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7 of the Most Depressing Streaks of Futility

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For the first time in 20 years, the Pittsburgh Pirates will finish with more wins than losses! The last time that happened, “End of the Road” by Boyz II Men stood atop the Billboard charts, Silence of the Lambs had won the Oscar for Best Picture, and Barry Bonds still looked like this.

Here are some of the worst season-by-season losing streaks in the wide wide world of sports.

1. Philadelphia Phillies (16 straight)

The baseball gods have not been kind to Pennsylvania. The Phillies won 38 percent of their games from 1918 to 1931. In 1932, they eked out just enough Ws to call it a winning season, promptly starting another marathon losing streak the next year. It lasted 16 years. If it weren’t for the 1932 club, the Phillies would have set a dismal record of 31 straight losing seasons. Ouch.

2. Vancouver Canucks (15 straight)

The Canucks failed to breach the .500 mark from 1976 to 1991. But that didn’t keep them from making a run at Lord Stanley’s cup. In 1982, despite finishing three games below, the Canucks still slipped into the playoffs and made it into the Stanley Cup Finals. The magic died there—the Islanders swept them away.

3. Sacramento Kings (15 straight)

Back in the day, the Kings were Kansas City’s basketball team. That’s where their paltry 15-year-long losing streak began. Two years into that slump, the Kings picked up their things and moved to California. They wouldn’t finish as winners until 1999—a year shortened by a lockout.  

4. Tampa Bay Buccaneers (14 straight)

Most expansion football teams don’t start out as victors, but the Bucs outdid themselves. Despite a terrible inaugural 1976 season—where they finished 0-14—Tampa actually managed a few winning seasons. But it didn’t last. From 1983 to 1996, they failed to break .500, solidifying their beloved nickname as the “Yucks.”

5. Ottawa Rough Riders (17 straight at or below .500)

Founded in 1876, the professional Canadian Football team was one of the oldest and proudest sports organizations this side of the Atlantic. Then the '80s happened. For 17 straight years, the Riders finished at .500 or below, forcing them to fold in 1996.

6. Prairie View A&M Panthers Football (31 straight)

The Division I-AA school piled on 31 consecutive losing seasons from 1976 to 2006. Panthers’ fans would especially love to forget the '90s, when the team lost 80 straight games. Lately, though, things have been looking up. In 2009, Prairie View won the SWAC championship.

7. Oregon State Beavers Football (28 straight)

From 1971 to 1998, the Beavers could not rack up more than five wins per year, managing the worst season-by-season losing streak in Division I-A football. But they’ve turned it around since, making 10 bowl appearances.

Do you support a lovable loser? Share your favorite stories of woe below!

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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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