Arm ML Research Lab

Machine learning is finding increasing application across all compute tasks. Our research enables the ubiquitous application of energy-efficient machine learning by developing advanced hardware, software, and algorithms for this rapidly evolving area.
Accelerate Machine Learning

Our researchers are developing advanced, energy efficient hardware, software, and tools to support complex algorithms. Explore the Arm Research Impact Report 2021 to learn more.

More blogs

Machine Learning

Sparse Architecture Search (SpArSe): Democratizing and Enabling TinyML on Arm M-class

Igor Fedorov

Microcontrollers (MCUs) are the ubiquitous computer of our time, being tiny, cheap, and low power. Often powered by using solar cell, they are in your watch, fridge, and your car will contain about thirty…
- December 2, 2019
Skipping RNN State-updates Without Retraining the Original Model

Urmish Thakker

Recurrent Neural Networks (RNNs) are used in tasks where the strict order of the input conveys certain information, and so are classed as an important algorithm. These networks are being deployed on resource…
- November 25, 2019
Collaboration Case Study: Machine Learning Hardware with Harvard University

Paul Whatmough

University engagements play a significant role in our partnerships at Arm Research, helping us extend our reach and build understanding of technologies as they emerge. Harvard University is one of those…
- November 18, 2019
Alpha-Blending: Quantizing networks without using the STE

Matthew Mattina

Increasingly, intelligent applications are using neural networks at their core to deliver new functionality to users. These applications include language understanding and translation, image recognition…
- August 16, 2019
Taking Constrained ML to the Next Level

Charlotte Christopherson

One the primary research thrusts of our ML Research Lab is investigating ways to bring more machine learning applications to Arm's products, and to make existing applications more efficient.
- August 6, 2019
Efficient Hardware for Mobile Computer Vision via Transfer Learning

Paul Whatmough

Mobile computing is on the rise, and currently moving into some really exciting new applications and form factors – augmented reality (AR) glasses, unmanned aerial vehicles (UAVs), automated driver assistance…
- April 1, 2019
The Arm Research Workshop on Novel Algorithms

Bo Eyole

Arm Research is responsible for delivering a clear vision of disruptive and emerging technologies, and how they may affect our future. This disruptive technology landscape is used to develop our research…
- November 19, 2018
Giving a flexible edge to the IoT

Charlotte Christopherson

As the Internet of Things (IoT) continues to revolutionise our daily lives, the demand for smaller, smarter, and more diverse flexible technology has never been greater. A new collaborative project is…
- November 13, 2018
A Deep Learning Survival Guide for Computer Architects

Paul Whatmough

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…
- July 25, 2018
Arm ML Research Enables Augmented Reality Mobile Apps through Low-Power Machine Learning

Paul Whatmough

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…
- May 11, 2018
Smart Chips, Smart World: Future Chips Forum

Rob Aitken

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.
- April 30, 2018