Original image

America's Plan to Invade Everyone

Original image

Before that whole treason thing sullied his historical legacy, Benedict Arnold led an invasion force into Canada during the American Revolution. He failed miserably.

In 1839, a cow (American), a pig (Canadian) and a handful of militiamen (American) were injured in the Aroostook War, a short and unofficial conflict between Maine and Canada over a border dispute.

Invading Canada, it seems, is as American as apple pie. The only problem is that we suck at it. Well, traitors and lumberjacks do, anyway. If you want a job done right, you have to go to the big boys, but surely the federal government wouldn't ever dream of invading friendly, free-trading Canada. Would they?

Turns out, the United States government did have a plan to invade Canada. "Joint Army and Navy Basic War Plan - Red" is a 94-page, step-by-step plan to invade, capture and annex the land of maple syrup.

us_canada_flags.jpgThe plan was one of a handful of color-coded war plans developed as strategies for various hypothetical war scenarios by a War Department with too much time on its hands in the 1920s and 30s. In War Plan Red, the government imagined a conflict between the United States and England over international trade, with Canada, still a semi-independent British dominion at the time, as the launching point for English ground attacks.

Plan Red outlines a series of possible campaigns aimed at capturing key ports, cities and railroad lines before British reinforcements could arrive, preventing them from using Canadian resources and infrastructure to their advantage.

While a joint Army-Navy overseas force captured the port city of Halifax, cutting Canada off from the Atlantic, the U.S. Army would attack on three fronts, advancing from North Dakota, Vermont, and the upper Midwest to capture Winnipeg, Montreal and the nickel mines of Ontario, respectively. American forces were also supposed to capture British colonies in the Caribbean to defend the country from an attack from the south.

The Canadian Response

busterbrown.jpgThose wily Canucks were one step ahead of us, though. Colonel James "Buster" Sutherland Brown developed a plan called Defence Scheme No. 1 a full nine years before War Plan Red was drawn up. Buster's plan called for Canadian troops to attack and occupy Seattle, Portland, Minneapolis and St. Paul and Albany in order to divert American forces to the flanks long enough for English reinforcements to arrive. This isn't a bad plan considering the Canadian department responsible for war planning had an annual budget of $1,200, and Buster did most of his reconnaissance by driving across the border, taking photos and grabbing free maps at gas stations.

The hypothetical war, of course, never happened. Canada and the United States became allies during World War II, and partners in NATO and NAFTA. Today, the two countries share the world's longest demilitarized border, which has the world's largest number of legal crossings. War Plan Red and its color-coded siblings were withdrawn in 1939 and declassified in 1974. They now reside in the National Archives, where foreign spies can photocopy them for 15 cents a page (War Plan Red is online, too). And everyone lived happily ever after.

And those other color plans? Well, here are my favorites:

War Plan Citron: an invasion of Brazil

War Plan Emerald: intervention in Ireland in conjunction with War Plan Red

War Plan Green: war with Mexico in order to establish a pro-American government

War Plan Indigo: an invasion of Iceland (in 1941, parts of the plan were actually used during Battle of the Atlantic when the US relieved British occupation forces)

War Plan Lemon: an invasion of Portugal

War Plan White: plan for dealing with civil disturbances cause by Communist insurgents

Original image
iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
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!

Original image
Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
Original image
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]