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The First Woman to Hike the Appalachian Trail Was 67 Years Old

Sometime in the 1950s, Emma Gatewood read a National Geographic article about the Appalachian Trail, which mentioned that no woman had ever completed the entire 2050-mile hike. The mother of 11, and grandmother of 23, told her daughter Rowena, “If those men can do it, I can do it.” And in 1955, at 67 years old, she did.

Gatewood, who left an abusive husband after 30 years of marriage and raised her last three children alone, was nothing if not tough. Known as “Grandma Gatewood,” she hiked the entire trail by herself, without a sleeping bag, tent or compass. According to The Washington Post, Gatewood wore out six pairs of sneakers over the course of her 146-day walk, and carried little more than a blanket and shower curtain to protect her from the elements. 

After completing the hike, she told Sports Illustrated:

"I thought it would be a nice lark. It wasn't. There were terrible blow downs, burnt-over areas that were never re-marked, gravel and sand washouts, weeds and brush to your neck, and most of the shelters were blown down, burned down or so filthy I chose to sleep out of doors. This is no trail. This is a nightmare. For some fool reason they always lead you right up over the biggest rock to the top of the biggest mountain they can find. I've seen every fire station between here and Georgia. Why, an Indian would die laughing his head off if he saw those trails. I would never have started this trip if I had known how tough it was, but I couldn't and I wouldn't quit.”

But Gatewood didn’t just hike the trail once—she returned again in 1957, becoming the first person of either gender to walk the entire trail twice. Then, in 1964, walking the trail in sections, she became the first person to complete it three times. It seemed that Gatewood had caught the hiking bug, and for the next few years, she spent most of her time outdoors, cumulatively walking thousands of miles. 

According to The Washington Post, the publicity she brought had a major impact on the future of the Appalachian Trail: “Media coverage of her hike led to repairs and restoration of the trail and may, indeed, have saved the trail from falling into ruin. It also inspired a new crop of hikers.”

To learn more about Grandma Gatewood, check out Ben Montgomery’s book Grandma Gatewood's Walk: The Inspiring Story of the Woman Who Saved the Appalachian Trail, or look out for a screening of the recently completed documentary Trail Magic, which features interviews with Gatewood’s daughter and great-granddaughter (for a list of upcoming screenings check out their Facebook page).

[h/t The Washington Post]

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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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Name the Author Based on the Character
May 23, 2017
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