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9 Iconic VMA Performances

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Getty Images

MTV might not play music videos too much anymore, but at last night’s Video Music Awards, music was front and center in a series of buzzworthy performances: Lady Gaga changed costumes XX times while singing her new single, “Applause”; NSYNC reunited; Katy Perry boxed; and Miley was just being Miley, twerking her way across the stage in a performance of questionable taste. Here are a few other iconic performances from 26 years of VMAs.

Madonna, “Like a Virgin”

In what was then a controversial and envelope-pushing performance, Madonna performed her breakout hit while wearing a wedding dress/bustier and rolling around the stage at the very first Video Music Awards in 1984. She later said that the moment was unplanned—and she had lost her shoe and was just trying to retrieve it.

Nirvana, “Lithium”

At the 1992 VMAs, Cobain and company went off script, starting to perform another of their songs before launching into “Lithium.” Toward the end of the performance, bassist Krist Novoselic threw his guitar into the air; it came down and hit him on the head, and he stumbled offstage. Meanwhile, Cobain destroyed the equipment while drummer Dave Grohl mocked Guns ‘n Roses singer Axl Rose.

Michael Jackson, Medley

The King of Pop brought out all of his signature dance moves—and Slash!—for this 15-minute medley of his hits from the 1995 VMAs.

Oasis, “Champagne Supernova”

It’s pretty amazing that famously feuding brothers Noel and Liam Gallagher could hold it together for this performance at the 1996 VMAs.

P. Diddy, “I’ll Be Missing You”

For the performance of this tribute to Notorious BIG at the 1997 VMAs, Diddy (or was it Puff Daddy?) recruited Faith Evans, Sting, and a choir.

Britney Spears, “I’m A Slave 4 U”

The previous year, Spears got tongues wagging when she performed a cover of the Rolling Stones’ “I Can’t Get No Satisfaction” and her own song, “Oops! I Did it Again” in a sparkly, flesh colored ensemble. Her performance of “I’m A Slave 4 U” at the 2011 VMAs was controversial for another reason: PETA decried her use of live animals as props.

R. Kelly, “Trapped in the Closet”

The singer brought his oddly compelling musical soap opera to the VMAs in 2005.

Pink, “Sober”

Singing live and swinging on the trapeze are terrifying enough on their own. Combine them, and you have to wonder how Pink pulled off this unforgettable performance from the 2009 VMAs. (The next year, she would put together a similarly stunning aerial routine for her Grammys performance of “Glitter in the Air.”)

Beyonce, “Love on Top”

Shortly before this joyous performance at the 2011 VMAs, Jay Z’s lady announced she was pregnant.

Obviously, these videos just scratch the surface of memorable VMA performances. Let us know your favorites in the comments!

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iStock // Ekaterina Minaeva
technology
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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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Stephen Missal
crime
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New Evidence Emerges in Norway’s Most Famous Unsolved Murder Case
May 22, 2017
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A 2016 sketch by a forensic artist of the Isdal Woman
Stephen Missal

For almost 50 years, Norwegian investigators have been baffled by the case of the “Isdal Woman,” whose burned corpse was found in a valley outside the city of Bergen in 1970. Most of her face and hair had been burned off and the labels in her clothes had been removed. The police investigation eventually led to a pair of suitcases stuffed with wigs and the discovery that the woman had stayed at numerous hotels around Norway under different aliases. Still, the police eventually ruled it a suicide.

Almost five decades later, the Norwegian public broadcaster NRK has launched a new investigation into the case, working with police to help track down her identity. And it is already yielding results. The BBC reports that forensic analysis of the woman’s teeth show that she was from a region along the French-German border.

In 1970, hikers discovered the Isdal Woman’s body, burned and lying on a remote slope surrounded by an umbrella, melted plastic bottles, what may have been a passport cover, and more. Her clothes and possessions were scraped clean of any kind of identifying marks or labels. Later, the police found that she left two suitcases at the Bergen train station, containing sunglasses with her fingerprints on the lenses, a hairbrush, a prescription bottle of eczema cream, several wigs, and glasses with clear lenses. Again, all labels and other identifying marks had been removed, even from the prescription cream. A notepad found inside was filled with handwritten letters that looked like a code. A shopping bag led police to a shoe store, where, finally, an employee remembered selling rubber boots just like the ones found on the woman’s body.

Eventually, the police discovered that she had stayed in different hotels all over the country under different names, which would have required passports under several different aliases. This strongly suggests that she was a spy. Though she was both burned alive and had a stomach full of undigested sleeping pills, the police eventually ruled the death a suicide, unable to track down any evidence that they could tie to her murder.

But some of the forensic data that can help solve her case still exists. The Isdal Woman’s jaw was preserved in a forensic archive, allowing researchers from the University of Canberra in Australia to use isotopic analysis to figure out where she came from, based on the chemical traces left on her teeth while she was growing up. It’s the first time this technique has been used in a Norwegian criminal investigation.

The isotopic analysis was so effective that the researchers can tell that she probably grew up in eastern or central Europe, then moved west toward France during her adolescence, possibly just before or during World War II. Previous studies of her handwriting have indicated that she learned to write in France or in another French-speaking country.

Narrowing down the woman’s origins to such a specific region could help find someone who knew her, or reports of missing women who matched her description. The case is still a long way from solved, but the search is now much narrower than it had been in the mystery's long history.

[h/t BBC]

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