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Teacher Appreciation Week: Animal (school)House

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For our final tribute to teachers, we're focusing on creatures -- today we visit the animal kingdom to see what learning looks like there.

Dolphins: Spongeworthy Under the Sea
Using tools was once thought to separate humans from primates, but now, it doesn't seem to distinguish us much from dolphins, either. Recently, scientists observed dolphins using sponges to protect their sensitive schnozzes while searching for food on the rough sea floor. Not only that, but they also appear to be especially shrewd in their choice of tools. They only select sponges that are conical, not flat, so their noseguards stay on even if they get jostled during use. Sponge use also appears to be a family tradition usually passed from mothers to daughters. Some researchers have even speculated that the behavior may have originated with one common ancestor (the "Sponging Eve," so to speak) that other dolphins copied.

Macaques: Monkeys that Wash and Learn
Scientists have long been impressed with the macaque, a type of monkey known to exhibit several unique learned behaviors, including wheat-washing, stone-handling, and group snowball-rolling. And if that's not enough to make you want to adopt one, consider this: It just might fix you dinner. Behavioral researchers on Koshima Island, off the coast of Japan, laid out sweet potatoes along the beach for a group of macaques, and one smart female monkey named Imo made sure to wash them in the ocean before eating. Pretty soon, other macaques had caught on, and the behavior has since been passed on to several new generations of macaques from Imo's troop.

Ants: An Apple for Your Teacher
While all the other entries on this list focus on animals that like to learn, it's far more difficult to find those that enjoy teaching (that arrogant, self-righteous calculus professor you had junior year included). On the whole, animals learn by imitation, not pedagogy. In fact, scientists know of only one exception to this rule, and that's the ant. In order to help the younger generation find the path to the grub, older ants utilize a technique called "tandem running." A professor ant takes the lead, but if it can't feel the eager limbs of the pupil on its posterior, the leader will slow down so the little learner can catch up. Though crude, this counts as teaching because the lead ants are willing to compromise their own bid for the ant buffet so their younger pals can catch up—and that's downright humanitarian, folks. At least for the ants.

You can read about seven more of those in Mark Peters' "10 Studious Animals to Cheat off off in School," found in our September/October issue. By the way, if you're a subscriber, you should be getting the November/December issue very soon... and if you're not, well, hey, get on that!

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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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Nick Briggs/Comic Relief
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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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