Embedded Computing Design

Tiera Oliver

January 19, 2026

Today’s AI models are growing exponentially.  The process of building, testing, and running AI models is continuously impacting developers and enterprises everywhere, as they increase in size and complexity and are integrated into various compute platforms.

Naama BAK

January 16, 2026

Documentation for semiconductor products and embedded systems software solutions is extensive, often reaching into thousands of pages. Navigating the mountain of documentation is time-consuming and potentially error-prone.  This translates into high support costs for the companies selling these products and frustration for engineers.

Embedded Computing Design Staff

January 5, 2026

Equipment downtime in a manufacturing facility, or in almost any industrial environment, represents more than just an inconvenience. It is a direct hit to a vendor’s productivity, profitability, and brand. As production lines become more automated and capital-intensive, the tolerance for unexpected failures continues to shrink. That reality is driving manufacturers toward predictive maintenance, where AI and machine learning are used to detect failures long before they result in unplanned shutdowns.

Gary Lin

December 29, 2025

The Secret AI Trio to Make Devices Smarter

System designers increasingly look for platforms capable of handling multiple AI workloads with efficient power consumption and low latency. Recent developments in embedded processors now combine general-purpose compute, graphics acceleration, and dedicated neural processing capabilities into a single System-on-Chip.

This article provides a technical walk-through demonstrating multi-model AI inference performance on the AIMB-2210 Mini-ITX platform featuring the AMD Ryzen Embedded 8000 processor.

Ken Briodagh

December 22, 2025

Video and computer vision are the most impactful applications for AI currently in the embedded industry. Manufacturing, Warehousing and Robotics are using computer vision and video in almost every modern use case, while Smart City Safety and Security is almost entirely focused on video data analysis. And these vertical markets need the AI in the embedded computing at the edge to power their applications and use cases.