Embedded Computing Design

There are many different ways to look at the tangled web of AI. For example, tackling from the inference perspective is one way of looking at the puzzle, as not everyone is doing that. 

Avnet recently surveyed part of its core audience, and the topic was AI’s Impact on Engineering. It doesn’t get much closer to home than that. 

The user interface, aka the HMI, is oftentimes the only interaction a user has with a platform. Hence, it represents your brand, and it needs to look great and work great.

There’s no moss gathering under the Connectivity Stands Alliance, as the group recently announced the latest rev of the ZigBee spec, version 4.0. This new version enhances the security efforts from the previous generation, and also takes a hard look at smart energy in the latest devices. 

One of the keys, as you’ll hear, is the backward compatibility that’s been maintained. Faisal Bhaiyat, the Co-Chair of ZigBee Working Group, Connectivity Standards Alliance, and also a Senior Software Architect with Silicon Labs, fills me in on the details on this week’s Embedded Executives podcast.

High-performance computing at the Edge involves systems that bring server-class processing closer to where data is generated. Instead of sending private information to the Cloud, devices at the network’s Edge, gateways, sensors, industrial controllers, cameras, and embedded AI platforms, run complex workloads locally. This is beneficial for applications like medical imaging, Edge servers, networking, and enterprise-level LLM (Large Language Model) deployment, and includes markets such as healthcare, industrial automation, smart cities, robotics, automotive, and advanced consumer devices. Its growth is driven by tighter latency requirements, rising data volumes, stronger privacy demands, and the need for more efficient, scalable distributed compute architectures.

You’re likely aware of many of the great things AI can do for you. And I’m guessing you’ve seen many of the nefarious things it can be used for. I was just brought up to speed on one of the latter items, and it’s something you should be aware of as well. 

In my discussion with Marcus Webster, the Founder and President of Webster and Webster Associates, I learned that people are using AI to help them get jobs, and in some cases, they are jobs that they should not be getting, for security reasons. People are submitting fake resumes and even conducting fake video-based job interviews. Honestly, it’s both fascinating and scary. 

Check out this week’s Embedded Executives podcast to learn more.

Hello Embedded Engineers, Developers and Makers! Welcome to In Case You Missed it: Embedded Insights, the weekly news show all about Embedded technologies and solutions from Embedded Computing Design.

Most of the RISC-V offerings that I’ve seen have been pushing very high performance, with lots of cores and lots of chips. Upbeat Technology is taking a different tack by looking at very low power levels. 

In my discussion with Jerry Chen, Founder and CEO of Upbeat Technology, he explains the reasons for that approach, and, as you’ll hear, he tells it like it is and explains why the company partnered with SiFive. 

The applications that make sense for the Upbeat offering include always-on IoT, wearables, drones/UAVs, smart audio, predictive maintenance, and edge-AI sensors, basically anything battery-powered. Hear our discussion on this week’s Embedded Executives podcast.

In this episode of Embedded Insiders, the VP of Sales and Business Development at Gateworks Corporation, Kelly Peralta, joins me to discuss the trends, challenges, and innovations surrounding Wi-Fi HaLow for industrial and IoT applications.

The next segment is sponsored by Analog Devices, and Contributing Editor, Rich Nass, and Analog Devices’ Senior Vice President of Software and Digital Platforms, Rob Oshan, discuss the complexity of designing AI systems and how Analog Devices’ CodeFusion Studio, which includes an IDE, a software development kit, and coding tools, is designed to accelerate the process. 

Check out the embedded world North America 2025 Best-in-Show winners. 

There are lots of semiconductor vendors that do a great job of providing AI hardware. But unfortunately, for many of them, their offerings end there, requiring developers to source software and tools from multiple sources. It’s no secret that designing a system with AI is complex enough. Having to go to different vendors for different pieces just adds multiple layers of complexity.