Hackaday Podcast Episode 343: Double Component Abuse, A Tinkercad Twofer, And A Pair Of Rants

October 24, 2025 by Kristina Panos 1 Comment

This week, Hackaday’s Elliot Williams and Kristina Panos met up across the universe to bring you the latest news, mystery sound, and of course, a big bunch of hacks from the previous seven days or so.

In Hackaday news, OMG Supercon is almost here! And we just revealed the badge! In other news, we’ve still got a contest running. Read all about the 2025 Component Abuse Challenge, sponsored by DigiKey, and check out the contest page for all the details.

On What’s That Sound, Kristina failed spectacularly. Will you fare better and perhaps win a Hackaday Podcast t-shirt? Mayhap you will.

After that, it’s on to the hacks and such, beginning with a really cool entry into the Component Abuse Challenge wherein a simple transmission line is used to multiply a voltage. We watch as a POV globe takes to the skies, once it has enough motors.

Then we discuss several awesome hacks such as an incredible desk that simulates beehive activity, a really great handheld PC build, and a Tinkercad twofer. Finally, we discuss the future of removable batteries, and the history of movable type.

Check out the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!

Download in DRM-free MP3 and savor at your leisure.

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Making WiFi Sound Like Dial-Up Internet

October 24, 2025 by Lewin Day 24 Comments

Dial-up modems had a distinctive sound when connecting, with the glittering, screeching song becoming a familiar melody to those jumping online in the early days of the Internet. Modern digital connections don’t really have an analog to this, by virtue of being entirely digital. And yet, [Nick Bild] decided to make WiFi audible in a pleasing tribute to the modems of yore.

The reason you could hear your dial-up modem is because it was actually communicating in audio over old-fashioned telephone lines. The initialization process happened at a low enough speed that you could hear individual sections of the handshake that sounded quite unique. Ultimately, though, once a connection was established at higher speed, particularly 33.6 k or 56 k, the sound of transmission became hard to discern from static.

Modern communication methods like Ethernet, DSL, and WiFi all occur purely digitally — and in frequencies far above the audible range. Thus, you can’t really “listen” to a Wi-Fi signal any more than you can listen to the rays of light beaming out from the sun. However, [Nick] found an anachronistic way to make a sound out of WiFi signals that sounds vaguely reminiscent of old-school modems. He used a Raspberry Pi 3 equipped with a WiFi adapter, which sniffs network traffic, honing in on data going to one computer. The packet data is then sent to an Adafruit QT Py microcontroller, which uses the data to vary the amplitude of a sound wave that’s then fed to a speaker through a digital-to-analog converter. [Nick] notes this mostly just sounds like static, so he adds some adjustments to the amplitude and frequency to make it more reminiscent of old modem sounds, but it’s all still driven by the WiFi data itself.

It’s basically WiFi driven synthesis, rather than listening to WiFi itself, but it’s a fun reference to the past. We’ve talked a lot about dial-up of late; from the advanced technology that made 56 k possible, to the downfall of AOL’s long-lived service. Video after the break.

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This Week In Security: Court Orders, GlassWorm, TARmageddon, And It Was DNS

October 24, 2025 by Jonathan Bennett 3 Comments

This week, a US federal court has ruled that NSO Group is no longer allowed to use Pegasus spyware against users of WhatsApp. And for their trouble, NSO was also fined $4 million. It’s unclear how much this ruling will actually change NSO’s behavior, as it intentionally stopped short of applying to foreign governments.

There may be an unexpected source of leverage the US courts can exert over NSO, with the news that American investors are acquiring the company. Among the requirements of the ruling is that NSO cannot reverse engineer WhatsApp code, cannot create new WhatsApp accounts, and must delete any existing WhatsApp code in their possession. Whether this actually happens remains to be seen.

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Robot Phone Home…Or Else

October 24, 2025 by Al Williams 64 Comments

We would have enjoyed [Harishankar’s] tear down of a robot vacuum cleaner, even if it didn’t have a savage twist at the end. Turns out, the company deliberately bricked his smart vacuum.

Like many of us, [Harishankar] is suspicious of devices beaming data back to their makers. He noted a new vacuum cleaner was pinging a few IP address, including one that was spitting out logging or telemetry data frequently. Of course, he had the ability to block the IP address which he did. End of story, right?

No. After a few days of working perfectly, the robot wouldn’t turn on. He returned it under warranty, but the company declared it worked fine. They returned it and, indeed, it was working. A few days later, it quit again. This started a cycle of returning the device where it would work, it would come home and work for a few days, then quit again.

