Mysterious Files PH

Perhaps the hardest thing for amateur astronomers just starting out is finding the things you want to look at. Prolific maker [mircemk] has submitted a quick-and-easy star-hopper device that will help guide your binoculars with laser-like precision using things you likely already have on hand: a smartphone, a mounting plate, and a green laser pointer.

The smartphone is running AstroHopper, an astronomy app that uses GPS and inertial navigation to know exactly where your phone is pointing, and offer an image of the sky on the screen. There are many others of this ilk, and there’s no reason [mircemk]’s trick won’t work with your favorite. The trick is decidedly simple: the smartphone is mounted to a flat plate, in line with a green laser pointer. Careful placement aligns the axis of the phone and the laser, and the mounting plate is set up to fit a tripod.

Using it is simple: with a labelled view of the sky displayed on the screen, one lines up the phone/laser combo with the desired object, and activates the laser pointer. [micremk] has wired in an on-off switch for this purpose and a large external battery, rather than relying on the stock pushbutton. Since the axis of the laser pointer and the phone are aligned, a green line launches out into the heavens for you to follow with your binoculars. Once you locate that green dot, you can turn off the laser. Yes, the computer has helped you find the object, but your muscles are doing the slewing and that will make it much more likely you start to learn the sky yourself rather than relying on electronic magic.

This is probably the simplest hack we’ve yet seen in the Frikkin’ Lasers Challenge, and yet also one of the most practical. If you enjoy playing with radiation that’s spontaneously emitted, there’s still time to get your entry together — the contest runs until July 23, 2026.

If you’re big into retrocomputing, you probably spend a lot of time chasing parts and machines on online classifieds or through local swap meets. But what if there was a different way to build a classic retro PC? What if you could put one together from bare chips, from the ground up?

[Jeroen Domburg] is no stranger to the pages of Hackaday. You might know him by his alias, [sprite_tm], under which he’s shared many projects, from miniaturizing old hardware to unearthing the secrets of undocumented commercial hardware. Now, he’s turning his considerable skills to figuring out how to build a retro PC in today’s world, and came to Hackaday Europe 2026 to show us all how it’s done.

Game On

[Jeroen’s] goal was simple—to build a powerful retro gaming PC from the ground up. The first thing to decide was which era to target, with [Jeroen] deciding that 1995 seemed the most personally relevant to his interests. This was the peak of the MS-DOS gaming era, before things like DirectX came in and the culture shifted to Windows gaming and the domination of 3D over all else.

What does a good 1995 machine look like? It was probably rocking a 486, or maybe a Pentium, with somewhere between 8-16 MB of RAM. You had a simple video card primarily built for 2D graphics, and a sound card that was probably some variant of Sound Blaster or other. [Jeroen] wanted to build such a machine with as much real silicon as possible, rather than just emulating hardware from this era, and he wanted to do this himself at the component level, rather than just plugging in bits and pieces from eBay. Building a vintage-style PC motherboard from scratch and getting it up and running is a bit of a job, but luckily [Jeroen] has the skills to make it possible.

While [Jeroen] was looking to the past, he also wanted to take advantage of modern quality of life improvements, mainly by eliminating mechanical parts. Old hard drives and floppy drives from this era are seriously showing their age by now, and becoming particularly unreliable. There are better storage solutions available today that are faster and easier to use. The choice was also made to use modern peripherals, rather than relying on 30-year-old keyboards and mice.

The core of the build was an AMD Elan SC520, running at 133 MHz. This was one of the so-called “586” chips that were spawned following the 486 era, in [Jeroen’s] words, being a “486 but a bit souped up.” This chip came out in 2000, a full six years after Intel curtailed 486 production, a time when the Pentium III was already hitting 1 GHz clock speeds. It’s an anachronistic choice for a 1995 machine, but [Jeroen] picked it for good reason. The Elan SC520 was more of a system-on-chip, integrating lots of supporting low-level hardware onto the CPU itself, like the real-time clock and programmable interval timer (PIT), which would make his build easier. [Jeroen] threw this on a board with an FPGA and an ESP32 and a smattering of support components, and got a general purpose machine up together in a tiny form factor. If you’re thinking of a Raspberry Pi built with a knockoff 486, you’re not far off the money.

