Hackaday Europe 2026: Space Oddities

September 14, 2026 by 2 Comments

If you’re in motorsport, or maritime, or mining fields, you can always call on a technician to come down and fix something when it’s broken. You can lay hands on the parts, reconfigure things, make repairs, and get something working again. In space, that’s seldom possible. If you’re lucky enough to have a manned mission, you might be able to make some running repairs; if you’re working with an unmanned robot, probe, or satellite, your options are altogether more limited. If you can’t find a fix, it’s game over—a particularly brutal result when huge budgets and years of work are on the line.

Janelle Wellons came down to Hackaday Europe to talk about space. More particularly, the engineering and debugging operations that keep all sorts of space programs alive. Her talk dives into some of the creative solutions engineers have had to come up with to save million-dollar missions from becoming unrecoverable boondoggles.

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Fly Brain Connectome Used To Trade Stocks And Play Games

September 14, 2026 by 24 Comments

Recently researchers finished mapping the central nervous system (CNS) connectome of not just the female Drosophila melanogaster (i.e. fruit fly) brain, but also that of the male D. melanogaster for a comparative analysis. Here the sexually dimorphic changes turned out to induce specific mating behavior that ensures that there will only be smooching between genetically fit D. melanogaster males and females, while the rest of the connectome remained effectively the same.

Of course, with this connectome in hand it led some people to ask themselves what else one can do with this connectome graph of about 160,000 neurons other than make a fruit fly into a fruit fly. So far we have seen [Nftechie] turn this connectome into a crypto stock trader with the Stonkfly project that uses the connectome’s reward circuits to potentially make profitable trades, though [Nftechie] says that they haven’t verified yet how good a fruit fly is at trading stocks, only that it does said stonks.

Over at [PC Gamer] they summarized a number of things that people have also done, including trying to make the connectome control a game of DOOM and Beat Saber. Each game frame stimulates sensory neurons, with the generated outputs then mapped to game controls, with dopamine-producing reward circuits wired in for reinforcement learning.

Although the D. melanogaster brain is only the merest fraction of the size of the human brain, it does provide us with a glimpse of what actual artificial intelligence research may lead to, as we unravel how even a 160,000 neuron connectome is enough to make these terrors of rotting plant matter do their wonderful things.

Rosy Retrocomputing

September 14, 2026 by 25 Comments

Most of us are guilty of romanticizing the past. Do you long to be the captain of a tall ship? Just as long as you don’t mind weevils in your food, vitamin deficiencies, and death from an infection when there were no antibiotics. Want to be a medieval knight? Even worse. But surely, retrocomputing is as fun as we remember, right? Turn your computer on, and it comes up with BASIC! Ready for you to write your own programs. None of this GUI foolishness. Of course, this is just another example of rosy retrospection.

Even if you like BASIC or a similar language today, things have changed. You have a nice text editor, a fast computer, debugging tools, along with things like named functions, no line numbers, and modern control structures. None of those things were very common in the 1980s. At least, not on a hobby-grade computer.

Why am I thinking about this? Well, the Hackaday Retrocomputing Challenge is on, and it occurred to me that I wanted to work with some young students in glorious MBASIC on a CP/M machine I built and modified from a Hackaday project. Perfect, right? Many of us started that way, so why shouldn’t they?

But it quickly got old. Even a simple program gets bogged down with GOTOs and GOSUBs to mysterious line numbers. It made me remember the time back in the early 1980s, or maybe even the late 1970s, that I wrote a BASIC preprocessor to scan BASIC with no line numbers and produce proper source, converting labels to line numbers in two passes.

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It’s The Speech Synthesiser You Wanted, For The Computer You Had

September 14, 2026 by 22 Comments

If you had an 8-bit computer in the 1980s and bought a speech synthesiser for it, what you got was invariably an alophone-based synthesiser using the SP0256 or similar. You definitely couldn’t afford DEC’s DECtalk, a high-end standalone speech synthesiser made famous to the masses as the unit used by Stephen Hawking. But now those two worlds can come together, thanks to [Michael Wessel], whose Perfect Paul ][ is a drop-in DECtalk emulator card for the Apple ][.

The PCB includes an RP2040-based Raspberry Pi Pico Zero, plus an I2S DAC and amplifier, speaker, and bus-interface logic. It appears at a set of memory addresses, and interfacing to it is as simple as POKEing DECtalk commands to those addresses. Looking at it, we are guessing this would be easy to bring to other 8-bit era machines.

