Variable-Pitch Propellers For More Efficient Quadcopter

Quadcopters tend to have very poor efficency because of their high disk loading. High disk loading– that is, how much weight each square meter of area swept by the propellers must carry–is almost unavoidable with conventinal quadcopters, which are controlled by throttling the four props. Make the propellers too big, and their inertia slows down that control loop, leading to stability problems. [rctestflight] had an idea to solve this, by borrowing a technology from the world of fixed-wing aviation: variable-pitch propellers.

In aircraft use, they are not new, dating back to the end of the first world war. They’re made for everything from the largest turboprops to the  75 kW(100 HP) Rotax 912. By varying the propeller pitch, you can keep the engine turning in its ideal RPM range but still vary thrust by taking a larger or shallower ‘bite’ out of the air with each sweep of the prop. You can probably see how this applies to the quadcopter: a well-designed pitch-change mechanism is going to be much quicker than throttling a big prop with lots of rotational inertia. That’s the theory.

To test it, [rctestflight] builds some large 3D-printed variable pitch props, hooks them up to regular drone motors via a belt drive, before going on–you guessed it–an RC test flight. To make that work, he’s got the pitch servo being driven from what should be the flight controller’s thrust output to each motor. Aside from the vibrations from imperfect balance on the 3D-printed props, it flies quite well– and much better with pitch control than trying to vary the RPMs of those heavy props. He’s even able to reverse the propeller pitch, making this perhaps the first quadcopter capable of autorotation. Well, almost, given that it lost control and came apart when he cut the throttle.

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A stick of DDR4 in DIMM format held by some alligator clips

Dodging A 60-Year-Old Design Flaw In Your RAM

Modern computers use dynamic RAM, a technology that allows very compact bits in return for having to refresh for about 400 nanoseconds every 3-4 microseconds. But what if you couldn’t afford even such a tiny holdup? [LaurieWired] goes into excruciating detail about how to avoid this delay.

But first, why do we care? It once again comes down to high-frequency trading; a couple nanoseconds of latency can be the difference between winning or losing a buy order. You likely miss all the caches and need to fetch data from the remote land of main memory. And if you get unlucky, you’ll be waiting on that price for a precious 400+ nanoseconds! [Laurie] explains all the problems faced in trying to avoid this penalty; you try to get a copy of the data on two independent refresh timers. That’s easier said than done; not only does the operating system hide the physical addresses from you, but the memory controllers themselves also scramble the addresses to the underlying RAM!

For the real computer architecture nerds, there’s a lot more to it, and [Laurie] goes over it in meticulous detail in the video after the break.
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an animated gif of the eye in motion.

Bending Faux-Neon LEDs Make For Animations Glass Tubes Can’t Match

Odds are, if you like neon lights, you’re not thrilled with the LED faux-“neon” strips that are supposed to replace them. They’ve got their advantages, but the light quality of RGB LEDs lacks something compared to the emission spectrum of nobel gas, at least to purists. On the other hand, you cannot create an animation by bending glass tubes, like [David Hamp-Gonsalves] has demonstrated with his Neon Animated Eye.

Back in the day, you’d have needed dozens of tubes for a flickery animation, but [David] figured that since these LED strips are flexible, why not flex them? He’s using addressable LEDs — WS2812s, specifically — so activating and deactivating the pupil of the eye is easy-peasy. Opening and closing the lid is accomplished with a geared motor driven by a TB6612 driver turning a barrel cam. The ends of the stiff LED strip being brought together and pulled apart result in the blinking effect here, but as [David] points out you’re hardly limited that specific motion. There’s a whole world of Tron-like glowing animatronics that can be created with this technique. Code and STLs are available on GitHub, though, if you want to replicate the eye exactly.

[David] says he’d like to see this in a storefront someday, but given that fatigue life is a thing, it might be something to keep in your back pocket for seasonal displays like Christmas and Halloween rather than something that’s going to run 24/7. On the other hand, if you’re careful about limiting flexion and which faux-neon strip you buy, you might be able to create an animation that can last for years.

This is hardly the first time we’ve seen these faux-neon strips , but it is the first time we’ve seen them animated. We can’t help but think the Hauntimator software we featured before would be a good paring with this hack.

