Embedded systems have changed immensely over roughly 25 years, according to the publisher’s synopsis of an August 31, 2026 episode of DevTalk with Rich and Vin. Its central contrast is between today’s AI-based computing platforms and older computers that were generally large and built for a single function. The synopsis frames the change broadly; it does not provide a technical, component-by-component history.
What the episode compares
DevTalk with Rich and Vin asks how embedded systems have changed over the last 25 years. The show is hosted by Rich Nass, executive vice president of Embedded Computing Design, and Vin D’Agostino, whom the publisher describes as a veteran embedded systems designer. Its stated scope includes embedded hardware, software and tools, as well as market issues when they affect engineers and developers. Embedded Computing Design published the episode synopsis on August 31, 2026.
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The synopsis’s main point is a shift in the kind of computing platform under discussion: present-day AI-based platforms are set against older embedded computers described as large and generally single-function. That is the publisher’s broad characterization, not a measured finding or a claim that every older or current system fits the description.
What the synopsis does—and does not—establish
- It establishes the comparison’s scope: roughly a quarter-century of change in embedded computing, viewed through the contrast between AI-based platforms and older, typically single-function computers.
- It does not identify a representative old or new system: no specific device, processor, architecture, or application is named in the available description.
- It does not specify the technologies discussed: although the show’s remit spans hardware, software and tools, the synopsis does not say which components, programming environments, or development tools the hosts cover.
- It offers no technical measurements or attributed quotations: the synopsis does not provide statistics or verbatim statements from Nass or D’Agostino. Its description of the change as immense is editorial framing, not a quantified industry result.
The publisher’s episode description is a short synopsis rather than a transcript or detailed set of show notes. The exact technologies and trade-offs addressed in the audio therefore cannot be established from that description alone.
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How to read the 25-year comparison
The episode’s framing is useful as a high-level prompt: embedded computing is no longer described only in terms of large, dedicated-function computers; AI-based platforms are now part of the comparison. It should not, on its own, be taken as evidence for particular changes in processor performance, memory, connectivity, power use, system size, software, or local AI inference. Those would require specific examples or supporting technical sources.
For engineers and curious readers, the clearest next questions are practical ones: what workload a system handles, how its compute and memory are organized, what size and power limits it faces, which software and tools support it, and whether AI inference runs locally. The synopsis does not answer those questions for either period, so it cannot support a like-for-like technical comparison on those axes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Who the episode may help
The episode is positioned for people interested in embedded hardware, software and tools, including engineers and developers considering how the field’s priorities have shifted. Readers looking for named components, detailed architectures, performance figures, or a verified account of particular design changes will need a transcript, detailed show notes, or other technical documentation; those details are not included in the accessible synopsis.
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