This first build had some issues that caused a lot of stress. Namely, the Elan SC520 was a large BGA, and it was difficult to verify if it was perfectly soldered or not. This meant that as [Jeroen] worked on the board and spun up the supporting FPGA and such, it was very difficult to know if things weren’t working because of his own code or because of a missing solder ball or a short. This led him to return to the drawing board.

The second attempt involved a regular CPU rather than the difficult-to-wrangle AMD system-on-chip. Namely, a classic i486 DX4-100 and AM486DX5-133 were sourced as potential CPU options. A C&T F65545 VGA chip was enlisted to handle graphical duties, being a laptop chipset that integrated lots of necessary support hardware into the one package. The plan was to throw just about everything else into an ECP5 LFE5UM-45 FPGA chipset, plus an ESP32-S3 to act as a peripheral interface. [Jeroen] decided to use SDRAM, which was much newer than that typically used with a 486, but this was chosen for being easy to integrate with the FPGA. With a goal to just get to a DOS prompt, [Jeroen] eliminated as much extraneous hardware as possible to get the project moving forward quickly. After spinning up a PCB, learning all about what it takes to bring up a 486-based machine, and working up the FPGA-based chipset, things all came together. A bit of cribbing from MiSTer projects helped, too. [Jeroen] eventually had his new old machine displaying a basic BIOS, then running some benchmarks, and then even running games like Commander Keen. The talk goes on to explain all the other little bits and pieces that come together, like storage, MIDI support, sound, and networking. Seeing it then turned into a portable game station named the Vapourdeck is just the icing on the cake.

If you just want to play some retro games, your quickest route will still be emulation or just purchasing components to build a 90s spec machine. If you want to really learn what makes a classic 486-era machine work, though, it’s hard to beat this approach. [Jeroen] even notes that taking a similar approach to his could let you build something up to the 500 MHz range or so, based on the chipsets and CPUs available from way back when. If you want to learn more or pursue this yourself, it’s well worth poring over the talk and checking out the project files online. Happy hacking.

There are many experimenters who have had a go at a mechanical television, and though there are a few challenges, it’s a relatively straightforward project in 2026. A hundred years ago though it was still beyond the cutting edge of technology, and that’s where [Paul Kocyla] is placing his build. It’s a mechanical TV system, using only parts that would have been available in the 1920s. The project isn’t finished yet, but we suggest following along for some fascinating insights into developments in early electronics.

As it stands he has a wooden chassis, a period power supply and amplifier, a synchronous motor, and of course the Nipkow disk that makes it all possible. The electronics aren’t quite finished, and he’s yet to source a neon lamp. This last party may be particularly tricky, as there were specific flat-plate neon lamps made for this application. It’s interesting to find that the motor would synchronize to the grid frequency and would need to be restarted a few times for the frame to be in the right place.

His last posting contains a particularly interesting nugget of information for anyone using tubes. The amplifier carries a 120 Hz hum, something difficult to trace. The culprit is the early tubes with directly heated cathodes formed from the heaters themselves; they had such a low thermal mass that they would “blink” at 120 Hz if fed with AC. A set of period copper oxide rectifiers solve this by feeding DC to the heaters. There’s a YouTube series to follow, and we’ve placed the most recent one in which he fixes the power supply, below the break.

Back in January, we marked the hundredth anniversary of mechanical TV’s invention. Meanwhile, some of us have been known to experiment in this direction too.

 

 

Sometimes, it’s hard to stop picking up your phone every few minutes to check on notifications and scroll endlessly through the slop of the day. [PushpendraC2] has been working on a solution to this problem that would ideally discourage such behavior —  a nifty little smartphone stand!

The concept is straightforward enough—the smartphone stand uses a simple tactile button to determine if your smartphone is sitting on the little 3D printed shelf, or not. However, the smarts inside do a bit more than that, too. An ESP32-S3 is charged with monitoring whether the smartphone is sitting in place, and starts counting “focus time” while it’s there. If the phone is picked up, the OLED display on the shelf starts ticking down a 5-second timer to encourage you to put it back. If you don’t, the focus time is reset and you lose your streak.

