On this episode of Embedded Insiders, the CEO of Qualinx, Tom Trill, joins the podcast to discuss GNSS and sovereignty. We're talking about revolutionizing GNSS with an ultra-low-power, high-performance, reconfigurable positioning and location chip designed to challenge conventional GNSS chip architectures. 

Should you use AI to generate code? Or should it be limited to code review? From my research, it depends on who you ask. 

In this case, I asked Rod Cope, the Chief Technical Officer at Perforce Software. Rod has a great deal of experience in this space, and he was my guest on this week’s Embedded Executives podcast.

ISO 8800 is a standard aimed at functional safety in automotive applications, pertaining to artificial intelligence. It provides the guidelines for integrating AI systems into any safety-related functions of road vehicles. In full disclosure, I wasn’t aware of this standard, and I was frankly surprised I wasn’t. 

To remedy the situation, I invited Jill Britton, the Director of Compliance at Perforce, onto this week’s Embedded Executives podcast. Jill explained what the standard is all about and which parts of it are key for embedded developers to understand.

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.

MINNEAPOLIS— Perforce Software is partnering with Siemens Digital Industries Software to transform how smart, connected products are designed and developed, reflecting a shared vision: the future of product innovation is software-defined, AI-powered, and silicon-enabled.

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.

Perforce Software recently released the 2025 State of Automotive Software Development Report*. The statistics showed there is more utilization of AI within environments, as well as the continuous challenges of code complexity, and the importance of safety and security. According to 49% of those surveyed, safety was the top concern in AI vehicle development.