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The Late Movies: Kinetic Typography

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The Late Movies

Kinetic Typography (“moving text”) has been around for at least half a century — movie title sequences often feature some form of moving text, and there are tons of famous examples. The Stars Wars opening crawl is one of the most famous bits of kinetic typography ever. (And if you want to go back a bit further, Saul Bass’s work on Hitchcock’s North By Northwest is considered a seminal moment in kinetic typography history.) These days, kinetic typography has evolved into a YouTube phenomenon — there are lots of YouTube videos of famous scenes or speeches rendered using animated text. I have collected a bunch below; if you have a favorite, post it in the comments!

Also, props to fellow blogger David Israel for noticing this trend last October. (He pointed to a rather internet-famous Stephen Fry speech rendered in kinetic typography.)

Social Life, With Friends

From a poem by Kenneth Koch:

You want a social life, with friends.
A passionate love life and as well
To work hard every day. What’s true
Is of these three you may have two
And two can pay you dividends
But never may have three.

Abbot and Costello’s “Who’s on First?”

“I Don’t Know’s on third….”

Jonathan Coulton’s “Shop Vac”

“It’s loud with the shop vac on.” The creator of this video estimates it took somewhere between 500-1000 hours (!). There’s a lot going on here, and it’s all very, very good. If you’re not familiar with Coulton, check out “Shop Vac” on his site.

The Dark Knight

“It’s not about money, it’s about sending a message. Everything burns!”

V for Vendetta

“I’m merely remarking upon the paradox of asking a masked man who he is.”

The Matrix

“This…this isn’t real?”

A Clockwork Orange

“Cabbages…knickers…uh…it’s not got a beak!?”

More?

There are zillions of these. Got a favorite?

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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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