Virtualizing IPhoneOS 1.0

Virtualizing computers is nothing new. However, Apple devices always present challenges. Just ask anyone who has built a Hackintosh. At least computer hardware is usually exposed, but on phones, the challenge is even harder due to mysterious devices. [Martijn] managed to reverse engineer the iPod Touch 1G enough to run iPhoneOS 1.0 on it and has several blog posts explaining how he did it.

The emulator is the ubiquitous QEMU. He has emulation for the critical hardware, including the cryptographic modules, the hardware clock, and the timer, along with memory and display and interface hardware. However, Wifi, some USB, audio, the light sensor, and some graphics hardware are still absent. That doesn’t stop the OS from booting, however.

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Floppy Disk Sales Are Higher-Density Than You Might Think

Floppies may be big in Japan, but nostalgic and/or needful Stateside floppy enthusiasts needn’t fret — just use AOL keyword point that browser toward floppydisk.com. There, you can buy new floppies of all sizes, both new and old, recycle your disks, or send them in to get all that precious vintage stuff transferred off of them.

That delightfully Web 1.0 site is owned by Tom Persky, who fancies himself the ‘last man standing in the floppy disk business’. Who are we to argue? By the way, Tom has owned that address since approximately 1990 — evidently that’s when a cyber-squatter offered up the domain for $1,000, and although Tom scoffed at paying so much as $1 for any URL, his wife got the checkbook out, and he has had her to thank for it ever since.

My business, which used to be 90% CD and DVD duplication, is now 90% selling blank floppy disks. It’s shocking to me. — Tom Persky

In the course of writing a book all about yours-truly’s favorite less-than-rigid medium, authors Niek Hilkmann and Thomas Walskaar sat down to talk with Tom about what it’s like to basically sell buggy whips in the age of the electric car.

Tom also owns diskduper.com, which is where he got his start with floppies — by duplicating them. In the 80s and 90s, being in this business was a bit like cranking out legal tender in the basement. As time wore on and more companies stopped selling floppies or simply went under, the focus of Tom’s company shifted away from duplication and toward sales. Whereas the business was once 90% duplication and 10% floppy sales, in 2022, those percentages have flopped places, if you will.

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Fork And Run: The Definitive Guide To Getting Started With Multiprocessing

Since the early 2000s, the CPU industry has shifted from raw clock speed to core counts. Pat Gelsinger famously took the stage in 2002 and gave the talk the industry needed, stating processors needed specialty silicon or multiple cores to reduce power requirements and spread heat. A few years later, the Core series was introduced with two or four-core configurations to compete with the AMD Athlon 64 x2.

Nowadays, we’re seeing heterogeneous chip designs with big and little cores, chiplets, and other crazy fabrication techniques that are fundamentally the same concept: spread the thermal load across multiple pieces of silicon. This writer is willing to put good money into betting that you’ll see consumer desktop machines with 32 physical cores in less than five years. It might be hard to believe, but a 2013 Intel Haswell i7 came with just four cores compared to the twenty you’ll get in an i7 today. Even an ESP32 has two cores with support in FreeRTOS for pinning tasks to different cores. With so many cores, how to even write software for that? What’s the difference between processes and threads? How does this all work in straight vanilla C98?

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Iron Nitrides: Powerful Magnets Without The Rare Earth Elements

Since their relatively recent appearance on the commercial scene, rare-earth magnets have made quite a splash in the public imagination. The amount of magnetic energy packed into these tiny, shiny objects has led to technological leaps that weren’t possible before they came along, like the vibration motors in cell phones, or the tiny speakers in earbuds and hearing aids. And that’s not to mention the motors in electric vehicles and the generators in wind turbines, along with countless medical, military, and scientific uses.

These advances come at a cost, though, as the rare earth elements needed to make them are getting harder to come by. It’s not that rare earth elements like neodymium are all that rare geologically; rather, deposits are unevenly distributed, making it easy for the metals to become pawns in a neverending geopolitical chess game. What’s more, extracting them from their ores is a tricky business in an era of increased sensitivity to environmental considerations.

