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Hike the Appalachian Trail in Just Five Months

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Stretching from Georgia to Maine, the Appalachian Trail weaves through 14 states. It can take some hikers up to one year to traverse all 2,168 miles, but with these tips, you can conquer hiking’s ultimate adventure in just five months.

1. Start Saving

Nearly 75 percent of hikers who start the trail will eventually call it quits. Often, their bodies can keep going, but they run out of money. Tearing down the trail burns up to 6000 calories a day, so you’ll need plenty of cash for food. You’ll also need money for emergencies, laundry, postage, and—if you don’t feel like roughing it every mile—hotels and restaurants. A full hike usually costs $3000, not including the cost of gear, so come stocked with a healthy bank account.

2. Hit the Post Office

If you think lugging groceries to your kitchen is a pain, try hauling your food 2,000 miles through the wilderness. It’s not going to work. Luckily, the Appalachian Trail crosses a road about every four miles, so hikers pass thorough lots of small towns. Although you can stock up on food there, it usually isn’t practical. Mail drops are a better idea. Experienced hikers often send themselves care packages, filled with a week’s worth of food, to towns hundreds of miles down the trail.

3. Pace Yourself

To finish the entire trail in five months, you’ll need to hike almost 15 miles a day. Even a hardened hiker will need to take some time getting used to all that walking. In the beginning, it’s recommended you only hike eight miles a day. As your body adapts, ramp up the mileage. When you reach Virginia, where the terrain is pretty tame, hike about 20 miles a day to make up for lost miles. (Or just jog the whole thing. In 2005, a runner completed the entire trail in just 47 days!)

4. Pack Light

Even if you’re mailing yourself food, you’ll still need to fight the temptation to hit the trail with a giant pack loaded with gear. While having everything under the sun in your pack may help you feel prepared, it will slow you down in a major way. Take a long look at your pack to make sure you’re not weighing yourself down with gear you don’t need.

5. Flip the Route

Who said you had to start at the beginning of the trail? Some hikers speed up their treks and avoid the crowds by starting in the middle. They hike north from Harpers Ferry, WV to Maine. One they reach the terminus, they drive back to Harpers Ferry and hike south to Georgia. Flip-flopping is a great way to see the whole trail while starting out in easier, faster terrain.

Whether you’re switching gears or following your own passions, the all-new 2015 Subaru Outback is built to take you to the place you’ve never been. Learn more or schedule a test drive today.

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iStock // Ekaterina Minaeva
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
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]