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Eiko Jones/National Geographic Your Shot

10 Beautiful Photos from National Geographic's Your Shot Community

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Eiko Jones/National Geographic Your Shot

Over its 125 year history, National Geographic has published a number of beautiful and iconic photographs (a few of which can be seen in this post we ran last month). Now, the magazine has launched a new photo-sharing platform called Your Shot that allows photography lovers to fulfill virtual assignments with the help of NatGeo photographers and editors. The first assignment, "Explore our Changing World," ends October 22. Here are 10 beautiful images that have been submitted so far; head over to the gallery for the first assignment (curated by NatGeo photographer Cory Richards and editor Sadie Quarrier) to see more.

Photos and captions courtesy of National Geographic and the photographers.

1. Best Shelter Ever

Photograph and caption by Arati Rao, National Geographic Your Shot

"A baby shelters under its mother one late afternoon in Sri Lanka."

2. The File on You Complete

Photograph and caption by Kathryn Nee, National Geographic Your Shot

"A stack of beautiful file cabinets found inside an abandoned factory in Georgia."

3. Weightless

Photograph and caption by Dimitris Maroulakis, National Geographic Your Shot

"Freediver slides peacefully over sea bed in the blue hole area of Vouliagmeni."

4. Ki Monastery, Spiti Valley, India

Photograph and caption by Stuart Edwards, National Geographic Your Shot

"The Ki Monastery is situated high in India's Himalayan region in the remote Spiti Valley. A few hundred Buddhist monks live here permanently, studying and worshiping in probably one of the most serene places I've ever seen."

5. Seagull

Photograph and caption by Junichi Saito, National Geographic Your Shot

"Feeding a seagull."

6. Night of Lightning at Grand Canyon

Photograph and caption by Rolf Maeder, National Geographic Your Shot

"It was such a wonderful experience to witness this beautiful thunderstorm far across the Grand Canyon!"

7. Kabul Balloons

Photograph and caption by Allen Rooke, National Geographic Your Shot

"Whilst on mission in Afghanistan for the World Food Programme, I had to travel the 10kms or so every day from the office to the warehouse complex. Winter in Kabul is cold, wet and usually shrouded in a heavy fog. These lads were walking along the road early in the morning and they made my day."

8. Cloud of Tadpoles

Photograph and caption by Eiko Jones, National Geographic Your Shot

"While photographing lilies in a local swamp a cloud of tadpoles swam by numbering in the thousands, all following along in a trail."

9. People at Prayer

Photograph and caption by Junaid Ahmed, National Geographic Your Shot

"Ijtema is the second largest muslim gatherings in the world after Hazz.The gatherings is so huge that people did not get place at the field to pray jumma prayer and sited themselves at road."

10. Meteorite

Photograph and caption by Noel Kerns, National Geographic Your Shot

"Abandoned farmhouse near Sanger, Texas. 3-minute exposure under a 3/4 moon, f/5.6, ISO 200. Interior of house light-painted with X2000 flashlights."

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iStock // Ekaterina Minaeva
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
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]