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Month in Review: September's Most Popular Stories

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If you're keeping score at home, September was the second-best month we've ever had. (The halcyon days of August '09 will be tough to top.) Thanks to everyone who has made mental_floss part of your routine, especially the folks who've been here for years and have aggressively spread the word about our site and magazine.

We've got some exciting stuff on tap for October and beyond. Stay tuned. For now, let's take a look at our ten most popular stories from September.

1. The Quick 10: 10 Secret Menu Items at Fast Food Restaurants*
by Stacy Conradt

You probably caught September's top story the first (or second or third or fourth) time around. Our biggest viral hit since 2007's Quarter Backs Quiz, Stacy's post has been featured by Yahoo!, CNN, USA Today and The Today Show (see Al Roker, Ann Curry & Natalie Morales talking about it here).

2. 4 People With Super Memory
by David K. Israel


What if you finished reading this article and remembered every detail of it for the rest of your life? That's the problem people with super-autobiographical memory face—and yes, it's often referred to as a problem, not a gift.

3. 11 Things Wal-Mart Has Banned
by Ethan Trex


It seems like the mega-store stocks just about everything. But not quite, though. There are a number of things that Wal-Mart has banned from its stores at some point. Here's a look at a few of them.

4. 10 Technologies We Stole From the Animal Kingdom
by David Goldenberg & Eric Vance


People have been lifting ideas from Mother Nature for decades. But today, the science of copying nature, a field known as biomimetics, is a billion-dollar industry. Here are some of our favorite technologies that came in from the wild.

5. 10 Unusual Playgrounds From Around the World
by David K. Israel

Playgrounds have come a long way since the early days of hot, steel slides and open-backed infant swings. Take a look at some of the amazing play-places popping up around the world.

6. How Do Countries Choose Which Side They Drive On?
by Linda Rodriguez

Why do different nations drive on different sides of the road? London correspondent Linda Rodriguez answers that age-old question.

7. 15 Companies That Originally Sold Something Else
by Ethan Trex

Some companies find their niche and stick to it. Others, though, have to adapt to changing markets in order to thrive. Here's a look at companies that switched industries at some point in their histories, including Avon, 3M and Tiffany.

8. Somewhat More Realistic Cartoon Characters
by Miss Cellania


Tools like Photoshop make it easier than ever to give texture and shadow to plain line drawings, so converting our favorite cartoon characters into a more realistic style is too tempting to pass up.

9. 11 Famous Actors and the Big TV Roles They Turned Down
by Kara Kovalchik


Dana Delany as Carrie Bradshaw? Paul Shaffer as George Costanza? Cosmo Kramer as Monk? Here's a look at 11 actors who passed on some of TV's most popular shows.

10. 6 Lost Treasures Just Waiting to Be Found
by Rob Lammle


Not everybody can just stumble upon a copy of the Declaration of Independence at a garage sale. To help you find your fortune, here are six tales of lost treasures that are just waiting for you to find them.

* Sure, Stacy's article was technically posted on August 31st (and therefore ineligible for "September's Most Popular Stories"), but when Al Roker talks about a story, we toss aside rules.

If you're new to mental_floss, here's what you missed in August.




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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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Name the Author Based on the Character
May 23, 2017
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