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Book Giveaway Winners

We owe some people some books! Our jury has reached verdicts in last week's giveaways. Here's who won, what they won, and why:

Prize: Problem Identified (And You're Probably Not Part of the Solution), by Scott Adams
Challenge: Name the four conference rooms in the new (completely fictional) Mental Floss, LLC headquarters
Winner: Paul
Winning Entry: 1. Good Question, 2. Don't Know, 3. Not Sure, 4. Somewhere
(Which should making answering the question, "Which conference room is that meeting in?" a lot of fun.)
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Prize: Trotsky: A Biography, by Robert Service
Challenge: Give us the name of a strangely titled biography or memoir

Winner: Linda
Winning Entry: Crazy Aunt Purl's Drunk, Divorced, and Covered in Cat Hair: The True-Life Misadventures of a 30-Something Who Learned to Knit After He Split, by Laurie Perry
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Prize: Mint Condition, by Dave Jamieson
Challenge: Tell us about a time you went overboard to complete a collection
Winner: Niki
Winning Entry: When I was in college, I was trying to collect a full set of candle holders from the Party Lite Candle Company to decorate my living room. The candle set was pretty, but not really a collector's item. I just wanted the matching set. There were tea candle sets, Jar Candle holders, and similar items. Then, they came out with a candle warmer "“ the catch: you had to host a party in order to be eligible to buy it. So, of course, I hosted the party, during mid terms. Then, the Party Lite consultant read the fine print: my party hadn't made quite enough money "“ and the sale was already closed, so I couldn't just add to it!

In order to get my friends to come to another party and buy more stuff before their first orders even came in, I promised to make everyone sushi. This involved me learning to make sushi and spending $200 on stuff to make sushi. The second party made enough money for me to spend $45 on an overpriced candle warmer.

Within a couple of months of receiving my prized posession, I accidentally broke it. After all of that trouble! I contacted the consultant to see about replacing it, but I would have had to throw another party. So I sold the rest of the set instead! Hahaha.
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Prizes: TBD
Challenge: What's something you've picked up re-watching a favorite movie that you don't think most people caught?
Winners: gmsc, TeacherPatti + nowheremen22
Winning Entries: In Indiana Jones and the Temple of Doom, the name of the Chinese club is "Club Obi Wan" (gmsc); "It took me about a thousand views of The Breakfast Club, but I finally noticed that "Student (or Man or something) of the Year" (from years past) was Carl the janitor. The picture is in the trophy case that they show in the beginning of the film, during the voice over; (TeacherPatti); "While watching Airplane! for the umpteenth time, my wife spotted something that neither of us had ever noticed. In the scene where Captain Oveur get's the emergency call about the sick girl, they pan past the magazine rack. My wife says, "What did that say?" I rewind and see that on the rack it has a label that says "Wacking Material" (nowheremen22).
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We'll post today's challenge shortly. Congratulations to all the winners—expect an email shortly. And thanks to everyone who played along.

Original image
iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
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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