Many people have begun experimenting with using machine learning in embedded systems as the two technologies have become more prominent in today’s society. That approach allows for overcoming many of ...

In this video, embedded systems consultant Martin Schroder outlines ten steps on self learning embedded systems. Embedded systems are everywhere in today’s increasingly complex electronics equipment.

Deep learning, probably the most advanced and challenging foundation of artificial intelligence (AI), is having a significant impact and influence on many applications, enabling products to behave ...

This course will discuss the trends and challenges of modern embedded systems, and introduce fundamental concepts in their design and evaluation. The course topics include 1) models of computation for ...

Deciding on the programming language for your next embedded product may not be as simple as just choosing C. While C has been the industry's go-to workhorse for the past 50 years, its features and ...

Deep learning techniques such as convolutional neural networks (CNN) have significantly increased the accuracy—and therefore the adoption rate—of embedded vision for embedded systems. Starting with ...

Intel wrote a white paper in collaboration with Daedalean, a startup working on machine-learned solutions in the aviation space. Published this week, the report features a reference design for an AI ...

Analytics-driven embedded systems bring analytics to embedded applications, moving many of the functions found in cloud-based, big-data analytics to the source of data. This allows for more efficient ...

One of the biggest dreams anyone has is to make a living doing what they love. For all hackers, makers, and DIYers with a passion for embedded systems, it may make sense initially to pursue embedded ...