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3 Conflicts Sparked by Food

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Food fights: They're not just for the middle school cafeteria!

1. The Pig War

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While the United States and Britain were settling their territorial disputes in the Pacific Northwest in the 19th century, a vaguely-worded treaty and a pig almost led to all-out war. The Treaty of Oregon had established the American boundary at “the middle of the channel which separates the continent from Vancouver's Island.” The hitch was that the San Juan Islands sat in between Vancouver Island and the mainland, meaning there was a channel on either side, and the treaty didn’t specify which one was the border.

The U.S. and Britain both claimed the islands as their own, and settlers from both countries began living and working on them. They coexisted well enough until June 1859, when an American farmer found a large pig rooting through his garden and eating his vegetables. This wasn’t the first time he’d seen the pig doing this, and he’d had enough, so he grabbed his gun and killed the animal.

The pig belonged to an Irishman who worked for the British trading company on the island, and the farmer approached him and offered $10 as compensation. An argument ensued, and when British authorities threatened to arrest the farmer, the American settlers asked for, and received, protection from the U.S. Army. The British responded by sending a small naval force.

Each side continued to counter the other with more military support, and by the end of the summer, the island hosted 461 American soldiers with 14 cannons and three British ships carrying 70 guns and 2140 soldiers. Both sides engaged in verbal sparring and goaded each other, but no shots were fired on either side.

When word of the situation reached Washington and London, the two governments negotiated an end to the conflict, and asked Kaiser Wilhelm of Germany to arbitrate the border dispute. The Germans sided with the Americans and established the border on the far side of the islands, giving possession of the islands to them and ending the war with only a single casualty—the poor pig.

2. The Turbot War

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In the early 1990s, Canada’s cod fishery in the Atlantic collapsed. Searching for an alternative fish that could be harvested sustainably, Canadian fisherman turned attention to Greenland halibut, sometimes known as turbot. But they weren’t alone: Foreign fleets also began fishing for turbot on the edge of Canada’s exclusive economic zone (EEZ)—the part of the ocean off a country’s coast where it has special rights to resources—sometimes crossing over into Canadian waters and taking fish illegally, or with gear banned in the country.

Worried that turbot would go the way of cod because of the foreign fishermen, the Canadian government decided to make an example of one of the ships. On March 9, 1995, boats from the Canadian coast guard, navy and Department of Fisheries and Oceans intercepted and captured a Spanish trawler operating near the edge of their waters. They impounded the boat, arrested its captain and crew, and later unveiled the boat’s illegal, small-mesh net at a press conference.

As Spain and Canada argued over the incident, fishing boats from both countries continued to fish for turbot, with Spanish naval patrol boats accompanying the Spanish trawlers for protection when they neared the edge of the EEZ. Concerned that the conflict would escalate, the European Union pressured Spain into a settlement that kept their ships well away from the EEZ and got the impounded trawler’s owner a refund for the money they paid to get it released.

3. The Egg War

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Not far off the coast of San Francisco sit the Farallon Islands, one of the largest seabird colonies in the United States. During the California Gold Rush, a group of entrepreneurs, led by a man known as Doc Robinson, looked at the bird egg-covered islands and saw their own kind of gold mine. Robinson and a few other men sailed to the islands in the early 1850s, declared themselves the owners of the land by right of possession, and started collecting and selling eggs as the Egg Company.

The Egg Company’s success eventually attracted imitators and competitors, including a company led by David Batchelder. In 1863, after already being run off by the Egg Company once before, Batchelder attempted to land on the islands with more than two dozen armed men and break Robinson’s egg monopoly by force. The Egg Company was waiting for them, though, and the two groups exchanged fire. Batchelder’s men eventually retreated, but not before one man from each side was killed and four of Batchelder’s men were wounded.

Afterwards, Batchelder was put on trial for murder and the Egg Company once again had control of the islands. Egging on the Farallons was eventually prohibited after government lighthouse keepers were attacked by eggers who thought that foghorn scared the birds away. The islands were later declared a wildlife refuge and are closed to the public today.

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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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May 23, 2017
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