Original image
Ben Kirchner

The Woman Who Struck Out the Babe

Original image
Ben Kirchner

Joe England loved wacky promotions. The owner of the AA Chattanooga Lookouts, Engel once traded a player for a turkey and stocked the grandstands with singing canaries. But in March 1931, he pulled his riskiest stunt yet—he signed a girl.

Jackie Mitchell was only 17 when she signed up to play pro ball. A southpaw from Tennessee, Mitchell had learned how to throw a nasty sinker from her neighbor, future Hall of Famer Dazzy Vance. But that didn’t matter to Engel: He was just curious if a female on the mound could boost ticket sales.

That April, he got his answer. The stands were packed for an exhibition game against the New York Yankees. And when the Lookouts’ starting pitcher was benched in the first inning, the fans got what they came for. Mitchell hit the mound—and Babe Ruth stared her down from the batter’s box.

Mitchell’s first pitch missed the mark, but her second was a masterful sinker. Ruth hacked—and missed. The crowd went nuts. When Ruth swung and missed a second time, he asked the umpire to check if the ball had been doctored. It hadn’t. When Mitchell’s fourth pitch nipped the corner of the plate, the ump called strike three. The crowd erupted. Ruth threw his bat, kicked up dirt, and cussed out the umpire before his teammates had to drag him to the dugout.

But Mitchell was just getting warmed up. When Lou Gehrig stepped to the plate, Mitchell struck him out on three straight pitches. The crowd gave her a standing ovation. The Yankees ultimately won 14–4, but Mitchell stole the headlines. “The prospect grows gloomier for misogynists,” a New York Times editorial lamented. Today, some historians believe Ruth and Gehrig whiffed on purpose—and it’s possible they did. But there’s no question that Mitchell had a killer arm. After a short tenure with the Lookouts, she spent five years playing for the semipro House of David club. In 1933, she got another chance to square off against the pros, pitching against the St. Louis Cardinals. This time around, she came home with a win.

This story originally appeared in an issue of mental_floss magazine. Subscribe here.

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
Name the Author Based on the Character
May 23, 2017
Original image