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The Late Movies: The Two Man Gentlemen Band

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Plenty of fans of this here blog can spout out wonderful facts, historical tidbits, and highlights of a classical education. It takes a truly special type of person, however, to take those kinds of things and set them to music. For your consideration, then, I offer The Two Man Gentlemen Band, a banjo/bass duo from New York that takes smart songwriting to a whole new level.

William Howard Taft

Everyone loves the story of Taft getting stuck in the bathtub, but it turns out that the story is even better with kazoos.

Prime Numbers

Banjo player and composer Andy Bean says, "We needed to sing a song about a lady's measurements without alerting grandmothers and other sensitive ears to the fact that we were singing about a lady's measurements.  Cloaking the lyrics in mathematical talk seemed an obvious choice."

Square Root of Two

I never even took calculus, but this song speaks to me.

My Baby's Off the Market

If you missed the bridge, the lyrics are: "According to the laws of supply and demand/ this baby ought to be walking with a wealthy man/ go down to the graveyard and tell Adam Smith/ his laws of economics don't apply when we kiss."

On the Badminton Court

You try to fit the word "shuttlecock" into a song.

They Can't Prohibit Us

Turning the 18th amendment into a love story.

This is by no means an exhaustive list of Gentlemen songs that, while entertaining, might actually help you on the SAT. Other titles include "Stonewall Jackson's Arm," "Ain't Nothin' Funny "˜bout the Death of Franklin Pierce," and "The Hindenburg Disaster." Banjo player Andy Bean and bassist Condon Fuller may in fact be coming to a town near you, check their website for tour dates. And if you like the Gentlemen, you might also like the Wiyos, Pokey LaFarge and the South City Three, and (total shameless self-promotion) my own band, the Freebadge Serenaders.

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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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