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A Warm Round of Applause for Our Newest Contributor

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Editor's Note: The mental_floss staff emails around a lot of articles. A few months ago, we realized that Bud Shaw of The Cleveland Plain Dealer had written a lot of the stories we'd been compelled to share. So we asked if he'd be interested in writing for us, and bam! Here we are. His first real article will come tomorrow, but here's an introduction from our newest contributor. Ladies and gentlemen, Bud Shaw!

Obviously lacking a keen eye for talent -- I thought I might become a big league pitcher before the day in Little League I gave up back-to-back home runs to twin brothers on the first two pitches of a game -- I've instead served as a sentry looking out for the odd characters in sports, the statistically quirky, the curiously hypocritical and the clueless.

Take, for example, Leon Spinks.

Spinks stood in his Sunday best inside a restaurant bar in suburban Detroit when I found him one frigid morning in 1991. I was on assignment for The National Sports Daily to write about Spinks' planned comeback as a heavyweight boxer nearly 13 years after his shocking upset of an aging Muhammad Ali earned him the heavyweight championship in just his eighth fight.

Spinks had another claim to fame -- the Olympic gold medal he won in Montreal fighting along side his brother, Michael, who also won gold. That made the gap-toothed smile he wore on the cover of Sports Illustrated after defeating the 36-year-old Ali in 1978 even more recognizable.


Well, three claims to fame. There were the late nights he kept, promoting his reputation as a party animal and no doubt playing a part in Spinks handing that same heavyweight title back to Ali when he lost a rematch seven months later.


OK, four claims to fame, but the fourth came later. One of the members of his expansive entourage was a tough looking character by the name of Mr. T.

But Spinks traveled much lighter on that Sunday afternoon in 1991, arriving at the restaurant with his wife after attending church. In a rambling, often unintentionally comical interview about his planned return to greatness, Spinks told me -- in an attempt to show his commitment to his craft, "I've stopped smoking and drinking."

I remember writing that in my notebook, circling the quote and adding a few asterisks. It wasn't that remarkable in and of itself. A lot of boxers give up their vices while training.

What made it so memorable is that Spinks was alternately sipping a mixed drink and puffing a cigarette as he spoke...
* * * * *
In three decades of sports writing, not every story carried a moral but the interview with Spinks did: don't believe everything you hear; in fact, it's more often recommended in this business to believe the exact opposite of what you hear...

Caught contradicting himself in the same 24-hour period, boxing promoter Bob Arum once cooly explained his flip-flopping by saying, "Yesterday I was lying. Today I'm telling the truth."
* * * * *
Sportswriting has taken me to six Olympics -- in Canada, South Korea, Atlanta, Salt Lake City, Japan and Australia.

It brought me to the home of a Buddhist monk in Nagano, Japan. I searched him out to talk about this mega sports event descending on a small town in a country where the lifestyles of the inhabitants outside the big cities are throwbacks to centuries gone by.

I had the right country, but this was the wrong monk.

Upon hearing that I worked in Cleveland where Ohio State football is religion -- he smiled and said, "Go Blue." Seems he did undergrad work at Michigan.
* * * * *
jesse-vWhile working at The National, I sat in the living room of a former pro wrestler running for mayor of a city in Minnesota. He talked about the local politics, how he'd rubbed people the wrong way by rumbling to council meetings on his motorcycle and challenging their opinions.


The mayoral hopeful didn't so much talk as growl during our interview. He spoke of having national political aspirations. Good luck with that, I thought.


Once his wrestling celebrity had time to wear off, I figured he'd have to put every Minnesota voter in a hammerlock to get enough votes to get elected to anything.

And that's how I "discovered" Minnesota Gov. Jesse "The Body" Ventura...
* * * * *
I've worked in the Pittsburgh area, New Jersey, Philadelphia, San Diego, Atlanta, Chicago, Detroit and Cleveland. I've been a sports columnist in Cleveland since 1991. The last time any Cleveland team won a championship was 1964, so it helps to keep a healthy sense of humor. Starting tomorrow, I'll give it a try with mental_floss once a month.

Bud Shaw is a columnist for The Cleveland Plain Dealer who has also written for the Philadelphia Daily News, San Diego Union-Tribune, Atlanta Journal-Constitution and The National. You can read his Plain Dealer columns at Cleveland.com.

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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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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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