Embedded Computing Design

I sometimes struggle to see the positive side when a new standard is announced, one that claims to “dramatically cut development time.”

Advanced AI applications now face fundamental challenges in latency and reliability. Hence, Edge-to-Cloud AI solutions that can be deployed with existing core IT infrastructure have become key AI enablers. Harnessing existing workflows is instrumental to Edge-ready solutions capable of closing complex gaps between core business IT investments, competencies, and next-generation AI opportunities.

Here’s a fact that won’t shock you—the automotive industry is in the midst of a huge transformation thanks to AI technology. Here’s another fact that won’t be a surprise—NVIDIA is smack in the middle of that transformation.

Is Intel teaming up with SiFive to produce RISC-V chips? It depends how much you read between the lines in a recent release from SiFive.

We spend a lot of time talking about the specification known as CHIP (Connected Home over IP). While the hard work on this topic continues, the names of the group and the standard have changed.

Note: This is the fourth in a series of four blogs (and associated podcasts). First, I looked at what it means to be operating an AIoT platform. In the second, I went through some of the subsystems that go into that AIoT platform, drilling down into the nuts and bolts. The third covered AMRs.

It’s obvious that you can do 5G without AI. However, the inverse is not always true—adding 5G to AI makes the AI platform run far more efficiently. In the third of three podcasts, I discussed this topic with Allan Yang, the CTO of Advantech. Allan brings a great perspective, as his company is one of the architects behind AI platforms. Hear all about it in this week’s Embedded Executives podcast.

Research says that users are playing music, podcasts, movies, and gaming directly on their handsets, without the use of an external audio device.

AI and all its varied facets are new to most of the world.

Memory technology doesn’t always advance at the swiftest pace, but there’s been some movement in this space as of late.

Virtium, a provider of industrial solid-state drive (SSD) and memory solutions, recently introduced a series of high-speed, small-form-factor memory modules.

It seems like there’s a new security solution popping up on a daily basis. One new entrant is SecuriThings, an IoT security vendor focusing on various industries, including healthcare.

There’s no moss gathering on the RISC-V stone. The group continues to make progress in just about all facets of its roadmap.

Note: This is the third in a series of four blogs (and associated podcasts). In the first blog, I looked at what it means to be operating a platform at the edge of the AIoT, where designers should start the process, and what path they should take to develop those systems. In the second, I went through some of the subsystems that go into that AIoT platform, drilling down into the nuts and bolts.

In this episode of the Embedded Insiders, Brandon and Rich discuss Silicon Laboratories recent divestiture of its infrastructure and automotive business units to SkyWorks Solutions. The sale includes the company’s power, isolation, broadcast, timing, and other products and IP. Silicon Labs CEO Tyson Tuttle said several years ago that the company is “all-in” on IoT, and this move appears to be him keeping his word. But was it the best move?

In part II of a three-part series, Allan Yang, the Chief Technology Officer of Advantech, joins to discuss whether the application defines and solves the problem, or has the IoT become a solution looking for a problem. I’m oversimplifying here, but check out this week’s Embedded Executives podcast to hear the details.

Is memory that’s aimed at a specific market really customized for that segment, or is it just marketing spiel? We have mobile memory, IoT memory, AI memory, and so on. Are they really different?

There’s no disputing that the amount of electronics within an automobile is growing at a staggering pace.

The Aetina Intelligent Management (AIM) framework simplifies the design and deployment of an AI platform that’s destined to reside at the Edge of the industrial IoT (IIoT). Based on NVIDIA Jetson GPU, AIM can handle the compute-intensive demands that are sure to come.

The term “size matters” definitely applies when it comes to power electronics.