AIoT
How Charlieplexing works: an interactive demo
Eleven pins, 104 LEDs, and a scan you can slow down until the trick falls apart. An interactive walkthrough of the Arduino UNO Q's charlieplexed matrix, built from the board's own devicetree.
The OpenMV AE3: A Time-of-Flight Doorman for the NPU
Part two of the OpenMV series shrinks the board and the power to a quarter of a watt, while running YOLO. Built on Alif's Ensemble E3 with two Cortex-M55s and two Ethos-U55 NPUs, the AE3 also carries something its bigger sibling does not, a VL53L8CX 8x8 ToF depth sensor.
The OpenMV N6: A MicroPython Camera with a Real NPU
The OpenMV N6 pairs an 800 MHz Cortex-M55 with ST's 600-GOPS Neural-ART NPU and a removable global-shutter camera, and MicroPython - YOLO object detection at 30 fps, in Python, under a watt. We tour the hardware properly, walk through setup, and build a people-counting application on the NPU.
A Real Dual-Brain Application on the Arduino UNO Q: an AI Brick, a Camera, and a Presence Lamp
Part two of the UNO Q series puts the board's dual-brain design to real work - a vision AI Brick on the Linux side detects a person through a camera, and the microcontroller side turns that into a smoothly breathing lamp that never stutters, no matter how hard the AI is working.
Arduino
Getting to Know the Arduino UNO Q: Two Brains, One Board, and Zephyr Underneath
The Arduino UNO Q pairs a quad-core Linux processor with a real-time STM32 microcontroller on one UNO-shaped board, and quietly runs Zephyr where the classic Arduino runtime used to be. This guide takes an engineer's look at the architecture.
From TinyML to Tiny Language Models: the State of Edge AI in 2026
A field guide to state-of-the-art edge AI in 2026, covering the models that now run on small devices, the neural accelerators that make them possible, and federated learning, grounded in the low-cost hardware used throughout this blog.