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Shorts That Don't Suck, Vol IV: Music Video Edition

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For our fourth installment of "shorts that don't suck," we turn to an art form which many have declared dead or dying: the music video. It seems that the age of the internet has done something drastic not only to the business of music, whose coffers have been drained by file-sharing and music-pirating, but to the business of the music video, which goes through every crisis that its parent business goes through. The main result of this has been that music video budgets have shrunk -- from the millions to the hundreds of thousands, to in many case the just-thousands -- and the way most people see them has changed. As you're probably aware, there aren't a whole lot of music videos on MTV anymore; YouTube is now one of the industry's main distribution platforms, and she is a fickle beast, indeed. It's not the million-dollar Paris Hilton music videos that get the most views these days; it's those silly OK Go people jumping around on their treadmills (34 million views) -- a video that probably cost a few hundred dollars to shoot.

Weezer: "Pork and Beans"
Capitalizing brilliantly on this new model of success, ever-popular Weezer made their new video not only for the internet, but starring the internet. (Didn't I just blog about internet memes?) Keep an eye out for the Numa Numa guy, Chris Crocker, some Mentos-'n'-Coke experiements, and countless more nerdy net in-jokes:

Emily Haines: "Dr. Blind"
This simple but haunting video for Emily Haines (of the band Metric) uses a bit of special effects, but not in a way that seems overtly music video-ish. There are no black hole suns expanding over cartoonish skies, no crazy lights, no guitar-wielding rock stars floating through digital universes. Just a girl who goes to pick up her prescription at a Wal-Mart pharmacy, and has a little bit of a freak-out.

The Arcade Fire: "Black Mirror"
If F. W. Murnau had ever directed music videos, they would've looked like this. It uses more digital tricks than you can shake a keyboard at, but makes every one of them look like an old-school silent era technique. Unlike the other videos in this post, it certainly wasn't cheap to make -- but when you're a band at the top of the (indie rock) pops, you can spend a little coin on your videos. Strange and beautiful, not to mention one of my favorite songs by one of my favorite bands, I couldn't help but include it.

Eric Avery: "All Remote and No Control"
I don't know much about Eric Avery (formerly of Jane's Addiction) but the director, Andy Huang, is a friend of mine, and I think the visuals he created for this video are stunning. Not to mention he basically made this in his bedroom, on a computer less powerful than the one I blog with. Hats off, Andy -- those people growing roots out of their faces are going to give me nightmares for years to come.

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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]