Raspberry Pi Official Magazine #139

Raspberry Pi puts you at the forefront of computer experimentation. It's an exciting place to be, albeit a tad precocious. That's why our Troubleshooting feature (page 42) is such a vital read. It's packed with information on how to overcome any snags you might encounter. Not only will this make your Raspberry Pi experience more enjoyable, but you'll also become a better computer expert. This month sees the welcome return of #MonthOfMaking (page 68), where we all get together to show off the big builds we've been working on. We've also got two cases that support the new PCIe drives: NVME Base (page 76) and Argon ONE V3 M.2 (page 78). Both will vastly speed up your Raspberry Pi 5. Whatever you make with Raspberry Pi, be sure to share…

The excitement around machine learning right now is all about generative AI, and the new generation of large language models (LLMs). But sometimes you should take a step back, and remember what we were all excited about last time. Because it could be time to get excited about it again. Before LLMs made it big, we were all excited by embedded machine learning – what's called TinyML – and Raspberry Pi is probably the most affordable way to get started. The inferencing performance (magpi.cc/bigbenchmarking) we see with Raspberry Pi 4 was comparable to or better than some of the new accelerator hardware, but your overall hardware cost is that much lower. But what if you want to go really tiny – microcontroller tiny? We have actually seen some really crazy…

We move in the kind of circles where news of the GitHub Universe (githubuniverse.com) conference lights up our social feeds each year. This time (well, now it's last time) we were super excited to see photos of the official conference badges. We noticed they look a lot like a Pimoroni Badger, which is powered by our RP2040 chip (magpi.cc/rp2040), so we took a closer look to see if we were right. Special custom gift GitHub's Martin Woodward made a dedicated repo (magpi.cc/badger2040git) to help conference attendees learn how to hack their badges. Lo and behold, in it he confirms that the hackable conference badges are indeed a custom version of the Badger 2040 (magpi.cc/badgerguide) that Pimoroni made especially for GitHub. “GitHub Universe Badger is electronically identical to the original Badger…

MAKER B-AROL-O Team The talented international team consists of Gianluca Tetri, Gianpaolo Macario, Pietro d'Agostino, Davide Macario, Andrea Podo and Orso Eric magpi.cc/freisa Real dogs tend to be fluffy and cute. Robodogs rather less so. But when you meet FREISA, a robotic dog created for a recent competition, you'll still want to give it a pat on the back and heap it with praise. For, just like its living, breathing canine counterparts, this impressive little thing is intelligent and skilled. It's capable of spotting a thirsty plant and making sure it gets enough water. FREISA – an acronym for Four-legged Robot Ensuring Intelligent Sprinkler Automation – is the brainchild of the B-AROL-O Team. This group won the popular vote of the OpenCV Spatial AI Contest in 2022 by creating a…

01 FREISA utilises its camera and a machine learning algorithm trained using Roboflow (roboflow.com) to tell the robot's navigation system where the plants are located. It will analyse the state of the leaves and work out which plants require watering. 02 If it identifies dried-up plants, the robot will then ready itself. It will use its legs to get into position so that the robot's pelvic-located 3D-printed water sprinkling system (which includes a reservoir) is able to best target the thirsty plant. 03 At this stage, the sprinkling system bursts into action thanks to servomotors and a syringe that is able to draw up 10ml of water. The water is then dispensed on to the plant, and this is confirmed to the plant's owner, keeping a log of the event.…

MAKER Ivan Kuleshov Ivan loves taking apart different devices to improve them, or learn how they work, and can't resist a hardware challenge. magpi.cc/uptimelab Self-confessed “hardware hacker” Ivan Kuleshov really likes making things. He's adept at using tools covering everything from microscopes to lathes, builds and flies drones and has won three separate hackathons. As long as he can remember, he's been beavering away on various projects related to hardware, from PC modding to the creation of homemade devices, racking up more than nine years on 3D printing and modelling. This aspect briefly became a business venture, but his day job is as a systems engineer in Munich with a string of certifications. His computing, coding and design skills also came in handy for his Mac Mini KVMac16 project, for…