Few things are as satisfying to watch as a good retrocomputer restoration project – we’re always happy to see someone bring a rusty old Commodore, Apple or Atari back to life. The goal is typically to get the machine as close to its original state as possible, except for perhaps a few non-intrusive mods like memory upgrades. [Drygol] however, had already done this so many times that he thought it was time to take a different route for once, and apply some creativity to an old Amiga 500 case. Originalists may shudder, but we quite like his funky blue-and-yellow A500 mod.
To be fair, [Drygol] wasn’t the first one to modify this specific Amiga’s case: one of its previous owners had already applied a rather shoddy blue paint job and defaced it with some stickers. [Drygol] decided to stick with the basic idea, but do it right this time. First he removed the old paint using concentrated lye, then gave it a fresh coat of blue. He also applied glow-in-the-dark paint to the Amiga logo embossed in the case and added a fluorescent yellow laser-cut circuit board ornament. It took a bit of experimenting to get all these elements just right, but the end result definitely looks the part.
The insides of the Amiga also needed some TLC: [Drygol] competely cleaned and lubricated the floppy drive, gave the motherboard a good ultrasonic scrub, and replaced dodgy capacitors all over. He expanded the RAM from 512 kB to 1 MB and added a Gotek floppy emulator, which can work in parallel with the original disk drive. To make the Gotek easy to operate, [Drygol] placed its OLED screen and a pair of touch-sensitive buttons in a cutout on the front of the case.
A matching blue mouse and gamepad, both connected through the MouSTer adapter, complete the setup. The result is a good-looking A500 with some modern conveniences that’s perfect for exploring the Amiga’s extensive software library. If custom colors aren’t your thing, you’ll be happy to know that the original shade of grey or beige might be available for your retro console, too.
The world of AI is abuzz, or at least parts of it are, at the news of Meta’s release of Llama 2. This is an AI text model which is thought to surpass ChatGPT in capabilities, and which the social media turned VR turned own all your things company wants you to know is open to all. That’s right, the code is open source and you can download the model, and Meta want you to feel warm and fuzzy about it. Unfortunately all is not as it seems, because of course the model isn’t open-source and is subject to a licensing restriction which makes it definitely not free of charge for larger users. This is of course disappointing to anyone hoping for an AI chatbot without restrictions, but we’re guessing Meta would prefer not to inadvertently enable a competitor.
Researchers at Google have posed themselves an interesting problem to solve: mastering the piano. However, they’re not trying to teach themselves, but a pair of simulated anthropomorphic robotic hands instead. Enter RoboPianist.
The hope is that the RoboPianist platform can help benchmark “high-dimensional control, targeted at testing high spatial and temporal precision, coordination, and planning, all with an underactuated system frequently making-and-breaking contacts.”
If that all sounds like a bit much to follow, the basic gist is that playing the piano takes a ton of coordination and control. Doing it in a musical way requires both high speed and perfect timing, further upping the challenge. The team hopes that by developing control strategies that can master the piano, they will more broadly learn about techniques useful for two-handed, multi-fingered control. To that end, RoboPianist models a pair of robot hands with 22 actuators each, or 44 in total. Much like human hands, the robot hands are underactuated by design, meaning they have less actuators than their total degrees of freedom.
The AI controls a vaguely humanoid-like creature, albeit with a heavily-simplified body and limbs. It “lives” in a 3D environment created in the Unity engine, which provides the necessary physics engine for the work. Meanwhile, the ML-Agents package is used to provide the brain for Albert, the AI charged with learning to walk.
The video steps through a variety of “deep reinforcement learning” tasks. In these, the AI is rewarded for completing goals which are designed to teach it how to walk. Albert is given control of his limbs, and simply charged with reaching a button some distance away on the floor. After many trials, he learns to do the worm, and achieves his goal.
Getting Albert to walk upright took altogether more training. Lumpy ground and walls in between him and his goal were used to up the challenge, as well as encouragements to alternate his use of each foot and to maintain an upright attitude. Over time, he was able to progress through skipping and to something approximating a proper walk cycle.
One may argue that the teaching method required a lot of specific guidance, but it’s still a neat feat to achieve nonetheless. It’s altogether more complex than learning to play Trackmania, we’d say, and that was impressive enough in itself. Video after the break.
Humans have always drawn lines in the sand, whether it’s to communicate a plan of attack or to indicate metaphorically a very real boundary. It’s also something we do just for the aesthetic pleasure, and this plotter from [aidenvigue] is great at performing in just that role.
The plotter traces patterns in the circular sand tray by dragging a small marble with a magnet. This is achieved with a pair of NEMA 17 stepper motors, set up in a polar coordinate fashion. One stepper motor controls the angle, while another motor controls the marble’s distance from the center point of the circle. It’s a simple way to build a circular plotter, and works far better than a Cartesian setup would for this geometry. The build uses an ESP32 as the brains of the operation. It hosts a web interface that allows various patterns to be selected and run on the device. It also runs a set of addressable SK6812 LEDs that light the sand rather nicely.
We’ve seen some great sand plotters before, and have always been particular fans of the larger variety. Video after the break.
Any time we mention Linux, it is a fair bet we will get a few comments from people unhappy that we didn’t refer to it as GNU/Linux or with some other appellation. To be fair, they aren’t wrong. Linux is a kernel. Much of what we think of as a Linux desktop OS is really from other sources, including, but not limited to, GNU. We thought about this after reading a report from [The Register] that Linux has nearly half of the desktop OS Linux market. Wait, what?
If you are like us, you probably think that’s a typo. It isn’t. But the more you think about it, the less sense it makes. You know that half of the world’s desktops don’t run Linux. But maybe they mean Unix? Nope. So how can Linux have almost half of the Linux market? That’s like saying nearly half of Hackaday readers read Hackaday, right?
Summer’s in full swing, and this week both Elliot and Dan had to sweat things out to get the podcast recorded. But the hacks were cool — see what I did there? — and provided much-needed relief. Join us as we listen in on the world of bats, look at a laser fit for a hackerspace, and learn how to make an array of magnets greater than — or less than — the sum of its parts. There’ll be flying eggs, keyboards connected to cell phones, and everything good about 80s and 90s cable TV, as well as some of the bad stuff. And you won’t want to miss Elliot putting Dan to shame with the super-size Quick Hacks, either, nor should you skip the Can’t Miss sweep with a pair of great articles by Al Williams.
Check out the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!