The idea of having software translation programs around to do things like emulate a Super Nintendo on your $3000 gaming computer or, more practically, run x86 software on a new M1 Mac, seems pretty modern since it is so prevalent in the computer world today. The idea of using software like this is in fact much older and easily traces back into the 80s during the era of Commodore and Atari personal computers. Their hardware was actually not too dissimilar, and with a little bit of patience and know-how it’s possible to compile the Commodore 64 kernel on an Atari, with some limitations.
This project comes to us from [unbibium] and was inspired by a recent video he saw where the original Apple computer was emulated on Commodore 64. He took it in a different direction for this build though. The first step was to reformat the C64 code so it would compile on the Atari, which was largely accomplished with a Python script and some manual tweaking. From there he started working on making sure the ROMs would actually run. The memory setups of these two machines are remarkably similar which made this slightly easier, but he needed a few workarounds for a few speed bumps. Finally the cursor and HMIs were configured, and once a few other things were straightened out he has a working system running C64 software on an 8-bit Atari.
Unsurprisingly, there are a few things that aren’t working. There’s no IO besides the keyboard and mouse, and saving and loading programs is not yet possible. However, [unbibium] has made all of his code available on his GitHub page if anyone wants to expand on his work and may also improve upon this project in future builds. If you’re looking for a much easier point-of-entry for emulating Commodore software in the modern era, though, there is a project available to run a C64 from a Raspberry Pi.
Thanks to [Cprossu] for the tip!
With the principles of molecular biology very much in the zeitgeist these days, we thought it would be handy to provide some sort of visual aid to help our readers understand the complex molecular machines at work deep within each cell of the body. And despite appearances, this film using interpretive dance to explain protein synthesis will teach you everything you need to know.
Now, there are those who go on and on about the weirdness of the 1960s, but as this 1971 film from Stanford shows, the 60s were just a warm-up act for the really weird stuff. The film is a study in contrasts, with the setup being provided by the decidedly un-groovy Paul Berg, a professor of biochemistry who would share the 1980 Nobel Prize in Medicine for his contributions to nucleic acid research. His short sleeves and skinny tie stand in stark contrast to the writhing mass of students capering about on a grassy field, acting out the various macromolecules involved in protein synthesis. Two groups form the subunits of the ribosome, a chain of ballon-headed students act as the messenger RNA (mRNA) that codes for a protein, and little groups standing in for the transfer RNA (tRNA) molecules that carry the amino acids float in and out of the process.
The level of detail, at least as it was understood in 1971, is impressively complete, with soloists representing things like T-factor and the energy-carrying molecule GTP. And while we especially like the puff of smoke representing GTP’s energy transfer, we strongly suspect a lot of other smoke went into this production.
Kitsch aside, and with apologies to Lewis Carroll and his Jabberwock, you’ll be hard-pressed to find a modern animation that captures the process better. True, a more traditional animation might make the mechanistic aspects of translation clearer, but the mimsy gyre and gimble of this dance really emphasize the role random Brownian motion plays in macromolecular processes. And you’ll never see the term “tRNA” and not be able to think of this film.
Continue reading “Retrotechtacular: Understanding Protein Synthesis Through Interpretive Dance”
Let’s be clear right up front: there are probably more obvious solutions to the problem of using a Russian calculator when you don’t speak Russian than printing new keys and engraving translated markings on them. But easy solutions are boring and generally considered beyond the scope of Hackaday articles, so let’s dive in.
They say that mathematics is the universal language, but that’s only true to an extent. Still, even with our
limited non-existent Cyrillic skills, the Russian keyboard on this RPN calculator isn’t that hard to figure out. But as [Amen] points out, in the midst of fevered calculations, one prefers not to mentally translate Χ→П to STO or remember that В↑ is the Enter key. So he printed a set of replacements for the confusing keys from PLA. While pondering how to safely fixture such small parts for the later engraving step, [Amen] hit on a genius solution: move the print bed to the CNC router and fixture everything in one go. The resulting characters are large enough to be legible and deep enough to be filled with air-drying polymer clay for contrast. After sanding and polishing, the calculator looks like it came from the Министерство электронной промышленности that way.
Honestly, we’d love to get a look inside this calculator. The insides of Russian electronics can be fascinating, and we’ve even seen entire forums dedicated to decapping Russian parts. But we understand the desire to keep it intact.
