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Joseph Kittinger: The First High-Altitude Jumper

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Wikimedia Commons

Next week, “Fearless Felix” Baumgartner will attempt the highest, fastest free fall in history when he leaps out of a capsule 23 miles above Roswell, New Mexico wearing just a pressurized suit and helmet. But Baumgartner isn’t the first person to make a crazy jump like this. That distinction belongs to Joseph Kittinger, who made a series of high altitude jumps between 1959 and 1960.

In order to build space capsules that would protect humans at high altitudes, the Air Force needed to know how people would fare many miles above the Earth. So in 1957, they recruited Kittinger—a young jet pilot in the Flight Test Division of the Air Force Missile Development Center—to a pre-Space Age military project called Manhigh. He went through a series of trials, including a 24-hour claustrophobia test in the capsule and a test in the high-altitude, low-temperature test chamber, before the actual mission. On June 2, 1957, Kittinger piloted an aluminum-alloy capsule carried by a balloon to 97,000 feet, setting a balloon altitude record. But Manhigh was just the first step. In Project Excelsior, Kittinger jumped from the capsule, which hovered at the edge of space, three times over the course of two years.

Leaping into the Unknown

The first jump, in November 1959 from 76,400 feet, was almost Kittinger’s last. The sun was blinding despite the negative-104 degree temperature. As Kittinger fell, his helmet nearly lifted off his shoulders, and his pilot chute choked him into a blackout.

Thankfully, his back-up chute opened, and Kittinger survived—and, amazingly, was eager to make the next jump. It occurred just a month later, 74,700 feet above the Jornada del Muerto (which translates to “Route of the Dead Man”). The issues were ironed out, the jump was successful, and Kittinger was ready for the third and final Excelsior mission in August of 1960, from a height of 102,800 feet—more than 19 miles.

His only protection was his pressurized suit, which didn’t totally work. During the ascent, the pressurization in his right glove failed, causing his hand to swell to twice its normal size. Kittinger, however, was determined to make the jump, so he didn’t report his swollen hand until he was at altitude. Falling through 90,000 feet, the skyjumper reached the speed of 614 mph. By the time he touched down, Kittinger held records for the highest balloon ascent, highest parachute jump, longest drogue-fall and fastest speed by a human being through the atmosphere.

And when Baumgartner makes his attempt next week, Kittinger will be there: Not only did he advise Fearless Felix, he’ll serve as CapCom (Capsule Communications) for the mission, and be the only radio contact with Baumgartner during the fall.

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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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