You can probably guess where this is going, but to be fair, we gave you a big hint. The fact that it would work for days after blocking the IP address wouldn’t seem like a smoking gun in real time.

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Tommy Flowers: How An Engineer Won The War

October 24, 2025 by Jenny List 26 Comments

Back in 2016, we took you to a collection of slightly dilapidated prefabricated huts in the English Home Counties, and showed you a computer. The place was the National Museum of Computing, next to the famous Bletchley Park codebreaking museum, and the machine was their reconstruction of Colossus, the world’s first fully electronic digital computer. Its designer was a telephone engineer named Tommy Flowers, and the Guardian has a piece detailing his efforts in its creation.

The front of the museum's Colossus MkII. — TNMOC’s Colossus MkII.

It’s a piece written for a non-technical audience so you’ll have to forgive it glossing over some of the more interesting details, but nevertheless it sets out to right a long-held myth that the machine was instead the work of the mathematician Alan Turing. Flowers led the research department at the British Post Office, who ran the country’s telephone system, and was instrumental both in proposing the use of electronic switches in computing, and in producing a working machine. The connection is obvious when you see Colossus, as its racks are the same as those used in British telephone exchanges of the era.

All in all, the article makes for an interesting read for anyone with an interest in technology. You can take a look at Colossus as we saw it in 2016 here, and if your interest extends to the only glimpse the British public had of the technology behind it in the 1950s, we’ve also taken a look at another Tommy Flowers creation, ERNIE, the UK Premium Bond computer.

Automatically Serving Up Canned Cat Food

October 23, 2025 by Bryan Cockfield 18 Comments

If there’s any one benefit to having a cat as a pet instead of a dog, it’s that they’re a bit more independent and able to care for themselves for many days without human intervention. The only thing that’s really needed is a way to make sure they get food and water at regular intervals, but there are plenty of off-the-shelf options for these tasks. Assuming your cat can be fed dry food, that is. [Ben Heck]’s cat has a health problem that requires a special canned wet food, and since there aren’t automatic feeders for this he built his own cat-feeding robot.

Unlike dry food that can dispense a measured amount from a hopper full of food, the wet food needs to be opened and dispensed every day. To accomplish this, his robot has a mechanism that slowly slides a wedge under the pull tab on the can, punctures the can with it, and then pulls it back to remove the lid. From there the food is ejected from the feeder down a ramp to a waiting (and sometimes startled) cat. The cans are loaded into 3D-printed cartridges and then stacked into the machine on top of each other, so the machine can dispense food cans until it runs out. This design has space for six cans.

Although there are many benefits to having pets of any sort, one of the fun side quests of pet ownership is building fun things for them to enjoy or to make caring for them easier. We even had an entire Hackaday contest based on this premise. And, if biological life forms aren’t your cup of tea, there are always virtual pets to care for as well.

Thanks to [Michael C] for the tip!

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Making The Smallest And Dumbest LLM With Extreme Quantization

October 23, 2025 by Maya Posch 15 Comments

Turns out that training on Twitch quotes doesn't make an LLM a math genius. (Credit: Codeically, YouTube) — Turns out that training on Twitch quotes doesn’t make an LLM a math genius. (Credit: Codeically, YouTube)

The reason why large language models are called ‘large’ is not because of how smart they are, but as a factor of their sheer size in bytes. At billions of parameters at four bytes each, they pose a serious challenge when it comes to not just their size on disk, but also in RAM, specifically the RAM of your videocard (VRAM). Reducing this immense size, as is done routinely for the smaller pretrained models which one can download for local use, involves quantization. This process is explained and demonstrated by [Codeically], who takes it to its logical extreme: reducing what could be a GB-sized model down to a mere 63 MB by reducing the bits per parameter.

While you can offload a model, i.e. keep only part of it in VRAM and the rest in system RAM, this massively impacts performance. An alternative is to use fewer bits per weight in the model, called ‘compression’, which typically involves reducing 16-bit floating point to 8-bit, reducing memory usage by about 75%. Going lower than this is generally deemed unadvisable.

Using GPT-2 as the base, it was trained with a pile of internet quotes, creating parameters with a very anemic 4-bit integer size. After initially manually zeroing the weights made the output too garbled, the second attempt without the zeroing did somewhat produce usable output before flying off the rails. Yet it did this with a 63 MB model at 78 tokens a second on just the CPU, demonstrating that you can create a pocket-sized chatbot to spout nonsense even without splurging on expensive hardware.

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