Four Choppers And A Blimp: The Bizarre Piasecki Helistat

Over two decades after it was last deflated, detached from its gondola, and crated up at Lakehurst, the gas bag of an N-class ZPG-2W blimp was broken out and dusted off for what might have been the most bizarre afterlife in aviation history: as a key building block for the U.S. Forest Service’s Piasecki PA-97 Helistat.

Just look at it! It’s an antique blimp gas bag, four war-surplus helicopters pulled from the boneyard, and a whole maze of aluminum tubing. That the U.S. Forest Service, of all agencies, was the one building what amounts to the airship version of an X-plane is also weird enough to be called bizarre. Getting Frank Piasecki to design this thing, a man who did as much as almost anyone else to kill the airship, might be considered ironic, but to stay on theme, I’ll call it bizarre.

If you’re not already a quadrotor-blimp afficionado, we have some explaining to do.

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Skylab Under The Ocean

A crew lives on a station in a hostile environment. Leaving that environment requires oxygen tanks and specialized gear to deal with pressure differentials. A space station? Nah. A base built on the ocean floor. The US Navy was interested in such a base in the 1960s, and bases like this are a staple of science fiction. But today, we see more space stations than underwater bases. Have you ever wondered why?

Diving deep underwater is a tricky business. At a certain depth, the pressure forces gas like nitrogen to dissolve into your body. By itself, this isn’t a problem, but when you ascend, it is a big problem. If the gas all comes out at the same time, you get bubbles, which can cause decompression sickness, commonly called the bends. The exact problems vary, but the bends often cause extreme joint pain, fatigue, or a rash. Sometimes people die.

While you think of the bends as a deep-sea diver’s problem, it can also happen in airplanes and outer space. Any time you go from high pressure to low pressure quickly, you are subject to decompression sickness. Depending on what you are doing, there are different ways to mitigate the problem. For diving, traditionally, you simply don’t surface too quickly.

You dive, do your work, and then head towards the surface, stopping at preset stops to let the pressure equalize gradually. Physics is a bear, though. The longer you stay at a given depth, the longer you have to decompress.

That means you rapidly reach a point of diminishing returns. Suppose you dive to the ocean floor. You spend an hour working. Then you have to spend, say, eight hours gradually rising to the surface. That makes extended operations at significant depth impractical.

George Bond was thinking about all this and had an interesting idea. It is true that, in general, the longer you stay down, the more gas your body absorbs. But it is also true that, eventually, your tissues saturate, and then you don’t absorb any more.

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TurboQuant: Reducing LLM Memory Usage With Vector Quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of parameters, times N bits per parameter, equals N-billion bits of storage required for a full model. Since increasing the number of parameters makes the models appear smarter, correspondingly the size of these models and their associated caches has been increasing rapidly.

Vector quantization (VQ) is a method that can compress the vectors calculated during inference to take up less space without significant loss of data. Google’s recently published pre-print paper on TurboQuant covers an LLM-oriented VQ algorithm that’s claimed to provide up to a 6x compression level with no negative impact on inference times.

The tokens aren’t directly encoded in the vector space, but their associated key value is, which along with the single token per inference process creates the need for a key-value (KV) cache, the size of which scales with the size of the model. Thus by compressing the KV cache using VQ, it will reduce its size and correspondingly speed up look-ups due to the smaller size in memory. One catch here is that VQ is due to the nature of quantization some accuracy will be lost. The trick here is thus to apply VQ in such a way that it does not affect this accuracy in a noticeable manner.

Other aspects that had to be taken into account by the TurboQuant algorithm was fast computation to keep up with real-time requirements, along with compatibility with so-called ‘AI accelerator’ hardware.

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AI For The Skeptics: Pick Your Reasons To Be Excited

It’s odd being a technology writer in 2026, because around you are many people who will tell you that your craft is outdated. Like the manufacturers of buggy-whips at the turn of the twentieth century, the automobile (in the form of large language model AI) is on the market, and your business will soon be an anachronism. Adapt or go extinct, they tell you. It’s an argument I’ve found myself facing a few times over the last year in my wandering existence, and it’s forced me to think about it. What are the reasons everyone is excited about AI and are those reasons valid, what is there to be scared of, and what are the real reasons people should be excited about it?

If We Gotta Take This Seriously, How Can We Do It?

A couple in a horse drawn buggy, circa 1900ish
The futures looking bright in the buggy-whip department! Public domain.

