2026-02-22 02:00:53
Although digital computers are – much like their human computer counterparts – about performing calculations, another crucial element is that of memory. After all, you need to fetch values from somewhere and store them afterwards. Sometimes values need to be stored for long periods of time, making memory one of the most important elements, yet also one of the most difficult ones. Back in the 1950s the storage options were especially limited, with a 1959 Bell Labs film reel that [Connections Museum] digitized running through the bleeding edge of 1950s storage technology.
After running through the basics of binary representation and the difference between sequential and random access methods, we’re first taking a look at punch cards, which can be read at a blistering 200 cards/minute, before moving onto punched tape, which comes in a variety of shapes to fit different applications.
Electromechanical storage in the form of relays are popular in e.g. telephone exchanges, as they’re very fast. These use two-out-of-five code to represent the phone numbers and corresponding five relay packs, allowing the crossbar switch to be properly configured.
After these types of memory, we move on to magnetic memory, in the form of well-known magnetic tape that provide mass storage in relatively little space. There is also the magnetic drum, which is much like a very short and very fast tape and provides e.g. working memory. This is what e.g. the Bendix G-15 uses for its clock signal and working memory, while magnetic tape and punched tape are used for application and data storage.
Next we cover magnetic-core memory, which stores a magnetic orientation in its ferrite rings or on a ferrite plate. This is non-volatile memory, but has low bit density and performs destructive reads, preventing its use beyond the 1970s. Today’s NAND Flash memory has significant overlap with core memory in its operating principles, both in its advantages and disadvantages.
An interesting variation on core memory is Twistor memory, which saw brief use during the late 1960s and early 1970s. Invented by Bell Labs, it was supposed to make for cheaper core-like memory, but semiconductor memory wiped out its business case, along with the similar bubble memory. An interesting feature of Twistor memory was the ability to add write-inhibit cards containing permanent magnets.
Fascinatingly, a kind of crude mask ROM is also demonstrated, before we move on to the old chestnut of vacuum tubes. Demonstrated is a barrier-grid tube, which uses electrons to create an electrostatic charge on a mica surface. This electron beam is also used to read the value, which is naturally destructive, making it somewhat similar to core memory in its speed and functionality.
Finally, we get the flying-spot store system, which is a type of optical digital memory. This is reminiscent of optical disc systems like the Compact Disc, and a reminder of all the amazing breakthroughs that we’d be seeing over the next decades.
Perhaps the best part about this video is that it shows the world as it sidled still mostly unaware towards these big changes. Memory storage was still the realm of largely hand-assembled, macro-sized devices, vacuum tubes and chunky electromechanical relays. Only a few years after this video was released, we’d see semiconductor technology turn the macro into micro, by the 1970s nerds would be fighting over who had the most RAM in their home computers, and CD-ROMs would set the world of computer storage and home game consoles ablaze by the 1990s with literally hundreds of MBs of storage per very cheap disc.
2026-02-21 23:00:19
Your project doesn’t necessarily have to be a refined masterpiece to have an impact on the global hacker hivemind. Case in point: this great demo of using a 64-point time-of-flight ranging sensor. [Henrique] took three modules, plugged them into a breadboard, and wrote some very interactive Python code that let him put them all through their paces. The result? I now absolutely want to set up a similar rig and expand on it.
That’s the power of a strong proof of concept, and maybe a nice video presentation of it in action. What in particular makes [Henrique]’s POC work is that he’s written the software to give him a number of sliders, switches, and interaction that let him tweak things in real time and explore some of the possibilities. This exploratory software not only helped him map out what directions to go, but they also work in demo mode, when he’s showing us what he has learned.
But the other thing that [Henrique]’s video does nicely is to point out the limitations of his current POC. Instantly, the hacker mind goes “I could work that out”. Was it strategic incompleteness? Either way, I’ve been nerd-sniped.
So are those the features of a good POC? It’s the bare minimum to convey the idea, presented in a way that demonstrates a wide range of possibilities, and leaving that last little bit tantalizingly on the table?
2026-02-21 20:00:50
[Oliver Pett] loves creating automata; pieces of art whose physicality and motion come together to deliver something unique. [Oliver] also has a mission, and that mission is to complete the most complex automata he has ever attempted: The Archer. This automaton is a fully articulated figure designed to draw arrows from a quiver, nock them in a bow, draw back, and fire — all with recognizable technique and believable motions. Shoot for the moon, we say!
He’s documenting the process of creating The Archer in a series of videos, the latest of which dives deep into just how intricate and complex of a challenge it truly is as he designs the intricate cams required.
[Oliver] turned to modern CAD software and after making a digital twin of The Archer he’s been using it to mathematically generate the cam paths required to create the desired movements and transitions, instead of relying on trial and error. This also lets him identify potential collisions or other errors before any metal is cut. The cams are aluminum, so the fewer false starts and dead ends, the better!
Not only is The Archer itself a beautiful piece of work-in-progress, seeing an automaton’s movements planned out in this way is a pretty interesting way to tackle the problem. We can’t wait to see the final result.
Thanks [Stephen] for the tip!
2026-02-21 17:00:17
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.
2026-02-21 14:00:14
On the list of cars widely regarded as the most reliable vehicles ever built, up there with the Toyota Land Cruiser, the Honda Civic, and the Mercedes W123 diesels, is the unassuming Toyota Prius. Although it adds a bit of complexity with its hybrid drivetrain, its design eliminates a number of common wear items and also tunes it for extreme efficiency, lengthening its life and causing minimal mechanical stress. The Prius has a number of other tricks up its sleeve as well, which is why parts of its hybrid systems are often used in EV conversions like [Jeremy]’s electric CJ-5 Jeep.
Inside the Prius inverter is a buck/boost converter used for stepping up the battery voltage to power the inverter and supply power to the electric motor. [Jeremy]’s battery is much higher voltage than the stock Prius battery pack, though, which means he can bypass the converter and supply energy from his battery directly to the inverter. Since the buck/boost converter isn’t being used, he can put it to work doing other things. In this case, he’s using it as a charger. Sending the AC from a standard EV charging cord through a rectifier and then to this converter allows the Prius hardware to charge the Jeep’s battery, without adding much in the way of extra expensive electronics.
There are some other modifications to the Prius equipment in this Jeep, though, namely that [Jeremy] is using an open-source controller as the brain of this conversion. Although this video only goes into detail on some of the quirks of the Prius hardware, he has a number of other videos documenting his journey to convert this antique Jeep over to a useful electric farm vehicle which are worth checking out as well. There are plenty of other useful things that equipment from hybrid and electric vehicles can do beyond EV conversions as well, like being used for DIY powerwalls.
2026-02-21 11:00:24
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.
Some people obsess about fonts, and some about colors. If you are in the latter camp, this is probably old hat for you. However, if you want a glimpse into just how complicated it is to accurately represent colors, this is a fascinating read. You can learn about the Bezold-Brücke shift, the Helmholtz-Kohlrausch effect, and the Abney effect. Maybe that’ll help you win a bar bet one day.
The post winds up in the strangest place: spectroscopy. So if you want to see how color representation applies to analyzing blue sky, neon tubes, and a MacBook display, you’ll want to skip to the end.
We’ve nerded out on color spaces before. In some cases, the right representation is everything.
