When content gets posted to Embedded Computing Design that’s latest “The Basics of …” or “XYZ 101,” the content usually gets tons of page views. I always wondered why that was the case. Are our engineers not as knowledgeable as we think? Are they just checking to make sure their assumptions are correct? I decided this would be a good topic for Vin, who teaches classes in some of these basics. Check out this edition of DevTalk with Rich and Vin to see the response.
When it comes to the ecosystem, particularly around AI, you need all the parts to be available if you want to develop a system. We know that ecosystems forever continue to evolve, but it’s safe to dive into the waters at this point, according to Mohammed Dogar, the Vice President and Head of Global Business Development and Ecosystem at Renesas Electronics. In this week’s Embedded Executive podcast, we discuss, among other things, how the AI ecosystem has evolved, and what users can expect at this point.
Wearable medical devices are poised to take off. I mean, really take off, thanks to a few different drivers, such as the aging population, the pandemic, and some concessions from the insurance companies.
There’s a lot going on in the background of your design. In fact, in most cases, 90% (or more) of the development time is spent on things other than the HMI. However, it’s that HMI that gets all the attention because it’s the part of the design that the end user actually sees and interacts with.
Admit it—you’re confused by all the “information” that’s circulating regarding how to design a system with AI. The first thing that must be clear is this: you are not designing an AI system.
Developers struggle with how to manage the power in their end devices. There’s obviously a tradeoff between performance and how much/how long to keep components powered up. It’s obviously application-specific, but it’s important to make the right decision.
It’s the little things in life, right? In the case of NXP’s new top-side cooling for RF power, that’s exactly right.
Embedded Executive: While Embedded Technology Progresses Slowly, Security Moves Super-Fast, Infineon Technologies - PodcastNovember 08, 2023
We talk about security a lot here at Embedded Computing Design. If it’s not the number one subject, it’s certainly in the top three.
Infineon recently held its annual OktoberTech event, where it showcased the company’s vast array of technologies as well as those of its customers. Embedded Computing Design’s Rich Nass sat down with Infineon Americas President Maher Matta to discuss things like sustainability, how to deal with such a wide range of products, and the need for an event like OktoberTech.
The Redmi design team was able to capture small size and long run times with minimal BOM.
We have an engineering shortage. Anyone who's familiar with our space wouldn't dispute that. And if you look at the projections, we’re going to need a whole lot more of us going forward. Why is that the case, and more importantly, what are we going to do about it?
Quantum computing raises the potential for anything to be hacked, and that includes government systems. Hence, the people behind the CHIPS Act want to make sure that the money that’s used for semiconductor development is being used in the areas that it deems most important.
Quantum computing can be a very complex area. Many experts will tell you that it could be as long as a decade before quantum computers actually appear on the scenes.
If you’re a consumer, 5G is likely in your universe. If you’re working on the industrial side, you’re likely not seeing 5G at all. And it may be many years before it’s even available in limited deployments. Why is that? That’s the question I asked of Olivier Pauzet, the EVP of Strategy for Sequans Communications in this week’s Embedded Executives podcast.
Are you wondering what would be considered a practical application for AI at the endpoint (the place where the data is captured)? Well, you’re in luck, because Rich is moderating a panel at Renesas’ AI Live virtual conference that specifically covers that topic.
Sustainability continues to be a topic of interest. First, what does sustainability actually mean? Second, what are some of the industry giants doing about it?
In the first of this on-going blog series, we explained why a developer should consider implementing Windows on Arm (WoA), and in Part II, we talked about why you should be implementing Windows on Arm using Advantech hardware. Here in Part III, we’ll talk about the steps you should take to actually deploy Windows IoT on Advantech Arm-based hardware.
Bringing all the different elements together for an AI-based hardware platform is harder than it sounds, especially when you start considering the environmental conditions. Getting it to work in the lab is one thing, but the real world presents challenges you may not have thought of.
When it comes to AIoT, some of the terms and techniques you’ll need to familiarize yourself with include Edge computing, machine learning (ML), TinyML, anomaly detection, natural language processing, computer vision, and predictive maintenance.
As you would expect, “Windows on Arm” refers to a version of the Microsoft Windows operating system that’s designed to run on devices powered by Arm-based processors. Such devices are quite plentiful. They are in most of our smartphones, tablets, and a slew of other low-cost devices, many of them powered by batteries.