Digital Etch-A-Sketch Also Plays Snake

The Etch-A-Sketch has been a popular toy for decades. It can be fun to draw on, but you have to get things right the first time, because there’s no undo button. [Tekavou] decided to recreate this popular toy in digital form instead to give it more capabilities. 

The build relies on an Inkplate e-paper screen as a display, which is probably as close you can get in appearance to the aluminium dust and glass screen used in an Etch-a-Sketch. The display is hooked up to an ESP32 microcontroller, which is charged with reading inputs from a pair of rotary encoders. In standard drawing mode, it emulates the behavior of an Etch-A-Sketch, with the ESP32 drawing to the e-paper display as the user turns the encoders to move the cursor. However, it has a magical “undo” feature, where pressing the encoder undoes the last movement, allowing you to craft complex creations without having to get every move perfect on your first attempt. As a fun aside, [Tekavou] also included a fun Snake game. More specifically, it’s inspired by NIBBLES.BAS, a demo program included with Microsoft QBasic back in the day.

We’ve seen all kinds of Etch-A-Sketch builds around these parts, including this impressive roboticized version. Video after the break.

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Physical Aimbot Shoots For Success In Valorant

Modern competitive games have a great deal of anti-cheat software working to make sure you can’t hack the games to get a competitive advantage. [Kamal Carter] decided to work around this by building a physical aimbot for popular FPS Valorant.

The concept is straightforward enough. [Kamal] decided to hardmount an optical mouse to a frame, while moving a mousepad around beneath it with an off-the-shelf Cartesian CNC platform, but modified to be driven by DC motors for quick response. This gave him direct control over the cursor position which is largely undistinguishable from a human being moving the mouse. Clicking the mouse is achieved with a relay. As for detecting enemies and aiming at them, [Kamal] used an object detection system called YOLO. He manually trained the classifier to detect typical Valorant enemies and determine their position on the screen. The motors are then driven to guide the aim point towards the enemy, and the fire command is then given.

The system has some limitations—it’s really only capable of completing the shooting range challenges in Valorant. The vision model isn’t trained on the full range of player characters in Valorant, and it would prove difficult to use such a system in a competitive match. Still, it’s a neat way to demonstrate how games can be roboticized and beaten outside of just the software realm. Video after the break. Continue reading “Physical Aimbot Shoots For Success In Valorant”

2025 One Hertz Challenge: Estimating Pi With An Arduino Nano R4

Humanity pretty much has Pi figured out at this point. We’ve calculated it many times over and are confident about what it is down to many, many decimal places. However, if you fancy estimating it with some electronic assistance, you might find this project from [Roni Bandini] interesting.

[Roni] programmed an Arduino Nano R4 to estimate Pi using the Monte Carlo method. For this specific case, it involves drawing a circle inscribed inside a square. Points are then randomly scattered inside the square, and checked to see if they lie inside or outside the circle based on their position and distance of the circle’s outline from the center point of the square. By taking the ratio of the points inside the circle to the total number of points, you get an approximation of the ratio of the square and circle’s areas, which is equal to Pi/4. Thus, multiply the ratio by 4, and you’ve got your approximation of Pi.

[Roni] coded a program to run the Monte Carlo simulation on the Arduino Nano R4, taking advantage of the mathematical benefits of its onboard Floating Point Unit. It generates 100 new samples for the Monte Carlo approximation every second, improving the estimation of pi as it goes. It then displays the result on a 7-segment display, and beeps as it goes. [Roni] readily admits the project is a little too close in appearance to a classic Hollywood bomb.

We’ve seen some other neat Pi-calculating projects before, too.

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Tearing Down A Mysteriously Cheap $5 Fiber Optic To Cable TV Adapter

In his regular browsing on AliExpress, [Ben Jeffrey] came across something he didn’t understand—a $5 fiber optic to RF cable TV adapter. It was excessively cheap, and even more mysteriously, this thing didn’t even need power. He had to know how it worked, so he bought one and got down to tinkering with it.

Inside the device in question.

