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To: BeenRetired who wrote (41869)	10/7/2025 10:24:40 AM
From: BeenRetired	Respond to of 42355

QCOM Edge: Foundries.io 3/24, Edge Impulse 3/25. Now Arduino. Yahoo finance: Qualcomm to acquire Arduino amid edge computing push Daniel Howley ·Technology Editor Tue, October 7, 2025 at 6:00 AM PDT 2 min read Qualcomm ( QCOM) announced on Monday that it is acquiring open-source hardware and software developer Arduino as it seeks to further grow its footprint in the edge computing space and push beyond its heavy reliance on the smartphone market. The companies did not release pricing details of the acquisition. Qualcomm previously acquired edge computing company Foundries.io in March 2024 and announced it was acquiring Edge Impulse in March 2025. Edge computing includes computers that help power processing far away from data centers, ranging from point-of-sale systems in retail stores to small sensors that allow workers to remotely monitor offshore wind turbines to internet of things (IoT) devices such as smart TVs and cars. Applications generally require a balance between computing performance and power usage. Italian company Arduino develops software and hardware that help power everything from hobbyist robots and rudimentary home automation projects to enterprise IoT platforms.

To: BeenRetired who wrote (41869)	10/7/2025 10:46:18 AM
From: BeenRetired	Respond to of 42355

6nm Dragonwing™ QRB2210 Arduino UNO Q Breakdown by Chip QRB2210: Designed for ultra-low power applications like small robots and IoT devices. Its sub-3W profile makes it ideal for fanless designs and battery-operated systems. QRB4210: Slightly older node and higher thermal envelope. Used in mid-tier robotics platforms with modest AI workloads. QRB5165 (RB5): Based on Snapdragon 865, this chip supports advanced AI, multiple cameras, and high-throughput tasks. Power draw can spike to 15W under full load, but typically hovers around 7–10W in balanced use. If you're optimizing for thermal envelope or battery life in a robotics platform, QRB2210 is the most efficient. For edge AI with real-time vision and inference, QRB5165 offers the best performance-per-watt tradeoff. Want help mapping these to Arduino, Lantronix, or Thundercomm devkits?