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Since the Pi 5's launch, a number of Pi case redesigns have launched, and there are a few new entrants with something to offer. Like Fractal's 'Baby North'... which, unfortunately, is only a prototype designed for their displays at Computex, and is not being planned for sale. At least not for now! I'll write more about this case later in this post.

The Pi 5's thermals are close enough to the Pi 4 that old cooling solutions work okay, but the port layout and inclusion of a power button means at least minimal redesigns are necessary.

Here are a few of the Pi 5 cases I've been testing (most for over a month, in various places), and my thoughts on each.

Raspberry Pi 5 Case (official)

The official case for the Raspberry Pi 5 is like a saltine cracker.

For a few weeks I've been beta testing remote shell, the latest addition to Raspberry Pi Connect. Just a couple hours ago I was on a flight home from the new Micro Center in Charlotte.

One huge problem with VNC or remote desktop is how flaky it is if you have limited bandwidth or an unstable connection, like on an airplane.

It takes forever to start a screen sharing session, and the airplane's flaky WiFi usually causes the session to lock up, meaning you can't do much at all.

Remote terminal access, just relaying text commands, is the best solution for that problem. And sure, I have a VPN I could use with SSH to get to my Pi, but Raspberry Pi Connect just added support for remote shell access.

I gave away 480 Raspberry Pi Picos at Open Sauce last weekend, and ran into a number of challenges doing so. All of them self-inflicted, of course. I didn't want to just hand them out like candy—or, well... that's exactly what I did:

My initial plan was to build a backpack mount for a full 480-Pico reel (they sell them in bulk like that, for pick-n-place machines). However, there was a major flaw with that design.

Constraints

I needed to get through TSA, so I could fly to San Francisco. Driving was out of the question, as my wife is almost full-term and I could not leave her for more than a week in the middle of summer, when the kids have about 15 events per week!

A full reel would require a knife or scissors, and I didn't want to check the bag whatever I built was in.

Red Hat Enterprise Linux 8 is supported until 2029, and that distribution includes Python 3.6 for system python. Ansible's long been stuck between a rock and a hard place supporting certain modules (especially packaging modules like dnf/yum on RHEL and its derivatives, because the Python bindings for the packaging modules are stuck supporting system Python.

Users are getting errors like:

/bin/sh: /usr/bin/python3: No such file or directory
The module failed to execute correctly, you probably need to set the interpreter.\nSee stdout/stderr for the exact error.

...or...

SyntaxError: future feature annotations is not defined

As ansible-core evolves, they don't want to support old insecure versions of Python forever—Python 3.6 was out of security support back in 2021!.

I'm in full-on procrastination mode with Open Sauce coming up in 10 days and a project I haven't started on for it, so I decided to try building the stable AI PC with all the AI accelerator chips I own:

• Hailo-8 (26 TOPS)
• Hailo-8L (13 TOPS)
• 2x Coral Dual Edge TPU (8+8 = 16 TOPS)
• 2x Coral Edge TPU (4+4 = 8 TOPS)

After my first faltering attempt in my testing of Raspberry Pi's new AI Kit, I decided to try building it again, but with a more 'proper' PCIe setup, with external 12V power to the PCIe devices, courtesy of an uPCIty Lite PCIe HAT for the Pi 5.

I'm... not sure it's that much less janky, but at least I had one board with a bunch of M.2 cards instead of many precariously stacked on top of each other!

Raspberry Pi today launched the AI Kit, a $70 addon which straps a Hailo-8L on top of a Raspberry Pi 5, using the recently-launched M.2 HAT (the Hailo-8L is of the M.2 M-key variety, and comes preinstalled).

The Hailo-8L's claim to fame is 3-4 TOPS/W efficiency, which, along with the Pi's 3-4W idle power consumption, puts it alongside Nvidia's edge devices like the Jetson Orin in terms of TOPS/$ and TOPS/W for price and efficiency.

Google's Coral TPU has been a popular choice for a machine learning/AI accelerator for the Pi for years now, but Google seems to have left the project on life support, after the Coral hardware was scalped for a couple years about as badly as the Raspberry Pi itself!