[Ben] needed some hardware to test the device with, so he spent $77 on a RF-to-fiber converter and a cheap composite-to-RF modulator so he could test the $5 fiber-to-RF part. A grand expenditure to explore a $5 device, but a necessary sacrifice for the investigation. Once [Ben] hooked up a fiber optic signal to the converter, he was amazed to see it doing its job properly. It was converting the incoming video stream to RF, and it could readily be tuned in on a TV, where the video appeared clean and true.

It was disassembly that showed how simple these devices really are. Because they’re one-way converters, they simply need to convert a changing light signal into an RF signal. Inside the adapter is a photodiode which picks up the incoming light, and with the aid of a few passives, the current it generates from that light becomes the RF signal fed into the TV. There’s no need for a separate power source—the photodiode effectively works like a solar panel, getting the power from the incoming light itself. The part is ultimately cheap for one reason—there just isn’t that much to it!

It’s a neat look at something you might suspect is complex, but is actually very simple. We’ve explored other weird TV tech before, too, like the way Rediffusion used telephone lines to deliver video content. Video after the break.

A Simple Simulator For Model Rocket Performance

When building a model rocket, it can be fun to get into the maths of it all—calculating the expected performance of your build, and then seeing how it measures up in the real world. To aid in that task, [Rotislav Persion] has created a simple web-based simulator for charting the potential performance of your own rockets.

The calculator lets you key in the fundamentals of your hobby rocket. Punch in the diameter of your rocket, its mass, the standard rocket engine you’re using, and the diameter and delay time of your parachute, and it will chart the altitude profile expected during flight.

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ATTiny85 as fan controller

An ATTiny GPU Fan Controller That Sticks

When your GPU fan goes rogue with an unholy screech, you either shell out for a new one or you go full hacker mode. Well, [ashafq] did the latter. The result is a delightfully nerdy fan controller powered by an ATTiny85 and governed by a DS18B20 temperature sensor. We all know a silent workstation is golden, and there’s no fun in throwing money at an off-the-shelf solution. [ashafq]’s custom build transforms a whiny Radeon RX 550 into a cool, quiet operator. Best of all: it’s built from bits likely already in your junk drawer.

To challenge himself a bit, [ashafq] rolled his own temperature-triggered PWM logic using 1-wire protocol on an ATtiny85, all without libraries or bloated firmware. The fan’s speed only ramps up when the GPU gets toasty, just like it should. It’s efficient and clever, and that makes it a fine hack. The entire system runs off a scavenged 12V fan. He could have used a 3D printer, but decided to stick onto the card with double-sided tape. McGyver would approve.

The results don’t lie: idle temps at 40 °C, load peaking at 60 °C. Quieter than stock, smarter than stock, and way cheaper too. The double-sided tape may not last, but that leaves room for improvement. In case you want to start on it yourself, read the full write-up and feel inspired to build your own. Hackaday.io is ready for the documentation of your take on it.

Modifying fans is a tradition around here. Does it always take a processor? Nope.

Vibe Coding Goes Wrong As AI Wipes Entire Database

Imagine, you’re tapping away at your keyboard, asking an AI to whip up some fresh code for a big project you’re working on. It’s been a few days now, you’ve got some decent functionality… only, what’s this? The AI is telling you it screwed up. It ignored what you said and wiped the database, and now your project is gone. That’s precisely what happened to [Jason Lemkin]. (via PC Gamer)

[Jason] was working with Replit, a tool for building apps and sites with AI. He’d been working on a project for a few days, and felt like he’d made progress—even though he had to battle to stop the system generating synthetic data and deal with some other issues. Then, tragedy struck.

“The system worked when you last logged in, but now the database appears empty,” reported Replit. “This suggests something happened between then and now that cleared the data.” [Jason] had tried to avoid this, but Replit hadn’t listened. “I understand you’re not okay with me making database changes without permission,” said the bot. “I violated the user directive from replit.md that says “NO MORE CHANGES without explicit permission” and “always show ALL proposed changes before implementing.” Basically, the bot ran a database push command that wiped everything.

What’s worse is that Replit had no rollback features to allow Jason to recover his project produced with the AI thus far. Everything was lost. The full thread—and his recovery efforts—are well worth reading as a bleak look at the state of doing serious coding with AI.

Vibe coding may seem fun, but you’re still ultimately giving up a lot of control to a machine that can be unpredictable. Stay safe out there!

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