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The Map With Only 38 States

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1. The One With Only 38 States

If George Etzel Pearcy had his way, Lynyrd Skynyrd's famous song would have been called "Sweet Home Talladego." In 1973, the California State University geography professor suggested that the U.S. should redraw its antiquated state boundaries and narrow the overall number of states to a mere thirty-eight.

Pearcy's proposed state lines were drawn in less-populated areas, isolating large cities and reducing their number within each state. He argued that if there were fewer cities vying for a state's tax dollars, more money would be available for projects that would benefit all citizens.

Because the current states were being chopped up beyond recognition, part of his plan included renaming the new states by referencing natural geologic features or the region's cultural history.

While he did have a rather staunch support network—economists, geographers, and even a few politicians argued that Pearcy's plan might be crazy enough to work—the proposal was defeated in Washington, D.C. Imagine all the work that would have to be done to enact Pearcy's plan: re-surveying the land, setting up new voter districts, new taxation infrastructure—basically starting the whole country over. It's easy to see why the government balked.

The map above was published in 1973. Oddly, it doesn't show any city locations to help illustrate Pearcy's argument. At this point, I should tell you that I make maps for a living. So I did my best to replicate Pearcy's map using population data from the 2000 census to show current high population cities and where they would fall within the new states. Here's what I came up with:

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As you can see, many of the new states contain a small number of major metropolitan areas, and the problem of dual-state cities has been solved. While Pearcy's proposal might have been a logistical nightmare to make a reality, that doesn't necessarily mean it was a bad idea.

2. The One Where Greenland & Africa are the Same Size

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In 1973, Arno Peters, a German filmmaker and journalist, called a press conference to denounce the widely accepted map of the world known as the "Mercator Map" (above). Peters' position was that the Mercator Projection—a cylindrical projection first developed in 1569 by Flemish cartographer Gerardus Mercator—was not only inaccurate, but downright racist. Peters pointed out that the Mercator map has a distortion in the northern hemisphere, making North American and Eurasian countries appear much larger than they actually are. For example, Greenland and Africa are shown as roughly the same size, although in reality Africa is about fourteen times larger. In contrast, the regions along the equator—Africa, India, and South America, to name a few—appear smaller, especially when seen next to the distorted northern half of the map. It was Peters' belief that this error led many in the developed world to ignore the struggles of the larger, poorer nations near the equator.

Of course Peters had a suggestion on how to fix this problem—his own map. The Peters Projection map, which claimed to show the world in a more accurate, equal-area fashion.

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Because Peters' map showed the size of developing nations more accurately, charitable organizations that worked in those regions quickly gave him their endorsement. Eventually his map became so well received that some were calling for an all-out ban on the Mercator map, believing it to be an outmoded symbol of colonialism.

The thing is, cartographers agreed that the Mercator map was outdated, inaccurate, and wasn't the best way to represent the world's landmasses. They'd been calling for the use of a new projection since the 1940s.

One of the reasons experts wanted to move away from the Mercator was because of the distortion. However, they also understood that it was distorted for good reason. The Mercator map was intended as a navigational tool for European mariners, who could draw a straight line from Point A to Point B and find their bearings with little trouble. Because it was made for European navigators, it was actually helpful to show Europe larger than it really was. It wasn't a political statement, but a decision made purely for ease-of-use.

However, the biggest insult to cartographers was the Peters projection itself. Peters claimed to have created the projection, when in fact, it was essentially the same thing as devised in 1855 by a cartographer named James Gall. Many have recognized this similarity and now you'll often see Peters' map called "The Gall-Peters Projection."

Today, the controversy is mostly dead. Both projections are seen as flawed and have fallen into disuse as more accurate maps have been developed. In classrooms now, you're more likely to see the Robinson Projection or the Winkel Tripel Projection. The Gall-Peters map is still favored by some organizations, though many map publishers don't even produce it anymore. And despite the controversy, the Mercator projection is still one of the most widely used navigational tools in the world—it's the primary projection for Google Maps.

3. The One that Claims the Chinese Got Here First

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It seems everyone wants to ruin Christopher Columbus' biggest claim to fame. This time it's a Chinese map that is threatening to rewrite history.

Purchased from a Shanghai dealer in 2001 by Liu Gang for a mere $500, the map shows the world—including a well-developed picture of North and South America. While text on the map indicates it was drawn in 1763, it claims to be a copy of another map drawn in 1418. The original map was cited as belonging to the great Chinese explorer, Zheng He, whose known travels include India and eastern Africa. However, thanks to numerous errors and anachronisms, the map's authenticity has been called into question.

For example, California is shown as an island, which is a famous mistake made by European maps of the 17th Century. Furthermore, the detailed representation of river systems would be difficult to attain by such large ships as those used by Zheng He, whose fleets sometimes carried up to 28,000 men. Finally, the Chinese did not have an understanding of how to create a map projection at that time, a skill necessary to translate a 3-D globe to a 2-D map. In short, they didn't even know how to make this map when it was supposed to have been drawn.

The annotations on the map also seem to be largely erroneous. A perfect example is a note stating of Eastern Europe: "The people here all worship God (shang-di) and their religion is called "˜Jing.'" However, according to noted professor and map critic, Dr. Geoff Wade, the term "shang-di" for the Christian God was not introduced until the late 16th Century. Perhaps most damaging are the many references to the "Great Qing Ocean" regarding the waters off China. Unfortunately, the Qing Dynasty began in 1644—more than 200 years after the original map was supposed to have been made.

Based upon this evidence, it seems likely that the Chinese map of the New World is the product of a 1763 cartographer using the terminology of his time, combined with data from European maps. Therefore, while Zheng He can definitely claim to be a great explorer, it is doubtful he ever made it to America.

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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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May 23, 2017
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