It’s also possible to tap a touch sensor on the device which sets a reminder timer, prompting you to put your phone back after a set period of time, between 2 to 30 minutes. A buzzer will then start going off to prompt you to put the phone down. If you want to track the devices impact, you merely need to log in to the web server hosted by the ESP32, which shows your current focus session time, along with a heatmap of your daily productivity.

It’s a simple idea, but one that uses a few neat psychological hooks to encourage compliance and behavioral change. We’ve featured similar projects in this vein before, No surprise, as phone addiction is a problem experienced by many.

Reachy Mini is a limbless desktop robot from Hugging Face made for human interaction experiments, and to give you an idea of what it’s like is a guide on how to implement expressive, local conversational AI complete with head movements and antenna wiggles. It’s conversational in the sense that it aims to feel natural, with low-latency responses and the ability to interrupt, with everything running on local hardware if one so wishes.

The software stack is essentially VAD (voice activity detection) → STT (speech-to-text) → LLM (large language model) → TTS (text-to-speech) which allows users to tweak things to their liking, or independently swap or modify pieces as things evolve.

This also allows users to tailor the services to match whatever their hardware is capable of. For example, one could easily use a frontier AI model via remote API for the LLM while keeping everything else local.

The local models in the example configuration are effective and relatively modest (Qwen3-4B-Instruct for the LLM, and even smaller models for the rest) but it’s nice to have the option to offload parts to remote providers if necessary.

Reachy Mini looked very interesting when it was launched as a kit last year, and since then Hugging Face has built up an impressive software suite and infrastructure through which users can easily share their applications. If you’re curious, there’s a simulator for Reachy Mini which should give you an idea of what it can do.

[Sam Wilkinson] recently installed a Dreo CLF513S ceiling fan in his place — it’s cheap, well-sized, and blows air around as you’d expect it to. The only problem is that it only works with an ugly cloud-only smart home setup out of the box. Never mind, though, because [Sam] figured out how to hack up a custom solution.

Hacking efforts began with the included remote control. [Sam] identified that the remote had to be RF, since it didn’t need line of sight to work properly. The FCC ID on the back of the device further indicated this was the case. Armed with that knowledge, it was simply a case of figuring out the commands sent by the remote, building something to replay them, and then hooking that into [Sam]’s existing Home Assistant setup.

The remote ran on 433.92 MHz, a not-uncommon bit of spectrum for these sort of appliances. An RTL-SDR was thusly enlisted to capture the output, with a spectrogram indicating the remote used simple on-off keying to send commands. Once commands were captured, [Sam] grabbed an ESP32-C6 microcontroller, hooked it up to a RFM69HCW radio transceiver, and programmed it to replay the fan on/off command. From there, a little dabbling with MQTT got the ESP32 controlling the fan as desired from within the Home Assistant ecosystem.

Sometimes, it’s hard to find smart home gear that actually suits your tastes and budgets. Often, a bit of tinkering can shape existing appliances to bend to your will instead. If you’re tweaking your own gear to better fit your smart home, don’t hesitate to notify the tipsline.

If you’re a fleshy human, you probably learn to play video games by looking at the screen and pressing the buttons, and maybe copying the way you’ve seen others play the game before. [tryfonaskam] has recently been trying to teach an AI to play games in much the same way.

[tryfonaskam] built PILA—short for Polytrack Imitation Learning Agent. As you might have guest from the name, it’s an AI agent designed to play a simple racing game called PolyTrack. Rather than manually programming the agent’s behavior, PILA instead trains itself through supervised learning, where it observes the gameplay state via screen capture and monitoring the keyboard inputs made by human players as they drive the tracks. It then uses this to guide its own behavior, and learns to play the game by itself. The model receives live frames from the graphics engine while playing, and then predicts the appropriate actions and makes the right keyboard inputs in turn to steer the car through the track.

This project reminds us of similar efforts to teach a raw AI how to play Trackmania, or the Drivatar technology in the Forza series of racing games.