Hydrogen! It’s a highly flammable gas that seems way too cool to be easy to come by. And yet, it’s actually trivial to make it out of water if you know how. [Maciej Nowak] has shown us how to do just that with his latest build.

The project in question is a simple hydrogen generator that relies on the electrolysis of water. Long story short, run a current through water and you can split H₂O molecules up and make H₂ and O₂ molecules instead. From water, you get both hydrogen to burn and the oxygen to burn it in! Even better, when you do burn the hydrogen, it combines with the oxygen to make water again! It’s all too perfect.

This particular hydrogen generator uses a series of acrylic tanks. Each is fitted with electrodes assembled from threaded rods to pass current through water. The tops of the tanks have barbed fittings which allow the gas produced to be plumbed off to another storage vessel for later use. The video shows us the construction of the generator, but we also get to see it in action—both in terms of generating gas from the water, and that gas later being used in some fun combustion experiments.

Pedants will point out this isn’t really just a hydrogen generator, because it’s generating oxygen too. Either way, it’s still cool. We’ve featured a few similar builds before as well.

We’re all pretty familiar with AI’s ability to create realistic-looking images of people that don’t exist, but here’s an unusual implementation of using that technology for a different purpose: masking people’s identity without altering the substance of the image itself. The result is the photo’s content and “purpose” (for lack of a better term) of the image remains unchanged, while at the same time becoming impossible to identify the actual person in it. This invites some interesting privacy-related applications.

The paper for Face Anonymization Made Simple has all the details, but the method boils down to using diffusion models to take an input image, automatically pick out identity-related features, and alter them in a way that looks more or less natural. For this purpose, identity-related features essentially means key parts of a human face. Other elements of the photo (background, expression, pose, clothing) are left unchanged. As a concept it’s been explored before, but researchers show that this versatile method is both simpler and better-performing than others.

Diffusion models are the essence of AI image generators like Stable Diffusion. The fact that they can be run locally on personal hardware has opened the doors to all kinds of interesting experimentation, like this haunted mirror and other interactive experiments. Forget tweaking dull sliders like “brightness” and “contrast” for an image. How about altering the level of “moss”, “fire”, or “cookie” instead?

A little while ago Oasis was showcased on social media, billing itself as the world’s first playable “AI video game” that responds to complex user input in real-time. Code is available on GitHub for a down-scaled local version if you’d like to take a look. There’s a bit more detail and background in the accompanying project write-up, which talks about both the potential as well as the numerous limitations.

We suspect the focus on supporting complex user input (such as mouse look and an item inventory) is what the creators feel distinguishes it meaningfully from AI-generated DOOM. The latter was a concept that demonstrated AI image generators could (kinda) function as real-time game engines.

Image generators are, in a sense, prediction machines. The idea is that by providing a trained model with a short history of what just happened plus the user’s input as context, it can generate a pretty usable prediction of what should happen next, and do it quickly enough to be interactive. Run that in a loop, and you get some pretty impressive clips to put on social media.

It is a neat idea, and we certainly applaud the creativity of bending an image generator to this kind of application, but we can’t help but really notice the limitations. Sit and stare at something, or walk through dark or repetitive areas, and the system loses its grip and things rapidly go in a downward spiral we can only describe as “dreamily broken”.

It may be more a demonstration of a concept than a properly functioning game, but it’s still a very clever way to leverage image generation technology. Although, if you’d prefer AI to keep the game itself untouched take a look at neural networks trained to use the DOOM level creator tools.

Back in the summer our eye was caught by [Jazzy Jane]’s new signal generator, or perhaps we should say her new-to-her signal generator. It’s an Advance E1 from around 1950, and it was particularly interesting from here because it matches the model on the shelf above this bench. She’s back with a new video on the E1, allowing us a further look inside it as she replaces a dead capacitor, gets its audio oscillator working, and upgrades its sockets.

Treating us to a further peek inside the unit, first up is a leaky capacitor. Then a knotty question for old tech enthusiasts, to upgrade or not? The ancient co-ax connectors are out of place on a modern bench, so does originality matter enough to give it a set of BNC sockets? We’d tend to agree; just because we have some adapters for the unit here doesn’t mean it’s convenient. Following on from that is a period variable frequency audio mod which has failed, so out that comes and a little fault-finding is required to get the wiring of the audio transformer.

