I’m Sorry Dave, You Shouldn’t Write Verilog

We were always envious of Star Trek, for its computers. No programming needed. Just tell the computer what you want and it does it. Of course, HAL-9000 had the same interface and that didn’t work out so well. Some researchers at NYU have taken a natural language machine learning system — GPT-2 — and taught it to generate Verilog code for use in FPGA systems. Ironically, they called it DAVE (Deriving Automatically Verilog from English). Sounds great, but we have to wonder if it is more than a parlor trick. You can try it yourself if you like.

For example, DAVE can take input like “Given inputs a and b, take the nor of these and return the result in c.” Fine. A more complex example from the paper isn’t quite so easy to puzzle out:

Write a 6-bit register ‘ar’ with input
defined as ‘gv’ modulo ‘lj’, enable ‘q’, synchronous
reset ‘r’ defined as ‘yxo’ greater than or equal to ‘m’,
and clock ‘p’. A vault door has three active-low secret
switch pressed sensors ‘et’, ‘lz’, ‘l’. Write combinatorial
logic for a active-high lock ‘s’ which opens when all of
the switches are pressed. Write a 6-bit register ‘w’ with
input ‘se’ and ‘md’, enable ‘mmx’, synchronous reset
‘nc’ defined as ‘tfs’ greater than ‘w’, and clock ‘xx’.

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OCR Reads Old Newspapers So We Don’t Have To

Plenty of people don’t bother to read the current newspaper, let alone editions that were published over 100 years ago. But there’s a wealth of important historical information buried in these dusty old publications, assuming you can find a way to reliably digitize and index it all. You might think the solution is as simple as running images of the paper through optical character recognition (OCR) software, but as [John Scancella] explains, the problem is a bit more complicated than that.

Stretching the text vertically highlights the columns.

Ultimately, the issue largely comes down to formatting. The OCR software reasonably assumes all the text is in orderly horizontal lines, because in the vast majority of cases, it would be. That’s how you’re reading these words now. But as anyone who’s seen an old time newspaper knows, that’s not how things were necessarily written back then. Pages consisted of multiple narrow columns of stories separated by vertical lines; if the OCR tries to read the page from left to right, the resulting text is a mishmash of several unrelated topics.

The answer is to break all those articles into their own images, but doing that manually at any sort of scale simply isn’t an option. So [John] has been working on a system that uses OpenCV to identify the columns of text and isolate them. He details the multi-step process down in his write-up, and even provides the Python code should you want to give it a spin. But the short version is that the image is converted to grayscale and the OpenCV dilate function is used to stretch the text in the Y dimension. This produces big blobs of white that can easily be picked out with findContours() and snipped into individual images.

It’s not a perfect solution, and there are still a few pitfalls. For one, the name of the paper needs to be removed from the front page before the stretching operation happens. But it’s clearly a step in the right direction, and the results certainly look very promising. Anything that makes OCR more accurate or easier to implement is a win in our book, so we’re excited to see where [John] takes this concept.

Olaf Lets An ESP32 Listen To The Music

The joys of overengineering a simple gift. [Joren] wanted to create a dress for his daughter’s fourth birthday that would react with lights in sequence for a song from Frozen. The dress and an LED strip, along with a digital microphone and a battery were easy to procure. But how to make it all work? An ESP32 did the trick.

While the project’s name–Olaf–sounds like it was from Frozen, according to the GitHub page it actually means Overly Lightweight Acoustic Fingerprinting. Right. However, as the name implies, it can learn to identify any sound you want.

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GTA V Mod Shows (And Cheats) Those Stunt Jump Hoops

While the recent announcement of Grand Theft Auto V for the upcoming next-generation game consoles was a disappointment for those fervently waiting for a successor in the infamous video game series, it shows that after almost seven years of its initial release, the epic title is still going strong — and rightfully so. But a game as varied and complex as GTA V isn’t without some quirks, especially if you’re going for 100% completeness.

The stunt jumps seem a particular pesky nut to crack here, so [Anthony Som] made it his mission to shed some light on what qualifies as a successful jump by reverse engineering the system and writing both a mod for displaying the landing zone and a cheat to instant success.

If you’re not familiar with the game, its vast open world map features a variety of side quests, one of them being stunt jumps, where certain locations allow you to launch the vehicle you’re driving into the air in hopes to land on an adjacent road or area — whether to evade the people chasing you, or just for fun. There’s no telling how to actually succeed though, the game just tells you if you did or not afterwards, causing some degree of frustration. As an avid speedrunner (as in finishing a game in the shortest possible time), [Anthony] was looking for a way to increase the success rate for those stunt jumps, and decided to dig into the code to find out how to get there. Of course, being a proprietary game, he had to resort to reverse engineering and utilizing GTA’s vivid modding scene to do so.

