Arm’s ARMv8.1-M architecture specification redefines its microcontroller offerings (Fig. 1). It includes the company’s Helium technology, which addresses machine-learning (ML) applications. Arm ...

STMicroelectronics (NYSE:STM) is ready to launch its new series of microcontrollers with machine learning capabilities in high volumes. The Switzerland-based company said the STM32N6 microcontroller, ...

Well, there's always something unexpected going on here in the Pleasure Dome (my office). Just a few days ago, for example, I received an email from author and lecturer Don Wilcher … Don explained ...

I am in the process of updating my book "Electronics Explained," published by Newnes/Elsevier. The book is essentially a basic electronics text for those learning about electronics for the first time.

CMSIS-NN is an open-source library of optimized software kernels that maximize NN performance on Cortex-M cores with minimal memory footprint overhead. Machine learning (ML) algorithms are moving to ...

TAINAN, Taiwan, June 30, 2020 (GLOBE NEWSWIRE) -- Himax Technologies, Inc. (Nasdaq: HIMX) (“Himax” or “Company”), a leading supplier and fabless manufacturer of display drivers and other semiconductor ...

As a result, this project is set up as a how-to for others looking to dive further into the world of microcontrollers that don’t have the same hand-holding setup as the Arduino. To take care of the ...

TOKYO--(BUSINESS WIRE)--Renesas Electronics Corporation (TSE:6723), a premier supplier of advanced semiconductor solutions, today announced the qualification of their RX65N Group of microcontrollers ...

What’s the best way to learn electronics? It’s a pithy question to ask a Hackaday audience, most of whom are at least conversant in the field already. Those who already have learned often have just ...

“You know the feeling: You see an old 14.4 kbit/s modem and suddenly you get that urgent need to cut it open and turn it to a beautiful, sleek, high-tech, and absolutely useless clock that can run on ...

Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there ...