2001: An Air Quality Odyssey

2001: A Space Odyssey not only pushed the boundaries of filmmaking, but introduced us to one of the most enduring villains in all of media. The HAL 9000 artificial intelligence was human-like but inhuman, a singular uncanny red light on a wall, tasked not only with control of a spaceship and its inner workings but also with being a companion for its occupants. It’s gone on to be the inspiration and basis of many projects around here, where it is generally given much less scope than control of a space ship and instead is tasked with something like monitoring air quality in a home.

Called the PAL 8000 by its creator [Arnov], this uses a Raspberry Pi Pico 2 at its core which monitors a volatile organic compound (VOC) sensor to take air quality measurements. The device features a custom 3D printed enclosure with glowing LEDs and plays contextual audio responses based on air quality levels, completing the HAL 9000 theme. The project also includes a local web dashboard which reports on its data, allowing users to see information in real time rather than relying on HAL’s voice reports alone.

For those looking to build other HAL-inspired projects, [Arnov] has made many of the printing files available on the project’s site. It’s a well-polished build faithful to the source material and could be a great addition to any home automation system for many other tasks beyond air quality monitoring. Perhaps something like a more general-purpose voice assistant, minus the megalomania.

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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”

Are We Surrendering Our Thinking To Machines?

“Once, men turned their thinking over to machines in the hope that this would set them free. But that only permitted other men with machines to enslave them.” — so said [Frank Herbert] in his magnum opus, Dune, or rather in the OC Bible that made up part of the book’s rich worldbuilding. A recent study demonstrating “cognitive surrender” in large language model (LLM) users, as reported in Ars Technica, is going to add more fuel to that Butlerian fire.

Cognitive surrender is, in short, exactly what [Herbert] was warning of: giving over your thinking to machines. In the study, people were asked a series of questions, and — except for the necessary “brain-only” control group — given access to a rigged LLM to help them answer. It was rigged in that it would give wrong answers 50% of the time, which while higher than most LLMs, only a difference in degree, not in kind. Hallucination is unavoidable; here it was just made controllably frequent for the sake of the study.

The hallucinations in the study were errors that the participants should have been able to see through, if they’d thought about the answers. Eighty percent of the time, they did not. That is to say: presented with an obviously wrong answer from the machine, only in 20% of cases did the participants bother to question it. The remainder were experiencing what the researchers dubbed “cognitive surrender”: they turned their thinking over to the machines. There’s a lot more meat to this than we can summarize here, of course, but the whole paper is available free for your perusal.

Giving over thinking to machines is nothing new, of course; it’s probably been a couple decades since the first person drove into a lake on faulty GPS directions, for example. One might even argue that since LLMs are correct much more than 50% of the time, it is statistically wise to listen to them. In that case, however, one might be encouraged to read Dune.

Thanks to [Monika] for the tip!

Espressif’s New ESP32-S31: Dual-Core RISC-V With WiFi 6 And GBit Ethernet

In a move that’s no doubt going to upset and confuse many, Espressif has released its newest microcontroller — the ESP32-S31. The confusing part here is that the ESP32-S series was always the one based on Tensilica Xtensa LX7 cores, while the ESP32-C series was the one using RISC-V cores.

That said, if one looks at it as a beefier -S3 MCU it does have some appealing upgrades. The most obvious improvements are with the use of WiFi 6, as well as Bluetooth Classic and LE 5.4, including LE Audio. There is also Thread and Zigbee support for those who are into such things.

The Ethernet MAC got a bump from the 100 Mbit RMII MAC in previous MCUs and is now gigabit-rated, while the number of GPIO is significantly higher at 60 instead of 45 on the -S3. On the RAM side, things are mostly the same, except for DDR PSRAM support, with octal SPI offering up to 250 MHz compared to 80 MHz on the -S3.

On the CPU side the up-to-320 MHz RISC-V cores are likely to be about as powerful as the 240 MHz LX7 cores in the -S3, based on the ESP32-C series performance in terms of IPC. Overall it does seem like a pretty nice MCU, it’s just confusing that it doesn’t use LX7 cores with the series it was put into. When this MCU will be available for sale doesn’t seem to be known yet, with only samples available to select customers.