Tech In Plain Sight: Projection Clocks

February 23, 2026 by Al Williams 12 Comments

You wake up in the middle of the night. Is it time to get up? Well, you can look at the nightstand clock. Unless your partner is in the way. Whoops. Even then, without your glasses, the time is just a fuzzball of light. You could ask Alexa, but that’s sure to wake your partner, too. The answer is a projection clock. In its modern form, it shoots a digital time display on a wall or ceiling with digits so large that you don’t need your glasses. If you can see the ceiling, you can tell what time it is.

New Tech

A modern invention, of course. No, not really. According to [Roger Russel], a UK patent in 1909 used an analog clock face and lightbulbs to project the clock face and hands on the ceiling. Unfortunately, [Roger’s] website is no more, but the Wayback Machine is on the job. You can see a device of the same type at the British Museum.

A modern projection clock on the ceiling.

In 1938, [Leendert Prins] filed for a patent on a similar projection clock. Sometimes known as “ceiling clocks” or “night clocks,” these devices often have a regular clock visible as well as a way to project the time. In the old days, this was often an image of a translucent analog clock lit up by light bulbs. In the modern era, it is almost always either LEDs or an LCD with a halogen backlight. Of course, there are many variations. A clock might use numbers on a rotating drum with a lamp behind it, for example.

Development

It isn’t hard to imagine someone putting a pocket watch in a magic lantern as a prototype. In general, some bright light source has to pass through a condenser lens. The light then travels through the LCD or translucent clock face. Finally, a projector lens expands the image.

We couldn’t find much about the actual history of old projection clocks outside of [Roger’s] defunct website. But if you can project an image and build a clock, all you need is the idea to combine them.

Continue reading “Tech In Plain Sight: Projection Clocks” →

Nuclear Waste Remediation By Proton Beam

February 23, 2026 by Al Williams 39 Comments

One of the issues with nuclear power plants is that they produce long-lived radioactive waste. Storing spent nuclear fuel is a real problem. However, researchers at the Department of Energy’s Thomas Jefferson National Accelerator Facility have made strides not only to produce more electricity from spent fuel but also to break it down into shorter-lived nuclear waste. [Aman Tripathi] shares the details about NEWTON, a program to fire high-energy protons at a target to produce a flood of neutrons that can interact with nuclear waste. You can read the original press release, too.

Short-lived, of course, is a relative term. Unprocessed spent fuel may be dangerous for about 100,000 years. After the proposed processing, the danger period is down to “only” 300 years. On the plus side, the process generates a lot of heat, which you can convert to electricity in the usual way.

Continue reading “Nuclear Waste Remediation By Proton Beam” →

Calculus By Oscilloscope

February 23, 2026 by Al Williams 18 Comments

Even entry-level oscilloscopes today have simple math functions such as adding or subtracting two channels. But as [Arthur Pini] notes, more advanced scopes can now even do integration and differentiation. He writes about using these tools to make measurements on capacitors and inductors. The post in EDN is worth a read, even if your scope doesn’t offer this sort of math yet.

It makes sense that capacitors and inductors would benefit from this feature. After all, the current through a capacitor, for example, is proportional to the rate of change in the voltage across it. That’s a derivative. Since the scope can measure voltages, it can also differentiate to find the current.

The same idea applies to inductors, where the current through an inductor is related to the integral of the voltage across it. It is a simple matter to measure the voltages and perform an integration to determine the current.

Continue reading “Calculus By Oscilloscope” →

Running In Printf

February 22, 2026 by Al Williams 7 Comments

You may or may not know, but printf is a Turing-complete language, once you exploit all the strange and wonderful format characters in it (especially %n). But who has time to write code as printf modifiers? Now, thanks to [sebsite], you can at least write in a slightly higher level assembly language and compile to printf. Practical? No. Cool? Undeniably.

As an example, the page shows fizzbuzz written in the assembler:

alias i, fizz, buzz

->fizz ([i] + 1) % 3 == 0
->buzz ([i] + 1) % 5 == 0
->i [i] + 1
->exit [i] == 100

[i] if !![i] & ![fizz] & ![buzz]
"Fizz" if [fizz]
"Buzz" if [buzz]
"\n" if [i]

The alias keyword defines constants and, owing to default values, sets i to zero, fizz to one, and buzz to 2. The “arrow” statements store a result into a variable (so the first assignment sets the resulting value into fizz).

Continue reading “Running In Printf” →

Quieting Noisy Resistors

February 21, 2026 by Al Williams 20 Comments

[Hans Rosenberg] has a new video talking about a nasty side effect of using resistors: noise. If you watch the video below, you’ll learn that there are two sources of resistor noise: Johnson noise, which doesn’t depend on the construction of the resistor, and 1/f noise, which does vary depending on the material and construction of the resistor.

In simple terms, some resistors use materials that cause electron flow to take different paths through the resistor. That means that different parts of the signal experience slightly different resistance values. In simple applications, it won’t matter much, but in places where noise is an important factor, the 1/f or excess noise contributes more to errors than the Johnson noise at low frequencies.

Continue reading “Quieting Noisy Resistors” →

MicroGPT Lets You Peek With Your Browser

February 21, 2026 by Al Williams 2 Comments

Regardless of what you think of GPT and the associated AI hype, you have to admit that it is probably here to stay, at least in some form. But how, exactly, does it work? Well, MicroGPT will show you a very stripped-down model in your browser. But it isn’t just another chatbot, it exposes all of its internal computations as it works.

The whole thing, of course, is highly simplified since you don’t want billions of parameters in your browser’s user interface. There is a tutorial, and we’d suggest starting with that. The output resembles names by understanding things like common starting letters and consonant-vowel alternation.

At the start of the tutorial, the GPT spits out random characters. Then you click the train button. You’ll see a step counter go towards 500, and the loss drops as the model learns. After 500 or so passes, the results are somewhat less random. You can click on any block in the right pane to see an explanation of how it works and its current state. You can also adjust parameters such as the number of layers and other settings.

Of course, the more training you do, the better the results, but you might also want to adjust the parameters to see how things get better or worse. The main page also proposes questions such as “What does a cell in the weight heatmap mean?” If you open the question, you’ll see the answer.

Overall, this is a great study aid. If you want a deeper dive than the normal hand-waving about how GPTs work, we still like the paper from [Stephen Wolfram], which is detailed enough to be worth reading, but not so detailed that you have to commit a few years to studying it.

We’ve seen a fairly complex GPT in a spreadsheet, if that is better for you.

Displaying The Rainbow

February 20, 2026 by Al Williams 23 Comments

True or false? Your green laser pointer is more powerful than your red one. The answer is almost certainly false. They are, most likely, the same power, but your eye is far more sensitive to green, so it seems stronger. [Brandon Li] was thinking about how to best represent colors on computer screens and fell down the rabbit hole of what colors look like when arranged in a spectrum. Spoiler alert: almost all the images you see of the spectrum are incorrect in some way. The problem isn’t in our understanding of the physics, but more in the understanding of how humans perceive color.

Perception may start with physics, but it also extends to the biology of your eye and the psychology of your brain. What follows is a lot of math that finally winds up with the CIE 1931 color space diagram and the CIE 2012 system.

Continue reading “Displaying The Rainbow” →