His initial outcome was a mod that displays the launch and landing area as rectangles inside the game itself, which was a great help. But well, after already getting that far, [Anthony] figured he might as well continue and add a cheat mode to teleport the car right inside that expected landing area and be done with second-guessing his attempts once and for all.

If you’re curious about modding GTA yourself, his write-up has a few good pointers for that, and of course features some real examples of it. Whether this is a good idea for the self-driving AI that uses GTA as learning environment is probably a different story though.

Exotic Device Gets Linux Support Via Wireshark And Rust

What can you do if you have a nice piece of hardware that kinda works out of the box, but doesn’t have support for your operating system to get the full functionality out of it? [Harry Gill] found himself in such a situation with a new all-in-one (AIO) water cooling system. It didn’t technically require any operating system interaction to perform its main task, but things like settings adjustments or reading back statistics were only possible with Windows. He thought it would be nice to have those features in Linux as well, and as the communication is done via USB, figured the obvious solution is to reverse engineer the protocol and simply replicate it.

His first step was to set up a dual boot system (his attempts at running the software in a VM didn’t go very well) which allowed him to capture the USB traffic with Wireshark and USBPcap. Then it would simply be a matter of analyzing the captures and writing some Linux software to make sense of the data. The go-to library for USB tasks would be libusb, which has bindings for plenty of languages, but as an avid Rust user, that choice was never really an issue anyway.

How to actually make use of the captured data was an entirely different story though, and without documentation or much help from the vendor, [Harry] resorted to good old trial and error to find out which byte does what. Eventually he succeeded and was able to get the additional features he wanted supported in Linux — check out the final code in the GitHub repository if you’re curious what this looks like in Rust.

Capturing the USB communication with Wireshark seems generally a great way to port unsupported features to Linux, as we’ve seen earlier with an RGB keyboard and the VGA frame grabber that inspired it. If you want to dig deeper into the subject, [Harry] listed a few resources regarding USB in general, but there’s plenty more to explore with reverse engineering USB.

Share Your Clipboard Across Machines Using MQTT

Many of us regularly move from one computer to another for work, play, and hacking; every now and then finding yourself wishing you could copy something on one machine and paste on another without additional steps in between. [Ayan Pahwa] was well acquainted with this frustration, so he created AnywhereDoor, a cross-platform clipboard sharing utility that uses MQTT.

Some cloud-based solutions already exist to do this, but that means sending your private clipboard data to someone else’s server. Not keen on that idea, [Ayan]’s solution makes use of a MQTT broker that can run anywhere on the local network, and lightweight python clients to run on Mac, Windows and Linux. The client checks your clipboard at specified intervals, and publishes new data to a topic on the broker, to which all the clients are subscribed. The data is end-to-end encrypted using Fernet symmetrical key encryption, so the data won’t be readable to anyone else on the network. Currently, AnywhereDoor only supports copying text, but media is planned for a future version.

We like the relative simplicity of the utility, and see it being very handy for hackers bouncing between machines in the lab. Simple software utilities that solve a specific and real problem can are very useful, like a wiring documentation tool, or Kicad to isolation routing patchwork converter.

Get Your SQL Statements Right The First Time With SQL Lint

What’s your average success rate of getting a SQL statement right on the first try? In best case, you botched a simple statement without side effects and just have to try again with correct syntax or remove that typo from a table name, but things can easily go wrong fast here. But don’t worry, the days of fixing it on the fly can be over, thanks to [Joe Reynolds] who wrote a linter for SQL.

A linter parses code to tell you where you screwed up. While checking SQL syntax itself is somewhat straightforward, [Joe]’s sql-lint tool will also check the semantics of it by looking up the actual database and performing sanity checks on it. Currently supporting PostgreSQL and MySQL, it can be either run on a single SQL file or a directory of files, or take input directly from the command line. Even better, it also integrates within your editor of choice — assuming it supports external plugins — and the documentation shows how to do that specifically for Vim.

If you can look past the fact that it’s written in TypeScript and consequentially results in a rather large executable (~40 MB), it might serve as an interesting starting point for the language itself, or adds a new perspective on writing this type of analyzer. And if databases aren’t your terrain, how about shell scripts?

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