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1000 Blank White Cards

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I like card games as much as the next guy, but it seems like half the fun must be in creating the cards and making up the rules. (Okay, maybe that's just one-third of the fun. But still.) If you enjoy creating games as much as playing them, check out 1000 Blank White Cards, a party game in which creating the deck is part of the action. (A sample card is pictured at left: Self Trepanation (lose 2000 points).)

A game of 1000 Blank White Cards, or 1KBWC for short, consists of three general stages (described after the jump...)

1. Deck Creation - in which players create some number of cards, starting with a stack of blanks (up to the eponymous 1000 if you expect to play until next year). Depending on the expected duration of the game, you might create a hundred cards in advance -- or you might start with a handful and make more as you go along. Each card can contain any drawing or text you want -- the card can implement rules (all players must discard a card, for example), give you free turns, add or subtract points, end the game, make the player perform a task, anything you want. Also note that deck creation is explicitly allowed during game play, so this early phase is just about setting up the initial game, which will evolve during play.

Solar Power Card2. Game Play - in which players draw five-card hands and play them "on" other players. For example, you might draw the Solar Power card, which simply has an illustration of a Lego man driving a solar-powered buggy -- it does nothing on its own (though you might get creative and combine it with something else -- for example, by creating an "Al Gore" card that grants +50 points for any player with a solar-powered vehicle). Or you might draw the I Have No Arms card, which offers eight points if you pick something up with your teeth. (Note that points are completely arbitrary, though many cards offer plus or minus points for various reasons.) As mentioned above, players are encouraged to create new cards during game play, so if you picked up the Pies card (a picture of three pies), you might create a "+5 points per pie in hand" card and play it. Eventually game play ends when the players decide it's over, or something in the game mechanisms (perhaps a "Game Over" card) declares the end. The player with the most points wins. (Unless the game has been altered, perhaps by a "Lowest Points Wins" card....) You can see the inherent complexity of this Nomic game, in which the game mechanics change during game play.

Pies! Card3. Epilogue - in which the characters decide which of the cards created during the game should be kept for future games. This is purely arbitrary, and offers another way to "win" the game -- by adding your cards to future decks.

History and Further Reading - 1KBWC was invented by Nathan McQuillen, and spread through university towns until it was finally written up in GAMES Magazine and even an edition of Hoyle's Rules of Games. (Read more about the game's history.) Several online lists of cards are available, but beware -- many may be offensive or non-work-safe! Check out: Random Card Server from Boston, Another Random Card Server from Boston, Random Card Server from Seattle, Flickr group. Recommended reading: Bob: 1KBWC in Boston, Wikipedia page on 1KBWC.

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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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