Javier Fernandez-Marques recently completed his internship with us at Arm ML Research Lab, working with the Machine Learning team in Cambridge UK, and in Boston, US. During his four months, Javier’s research focused on Winograd convolutions, the very…

Architectural Simulators

Architecture simulators of various kinds are a key tool in the computer architecture toolbox. They provide a convenient model of real hardware, such as a CPU or even a whole System on Chip (SoC), at a level of abstraction that…

Why TinyML?

Researchers have studied neural network compression for quite some time. However, the need for always-on compute has led to a recent trend towards executing these applications on even smaller IoT devices. These devices can have total system…

2019 was yet another year of incredible technology discovery. From healthcare, to food, to artificial intelligence¹, exciting and inspiring advancements have been made across the research community, and Arm Research is no exception. Our teams have shared their…

Microcontrollers (MCUs) are truly the ubiquitous computer of our time. They are tiny, cheap, and low power. They can often be powered indefinitely using a solar cell. They are in your watch, your fridge, and your car contains about 30 of them. The average…

Recurrent Neural Networks (RNNs) are an important class of algorithms. They are used in tasks where the strict order of the input conveys certain information, for example, natural language processing (NLP) and time-series based data. Increasingly, these…

Partnerships are important to us at Arm. We are an ecosystem company, which means that we strive to work together with partner companies for mutual success. This philosophy extends to Arm Research, where partnerships allow us to extend our reach further…

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. Increasingly complex demands have driven the development of smart sensors to monitor…

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, and object tracking and localization. Furthermore…

The Arm ML Research Lab explores cutting edge techniques and state-of-the-art algorithms. One of our primary research thrusts is investigating ways to bring more machine learning applications to Arm's products, and make existing applications more efficient

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 systems (ADAS) in automobiles, and more.…

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 strategy, which guides internal research, external…

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'. To help computer architects get “up to speed” on deep learning, I co…

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…

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.

'Smart Chips, Smart World' was the theme of this year's forum, organized by the Innovation Center for Future…