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How To Revive the Dead

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If you're like us, you are so over bobbing for apples. Instead, why not try having some real fun this Halloween? We suggest scaring small children, egging your boss' house, or bringing deceased creatures back to the land of the living.

1 extinct species (preferably herbivorous, just in case)
Its modern, surviving relatives
20-odd years of careful breeding

Ever since things went horribly wrong in Jurassic Park, mankind has carefully pondered the ethical and biological dilemmas of reviving extinct species and thought, "Hey, I could do better than that." And, sure enough, over the past 10 years, Michael Crichton-esque cloning experiments have popped up like gophers all around the world. Currently, teams of researchers are attempting to replicate the Tasmanian Thylacine (a dog-like marsupial) and the Spanish Bucardo Mountain Goat (the last of which was smushed by a falling tree in 2000). There was even a failed attempt to resurrect the Wooly Mammoth.

However, there are several problems with these experiments. For one thing, ancient (read: cool) animals like the mammoth don't have enough intact DNA to clone, so you're pretty much limited to saving the Bucardo goats of the world. For another, clones are notoriously unstable. In 2000 an Iowan cow successfully gave birth to the clone of an endangered Asian Guar Ox—only to see the calf die from illness a few days later. And clones, being clones, can't breed with themselves; so you can't really revive a whole species, just an individual. But, a group of dedicated scientists in South Africa may have found a way around these dead ends—at least for one long-gone subspecies.

The quagga—an animal resembling a cross between a zebra and a horse—died out in the late 1800s after several decades of over-zealous hunting. Long thought to be a distinct species, the quagga was outed as a cousin of the Plains Zebra by taxidermist Reinhold Rau, who tested fragments of quagga DNA in the early 1980s. Rau realized that if the quagga had originally evolved from the Plains Zebra naturally, he might be able to replicate the subspecies through selective breeding today. In 1987, he launched the Quagga Project, an organization that tracked down Plains Zebras with quagga-like traits and began breeding the animals in the Karoo National Park, the quagga's ancestral home. By 2005, the Project had succeeded in producing Henry, a light-brown baby zebra whose stripes fade out around the middle of his body.

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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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