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Wikimedia Commons

A Parrot’s First Flight

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Wikimedia Commons

In the latest issue of the print magazine, I have a story about the kakapo, a cartoonishly cute species of parrot that looks like a parakeet crossed with an owl crossed with a Muppet. (You can read it here.) Kakapos are squat, chubby and flightless, and build their nests on the ground and in the open. They’re also nocturnal, and feel their way through the dark forests with patches of whisker-like feathers on their faces. The whole while, they give off a strong, musty scent that’s impossible to ignore. All of this made them easy pickings for human hunters, plus the dogs, cats, rats, and other predators that humans introduced the to the parrot's home in New Zealand. In just a few centuries, one of the country’s most common birds soon disappeared from the main islands, and today there are only 126 kakapo left in carefully monitored, predator-free communities on the smaller islands.

A handful of the birds were transferred to an island that is also, conveniently, one of the last remaining refuges of the Hades flower, an endangered plant that scientists only recently realized had strong ecological ties to the bird. I couldn’t get into too much detail about the transfer operation itself because of space constraints, so here’s the story of how a flightless bird finally took to the skies. 

In the early morning hours one April day last year, parrot wranglers from the New Zealand Department of Conservation’s Kakapo Recovery Team (KRT) captured seven of the birds on Codfish and Anchor Islands by hand (all 126 remaining kakapo wear radio transmitters, so they’re easy to find) and placed them into individual pet carriers. Their destination: Hauturu, the “resting place of lingering breezes.”

Called Little Barrier Island in English, Hauturu had been home to a group of kakapo (Strigops habroptilus) in the early 1980s, but the birds had to be removed after the discovery of accidentally-introduced kiore, or Polynesian rats. With the island’s rats eradicated, the KRT hoped that Hauturu would now be safe for kakapo eggs and chicks, and a suitable place for a large, unmanaged kakapo population. On paper, it’s one of the last New Zealand islands where the birds could live without constant human babysitting. It’s big enough for the birds to live and breed there, and outside of the swimming range of rats, stoats, and other predators living on the other islands. 

After the kakapo were snatched up, they were taken by helicopter to the large South Island. There, they were loaded on an airplane and taken to North Island. At the Auckland airport, they were put on another helicopter and taken to Hauturu, where they were released from their carriers. 

That might sound stressful, but kakapo didn’t seem to mind.

“Kakapo appear to be hardy travelers and the main risk is heat stress,” Kakapo Recovery Program Manager Deidre Vercoe Scott said. The birds just needed to be kept cool and comfortable with some damp towels in their crates and some apples and carrots to snack on.

“This was one of the most complex transfers we have done simply because of the distance the birds had to travel,” Vercoe Scott said. “But with careful planning we were able to achieve it within a day, meaning the birds were not disturbed during their normal active period during the night.”

A few months after they arrived, the birds were captured again so KRT members could see how they were adjusting to their new digs. On the whole, Vercoe Scott said, they had settled in well and were in good health. A few of the birds had been part of the island’s previous kakapo population and seemed to have no problems coming back home again. One bird, after a 14 year absence, was able to find her old nesting sites and home range within a week of returning.

Sounds like a happy ending, but this is just the beginning of the kakapo’s adventures on Hauturu. The birds didn’t breed last year, and the KRT wasn’t expecting them to, so soon after transfer. This year might be different, and December through February, their human guardians will keep a close eye on them to “see whether or not they are keen,” said Vercoe Scott. These birds aren’t expected to establish a population on the island just yet, though, so there’s no pressure for romance. Rather, they’re pioneers and guinea pigs testing the suitability of Hauturu as a long-term, unmanaged home. Their service to their species could last as long as 10 years, giving conservationists enough data on breeding success to make the call on whether the birds will return to where they came from or be joined by waves of new settlers, and allowed to live alone and in peace on the little island where lingering breezes rest. 

Original image
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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