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.

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 ...

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 ...

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 ...

Below is a curated list of machine learning development providers that stand out in 2026 for their ability to build enterprise-grade ML solutions tailored to complex business environments.

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 ...

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 ...

Key to the performance, low power and low memory bandwidth capabilities of CDNN is the CEVA Network Generator, a proprietary automated technology that converts a customer's network structure and ...

Some of the most valuable events at DAC are the IP Track sessions, which give small and midsize companies a chance to share innovations that might not get much attention elsewhere. The use of IP in ...

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 ...