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Another other thing about SPAM

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Yesterday, we explored the origins of spam (the email annoyance); today, let's focus on the potted meat.

First, let's get the ingredients out of the way. SPAM comes, via a lot of processing, from pigs "“ it's made of chopped pork shoulder meat with ham, salt, water, sugar, and sodium nitrite. Unless, that is, it's SPAM Lite, in which case there's also some chicken in there. Or SPAM Oven Roasted Turkey, which includes (we assume) turkey and is suitable for Muslims.

Now that we know what it's made of, why? SPAM was invented in the late-Depression era, in 1937, which may explain at least some of why it seemed like a good idea: people were desperate. According to Nikita Khrushchev's book, "Khrushchev Remembers," SPAM was a godsend for another hungry group -- Russian soldiers in World War II. For a further illustration of how bad things were, British Prime Minister Margaret Thatcher "“ who we really, really can't imagine eating SPAM -- reportedly once referred to it as a "wartime delicacy."

And what does "SPAM" "“ sorry, we have to capitalize it that way, Hormel says so "“ actually stand for? Despite convincing evidence, it doesn't stand for "something posing as meat." The company's official explanation is that it's short for "spiced ham," but that wasn't always its party line. Hormel has also stated in the past that the name stands for "shoulder of pork and ham," although we can sort of understand why it wouldn't necessarily want to drive home the whole "shoulder" thing today. The name was suggested by Kenneth Daigneau, an actor who received the $100 prize in a contest Hormel had sponsored. Conveniently, he just happened to be the brother of a Hormel vice president. We think there's just a little too much mystery in this mystery meat. Then again, SPAM has sold over 6 billion cans, and what have we done lately?

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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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Name the Author Based on the Character
May 23, 2017
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