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The Quick 10: 10 People with Perfect Pitch

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We talked ("talked," I suppose) last week about people with photographic memories, and in my mind, perfect pitch - knowing exactly what pitch a note is and even being able to sing it back perfectly in tune - falls somewhere in that spectrum of abilities. Here are 10 people who are (or would have been) undoubtedly quite awesome at karaoke thanks to their abilities:

1. Michael Jackson. And he has no less than Will.i.am to back him up. When he recorded a song with MJ in 2009, Will.i.am reported being both frustrated and in awe that Jackson warmed up for three hours to sing a five-minute song. "He mi mi mi'd for three hours. Perfect pitch."
2. Mariah Carey. Her mother discovered Mariah's absolute pitch when, at the age of four, Mimi could sing back exactly what she heard in any song perfectly.

3. Ella Fitzgerald. The First Lady of Song was so dead on that her band would warm up to her voice.

4. Bing Crosby.

Hoagy Carmichael joked in his autobiography that he once shared a train berth with Bing, who had an interesting sleep habit: "Bing had gone to sleep in a wink of an eyelash, snoring slightly in perfect pitch to the train whistle as we rumbled through the desert."

5. Florence Henderson actually got a college scholarship due to her pitch-perfect singing talent. She attended the American Academy of Dramatic Arts in New York.

6. Mozart. People were wowed by him when he was just a young lad "“ an anonymous person wrote this letter after hearing seven-year-old Wolfgang perform:

"I saw and heard how, when he was made to listen in another room, they would give him notes, now high, now low, not only on the pianoforte mbut on every other imaginable instrument as well, and he came out with the letter of the name of the note in an instant. Indeed, on hearing a bell toll, or a clock or even a pocket watch strike, he was able at the same moment to name the note of the bell or time piece."

7. Beethoven"¦ we think. Experts just assume he had it since he was able to compose such perfect music without hearing it.

8. Paul Shaffer. The next time you're tempted to think of him as merely David Letterman's sidekick, remember that Shaffer is a musician with quite an impressive resume "“ probably thanks in part to having absolute pitch.

9. Jimi Hendrix. There's reason to believe Hendrix had perfect pitch. One story goes that when he was first learning the guitar, he couldn't afford a tuner. Instead, he went to a music store, played the open strings, and then went home and tuned to the notes he heard.

10. Yanni. A Dateline interviewer tested his ability once by playing random keys on the piano and having Yanni identify them. He was right every time.

Julie Andrews, long rumored to have perfect pitch, has denied it on a couple of occasions.

I love to belt out tunes when I'm in the car alone, but perfect pitch? Good God, no. I don't think I even have mediocre pitch. How about you?

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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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