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Image Macros: I'm in Your X, Y'ing Your Z

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Okay, now that I've spent the first three days of this week talking about LOL Cats, it's time to move on to something marginally more advanced: the "I'm in Your X, Y'ing Your Z" Image Macros.

According to several web sources (which are so not-work-safe I won't link them), this genre of Image Macros started with the statement, "I'm in your base killing your d00ds" (that last word being a Leet spelling of "dudes"), from a classic video game. Non-gamer translation: "You lose."

This Image Macro genre first came to my attention, you guessed it, as a LOL Cat:

After the jump, I explore some unique characteristics of the Image Macro, including a political Image Macro.

Of course, things had to go a level deeper than just Leet speak and cats. The day after the 2006 US Congressional Election, a version of the "I'm in your X, Y'ing your Z" Image Macro appeared showing Nancy Pelosi, the new Speaker of the US House of Representatives. Boing Boing featured the image, which read: I'm in ur house impeachin ur doodz." (They also featured a rather wonderful LOL Bird.)

Nancy Pelosi

Five days after the election, a top 10 list appeared, with a hilarious variety of Image Macros based on the theme. My favorite:

I'm in ur base killin ur doodz

So this is fun and all, but what's the point? Well, I believe that the Image Macro is a new form of art, native to the web. This new form has some unusual characteristics -- primary being that most images are by anonymous authors (though some communities create the macros collaboratively, with known authors). The images are frequently reproduced in blogs (*ahem* like this one), in which the main attribution is simply the location where the image was found. In their inherent anonymity, Image Macros are like Graffiti (minus the tagging).

Another unusual characteristic of Image Macros is the rapid adoption and evolution of new genres. A single popular image can spawn an entire genre of Image Macros with their own syntax and style. Responses to an original image range from copycat images (if you'll excuse the expression) to fairly complex new statements. You can see this in action in the "Invisible" LOL Cats, in which Invisible Bike leads to Invisible Bike Crash, and finally to Invisible Everything. While classical art is responsive in this way, the speed with which the genre is created, extended, and integrated with other genres is impressive.

Also, due to the sheer number of Image Macros in the wild, lots of sites have created their own collections, generally going on for many pages. We've linked earlier in the week to the LOL Cat blog, I Can Has Cheezburger -- after being linked by Digg today, they have shut down temporarily due to excessive bandwidth usage. Each of these sites is effectively an online museum of art, curated by amateurs. You can see the influence of the curator in some collections in which images have been presented in a particular sequence (it's a fairly crass example -- not for the easily offended -- but the "ceiling cat" sequence at the end of this collection shows what I mean).

Here's a small, non-ordered collection of some LOL Cat X/Y/Z favorites, to reward you for reading this far:

I'm on yer table trimn all yer plants

Bustin ur mythz

Im in ur truck makin the duliverys

Grammar Cat

So what do you think? Do LOL Cats and X/Y/Z Image Macros qualify as art?

Tomorrow we'll wrap up the Image Macro series with some unexpected evolutions of the form. Stay tuned!

Resources related to today's post: LOL Cat site with lots of X/Y/Z examples (many images above are from this site). See also the collection from the "Error: Access Denied" site.

This article is part of a series. Read the rest:

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iStock // Ekaterina Minaeva
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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