learning (ML), IoT, security and blockchain are likely to begin to make a real difference in the way all of us interact with technology in 20…

Arm's new ML developer site provides resources, product information and a shared knowledge base to help you to tackle your ML challenges at the edge.

A new documentary, Friend In The Machine, explores the role AI and robotics might play in our lives. Jem Davies, who features in the film, ponders whether a machine could ever be a substitute for a human…

Amiko Respiro smart asthma inhalers use machine learning and Arm low-power Cortex-M processors to montior and improve treatments - and change lives.