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received in a way where it’s kind of like war stories,” Schneck said. “They’ve seen a lot of this pain, and they want more people to be involved in the industry.” Avocado OS supports Mac, Windows, and Linux workstations and targets a wide range of silicon, including NVIDIA, Qualcomm, NXP, and Raspberry Pi compute modules. As embedded teams become more interdisciplinary – blending hardware engineers with data scientists, photonics specialists, and AI developers – Avocado OS is intended to reduce bottlenecks and accelerate time to market. “We’re here to be able to design solutions that make their lives easier,” Schneck added, “and not just try to be able to take something that’s off the shelf and make it work for them.”
Analog Devices: Edge AI and high-speed interfaces for real-world decision making
Analog Devices highlighted its latest advances in edge AI and high-speed connectivity, with Marcus Greenhill, director of digital health systems, presenting technologies designed to simplify real-world deployment. A key focus was GMSL (Gigabit Multimedia Serial Link), a high-speed, cost efficient, simple, scalable, serial interface originally developed for automotive camera systems. By transmitting power and data over low-cost coaxial or twisted pair cable, GMSL offers a lightweight, efficient alternative to traditional cabling. “You can transmit both power and high-speed data over a single line,” Greenhill said. “It simplifies manufacturing and makes integration far more efficient.” The technology is now being explored for use in healthcare (e.g. endoscopy) and robotics, where flexible, compact cabling is essential. Also discussed was the MAX 78000 edge AI processor, part of Analog Devices’ strategy
to bring intelligence closer to the sensor. With cloud-based AI facing latency and bandwidth constraints, the company is investing in embedded neural engines that enable real-time decision-making in wearables, industrial systems, and mobile robotics. The acquisition of Maxim Integrated has expanded its digital capabilities, allowing Analog Devices to combine sensor innovation with software, algorithms, and privacy-conscious design – particularly in regulated sectors like healthcare.
Embedd.it: AI-powered MCU tool
Embedd.it launched its Graphical MCU Configurator. The free, vendor-independent tool is designed to help OEMs decouple hardware from software and accelerate
development. Supporting over 1,400 MCU families – including STMicroelectronics, Renesas, NXP and Texas Instruments – the tool enables developers to visually assign pin functions, configure settings and generate device trees and overlays. “Our configurator makes software migration far easier than it was before,” CTO Valentine Gololobov said. “It allows you to configure not only the MCU, but the entire board with peripherals and other components.”
Powered by
Embedd.it’s AI-enabled Data Hub, the tool extracts and validates component data from inconsistent sources, producing machine-readable outputs for configuration and code generation. For safety- critical applications, deterministic generators and manual validation ensure reliability. Developers can also reconfigure existing
DTS files and port designs across vendors, supporting second-sourcing strategies and supply chain resilience.
Looking ahead,
Embedd.it plans to automate full board support packages and OS setup, allowing developers to focus solely on application logic. “We’re going to handle everything else,” Gololobov added. The tool is available as a Visual Studio Code extension, web app or enterprise-hosted solution.
NXP: Radar intelligence and edge AI
NXP Semiconductors introduced its PurpleBox radar reference design, developed to consolidate and interpret data from vehicle-mounted corner radar units as part of broader sensor fusion strategies. Designed for
32 October 2025
Components in Electronics
www.cieonline.co.uk
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