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The 1927 U.S. Plan to Invade Canada

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Dan Lewis runs the wildly popular daily newsletter Now I Know (“Learn Something New Every Day, By Email”). To subscribe to his daily email, click here.

The United States and Canada, by and large, have been peaceful neighbors — especially since Canada became a de facto independent nation under the British North America Act in 1867. But while the two nations are friendly and, typically, allies, things can change. And in 1927, the United States planned for just such a scenario.

At the time, Canada was still mostly under British control, and even though the United States and the United Kingdom were friendly — they fought on the same side in the Great War — things could always change. The U.S. was concerned that the UK’s imperial desires might extend back to the U.S., and the U.S. was not going to be caught unprepared. The U.S. Army developed “War Plan Red,” a comprehensive strategy to foil any British expansion into its long-former colony.

War Plan Red assumed that, in the case of war, Britain had two significant advantages. First, the British navy was a formidable force, able to control the seaways and therefore the U.S. export economy. Second, the UK controlled Canada, and could have used it as a staging ground for an invasion of the United States. The American plan was to strike Canada first.

Specifically, U.S. forces would invade Nova Scotia, hoping to take Halifax, which (American strategists assumed) would be the focal point for the British Navy in North America. If this failed, the U.S. would try to take New Brunswick, isolating Nova Scotia from the mainland. After securing that region, American forces would target Quebec City, further separating east from west; Ontario, taking control of much of Canada’s manufacturing (at the time); Winnipeg, a railway transit hub; and Vancouver, as part of a belt-and-suspenders approach toward controlling the ports. War Plan Red only laid plans for military action in the Western Hemisphere — America never intended to attack the British Isles. Rather, the plan was to hold Canada hostage, so to speak, in hopes that Britain would agree to a peace treaty to free its largest New World territory.

In 1974, the United States declassified War Plan Red. which created a minor ripple in U.S./Canadian relations — but it quickly passed.

Bonus Fact

The U.S. was not the only North American country with intracontinental war plans. In 1921 — six years before War Plan Red was drafted — Canada developed its own plan, named Defence Scheme No. 1. The scheme outlined plans for a counter-attack on the U.S. in case of an invasion from its neighbors to the south. Like War Plan Red, the plan was never put into action. Unlike War Plan Red, Scheme No. 1 was short lived — it was terminated in 1928 in an effort to foster a stronger relationship between the U.S. and Britain.

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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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