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'Fake' Etymology: The Story Behind One of the Dictionary’s Most Intriguing Words

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It’s probably fair to say that fake is fast becoming one of the biggest buzzwords of 2017. But behind the word is a rather tricky—and largely unsolved—etymological story that takes us back to the secret slang of early 19th century criminals. Take a look at this:

“To fake any person or place, may signify to rob them; to fake a person, may also imply to shoot, wound, or cut; to fake a man out and out, is to kill him; a man who inflicts wounds upon, or otherwise disfigures, himself, for any sinister purpose, is said to have faked himself; if a man’s shoe happens to pinch, or gall his foot, from its being overtight, he will complain that his shoe fakes his foot sadly; it also describes the doing of any act, or the fabricating any thing, as, to fake your slangs, is to cut your irons in order to escape from custody; to fake your pin, is to create a sore leg, or to cut it, as if accidentally, with an axe, etc., in hopes to obtain a discharge from the army or navy, to get into the doctor’s list, etc.; to fake a screeve, is to write a letter, or other paper; to fake a screw, is to shape out a skeleton or false key, for the purpose of screwing a particular place; to fake a cly, is to pick a pocket; etc., etc., etc.”

That’s an extract from A New and Comprehensive Vocabulary of the Flash Language, a dictionary of criminal slang compiled by James Hardy Vaux in 1819. Surprisingly, this definition provides us with the earliest known record of the current meaning of fake. Although the Oxford English Dictionary dates the word to 1775, their earlier record of it looks to be a misreading of false, and so can’t be guaranteed. Fake is also a naval term used to describe coiled rope that appears to be older, but that’s considered unrelated. So we’re not dealing with some long-established Anglo-Saxonism here. Instead, fake, in the sense of something being bogus or counterfeit, apparently began life a little over 200 years ago among the “flash” language used by criminals in 18th- and 19th-century England.

Vaux’s “flash” was a veiled jargon used by criminals to keep their activities a secret from the authorities, their victims, or anyone else who happened to overhear their scheming. For example, a jump was a ground-floor window. Dummy-hunters were robbers of wallets and pocketbooks. A fly cove was a shopkeeper who could not easily be robbed. A hoxter was the inside pocket of a coat. And knapping a Jacob from a danna-drag meant “stealing a ladder from a night workman” for the purposes of scaling a wall or reaching a high window.

It’s fair to presume Vaux would likely have had insider knowledge of this kind of thing. Despite being credited with producing the very first dictionary ever compiled in Australia, Vaux was a British-born ex-convict who included in his dictionary all those terms he had heard while serving time in penal colonies in Australia in the early 1800s—fake among them.

So we know the word has criminal origins, and presumably dates back to sometime around the late 18th century, but where did it come from? Admittedly, it’s hard to say—not least of all because Vaux’s explanation is so wide-ranging that it gives us little, if any, detail to go on.

Faking, according to Vaux’s definition, could once be taken to mean everything from robbing to murdering, cutting to breaking, pinching to writing, and making something to breaking something. In fact, Vaux was compelled to introduce this entry in his dictionary with the caveat that fake was “a word so variously used, that I can only illustrate it [here] by a few examples.”

Amidst the blizzard of competing definitions, the use of fake to mean “counterfeit” or “artificial” is at least beginning to emerge in Vaux’s explanation, most notably in the expression “to fake your pin,” which meant to feign illness or injury to escape work or military service. It’s this sense of the word that has survived to this day—and it could be this that points us toward where the word might actually have originated.

One theory claims that fake could be related to the German fegen or Dutch vegen, both meaning “to polish,” or “to wipe clean”—the implication being that something might once have been said to have been “faked” when it had been cleaned up to appear more valuable than it actually was. If that’s the case, then fake might be related to a dialect term feak or fyke, meaning “to twitch or move quickly,” or else feague, an 18th-century slang word meaning “to put ginger or a live eel up a horse’s anus to make it appear more sprightly.” (No, really.) Alternatively, fake might derive from fac, a derivative of the Latin verb facio, which literally means to “make” or “do.” This more general explanation is less imaginative, but might at least account for the word’s array of different meanings in Vaux’s dictionary.

It’s hard to say which—if any—of these theories is correct without further written evidence, but we can at least be sure that "faking" things is not quite as old as we might think.

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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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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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