Getty Images Is Suing An AI Image Generator For Using Its Images

As per the Getty Images legal complaint, the Stable Diffusion AI seems to reproduce gooey versions of the Getty Images watermark in some of its output. Credit: Getty Images

Many AI systems require huge training datasets in order to achieve their impressive feats. This applies whether or not you’re talking about an AI that works with images, natural language, or just about anything else. AI developers are starting to come under scrutiny for where they’re sourcing their datasets. Unsurprisingly, stock photo site Getty Images is at the forefront of this, and is now suing the creators of Stable Diffusion over the matter, as reported by The Verge.

Stability AI, the company behind Stable Diffusion, is the target of the lawsuit for one good reason: there’s compelling evidence the company used Getty Images content without permission. The Stable Diffusion AI has been seen to generate output images that actually include blurry approximations of the Getty Images watermark. This is somewhat of a smoking gun to suggest that Stability AI may have scraped Getty Images content for use as training material.

The copyright implications are unclear, but using any imagery from a stock photo database without permission is always asking for trouble. Various arguments will likely play out in court. Stability AI may make claims that their activity falls under fair use guidelines, while Getty Images may claim that the appearance of perverted versions of their watermark may break trademark rules. The lawsuit could have serious implications for AI image generators worldwide, and is sure to be watched closely by the nascent AI industry. As with any legal matter, just don’t expect a quick answer from the courts.

[Thanks to Dan for the tip!]

Two goniometers sit on a table. One is an open wooden box with a long piece of plywood along the bottom. A laser distance finder rests on the front edge and a printed angle scale has been attached to the back side of the box. To the right of this box is a much smaller goniometer made from an orange pipe cap with a small strip of paper serving as the angle scale inside the interior edge. It is attached to a wooden handle that looks vaguely like a V. A laser pointer can be inserted from the bottom where a hole has been drilled through the wood.

Goniometer Gives You An Edge At Knife Sharpening

Sometimes you absolutely, positively need to know the angle of the cutting edge on a knife. When you do, the best tool for the job is a laser goniometer, and [Felix Immler] shows us three different ways to build one. (YouTube)

The underlying principle of all three of these builds is to project reflected laser light off a knife blade onto a scale going from 0-45˚. [Immler] shows a basic demonstration of this concept with a hinge toward the beginning of the video (after the break). Blades with multiple bevels will reflect light to each of the appropriate points on the scale.

The simplest version of the tool is a printed PDF scale attached to a wooden box with a hole for the blade to pass through. The next uses a large pipe end cap and a drilled-out piece of wood to create a more manageable measuring tool. Finally, [Immler] worked with a friend to design a 3D printed goniometer with differently-sized adapters to fit a variety of laser pointers.

Now that you’re ready to precisely sharpen your blades, why not sharpen this guacamole bot or try making your own knife from raw ore?

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Decorative Clock Uses LED Strips To Beautiful Effect

Clocks used to be dowdy old things with mechanical hands and sometimes even little cuckoo birds that would pop out to chime the hour. [David] built something altogether more modern that uses shifting colors on LED strips to tell the time.

The core of the build is an ESP8266, which queries an NTP time server to keep itself synced up with the current time as accurately as possible. It then controls a WS2812B LED strip to display the time. The strip itself is hidden in a 3D-printed housing behind an opaque wooden ring, with the light from the LEDs diffusing out nicely on to the wall upon which the clock is mounted.

The display shows three “hands” in the colors it projects on the wall. The red second hand is projected inside and outside the ring. The minute hand is green, and projects outside the ring. Meanwhile, the hour hand is blue, and projects inside the ring. Without any numerical markings, you won’t get an exact reading of the time, but you can figure it out closely enough. As a bonus, the clock looks like a stylish light-based wall sculpture and your guests may not even realizes it tells the time.

We’ve featured [David’s] work before too, in the form of the handy ESP8266 breadboard socket. Video after the break.

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Reverse Engineering British Rail Tickets

There was a time when to take a British rail journey was to receive a ticket barely changed since Victorian times — a small cardboard rectangle printed with the destination through which the inspector on the train would punch a hole. In recent decades these were replaced by credit-card-sized thin card, and now increasingly with scanable 2D codes from an app. These caught the attention of [eta], and she set about reverse engineering their operation.

The codes themselves are Aztec barcodes, similar to a QR code but with a single central fiducial mark. At first glance they resemble the codes used by non-UK ticketing systems, but she soon found out that they don’t follow the same standard. There followed a lengthy but fascinating trail of investigation, involving app decompilation of a dodgy copy of the ticket inspector app to find public keys, and then some work with a more reputably sourced app from another ticketing company.

Along the way it revealed a surprising amount of traveler data that maybe shouldn’t be in the public domain, and raises the question as to why the ticketing standard remains proprietary. It’s well worth a read.

If you’d like more UK rail ticket hacking, it formed the subject of a talk at EMF 2022.

Ski Season Sees Apple’s Crash Detection System Fire Deluge Of False Positives

Smartphone features used to come thick and fast. Cameras proliferated, navigation got added, and then Apple changed the game by finally making touch computing just work. Since then, truly new features have slowed to a trickle, but Apple’s innovative crash detection system has been a big deal where safety is concerned.

The problem? It’s got a penchant for throwing false positives when iPhone and Apple Watch users are in no real danger at all. We first covered this problem last year, but since then, the wintery season has brought yet more issues for already-strained emergency responders.

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Does Programming A Robot With ChatGPT Work At All?

ChatGPT has been put to all manner of silly uses since it first became available online. [Engineering After Hours] decided to see if its coding skills were any chop, and put it to work programming a circular saw. Pun intended.

The aim was to build a line following robot armed with a circular saw to handle lawn edging tasks.  The circular saw itself consists of a motor with a blade on it, and precisely no safety features. It’s mounted on the front of a small RC car with a rack and pinion to control its position. [Engineering After Hours] has some sage advice in this area: don’t try this at home.

ChatGPT was not only able to give advice on what parts to use, it was able to tell [Engineering After Hours] on how to hook everything up to an Arduino and even write the code. The AI language model even recommended a PID loop to control the position of the circular saw. Initial tests were messy, but some refinement got things impressively functional.

As a line following robot, the performance is pretty crummy. However, as a robot programmed by an AI, it does pretty okay. Obviously, it’s hard to say how much help the AI had, and how many corrections [Engineering After Hours] had to make to the code to get everything working. But the fact that this kind of project is even possible shows us just how far AI has really come.

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Ask Hackaday: Incidental Earthquake Detection

It never seems to fail: at the very moment that human society seems to reach a new pinnacle of pettiness, selfishness, violence, and self-absorption, Mother Nature comes along and reminds us all who’s really in charge. The obvious case in point here is the massive earthquakes near the border of Turkey and Syria, the appalling loss of life from which is only now becoming evident, and will certainly climb as survivors trapped since the Monday quakes start to succumb to cold and starvation.

Whatever power over nature we think we can wield pales by comparison with the energy released in this quake alone, which was something like 32 petajoules. How much destruction such a release causes depends on many factors, including the type of quake and its depth, plus the soil conditions at the epicenter. But whatever the local effects on the surface, quakes like these have a tendency to set the entire planet ringing like a bell, with seismic waves transmitted across the world that set the needles of professionally maintained seismometers wiggling.

For as valuable as these seismic networks are, though, there’s a looser, ad hoc network of detection instruments that are capable of picking up quakes as large as these from half a planet away. Some are specifically built to detect Earth changes, while some are instruments that only incidentally respond to the shockwaves traveling through the planet. And we want to know if this quake showed up in the data from anyone’s instruments.

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