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Your Official Groundhog Round Up

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Getty

In case you haven't already heard, Punxsutawney Phil predicted an early spring! If you're not sold on Phil's accuracy rate, however, there are plenty of other groundhogs you can consult instead. Here they are, complete with what they declared today:

1. Buckeye Chuck

Tired of waiting on word from across state lines, Ohio managed to find their own forecasting groundhog back in the 1970s. Hailing from Marion, Ohio, Buckeye Chuck is said to be accurate about 75 percent of the time.  His 2016 verdict: Six more weeks of winter.

2. General Beauregard Lee

General Beau is likely the only groundhog with not one, but two honorary doctorates. His degree from the University of Georgia declares that he is a "Doctor of Weather Prognostication", while Georgia State bestowed a "Doctor of Southern Groundology" title upon him. As befitting of any grand Atlantean, General Beau has his very own version of Tara. His 2016 verdict: Early spring.

3. Balzac Billy

Despite the fact the Balzac Billy in Alberta, Canada, is just a dude in a groundhog costume crawling out of a mulch pile (or perhaps because of it), "The Prairie Prognosticator" boasts about an 80 percent accuracy rate. His 2016 verdict: Early spring.

4. Staten Island Chuck

This little guy, whose formal name is Charles G. Hogg, is notorious for nipping Mayor Michael Bloomberg during the 2009 prediction ceremony at the Staten Island Zoo. His 2016 verdict: Early spring.

5. Wiarton Willie

Willie, an albino groundhog, has been predicting the weather since the 1950s—even though he was nothing but a fur hat back then. The story goes something like this: In 1957, a fellow named Mac McKenzie used Groundhog Day as an excuse to throw a boozy bash for his friends. Reporter Frank Teskey somehow got wind of the affair and misinterpreted that there was a big Groundhog Day festival in Wiarton, Ontario. When he arrived and discovered that the gathering was just a few guys drinking with no groundhog in sight, Teskey complained that he was going to be in trouble for having no story. In response, McKenzie grabbed a white fur hat from a female party-goer, half-buried it in the snow outside, and declared that Wiarton was home to a rare albino groundhog. The legend has grown, and now thousands of people show up yearly to celebrate Wiarton Willie, who has been upgraded from a fur hat to a real, live groundhog. His 2016 verdict: Six more weeks of winter.

6. Shubenacadie Sam

Thanks to Nova Scotia's time zone, Shubenacadie Sam at the Shubenacadie Wildlife Park is the first to make a prediction for North America every year. His 2016 verdict: Early spring.

7. Queen Charlotte

Queen Charlotte the groundhog made her public debut in Charlotte, North Carolina, this year. Though she predicted six more weeks of winter last year, she did so in a private ceremony—at the time, the Queen was new to the limelight and wasn't ready to perform in front of a crowd of onlookers. Her 2016 verdict: Early spring.

8. Jimmy the Groundhog

It seems that Jimmy the Groundhog from Sun Prairie, Wisconsin, wasn't too thrilled about coming out of hibernation last year. When Jimmy's handler held him up to Mayor Jon Freund's ear to "whisper" his weather findings, the groundhog gave the mayor a little nip on the ear. Jimmy didn't get the chance to get so up close and personal this year—he had to stay in his cage for the official announcement. His 2016 verdict: Early spring.

9. Chuckles

Chuckles the Groundhog makes her predictions live from the Lutz Children's Museum in Manchester, Connecticut. They're currently on Chuckles VIII, an orphaned groundhog who was sworn in to her position in 2013 using a copy of the Farmer's Almanac. Her 2016 verdict: Early spring.

10. Polk County Paula

Polk County Paula, a groundhog mascot from Des Moines, predicts the weather and distributes free bottles of Miller High Life. It probably helps the "more winter" predictions go down a little easier. Her 2016 verdict: Early spring.

Good news: Early spring has the majority. Happy Groundhog Day!

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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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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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