This page provides instructions for running AI models powered by Hailo NPUs on Raspberry Pi 5. The Hailo NPU is an AI accelerator chip designed to run neural networks; instead of Raspberry Pi’s CPU doing the AI work, the NPU handles it more efficiently.

AI HATs are add-on boards for Raspberry Pi 5 that come with a built-in AI accelerator chip: the Hailo neural processing unit (NPU). The Hailo NPU allows Raspberry Pi 5 to run hardware-accelerated AI models locally, removing the need to send data to a remote cloud server for processing. This edge AI approach improves performance, reduces latency, and helps to keep data private.

Using **fbi** to show a custom splash screen during boot. Take a look at the comments for further configuration to tune it up more.

Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification.

Suppose you are running a Python systemd service that opens some file descriptors (these can be regular files, named pipes, sockets, and so on). When the service is stopped, it needs to finish cleanly by closing and/or removing the associated resources. This post presents two manners in which the service may be stopped gracefully.

One of our customers designing an embedded Linux system with specific audio needs had a use case where they had a sound card with more than one audio channel, and they needed to separate individual channels so that they can be used by different applications. This is a fairly common use case, we would like to share in this blog post how we achieved this, for both input and output audio channels.

Because I had been previously using my Pi as a headless server, I hadn’t installed a desktop environment. I wanted to add a lightweight heads-up display to the server, and I wanted a graphical application that could operate without X, the usual graphical system on Linux.
Writing such a lightweight application required understanding how to interact more directly with my new screen, the learnings from which I’ll share here. This article is a summary of multiple sources I pieced together.

Raspberry Pi controlling small LED array. Here is using a LED strip, but the chip may be the same to move the wished module:
https://amzn.eu/d/iVcOwJG

Example in Python of a TTS server for Catalan ONNX models

More into the side of how to ensure that the Raspberry Pi 5 behaves correctly having an Ollama service running. Memory, CPU, Temperature... very interesting to have control over the hardware behaviour, to peek on what's important to control.