The Akida platform delivers sub-watt continuous inference versus multi-watt power consumed by competitive FPGA or GPU-based edge AI modules.

Tom Fenton moves from local AI concepts to hands-on tools for matching LLMs to hardware, running local chatbots with Ollama and benchmarking AI performance.

CrossLinkU-NX SoM board from Lattice Semiconductor. The SoM Board is optimised for resource‑constrained vision, sensor, edge, ...

This Frigate server monitors my home and, unlike cloud-based alternatives, protects my privacy ...

The privacy trade-off is worth every penny ...

What if a device could see the world the same way humans do, seeing objects, recognizing them, and understanding what they are in real time? Just like our eyes capture visuals and our brain instantly ...

Equipped with a quad-core CPU and up to 8GB or 16GB RAM, it can handle computer vision workloads using OpenCV, TensorFlow Lite, or lightweight YOLO models. For applications that demand higher speed ...

Arducam recently launched the All-in-One Raspberry Pi AI Camera Kit with CM5, a Raspberry Pi CM5-based PoE outdoor security camera featuring a 12.3MP Sony IMX500 AI vision sensor housed in an ...

So you bought a Raspberry Pi. Then you used the former children’s project board to create a home server, or perhaps a functional robot. What’s next? Adding artificial intelligence, obviously. The ...

Imagine a vehicle cruising at 54 kilometres per hour, roughly the speed of an object moving 0.5 metres per frame at 30 frames per second (0.5×30×3.6=54 km/hr). Mounted on the vehicle’s roof is a ...