These instruments are not by any means compact, but they do have the advantage of being exceptionally well-built and above all cheap. We hope readers appreciate videos like the one below the break, and that you’re encouraged not to be scared of diving in to older items like this one to fix them. Meanwhile the first installment is here.

Steam turbines have helped drive a large chunk of our technological development over the last century or so, and they’ll always make for interesting DIY. [Hyperspace Pirate] built a small turbine and boiler in his garage, turning fire into flowing electrons, and learning a bunch in the process.

[Hyperspace Pirate] based the turbine design on 3D printed Pelton-style turbines he had previously experimented with, but milled it from brass using a CNC router. A couple of holes had to be drilled in the side of the rotor to balance it. The shaft drives a brushless DC motor to convert the energy from the expanding steam into electricity.

To avoid the long heat times required for a conventional boiler, [Hyperspace Pirate] decided to use a flash boiler. This involves heating up high-pressure water in a thin coil of copper tube, causing the water to boil as it flows down the tube. To produce the high-pressure water feed the propane tank for the burner was also hooked up to the water tank to pressurize it, removing the need for a separate pump or compressed air source. This setup allows the turbine to start producing power within twelve seconds of lighting the burner — significantly faster than a conventional boiler.

Throughout the entire video [Hyperspace Pirate] shows his calculation for the design and tests, making for a very informative demonstration. By hooking up a variable load and Arduino to the rectified output of the motor, he was able to measure the output power and efficiency. It came out to less than 1% efficiency for turning propane into electricity, not accounting for the heat loss of the boiler. The wide gaps between the turbine and housing, as well as the lack of a converging/diverging nozzle on the input of the turbine are likely big contributing factors to the low efficiency.

Like many of his other projects, the goal was the challenge of the project, not practicality or efficiency. From a gyro-stabilized monorail, to copper ingots from algaecide and and a DIY cryocooler, he has sure done some interesting ones.

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OOO (Out of Office) has created a new AI tool called the AI Trip Generator. The app uses databases and recommendations to create customized trip and travel ideas. To use the tool, you enter in your desired destination along with how many days you’ll be staying, then select the vibe you’re looking for. The AI […]

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[DTSS_Smudge] correctly intuits that if you are interested in an old Heathkit signal generator, you probably already know how to solder. So, in a recent video, he focused on the components he decided to update for safety and other reasons. Meanwhile, we get treated to a nice teardown of this iconic piece of test gear.

If you didn’t grow up in the 1960s, it seems strange that the device has a polarized line cord with one end connected to the chassis. But that used to be quite common, just like kids didn’t wear helmets on bikes in those days.

A lot of TVs were “hot chassis” back then, too. We were always taught to touch the chassis with the back of your hand first. That way, if you get a shock, the associated muscle contraction will pull your hand away from the electricity. Touching it normally will make you grip the offending chassis hard, and you probably won’t be able to let go until someone kindly pulls the plug or a fuse blows.

These signal generators were very common back in the day. A lot of Heathkit gear was very serviceable and more affordable than the commercial alternatives. In 1970, these cost about $32 as a kit or $60 already built. While $32 doesn’t sound like much, it is equivalent to $260 today, so not an impulse buy.

Some of the parts are simply irreplaceable. The variable capacitor would be tough to source since it is a special type. The coils would also be tough to find replacements, although you might have luck rewinding them if it were necessary.

We are spoiled today with so many cheap quality instruments available. However, there was something satisfying about building your own gear and it certainly helped if you ever had to fix it.

There was so much Heathkit gear around that even though they’ve been gone for years, you still see quite a few units in use. Not all of their gear had tubes, but some of our favorite ones did.

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Magic Tellers is an AI-powered service that lets you create personalized stories, children’s books, and coloring books. The platform has a database of story templates that can be tailored to each child’s needs. It has tools to translate stories into 50+ languages, so kids can learn new languages too. Each story also comes with a […]

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