Continue reading “3D-Printer And CNC Make This Russian Calculator Bilingual”
How does a submarine talk to an airplane? It sounds like a bad joke but it’s actually a difficult engineering challenge.
Traditionally the submarine must surface or get shallow enough to deploy a communication buoy. That communication buoy uses the same type of radio technology as planes. But submarines often rely on acoustic transmissions via hydrophones which is fancy-talk for putting speakers and microphones in the water as transmitters and receivers. This is because water is no friend to radio signals, especially high frequencies. MIT is developing a system which bridges this watery gap and it relies on acoustic transmissions pointed at the water’s surface (PDF warning) and an airplane with high-precision radar which detects the oscillations of the water.
The complexity of the described setup is mind-boggling. Right now the proof of concept is over short distances and was tested in a water tank and a swimming pool but not in open water. The first thing that comes to mind is the interference caused by waves and by aerosols from wind/wave interactions. Those challenges are already in the minds of the research team. The system has been tested to work with waves of 8 cm (16 cm measured peak to trough) caused by swimmers in the pool. That may not sound like much, but it’s about 100,000 times the surface variations being measured by the millimeter wave radar in order to detect the hydrophone transmissions. Add to that the effects of Doppler shift from the movement of the plane and the sub and you have a signal processing challenge just waiting to be solved.
This setup is very interesting when pitched as a tool for researching aquatic life. The video below envisions that transmitters on the backs of sea turtles could send communications to aircraft overhead. We love seeing these kinds of forward-thinking ocean research projects, like our 2017 Hackaday prize winner which is an open source underwater glider. Oceanic studies over long distances have been very difficult but we’re beginning to see a lot of projects chipping away at that inaccessibility.
Continue reading “Submarine To Plane: Can You Hear Me Now? The Hydrophone Radar Connection”
Star Trek has its universal language translator and now researchers from Facebook Artificial Intelligence Research (FAIR) has developed a universal music translator. Much of it is based on Google’s WaveNet, a version of which was also used in the recently announced Google Duplex AI.
The inspiration for it came from the human ability to hear music played by any instrument and to then be able to whistle or hum it, thereby translating it from one instrument to another. This is something computers have had trouble doing well, until now. The researchers fed their translator a string quartet playing Haydn and had it translate the music to a chorus and orchestra singing and playing in the style of Bach. They’ve even fed it someone whistling the theme from Indiana Jones and had it translate the tune to a symphony in the style of Mozart.
Shown here is the architecture of their network. Note that all the different music is fed into the same encoder network but each instrument which that music can be translated into has its own decoder network. It was implemented in PyTorch and trained using eight Tesla V100 GPUs over a total of six days. Efforts were made during training to ensure that the encoder extracted high-level semantic features from the music fed into it rather than just memorizing the music. More details can be found in their paper.
So if you want to hear how an electric guitar played in the style of Metallica might have been translated to the piano by Beethoven then listen to the samples in the video below.
Continue reading “Facebook’s Universal Music Translator”
by: [Hideyuki Yamamoto] based on this feature.
3Dプリンターメーカーが小さくて精度が高いプリンターを開発するのに躍起になっている中でShanghai WinSun Decoration Design Engineering Companyという中国にある会社がオリンピックプールの半分程度の大きさの巨大な3Dプリンターで実験を重ねているとBBCなどは報じている。
Continue reading “Japanese Edition: 3Dプリンターで24時間以内に住宅建設。しかもリサイクル材料を用いたエコ建築。”
We’re still about 150 years away from the invention of the universal translator by [Lt Cdr Sato] of the Enterprise NX-01, but [Dave] has something that’s almost as good: a speech recognition, translation, and text to speech setup for the Raspberry Pi that theoretically allows anyone to speak in sixty different languages.
After setting up all the Linux audio cruft, [Dave] digs in and starts on converting the guttural vocalizations of a meat speaker into something Google’s speech to text service can understand. From there, it’s off to Google again, this time converting text in one language into the writings of another.
[Dave]’s end result is a shell script that works reasonably well for something that won’t be invented for another 150 years. The video below shows the script successfully translating English to spanish, but it should work equally well with other languages such as dutch and latin, as well as less popular language such as esperanto and french.
Continue reading “Raspberry Pi Becomes A Universal Translator”