Supersized Calculator Brings The Whole Intel 4004 Gang Together

Though mobile devices and Apple Silicon have seen ARM-64 explode across the world, there’s still decent odds you’re reading this on a device with an x86 processor — the direct descendant of the world’s first civilian microprocessor, the Intel 4004. The 4004 wasn’t much good on its own, however, which is why [Klaus Scheffler] and [Lajos Kintli] have produced super-sized discrete chips of the 4001 ROM, 4002 RAM, and 4003 shift register to replicate a 1970s calculator at 10x the size and double the speed, all in time for the 4004’s 50th anniversary.

We featured this project a couple of years back, when it was just a lonely microprocessor. Adding the other MSC-4 series chips enabled the pair to faithfully reproduce the logic of a Busicom 141-PF calculator, the very first to market with Intel’s now-legendary microprocessor. Indeed, this calculator is the raison d’etre for the 4004: Busicom commissioned the whole Micro-Computer System 4-bit (MCS-4) set of chips specifically for this calculator. Only later, once they realized what they had made, did Intel buy the rights back from the Japanese calculator company, and the rest, as they say, is history.

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Hackaday Links: November 16, 2025

We make no claims to be an expert on anything, but we do know that rule number one of working with big, expensive, mission-critical equipment is: Don’t break the big, expensive, mission-critical equipment. Unfortunately, though, that’s just what happened to the Deep Space Network’s 70-meter dish antenna at Goldstone, California. NASA announced the outage this week, but the accident that damaged the dish occurred much earlier, in mid-September. DSS-14, as the antenna is known, is a vital part of the Deep Space Network, which uses huge antennas at three sites (Goldstone, Madrid, and Canberra) to stay in touch with satellites and probes from the Moon to the edge of the solar system. The three sites are located roughly 120 degrees apart on the globe, which gives the network full coverage of the sky regardless of the local time.

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The Simplest Ultrasound Sensor Module, Minus The Module

Just about every “getting started with microcontrollers” kit, Arduino or otherwise, includes an ultrasonic distance sensor module. Given the power of microcontrollers these days, it was only a matter of time before someone asked: “Could I do better without the module?” Well, [Martin Pittermann] asked, and his answer, at least with the Pi Pico, is a resounding “Yes”. A micro and a couple of transducers can offer a better view of the world.

The project isn’t really about removing the extra circuitry on the SR-HC0, since there really isn’t that much to start. [Martin] wanted to know just how far he could push ultrasound scanning technology using RADAR signal processing techniques. Instead of bat-like chirps, [Martin] is using something called Frequency-Modulated Continuous Wave, which comes from RADAR and is exactly what it sounds like. The transmitter emits a continuous carrier wave with a varying frequency modulation, and the received wave is compared to see when it must have been sent. That gives you the time of flight, and the usual math gives you a distance.

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The King Of Rocket Photography

If you are a nerdy kid today, you have your choice of wondrous gadgets and time wasters. When we were nerdy kids, our options were somewhat limited: there was ham radio, or you could blow things up with a chemistry set. There were also model rockets. Not only were model rockets undeniably cool, but thanks to a company called Estes, you could find ready-to-go kits and gear that made it possible to launch something into the heavens, relatively speaking. But what about photographic proof? No live streams or digital cameras. But there was the Estes AstroCam 100. [Bill Engar] remembers the joy of getting film from your rocket developed.

Of course, photography was another nerdy kid staple, so maybe you did your own darkroom work. Either way, the Astrocam 110 was a big improvement over the company’s earlier Camroc. In 1965, if you wanted to fly Camroc, you had to cut a 1.5-inch piece of film in a darkroom and mount it just to get one terrible black-and-white photo. Or, you could buy the film canisters loaded if you had the extra money, which, of course, you didn’t.

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Using Multiple Quadcopters To Efficiently Lift Loads Together

Much like calling over a buddy or two to help with moving a large piece of furniture and pivot it up a narrow flight of stairs, so too can quadcopters increase their carrying capacity through the power of friendship and cooperation. However, unless you want to do a lot of yelling at your mates about when to pivot and lift, you’d better make sure that your coordination is up to snuff. The same is true with quadcopters, where creating an efficient coordination algorithm for sharing a load is far from easy and usually leads to fairly slow and clumsy maneuvering.

Simplified overview of the motion planner by Sihao Sun et al.
Simplified overview of the motion planner by Sihao Sun et al.

Recently. researchers at the Technical University of Delft came up with what appears to be a quite efficient algorithm for this purpose. In the demonstration video below, it’s easy to see how the quadcopters make short work of even convoluted obstacles while keeping themselves and their mates from getting tangled.

The research by [Sihao Sun] et al. appears in Science Robotics (preprint), in which they detail their trajectory-based framework and its kinodynamic motion planner. In short, this planner considers the whole-body dynamics of the load, the cables, and the quadcopters. An onboard controller for each quadcopter is responsible for translating the higher-level commands into specific changes to its rotor speeds and orientation.

Along with tests of its robustness to various environmental factors, such as wind, the researchers experimented with how many simultaneous quadcopters could work together with their available computing capacity. The answer, so far, is nine units, though they think that the implementation can be further optimized.

Of course, sometimes you just want to watch synchronized drones.

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An AI By Any Other Name

While there are many AI programs these days, they don’t all work in the same way. Most large language model “chatbots” generate text by taking input tokens and predicting the next token of the sequence. However, image generators like Stable Diffusion use a different approach. The method is, unsurprisingly, called diffusion. How does it work? [Nathan Barry] wants to show you, using a tiny demo called tiny-diffusion you can try yourself. It generates — sort of — Shakespeare.

For Stable Diffusion, training begins with an image and an associated prompt. Then the training system repeatedly adds noise and learns how the image degenerates step-by-step to noise. At generation time, the model starts with noise and reverses the process, and an image comes out. This is a bit simplified, but since something like Stable Diffusion deals with millions of pixels and huge data sets, it can be hard to train and visualize its operation.

The beauty of tiny-diffusion is that it works on characters, so you can actually see what the denoising process is doing. It is small enough to run locally, if you consider 10.7 million parameters small. It is pretrained on Tiny Shakespeare, so what comes out is somewhat Shakespearean.

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A photo of the LEGO sorter

Making A Machine To Sort One Million Pounds Of LEGO

You know what’s not fun? Sorting LEGO. You know what is fun? Making a machine to sort LEGO! That’s what [LegoSpencer] did, and you can watch the machine do its thing in the video below.

[Spencer] runs us through the process: first, quit your day job so you can get a job playing with LEGO; then research what previous work has been done in this area (plenty, it turns out); and then commit to making your own version both reproducible and extensible.

A sorting machine needs three main features: a feeder to dispense one piece at a time, a classifier to decide the type of piece, and a distributor to route the piece to a bin. Of course, the devil is in the details.

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