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Thanassi Karageorgiou / Museum of the Moving Image

Is the Internet as Obsessed With Cats as We Think It Is?

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Thanassi Karageorgiou / Museum of the Moving Image

Today, Friday August 7, New York's Museum of the Moving Image opens its doors on a new exhibit that shows just how broad the world of movies and film has become. "How Cats Took Over The Internet" explores a central tenet of the modern online experience—that cats rule the world wide web. But when he started to dig deeper, Jason Eppink, the curator (who does not own a cat and is, in fact, allergic to them) found the trend that's become a cliché wasn't exactly reflected in the numbers.

Even on sites where cute content flourishes—Reddit, YouTube, Tumblr, BuzzFeed, and Instagram—posts tagged as featuring cats and dogs seldom exceed .3 percent of a site’s traffic. And cats don't even always edge out their canine counterparts. The exhibit features a wall full of color-coded charts comparing the virality of cat content to content centered on dogs. On Reddit, the number of comments about cats and dogs has remained relatively equal since the site launched in 2007, with dogs in the lead for most of that time. Dog posts have exceeded cat posts on BuzzFeed for a few years now. Even on YouTube, the so-called "ground zero for cat videos," the Pets & Animals category accounts for less than 1 percent of all videos—and while 16 percent of views in that category are of cat clips, dogs garner 23 percent of views.

So why have cat videos become synonymous with online time-wasting? (One recent study claims they're actually energy boosting.) Another portion of the exhibit tackles this phenomenon with a number of different theories (interspersed with cat videos, of course). They cite the appeal of a "virtual cat park," an idea coined by Jack Shepard, editorial director at BuzzFeed. According to this theory, the Internet serves as a gathering place for cat owners, the same way a dog park serves to bring dog owners together. Similarly, there's the idea that self-described cat people—who, pre-Internet, felt stigmatized by society at large—were especially eager to join up with fellow cat lovers.

Another theory points to cats' tendency to ignore the humans (or cameras) around them, which gives cat videos a more voyeuristic feel. Add to that the fact that people are inclined to identify with living creatures in general (a characteristic called biophilia), attribute human-like internal lives to their pets (anthropomorphism), and just think kittens are downright adorable, and it isn't surprising that the idea that "Cats Rule the Internet" became a self-perpetuating truism. 

"How Cats Took Over The Internet" is at the Museum of the Moving Image from August 7, 2015 to January 15, 2016. All images courtesy Thanassi Karageorgiou / Museum of the Moving Image.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Name the Author Based on the Character
May 23, 2017
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