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LuckyPenny via YouTube

The Tasty Origins of the Snoopy Sno-Cone Machine

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LuckyPenny via YouTube

It was named one of the 100 best toys in history by no less an amusement authority than TIME magazine. It’s been in near-perpetual production for nearly 40 years, an eternity in the kids’ product market. It taught children about the value and reward of hard work, because it was kind of a huge hassle to use.

It’s the Snoopy Sno-Cone Machine, the heir apparent to the Easy-Bake Oven in the culinary toy genre. Introduced by Hasbro in 1979, it’s become a perennial favorite of Peanuts collectors, ‘80s nostalgia addicts, and kids who enjoy breaking a sweat by hand-cranking their own flavored ice shavings.

The rough idea for the machine was invented by Hasbro (then known as Hassenfeld Brothers) designer Sam Speers in the early 1960s. Speers developed the Frosty Sno-Man Sno-Cone Machine, which spit out chunks of ice through Frosty’s gaping belly. After kids stuffed cubes into the top of his head and turned the hand crank on the back, they could fill up a (small) cup and flavor it with the included sweetener. Budding entrepreneurs were encouraged to charge their friends for the treat with the included sales sign.

Frosty endured well into the 1970s, at which point Hasbro took notice of the potential for a cast change. By this time, Charles Schulz’s Peanuts had become a licensing phenomenon like no other. By 1967, mini-boutique shops were set up in department stores to centralize the volume of merchandise: plush dolls, shirts, night lights, and books.

To maintain focus on his art, Schulz opened a business office strictly for business deals, the Charles Schulz Creative Development Corporation, in 1970. (While employees were expected to maintain quality control, the sheer volume of licensees meant the occasional slip: Charlie Brown sold razor blades in Germany before Schulz put an end to it.)

In both the strip and in ancillary products, it was Snoopy who took center stage. The beagle was at one point the most popular licensed character of any in the retail business, which made a revised Sno-Cone machine with the dog perched on top a can’t-miss proposition for Hasbro. Thanks to the annual airings of A Charlie Brown Christmas, the characters had always held wintry, cold connotations. So Frosty was phased out, and Snoopy was brought in.

Despite the tendency for some children to violently mash action figures in the internal ice-shaving mechanism and the labor involved in getting even a small cup of ice, the Sno-Cone Machine sold so well for the next 25 years that Hasbro CEO Al Verrecchia called it an “annuity” in 2004. “It just keeps coming off the line, year after year,” he said.

Toy and crafts company Cra-Z-Art took over the license in 2012, making a near-identical Snoopy Sno-Cone with only a few exceptions. According to Cra-Z-Art spokesperson Charlie Zakin, the hand crank is easier to turn and the unit now has a clamp to secure it to a table during operation. And yes, it still comes with the tiny red shovel.

Cra-Z-Art
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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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