While machine-learning (ML) development activity most visibly focuses on high-power solutions in the cloud or medium-powered solutions at the edge, there is another collection of activity aimed at ...

TinyML is a generic approach for shrinking AI models and applications to run on smaller devices, including microcontrollers, cheap CPUs and low-cost AI chipsets. While most AI development tools focus ...

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 ...

As device sensors proliferate across every company’s value chain – from new product development through inspection, tracking, and delivery – tinyML is surfacing to provide actionable insights, ...

A team in Argentina is using sensors based on TinyML technology to study Chelonoidis chilensis tortoises. Little is known about its biology and the species is in a vulnerable state. The small sensors, ...