First Look: The Raspberry Pi AI Kit is a budget add-on for coders

The Raspberry Pi AI Kit is arguably one of the most sensitive consumer AI products released to date. This is not because it is the fastest AI accelerator – far from it – but because it targets two critical issues facing the world of AI technology.

Unlike most AI devices, it’s affordable ($70, not counting a Raspberry Pi 5 you’ll need to mount it on), which makes it much more accessible than most devices out there. And since it’s for the Raspberry Pi, a device that helps people learn to code, the kit is a great platform for preparing coders for AI. Given its specialized nature, we didn’t have a comparable or competing product to review against it, but we can definitely say that the Raspberry Pi AI Kit has a lot of promise.

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Unlocking the Raspberry Pi AI Kit

The $70 kit includes a Raspberry Pi M.2 HAT+ (an auxiliary board that you’ll plug into your Pi 5), a Hailo AI accelerator with a Hailo-8L AI chip, and the necessary mounting hardware to connect the HAT+ to the Raspberry Pi your 5 (which you’ll have to buy separately for $80). You can buy the components separately, but you’ll almost certainly pay more than $70 for the Hailo-8L AI accelerator alone.

(Credit: Michael Justin Allen Sexton)

With a TOP 13 AI processing power rating, the Hailo-8L stacks up well with other first-generation AI accelerators like those inside AMD’s Ryzen 7040 series mobile processors and Intel’s “Meteor Lake” laptop chips ( which are rated for 10 and 11 TOPS, respectively). Announced next-gen components like AMD’s upcoming Ryzen AI 300 chips and Intel’s Core Ultra “Lunar Lake” mobile chips will have a bit more, but 13 TOPS is enough to get by for now.

(Credit: Michael Justin Allen Sexton)

Putting the components together is easy and straightforward. You just need to attach the GPIO header, place the HAT+ on the Raspberry Pi 5, and then screw the mounting hardware (which consists of four screw fasteners) into the corner.

(Credit: Michael Justin Allen Sexton)

This device does not use the GPIO pins for any purpose; the header is simply there to make it easier to connect other devices to the GPIO with the HAT+ installed. Instead, the HAT+ connects using the Raspberry Pi 5’s single PCI Express 2.0 lane.

The M.2-based AI accelerator comes pre-installed on the HAT+, so all that’s left to do is connect the ribbon cable. This, too, comes pre-installed on the HAT+, but I found it easier to disconnect it and connect it first to the Raspberry Pi 5. The way the cable fits into the connectors on both devices makes this a bit easier.

(Credit: Michael Justin Allen Sexton)

Technically, this is what hardware configuration is all about. From there, you can install the software and start using the device, which we will discuss more in the next section. If you want to try out the demo software that the Raspberry Pi Foundation offers, you’ll also need to connect a camera, such as one of the Raspberry Pi’s camera modules. (We used the Raspberry Pi Camera 3 module pictured earlier.) This can be attached after the HAT+ is installed; that board even has a cutout for the cable to run through it, so there’s no problem adding a camera later or removing one if you no longer plan to use it.

(Credit: Michael Justin Allen Sexton)

No other hardware is strictly necessary, but if you want to equip your Raspberry Pi with a heater or fan, the installation leaves room for you to do so.

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Configuring the software and exploring the demos

With everything assembled, you’re ready to tackle the software to use your AI hardware. The company recommends that you start – before installing the Pi AI Kit – by making sure your Pi 5 is running the latest version of the Raspberry Pi operating system, along with the latest updates. We certainly agree with this advice and followed it before attaching HAT+.

Next, you need to install the necessary drivers and software for Hailo AI Accelerator to work. You achieve this by typing this command in a terminal…

$ sudo apt install hailo-all

…and rebooting the device after installation. If you want to try out the included demos, you’ll need to purchase them using the command below to download them…

$ git clone – -depth 1 https://github.com/raspberrypi/rpicam-apps.git ~/rpicam-apps

Currently, three demos are available that focus on using AI with the camera. Raspberry Pi calls the first of these a demo of pose estimation. It feels easily familiar to anyone who has owned an Xbox Kinect or similar device, as it essentially tracks your body movements by following 17 points across your body. The demo worked well when I tested it, tracking arm and body movements with reasonable accuracy.

The second is an object detection demo that tries to identify objects you hold in front of the camera. This, too, seemed to work quite well, but with more errors, sometimes giving the wrong answer first or switching answers. She knew, for example, that I was a person and that my cat was a cat, but she thought that one of my screwdrivers (with a small handle) was a pen.

The third demo focuses on image segmentation and allows you to isolate objects, with the idea that you can then remove the object or background and replace it with something else.

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Verdict: Still in development

All three demos provided worked with only minor glitches that weren’t too far off the mark. As it is, the Raspberry Pi AI kit is fun to play with, but there’s little reason to buy one unless you plan to use it to learn to create programs or devices that take advantage of the power of AI.

(Credit: Michael Justin Allen Sexton)

At its core, the Raspberry Pi 5 and the new AI Kit are designed to be used by students and hobbyists who want to learn to program and build their own semi-custom devices, and we see no reason why the kit shouldn’t be good about it. purpose. It doesn’t have much to offer (at least for now) if you’re not looking to develop your own code, but it’s a great way to get the ball rolling on independent AI software development at a low cost of entry.