I’ll start by repeating my tale from a few weeks ago when I asked readers what AI applications would survive when the hype is over. The reaction of a friend with decades of software experience on trying an AI coding helper stuck with me; she referenced her grandfather who had been born in rural America in the closing years of the nineteenth century, and recalled him describing the first time he saw an automobile. I agree with her that this has the potential to be a transformative technology, and while it’s entertaining to make fun of its shortcomings as I did three years ago when the idea of what we now call vibe coding first appeared, it’s already making itself useful in some applications. Simply dismissing it is no longer appropriate, but equally, drinking freely of the Kool-Aid seems like joining yet another hype bandwagon that will inevitably derail. A middle way has to be found. Continue reading “AI For The Skeptics: Pick Your Reasons To Be Excited”

CCA Ethernet Cables: Not Up To Scratch, But Are They Dangerous?

If you’ve ever bought a suspiciously cheap Ethernet cable from an online listing, there’s a decent chance you’ve encountered Copper Clad Aluminum. Better known as CCA, it’s exactly what it sounds like—an aluminium conductor with a thin skin of copper deposited on the outside. Externally, cables made with this material look largely like any other, with perhaps the only obvious tell being that they feel somewhat lighter in the hand.

CCA is cheaper than proper copper cabling, and it conducts signals well enough to function in an Ethernet cable. And yet, it’s a prime example of corner-cutting that keeps standards bodies and professional installers up at night. But just how dangerous is this silent scourge, found lurking in so many network cabinets around the world?

Not Up To Scratch

CCA wire is typically made by wrapping an aluminium core with copper strip and then extruding it through a die. Credit: USPTO

Everything you need to know about CCA is in the name—it refers to an aluminium wire with a thin copper cladding, typically applied through a die extrusion process. The reasoning behind this exploits a real physical phenomenon called the skin effect, wherein higher-frequency AC signals tend to travel along the outer surface of a conductor. The idea goes that since most of the current moves through the outer copper skin layer anyway, the less-conductive aluminium core doesn’t unduly impact the wire’s performance. Using copper-clad aluminium wiring is, in theory, desirable because aluminium is much cheaper than copper, which can really add up over long cable runs. Imagine you’re wiring a building with with hundreds of miles of Ethernet cabling, all with eight conductors each—the savings add up pretty quickly.

There’s a problem with CCA cabling in these contexts, though. Due to prevailing cabling standards, any cable made with CCA is technically not even a real Ethernet cable at all. The relevant documents are unambiguous.

ANSI/TIA-568.2-D requires conductors in Category-rated cable to be solid or stranded copper. No other materials are acceptable, and thus CCA is explicitly excluded from use in Category cable applications. A cable with CCA conductors cannot legitimately carry a Cat5e, Cat6, or any related designation under any circumstances. Similarly, ISO/IEC 11801 has the same requirement. The U.S. National Electrical Code also states that conductors in communications cables, other than coaxial cable, shall be copper. This isn’t a suggestion or a best practice; it’s the letter of the code. Anything lesser is simply not allowed. Continue reading “CCA Ethernet Cables: Not Up To Scratch, But Are They Dangerous?”

With Affordable Storage Options Dwindling, Where To Store Our Data?

These days our appetite for more data storage is larger than ever, with video files larger, photo resolutions higher, and project files easily zipping past a few hundred MB. At the same time our options for data storage are becoming more and more limited. For the longest time we could count on there always being a newer, roomier, faster, and cheaper form of storage to come along, but those days would seem to be over.

We can look back and laugh at low capacity USB Flash drives of the early 2000s, yet the first storage drive to hit 1 TB capacity did so in 2007, with a Hitachi Deskstar 7k100, only for that level of capacity in PCs to not really be exceeded nineteen years later.

We also had Blu-ray discs (BD) promise to cram the equivalent of dozens of DVDs onto a single BD, with two- and even four-layer BDs storing up to a one-hundred-and-twenty-eight GB. Yet today optical media is dying a slow death as the sole remaining cheap storage option. NAND Flash storage has only increased in price, and the options for those of us who have large cold storage requirements would seem to be decreasing every day.

So what is the economical solution here? Invest in LTO tapes using commercial left-overs, or give up and sign up for Cloud Storage™ for the low-low price of a monthly recurring fee?

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Ask Hackaday: How Much Compute Is Enough?

Over the history of this business, a lot of people have foreseen limits that look rather silly in hindsight– in 1943, IBM President Thomas Watson declared that “I think there is a world market for maybe five computers.” That was more than a little wrong. Depending on the definition of computers– particularly if you include microcontrollers, there’s probably trillions of the things.

We might as well include microcontrollers, considering how often we see projects replicating retrocomputers on them. The RP2350 can do a Mac 128k, and the ESP32-P4 gets you into the Quadra era. Which, honestly, covers the majority of daily tasks most people use computers for.

The RP2350 and ESP32-P4 both have more than 640kB of RAM, so that famous Bill Gates quote obviously didn’t age any better than Thomas Watson’s prediction. As Yogi Berra once said: predictions are hard, especially about the future. Continue reading “Ask Hackaday: How Much Compute Is Enough?”