AI and ML blog

This blog introduces how to deploy a PP-OCRv3 English text recognition model on Arm Cortex-M55 processor with Arm Virtual Hardware.

In this blog post, read about advancements in ML with Arm NN 2021.

As first step to deploy your NN model on Ethos-U, Vela Compiler is open-source and easy-use. Try it out and embrace the improvement of ML ability brought by Ethos-U to embedded system.

This blog post explains how to optimize a trained deep neural network model to run on Ethos-U55 and Ethos-U65.

This year’s Arm DevSummit Developer Competition winner explains how his wildfire detection solution uses tech to tackle real-life sustainability issues.

This Blog mainly introduced how Paddle-Lite improves performance of mobile devices with Arm technology, especially for CPU and Mali GPU.

Learn more about how the future of smart camera technology will bring with it profound transformations in the way we interact with each other and the world around us.

Build and deploy embedded machine learning applications for Arm Cortex-M55 CPU and Arm Ethos-U55 NPU with Arm ML Embedded Evaluation Kit.

Learn more about how to use Arm Streamline to profile different machine learning workloads for your applications.

This blog will show you how to train and quantize a recurrent neural network using TensorFlow, then unroll it ready for deployment on Arm Ethos-U55.

On-device face recognition with RGB cameras on digital televisions (DTVs) is set to become an increasingly important feature for users. Read more in this post.

In this blog we present a TinyML image recognition demo, on an Arm Cortex-M processor, using TensorFlow along with CMSIS-NN for optimized performance.

In this guest blog post, from Kentaro Niikura, read about how Renesas is implementing an advancement in AI.

How to convert models to run Ethos-U55 and Ethos-U65 for models trained in PyTorch.

This blog discusses the growth of smartwatches and how Arm is delivering processor power and efficiency capabilities for these devices.

Demand for compute is increasing, yet carbon emissions must be reduced. Machine learning can make workflows more efficient, reducing their carbon footprint.

Moving from SSE to Arm Neon is a transition many developers are looking to make, with many already making the jump to Neon. In this blog we look at an easier way to achieve this process, and the steps…

How do you enable your robot to navigate the complexities of world and be successful with the tasks & jobs you give them? Think about the elements that go into SLAM and learn about best practices for deployment…

This blog post is about sharing our experience in running PyTorch Mobile with NNAPI on various mobile devices. I hope that this will provide developers with a sense of how these models are executed on…

This blog explains how developers can create fitness and exercise applications on Smart TVs for the end-user.

This blog explains how to get real time results with CNN inference for Augmented Reality (AR) on Mobile.