Luckily, there’s more than one way to make a magnet, and it may soon be possible to build permanent magnets as strong as neodymium magnets, but without any rare earth metals. In fact, the only thing needed to make them is iron and nitrogen, plus an understanding of crystal structure and some engineering ingenuity.

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Teardown: How Many Teddy Ruxpins Does It Take To Start A Coven?

Well, I did it. I conquered my childhood fear of talking bears and brought a vintage Teddy Ruxpin animatronic stuffed bear into my home. There were and still are plenty of his brethren both young and old to choose from on the auction sites, and when I saw this particularly carefree barefoot Teddy in his Hawaiian shirt and no pants, I was almost totally disarmed. Plus, the description promised a semi-working unit with a distorted voice, and who among us could resist a specimen in such condition? Maybe the tape deck motor is going out, or it just needs a new belt. Maybe the tape itself messed up, and Teddy is fine. I had to find out.

But let me back up a bit. If you don’t know what I’m talking about, Teddy Ruxpin was a revolutionary toy that dropped in 1985. It’s a talking teddy bear that reads stories aloud, all the while moving his eyes and mouth to the sounds. Along with Teddy came special cassette tapes, corresponding story books, and outfits. I wanted one when I was a kid, but was also kind of scared of them. Since they were so expensive — about $250 inflation-adjusted for the bear and a single tape / book / outfit, plus another $15 for four D cells — I never did get one in my youth.

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Bare-Metal STM32: Adding An Analog Touch With ADCs

An Analogue to Digital Converter (ADC) is at its core a straight-forward device: by measuring an analog voltage within a set range and converting the measured level to a digital value we can use this measurement value in our code. Through the use of embedded ADCs in microcontrollers we can address many essential use cases, ranging from measuring the setting on a potentiometer, to reading an analog output line on sensors, including the MCU’s internal temperature and voltage sensors.

The ADCs found in STM32 MCUs have a resolution between 12 to 16 bits, with the former being the most common type. An ADC can be configured to reduce this resolution, set a specific sampling speed, and set up a multi-mode configuration depending on the exact ADC peripheral. STM32 MCUs feature at least a single ADC peripheral, while some have multiple. In this article we will take a look at how to configure and use the basic features of the ADCs in STM32 MCUs, specifically the ADCs found in F0 and the ADC5_V1_1 type as found in most F3-family MCUs.

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Edging Ahead When Learning On The Edge

“With the power of edge AI in the palm of your hand, your business will be unstoppable.

That’s what the marketing seems to read like for artificial intelligence companies. Everyone seems to have cloud-scale AI-powered business intelligence analytics at the edge. While sounding impressive, we’re not convinced that marketing mumbo jumbo means anything. But what does AI on edge devices look like these days?

Being on the edge just means that the actual AI evaluation and maybe even fine-tuning runs locally on a user’s device rather than in some cloud environment. This is a double win, both for the business and for the user. Privacy can more easily be preserved as less information is transmitted back to a central location. Additionally, the AI can work in scenarios where a server somewhere might not be accessible or provide a response quickly enough.

Google and Apple have their own AI libraries, ML Kit and Core ML, respectively. There are tools to convert Tensorflow, PyTorch, XGBoost, and LibSVM models into formats that CoreML and ML Kit understand. But other solutions try to provide a platform-agnostic layer for training and evaluation. We’ve also previously covered Tensorflow Lite (TFL), a trimmed-down version of Tensorflow, which has matured considerably since 2017.

For this article, we’ll be looking at PyTorch Live (PTL), a slimmed-down framework for adding PyTorch models to smartphones. Unlike TFL (which can run on RPi and in a browser), PTL is focused entirely on Android and iOS and offers tight integration. It uses a react-native backed environment which means that it is heavily geared towards the node.js world.

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