How tinyML differs from mainstream machine learning. How tinyML is being applied. What are some of the better-known tinyML frameworks, and where can you get more information? In the ebb and flow of ...

Tiny Machine Learning (TinyML) represents a transformative shift in deploying machine learning algorithms on resource‐constrained Internet of Things (IoT) devices. By enabling on-device inference and, ...

The combination of X925, A725, and A520 cores, Arm’s most powerful mobile CPU cluster for AI to date, brings 46% better performance than CPU clusters based on the Cortex-X4 released ...

There is a rapidly growing need for power-efficient artificial intelligence (AI) to run on smaller devices at the edge. Power-hungry edge devices send massive amounts of data to and from the cloud. At ...

The implications of TinyML accessibility are very important in today’s world. For example, a typical drug development trial takes about five years as there are potentially millions of design decisions ...

Infineon Technologies announced on May 16 the acquisition of Sweden-based startup Imagimob AB, a platform provider for machine learning solutions for edge devices. With this acquisition Infineon ...

Infineon’s recent acquisition of Imagimob, a Stockholm, Sweden-based supplier of TinyML platforms, raises a fundamental question: where the chip industry stands in adopting and accelerating this ...

Advanced semiconductor solutions provider Renesas Electronics Corporation released an update on its progress in providing artificial intelligence (AI) and tiny machine learning (TinyML) solutions one ...