Developing A Custom WearOS Watch Face

June 27, 2022 by Tom Nardi 13 Comments

When you think about customizing the face of a smartwatch, you probably imagine something akin to selecting a new wallpaper on an Android device, or maybe tweaking the color scheme a bit. But not [Sebastian SARBU], his plans were a bit grander than all that. So he cracked open Android Studio and started writing a truly custom watch face that would make the most out of the device’s display. Luckily for us, he’s not only released the source code for others to study, but has documented the development process in a series of videos that you can see below the break.

He’s dubbed the new interface his “Pizza Watch Face”, as it breaks the circular screen down into slices complete with a bits of multi-colored “crust” that can show various notifications using the fewest pixels possible. There’s no question the layout is able to pack a lot of information into a relatively small space, and while aesthetics are naturally subjective, we happen to think it looks pretty slick. Continue reading “Developing A Custom WearOS Watch Face” →

Linux Fu: Roll With The Checksums

June 22, 2022 by Al Williams 14 Comments

We are often struck by how often we spend time trying to optimize something when we would be better off just picking a better algorithm. There is the old story about the mathematician Gauss who, when in school, was given busy work to add the integers from 1 to 100. While the other students laboriously added each number, Gauss realized that 100+1 is 101 and 99 + 2 is also 101. Guess what 98 + 3 is? Of course, 101. So you can easily find that there are 50 pairs that add up to 101 and know the answer is 5,050. No matter how fast you can add, you aren’t likely to beat someone who knows that algorithm. So here’s a question: You have a large body of text and you want to search for it. What’s the best way?

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Edging Ahead When Learning On The Edge

June 21, 2022 by Matthew Carlson 10 Comments

“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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Screenshot of the OpenAsar config window, showing a few of the configuration options

OpenAsar Tweaks Discord’s Frontend, Improves Performance And Privacy

June 19, 2022 by Arya Voronova 14 Comments

Not all hacking happens on hardware — every now and then, we ought to hack our software-based tools, too. [Ducko] tells us about a partially open-source rewrite of Discord’s Electron-based frontend. Web apps can be hard to tinker with, which is why such projects are to be appreciated. Now, this isn’t a reverse-engineering of Discord’s API or an alternative client per se, but it does offer a hopeful perspective on what the Discord client ought to do for us.

First of all, the client loads noticeably faster, not unlike the famous GTA Online speedup (which was also a user-driven improvement), with channel and server switching made less laggy — and the Linux updater was de-cruft-ified as well. [Ducko] tells us how she got rid of the numerous NPM dependencies of the original code – it turned out that most of the dependencies could be easily replaced with Node.JS native APIs or Linux binaries like unzip. Apart from much-appreciated performance improvements, there are also options like telemetry bypass, and customization mechanisms for your own theming. You won’t get Discord on your Apple ][ just yet, but the native client will be a bit friendlier towards you.

While Discord is ultimately a proprietary platform, we do it see used in cool hacks every now and then, like this tea mug temperature-tracking coaster. Would you like to code your own Discord bot? We wrote a walk-through for that. Last but not least, if you like what we wrote and you happen to also use Discord, you should check out the Hackaday Discord server!

Diagram of the LTC protocol, showing the difference between 1 bits and 0 bits - both transmitted using one up and one down pulse, but with '1' bit pulses being half as short.

Animate Arcane Protocols With Interrupt-Backed Bitbanging

June 19, 2022 by Arya Voronova 10 Comments

We often take our “SoftwareSerial” libraries for granted, and don’t investigate what goes on under the hood — until they fail us, at least. Would you like to learn how to harness the power of interrupt-driven bitbanging? [Jim Mack] teaches us how to make our protocol implementations fly using the LTC protocol as a springboard.

LTC (Linear/[Longitudinal] TimeCode) is a widely-used and beautifully-crafted protocol that tends to fly under our radar, and is one that hackers could learn plenty from. It’s used for synchronization of audio/video devices during media production and playback. LTC’s signal is almost digital but not quite: it doesn’t need a clock, and it has no polarity. Additionally, it mimics an audio signal really well, you can decode it at any playback speed, and many other benefits and quirks that [Jim] outlines. You do need to maintain the timings, though, and [Jim]’s article shows us how to keep them right while not inconveniencing your primary tasks.

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Linux Fu: Up Your GDB Game!

June 14, 2022 by Al Williams 19 Comments

If you want to buy a car, there are plenty of choices. If you want to buy a jetliner, there are fewer choices. If you want to use the Large Hadron Collider, you have a choice of exactly one. The harder something is to create, the less likely there is to be many of them. If you are looking for a Linux debugger, there are only a few choices, but gdb is certainly the one you will find most often. There is lldb and a handful of non-open commercial offerings, but for the most part you will use gdb to debug software on Linux.

Of course, not everyone’s a fan of gdb’s text-based interface, so there’s no shortage of front ends available for it. In fact, gdb has two potentially built-in interfaces although depending on how you install gdb, you might not have both of them. Of course, if you use an IDE, it very likely is a front end for gdb among other things. But at the core is gdb and — usually — there is a window somewhere that you can stuff gdb commands into. Even emacs — which might be considered the original IDE — can run gdb and gives you a sort-of GUI experience.

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Yes We Have Random Bananas

June 12, 2022 by Al Williams 36 Comments

If you ask a normal person to pick a random number, they’ll usually just blurt out a number. But if you ask a math-savvy person for a random number, you’ll probably get a lecture about how hard it is to pick a truly random number. But if you ask [Valerio Nappi], you might just get a banana.

His post, which is in two parts, details how what computers generate are actually pseudo-random numbers. You can easily make sure that every number has the same probability of selection as any other number. The problem is that you have to start with something — usually called a seed. For the purposes of playing games, for example, you can grab some source of entropy like how many microseconds since a hardware timer last rolled over, the number of input pulses you’ve received from a mouse lately, or how long you had to wait for the enter key to depress after asking the user to press it. But if you know that seed and the algorithm you can perfectly predict what number the computer will generate next so it isn’t truly random.

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