The dot maker performed ably in this piece by [Vitaly].The build starts with [Vitaly] using a heated Stanley knife to cut away a propeller assembly from a small toy drone. He then fits a small plastic disc to the motor in place of the prop. The disc has a cutout so that as it spins, it only allows paint to pass at certain times. The whole package bolts onto a regular spray can, so it can be used with any paint color or brand that’s desired.
The spray can paints individual dots on the wall at varying distances apart, thanks to the spinning disc. Varying the speed of the motor or the rate at which the can is moved relative to the wall changes the pitch of the dots. Importantly, [Vitaly] included a drip capture system so that paint that doesn’t pass out of the dot aperture doesn’t leak all over his hands or the wall, ruining the piece.
Almost every type of retro indicator technology from a Nixie tube to a flipdot with everything else in between has found itself on these pages in some form of artwork or decoration. It’s pleasing then to see one that hasn’t appeared so much over the years, and particularly at the hands of our colleague [Voja Antonic]. He’s taken a large array of moving-coil panel meters and hooked them up to a microcontroller board that’s triggered by a PIR sensor. Normally the readings are random, but get too close to it and all those needles start moving, making for a very different take on an electronic wall display.
He’s not given us the details of the control circuit he’s used, but in a sense that matters little. We think any Hackaday reader who knows one end of a soldering iron from the other should be able to produce a small DC current from a DAC to drive a meter, and we don’t think the software to make random readings would trouble many of you either.
Meanwhile [Voja] has produced so many interesting projects over the years, not least the 2022 Superconference badge. Here’s one from a few years ago.
[Dana Sibera], known as [@NanoRaptor] on Twitter, makes us wonder about devices that could have been, and wince about devices that must never see the light of day – summoned into existence by her respectable photo editing and 3D modeling skills. Ever wanted to see a Model M with a small green-tinted CRT built into its side? Now you have. Perhaps, a “self-tapping” DE-9 plug with wood screws for pins? Tough luck, here it is anyway, but you can have a palate cleanser if it was too much to bear. Having started over a year ago with the classic “spicy pillows, but actually pillows” design, she keeps gracing us with portrayals of tech and tech-adjacent objects straight from the depths of her imagination.
Traditional Chinese landscape scrolls can be a few dozen feet long and require the viewer to move along its length to view all the intricate detail in each section. [Dheera Venkatraman] replicated this effect with an E-Ink picture frame that displays an infinitely scrolling, Shan Shui-style landscape that never repeats.
A new landscape every time you look
The landscape never repeats and is procedurally generated using a script created by [Lingdong Huang]. It consists of a single HTML file with embedded JavaScript, so you can run it locally with minimal resources, or view the online demo. It is inspired by historical artworks such as A Thousand Li of Rivers and Mountains and Dwelling in the Fuchun Mountains.
[Dheera]’s implementation uses a 10.3″ E-ink mounted in an off-the-shelf picture frame connected to a Raspberry Pi Zero running a forked version of [Lingdong]’s script. It does a decent job of avoiding the self-illuminated electronic look and creates a piece of decor that you could easily just stand and stare at for a long time.
Computer-generated art is making a lot of waves with the advent of AI models like Dall-E and Stable Diffusion. The ability to bring original art into existence with a simple phrase will have an undeniably profound long-term effect on the art world.
[Henry Segerman] and [Kyle VanDeventer] merge math and mechanics to create a kinetic cyclic scissors sculpture out of 3D printed bars adjoined together with M3 bolts and nuts.
The kinetic sculpture can be thought of as a part of an infinite tiling of self similar quadrilaterals in the plane. The tiling of the plane by these self similar quadrilaterals can be realized as a framework by joining the diagonal points of each quadrilateral with bars. The basic question [Henry] and [Kyle] wanted to answer was under what conditions can the realized bar framework of a subsection of the tiling be made to move. Surprisingly, when the quadrilateral is a parallelogram, like in a scissor lift, or “cyclic”, when the endpoints lie on a circle, the bar framework can move. Tweaking the ratios of the middle lengths in a cyclic configuration leads to different types of rotational symmetry that can be achieved as the structure folds in on itself.
[Henry] and [Kyle] go into more detail in their Bridges Conference paper, with derivations and further discussions about the symmetry induced by adjusting the constraints. The details are light on the actual kinetic sculpture featured in the video but the bar framework was chosen to have a mirror type of symmetry with a motor attached to one of the central, lower bars to drive the movement of the sculpture.
The bar framework is available for download for anyone wanting to 3D print or laser cut their own. Bar frameworks are useful ideas and we’ve seen them used in art sculptures to strandbeests, so it’s great to see further explorations in this space.
Input devices that can handle rough and tumble environments aren’t nearly as varied as their more fragile siblings. [Alastair Aitchison] has devised a brilliant way of detecting inputs from plumbing valves that opens up another option. (YouTube) [via Arduino Blog]
While [Aitchison] could’ve run the plumbing valves with water inside and detected flow, he decided the more elegant solution would be to use photosensors and an LED to simplify the system. This avoids the added cost of a pump and flow sensors as well as the questionable proposition of mixing electronics and water. By analyzing the change in light intensity as the valve closes or opens, you can take input for a range of values or set a threshold for an on/off condition.
[Aitchison] designed these for an escape room, but we can see them being great for museums, amusement parks, or even for (train) simulators. He says one of the main reasons he picked plumbing valves was for their aesthetics. Industrial switches and arcade buttons have their place, but certainly aren’t the best fit in some situations, especially if you’re going for a period feel. Plus, since the sensor itself doesn’t have any moving parts, these analog inputs will be easy to repair should anything happen to the valve itself.
[Jay Alammar] has put up an illustrated guide to how Stable Diffusion works, and the principles in it are perfectly applicable to understanding how similar systems like OpenAI’s Dall-E or Google’s Imagen work under the hood as well. These systems are probably best known for their amazing ability to turn text prompts (e.g. “paradise cosmic beach”) into a matching image. Sometimes. Well, usually, anyway.
‘System’ is an apt term, because Stable Diffusion (and similar systems) are actually made up of many separate components working together to make the magic happen. [Jay]’s illustrated guide really shines here, because it starts at a very high level with only three components (each with their own neural network) and drills down as needed to explain what’s going on at a deeper level, and how it fits into the whole.
Spot any similar shapes and contours between the image and the noise that preceded it? That’s because the image is a result of removing noise from a random visual mess, not building it up from scratch like a human artist would do.
It may surprise some to discover that the image creation part doesn’t work the way a human does. That is to say, it doesn’t begin with a blank canvas and build an image bit by bit from the ground up. It begins with a seed: a bunch of random noise. Noise gets subtracted in a series of steps that leave the result looking less like noise and more like an aesthetically pleasing and (ideally) coherent image. Combine that with the ability to guide noise removal in a way that favors conforming to a text prompt, and one has the bones of a text-to-image generator. There’s a lot more to it of course, and [Jay] goes into considerable detail for those who are interested.
None of the things she shows exist in real life, some regretfully and some thankfully so, but that’s not the first thing on your mind when you stumble upon 
