Tiny Machine Learning (TinyML) Market is Segmented by Type (C Language, Java), by Application (Agriculture, Manufacturing, Healthcare, Retail). The Tiny Machine Learning (TinyML) market is poised for ...

Aluminum and iconography are no longer enough for a product to get noticed in the marketplace. Today, great products need to be useful and deliver an almost magical experience, something that becomes ...

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, ...

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 ...

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 ...

From cars and TVs to lightbulbs and doorbells. So many of the objects in everyday life have ‘smart’ functionality because the manufacturers have built chips into them. But what if you could also run ...

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 ...

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 ...

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 ...

This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Deep learning models owe their initial success to large ...