This library simplifies the use of TensorFlow Lite Micro on Arduino boards, offering APIs in the typical Arduino style. It avoids the use of pointers or other C++ syntactic constructs that are ...

Abstract: Motion intent recognition for controlling prosthetic systems has long relied on machine learning algorithms. Artificial neural networks have shown great promise for solving such nonlinear ...

Hi, I'm Bill. I'm a software developer with a passion for making and electronics. I do a lot of things and here is where I document my learning in order to be able to inspire other people to make ...

Page 1: NVIDIA’s Jetson AGX Thor Brings Powerful New Tools To Robotics And Edge AI Developers Demos are fun and interesting, but so is writing your own software. Back in June we talked about our own ...

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...

While traditional artificial intelligence (AI) frameworks often struggle in ultra-low-power scenarios, two new edge AI runtime solutions aim to accelerate the deployment of sophisticated AI models in ...

Abstract: With the rapid development of deep learning techniques in mobile and embedded devices, light-weight inference engines (e.g., Paddle Lite and TensorFlow Lite) are emerged. In some real-time ...

This is a port of the TensorFlow Lite Micro Library to the Arduino platform, aimed at enabling Tiny Machine Learning (TinyML) experiments on all Arduino boards with mbed or ESP32 architecture. Tested ...

Google has launched AI Edge Gallery, an open-source platform that enables developers to run advanced AI models directly on Android devices, with iOS support planned for a future release. Released ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...