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A Brief History of the Absolutely Amazing "A"

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Most modern alphabets start with the letter “A,” or a near equivalent. It was also first in line in the ancient Greek and Phoenician—from which the Modern English alphabet is ultimately descended—alphabets, too.


Being the gateway to the other letters and to literacy, “A” has rich symbolic value. Grouped with “B” and “C,” or even standing all alone, it can represent the whole alphabet and the learning of it. When that trio is written on a blackboard, there’s no having to guess what the kids are learning. The “A” and its Greek cousin alpha are also shorthand for excellence and achievement. You get an “A” or “A+” for good work in school, an A-1 vessel is an well built boat of the highest class and many social animals, from dogs to humans, follow the lead of the alpha male.

Built Like an Ox

The “A” appears in some of the earliest known transcriptions of the ancient Canaanite or Semitic (no one is sure which came first) alphabet from which most modern alphabets descend, written on limestone tablets in central Egypt around 1800 BC. Like the rest of the letters in this alphabet, “A” is descended from an Egyptian glyph and started out as a picture of an ox’s head. Over time, the ox head was simplified (drawn like a “V” with a crossbar to make a snout, ears and horns) and rotated to get to what we have today, with the horns acting as the letter’s legs.

The Phoenicians ruled a small empire of maritime city-states and colonies around the Mediterranean and were the first people to extensively use the alphabet as it emerged Egypt. In the Phoenician alphabet, the ancient “A”—called the aleph—didn’t represent a vowel. It was, instead, a symbol for one of several “breath sounds” they used, and represented the sound of what linguist call a glottal stop, a catch in the throat from which a following letter pushes off. Sounds like this were common in the ancient Semitic languages, but are rare today. You can still find examples here and there, though, most notably in the way that people with Cockney accents swallow their T’s in glottal stops to turn “bottle” into “bah-owe.”

When the Greeks adopted the Phoenician alphabet, it wasn’t very well suited to the sounds of their language. The breathing sounds weren’t needed at all, so the Greeks instead employed those letters to represent their vowel sounds. They changed the shape of the aleph, too. When they borrowed the letter and dubbed it alpha, the ox-like (though rotated, so it also sort of looked like a “K”) Phoenician symbol didn’t have much meaning to them, so they rotated the letter some more. The horns became legs. At one point, one of the legs got lopped off, but was eventually reattached.

Today, the sound of the “A” varies among the different languages that use it, and sometimes even within the same language. In English alone, “A” stands in for twelve separate vowel sounds. The sound it makes in “pa” or “ma”—what linguists call the low, back vowel sound—is thought to have been its pronunciation in ancient Etruscan.

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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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May 23, 2017
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