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This clever AI hid data from its creators to cheat at its appointed task – TechCrunch

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Depending on how paranoid you are, this research from Stanford and Google will be either terrifying or fascinating. A machine learning agent intended to transform aerial images into street maps and back was found to be cheating by hiding information it would need later in “a nearly imperceptible, high-frequency signal.” Clever girl!

This occurrence reveals a problem with computers that has existed since they were invented: they do exactly what you tell them to do.

The intention of the researchers was, as you might guess, to accelerate and improve the process of turning satellite imagery into Google’s famously accurate maps. To that end the team was working with what’s called a CycleGAN — a neural network that learns to transform images of type X and Y into one another, as efficiently yet accurately as possible, through a great deal of experimentation.

In some early results, the agent was doing well — suspiciously well. What tipped the team off was that, when the agent reconstructed aerial photographs from its street maps, there were lots of details that didn’t seem to be on the latter at all. For instance, skylights on a roof that were eliminated in the process of creating the street map would magically reappear when they asked the agent to do the reverse process:

The original map, left; the street map generated from the original, center; and the aerial map generated only from the street map. Note the presence of dots on both aerial maps not represented on the street map.

Although it is very difficult to peer into the inner workings of a neural network’s processes, the team could easily audit the data it was generating. And with a little experimentation, they found that the CycleGAN had indeed pulled a fast one.

The intention was for the agent to be able to interpret the features of either type of map and match them to the correct features of the other. But what the agent was actually being graded on (among other things) was how close an aerial map was to the original, and the clarity of the street map.

So it didn’t learn how to make one from the other. It learned how to subtly encode the features of one into the noise patterns of the other. The details of the aerial map are secretly written into the actual visual data of the street map: thousands of tiny changes in color that the human eye wouldn’t notice, but that the computer can easily detect.

In fact, the computer is so good at slipping these details into the street maps that it had learned to encode any aerial map into any street map! It doesn’t even have to pay attention to the “real” street map — all the data needed for reconstructing the aerial photo can be superimposed harmlessly on a completely different street map, as the researchers confirmed:

The map at right was encoded into the maps at left with no significant visual changes.

The colorful maps in (c) are a visualization of the slight differences the computer systematically introduced. You can see that they form the general shape of the aerial map, but you’d never notice it unless it was carefully highlighted and exaggerated like this.

This practice of encoding data into images isn’t new; it’s an established science called steganography, and it’s used all the time to, say, watermark images or add metadata like camera settings. But a computer creating its own steganographic method to evade having to actually learn to perform the task at hand is rather new. (Well, the research came out last year, so it isn’t new new, but it’s pretty novel.)

One could easily take this as a step in the “the machines are getting smarter” narrative, but the truth is it’s almost the opposite. The machine, not smart enough to do the actual difficult job of converting these sophisticated image types to each other, found a way to cheat that humans are bad at detecting. This could be avoided with more stringent evaluation of the agent’s results, and no doubt the researchers went on to do that.

As always, computers do exactly what they are asked, so you have to be very specific in what you ask them. In this case the computer’s solution was an interesting one that shed light on a possible weakness of this type of neural network — that the computer, if not explicitly prevented from doing so, will essentially find a way to transmit details to itself in the interest of solving a given problem quickly and easily.

This is really just a lesson in the oldest adage in computing: PEBKAC. “Problem exists between keyboard and computer.” Or as HAL put it: “It can only be attributable to human error.”

The paper, “CycleGAN, a Master of Steganography,” was presented at the Neural Information Processing Systems conference in 2017. Thanks to Fiora Esoterica and Reddit for bringing this old but interesting paper to my attention.



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10 Iconic Movie Cars That Weren’t Even Real

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James Bond and cool cars together are the epitome of cool. The Bond franchise is famous for its car chases, extravagant crashes, and daring escapes. Six actors have portrayed agent 007 since 1963 and they have all driven a variety of cool cars, some of them equipped with space-age spycraft and defensive capabilities. The fifth Bond, Pierce Brosnan, drove one such cool car in The World is Not Enough, a BMW Z8. As an Englishman, Bond had historically driven English cars, like Aston Martin and Lotus, but a product tie-in with BMW in the nineties changed all that.

In this movie, we get to see Bond utilize some of the obligatory gadgets such as rocket launchers but also see a foretelling of things to come with a remote start and summon feature, something unheard of in 1999. However, something also unheard of is a 1999 Z8, because it did not exist until the 2000 model year. According to Top Gear, the production Z8 was not ready during filming, so BMW provided a couple of unfinished pre-production cars and gave producers specs to create other completely fabricated custom cars powered by a Chevy V8 with a Jaguar suspension for filming, particularly the scene where one gets sawed in half. The Z8 gets very little screen time in this movie, likely because they didn’t really have a complete car to work with.

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Halo Infinite’s Campaign Co-Op Beta Kicks Off Soon

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In the past, and in other major co-op games, playing co-op equals advancing the game only for the person who is hosting it. The other players join the game and progress for the host but are unable to retain that progress for their own saves, and they also cannot start up the game without the host being around to do it for them. It seems that with “Halo Infinite,” the developers behind the game wanted to take a different approach by making co-op progress accessible even after the gaming session is over. As Bender said, “One of our core principles is that we don’t want to require you to have an isolated co-op save.”

As a result of that new policy, every player’s progress is going to count toward their main playthrough. Any items, collectibles, achievements, and mission progress earned during a co-op session will carry over to an individual gamer’s save. There’s also a new approach referred to as “No Spartan Left Behind.” When you join a Fireteam and select your save slot, the game will look at mission completion across all the saves and then set up a game world for you and your friends. In that game world, any mission that has been completed will be marked as such, but only as long as every single member of the Fireteam will have it completed. If there’s even one person that hasn’t tackled it just yet, the mission will be incomplete for everyone in the co-op world.

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Satechi USB-C Slim Dock For 24-Inch iMac Review: Fixing Shortcomings

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There are plenty of iMac docks on the market today, especially after the launch of the 2021 M1 models. Part of the tradeoff for the computer’s gorgeously slim design is the dearth of ports, all of which are hidden behind its screen. But while many of these docks and hubs are advertised as compatible with the 24-inch iMac, Satechi’s new dock takes that to the extreme — in fact, the USB-C Slim Dock is designed only for the 24-inch M1 iMac. Sure, you could use it for other computers, but then you lose one of its biggest features.

That feature is actually the wide gap on its bottom that perfectly fits the base of the iMac. This makes the dock look almost like it’s part of the iMac itself, especially if you get matching colors. The dock also creates a wider base that you could put things on if you like. Either way, its exclusivity to the 2021 and 2022 M1 iMacs works in its favor, creating a seamless appearance that fits the machine perfectly.

Whether you match colors or not, the Satechi USB-C dock matches the build quality of the iMac it sits on. Made from durable aluminum, the accessory looks premium and stylish, adding some character to your desk just as much as the iMac does. The material also makes heat dissipation more effective, which comes in handy given its hidden superpower. If there’s one disappointing aspect of the dock, it would be that it’s available only in silver and blue colorways that won’t color match all the available iMac hues.

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