You can see and hear it sing in the video below the break, and it certainly has the feel of the real thing. We can say with certainty that this would have been a sensation had it appeared back in the early 1980s. This one may be a modern reproduction, but it’s not the first time DECtalk has appeared here; we’ve even brought you a real one.

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CircuitPython Goes Turbo With Precompiled Functions

September 14, 2026 by 15 Comments

It would not be at all original to declare that Python is the new BASIC. Like BASIC, it has been the first programming language for a whole generation of coders, and its main advantage is that it’s quick and easy to write in. Like BASIC it is an interpreted language, and thus rather slow to execute.

Thus while CircuitPython can be very useful for beginners and quick projects, it hits the limitations of the hardware far sooner than it needs to — unless you can pre-compile critical parts of the code, which you now can, thanks to CircuitPython Turbo by [Mikey Sklar] with some help from Anthropic’s Claude LLM.

Now if that sounds a lot like MicroPython’s ‘Viper’ and machine-code compiler, that’s because it is. CircuitPython is a fork of MicroPython with some handy extras on Adafruit boards, but Viper wasn’t one of them until now. Before the Turbo version, CircuitPython only ran in interpreted mode.

Like MicroPython, using CircuitPython Turbo you can flag sections to run as ‘native’, where instructions are compiled but values stay as python objects, which gets you about a 3X speedup. A little more rewriting to declare your variables and pointers and you can use ‘viper’ mode, which can — depending on what you’re up to — result in a 20x to 70x speedup. In Adafruit’s documentation, they demonstrate a Metro RP2040 calculating the Mandelbrot set 3x faster in Native and 19.7 times faster with Viper than normal Python bytecode.

The one thing that we miss from BASIC that CircuitPython Turbo doesn’t give is inline assembly– though interestingly enough, that is in the upstream MicroPython implementation, so perhaps its day will come here too. Not every job is suited to the use of Python on microcontrollers, but we’ve seen it used for everything from e-bikes to a Winamp-inspired music player.

Dramatically Increasing Usable Closet Space

September 13, 2026 by 27 Comments

As any science YouTuber or first-year physics student is quick to point out, the universe is mostly empty space. Not just space itself, but the amount of “empty” space between nuclei and their electrons is also huge. Getting rid of this empty space results in all kinds of interesting phenomena like degenerate matter and black holes. But the concept can be extrapolated into our daily lives as well; many things are so filled with air that we can get a lot more usable storage space by compressing them down a little bit. [Super Valid Designs] took this concept to a coat closet, building one that can hold an impressive number of coats.

He started by looking at an existing closet, which could hold around 21 coats but only if someone used two hands to cram the coats into the space. After a trip to a store which sells rugs, he saw a much better design that lets all the rugs pivot like the pages on a book, and took this idea to his closet using a similar mechanism designed for storing large blueprints instead of rugs. The closet he built around this mechanism has two hinged doors which allow a person easy access to the coats, and when opened the blueprint hangers pivot out like a book, allowing the coats to not only be easily accessed without disrupting the other coats, but also allow them to be compressed down by the closet door for storage.

For comparison, the original closet could only hold 10 coats when restricted to single-hand operation and 21 when using both. The new closet design is smaller, and can hold 24 coats with a single hand and over 30 when using both, a dramatic improvement of closet efficiency. To top it off, a set of cupboards on top and bottom allow for storing shoes and hats as well, and there’s even a garage for a robotic vacuum cleaner. Surprisingly, we don’t see many closet optimization builds around here. The closest we can come is another traditionally small space, a college dorm.

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Re-creating NASA’s Heat Shield Problem

September 13, 2026 by 16 Comments

After the Orion capsule of the Artemis I lunar mission returned to Earth, it was found that massive chunks of its heatshield had been ripped off, posing a serious risk to any future missions. In a recent video in which [polymatt] takes a break from repairing old laptop shells and the like, he tries to recreate the Orion’s heatshield using a variety of methods and materials.

For this test a number of samples were created, each using the same kind of segmented structure as the larger Orion heatshield. The filler was created from the published materials for the heat shield by NASA, requiring just serious mixing.

The resulting samples were then cured with thermocouples inserted, before they got blasted with the heat from a propane torch, trying to simulate the various re-entry patterns.

Perhaps unsurprisingly, the results matched the findings by NASA for why the Orion’s heat shield had failed, being the build-up of gases due to the sustained pyrolysis processes that eventually fractured the material. Despite some experimental flaws that injected residual heat from the copper structure, this still seems to be a pretty good setup to test ablative heat shields in DIY lab conditions.

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