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23 Vintage Photos of People Having Fun in the Snow

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Getty Images

It's cold outside, so get cozy and enjoy these historical photos of snow day shenanigans. Who knows—maybe they'll inspire you to bundle up, venture out, and have some fun. 

1888: A stereoscopic show of kids building a snowman in Niagara Falls, New York. Library of Congress.

1900: Sledding in Central Park. Library of Congress.

1901: Milton Wright, Ivonette Wright, and Leontine Wright,  children of Lorin Wright, and nephew and nieces of Wilbur and Orville Wright, pose for a snowy shot. Library of Congress.

1909: Senate pages have a snowball fight in Washington, D.C. Library of Congress.

1909: Irish explorer Sir Ernest Henry Shackleton and two members of his expedition team beside a Union Jack within 111 miles of the South Pole, a record feat. Getty Images.

1909: Boys in Washington, D.C. cleaning off the ice so they can skate. Library of Congress.

1909: Taking a sleigh ride. Library of Congress.

1914: A woman's skirt billows out as she pirouettes on a frozen lake in a park in Berlin. Getty Images.

1915: Mr. Harry Gooch's ice yacht. Getty Images.

1915: Sledding in New York City's Central Park. Library of Congress.

1923: Two jazz musicians slide downhill on a sledge carrying their instruments: a drum and a trumpet. Getty Images.

1926: Jimmy Botterell of London and companions, dressed in striped suits and top hats, on a bobsleigh at St. Moritz. Getty Images.

1931: A group of gents enjoy an impromptu snowball fight in the serene and stately setting of a still and snow covered Trafalgar Square, London. Getty Images

1935: A goalkeeper gets ready to play hockey. Getty Images.

1935: A group of Manchester Brownies from Manchester, New Hampshire, sitting on a sledge, dressed in swimming costumes. They enjoy their winter sports best when clad only in bathing suits. Getty Images.

1937: A 'mishap' on the 'toboggan run' on snow covered Hampstead Heath, London. Getty Images

1937: A farmer, who is bringing food supplies to animals in snow-covered fields, stops to play with two lambs and their mother, on his farm at Rumney, near Cardiff, Wales. Getty Images

1940: Boys build a snowman in Norwich, Conn. Library of Congress.

1942: Boys sledding in North Dakota. Library of Congress.

1955: Students at Plymouth State Teachers College, New Hampshire, square dance in their 'raquettes', or snow shoes. Getty Images

1965: The Beatles experiment with a toboggan while on holiday, Obertauern, Austria. Paul McCartney sits in front, John Lennon behind him, and George Harrison brings up the rear. Ringo Starr has fallen off the back. (And yes, that's them at the top of the post, too, goofing around in Washington, D.C. before a concert in 1964.) Getty Images.

1968: Two nuns from the Missionaries of Nazareth enjoying a downhill sledge ride near the Costa Brave in Nuria, Gerona, Spain. Getty Images.

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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]