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:
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 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.
US Border Patrol seizes thousands of fake vaccine cards and Pfizer stickers
The US Border Patrol has reported seizing thousands of fake COVID-19 vaccination cards and Pfizer inoculation seals, the latest confiscation in what has been at least several thousand counterfeit cards found by customs officers this year. The latest batch arrived at the Port of Cincinnati in multiple shipments.
The latest Customs and Border Patrol seizure of counterfeit COVID-19 cards was reported by the agency on September 16. A total of 1,683 blank COVID-19 vaccination record cards were seized across five shipments that arrived starting on August 16, according to the agency. As well, these shipments contained 2,034 Pfizer inoculation stickers.
The report came only one day after CBP officials in Pittsburgh reported that they’d likewise confiscated fake COVID-19 vaccination cards, though a lesser amount at 70. In the latest case, the agents noted that the cards originated from China and were being imported by people who lived in private residences in multiple states, including Texas and Maryland.
As with previous seizures involving counterfeit cards, the Customs officials noticed that the latest fake cards featured “substandard printing,” as well as misspelled words. Other confiscated counterfeit vaccination cards featuring the CDC logo have also been reported at ports in Anchorage, Chicago, and Memphis.
The FBI has repeatedly warned that making, buying, and selling fake COVID-19 vaccination cards is illegal and could result in penalties. Despite this, many anti-vaxers continue to seek ways to fake vaccination records in an effort to get around vaccine mandates.
HBO Max lures in new subscribers by cutting its premium price in half
HBO Max, one of the largest streaming services on the market, is luring in new and returning subscribers by slashing the cost of its premium plan for up to half a year. The price decrease makes the premium plan cheaper than the ad-based plan, at least during the promotion, giving subscribers access to new theatrical movies from Warner Bros., HBO originals, and more.
HBO Max is now the destination for streaming HBO content; the platform’s parent company recently made the move to remove its now-defunct HBO app from Amazon’s Prive Video Channels platform, leaving those customers to finally make the transition to the new service.
That change happened earlier this week, with the new discount promotion coming only a couple of days later. The new deal is available only for the Ad-Free plan, which ordinarily costs $14.99/month but is temporarily lower at $7.49/month.
The ad-free plan includes access to 4K UHD resolution content, the ability to download for offline viewing, and the rest of Warner Bros. 2021 movie premieres with same-day streaming access. It appears the new promotional pricing is available for new and returning subscribers, as well as those who are jumping to HBO Max after Amazon Prime Video Channels lost access to HBO.
Overall, this is a great deal for those who want to catch up on their favorite HBO shows or stream the latest Warner Bros. theatrical movies from the comfort of their homes. The same-day theatrical movie releases only apply to 2021, however — it’s unclear whether this holiday season’s COVID-19 cases will fuel another series of lockdowns and whether Warner Bros. will extend its hybrid releases into 2022.
Watch Apple break down the iPhone 13 differences
It’s iPhone 13 preorder day, and if you’ve been scratching your head about whether to go iPhone 13 mini, iPhone 13, iPhone 13 Pro, or iPhone 13 Pro Max, a new Apple video could help filter through the options. Announced on Tuesday, there’s no shortage of information out there on what changes Apple made in 2021, and what sets its four new smartphones apart.
Now, it probably shouldn’t come as a great surprise to you that Apple is very impressed by Apple’s new smartphones. If you’re hoping for unbiased, impartial commentary on the new iPhone 13 and iPhone 13 Pro, this really isn’t the video for that.
However, with Apple’s virtual event meaning no opportunity for hands-on reports from media, along with the fact that we’re not expecting the first round of reviews until sometime next week, for the moment we’ll have to take what we can get. Given the four-strong line-up again this year, too, it’s also an opportunity to compare and contrast if you’re on the fence about which iPhone model fits your particular needs. As ever, that’s not necessarily an easy decision.
Like was the case in 2020, for most people the iPhone 13 and iPhone 13 Pro seem likely to be the sweet spot in 2021. The iPhone 13 mini is most affordable, but the smaller display could leave it too small for some. We also need to see whether Apple’s claims that it has addressed the mini battery life are accurate, too.
At the other end of the scale, the iPhone 13 Pro Max clearly has appeal for those who don’t want to compromise: whether that’s on screen size, cameras, or anything else. With a starting price of $1,099, though, that’s a whole lot to spend on a new smartphone. Meanwhile, unlike with the iPhone 12 Pro and iPhone 12 Pro Max, there aren’t any obvious differences in the cameras this year.
Last year, the iPhone 12 Pro Max got sensor-shift image stabilization and a larger lens. This year, though, the iPhone 13 Pro and iPhone 13 Pro Max have the same camera specs. It means you don’t have to find space in your pocket for the very largest handset if you want the very best camera tech Apple has to offer.
Clearly, you shouldn’t be basing your entire purchasing decision on Apple’s video. All the same, if you’ve been wondering about new features like macro photography support, the new Super Retina XDR display with its 120Hz ProMotion refresh rate, and the new AI-powered Cinematic mode, this video offers a more in-depth look than Apple had time for during its keynote on Tuesday.
Preorders of the iPhone 13 family are open now, with deliveries expected to begin next Friday, September 24.
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