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Pop annotations: "U Can't Shine Like Me" by Lil' Romeo (feat. the Old Prospector)

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This week, Floss' senior annotator warms the bench while the Old Prospector tries his hand at a little pop cultural deconstruction. From his unhealthy obsession with precious metals to his impenetrably filth-laden colloquialisms, who better to tackle an anachronistic annotation of ghetto ingenue Li'l Romeo's new single? Let's get it started!

Are you serious, man?
They must not know who I be!
We got tha hood pressure in tha buildin'!

Are ya pullin' my donkey's tail?
They done woke up tha wrong doggie
It's hog-killin' time at the hookshop, sakes alive!

You can't shine like me
You know, ride like me
Pull dimes like me if you ain't from tha streets
I'm a hood star, you know who I'm is
I rock big ice, you can't live how I live!

Yer mail-order cowboys can't hold a candle
Can't grab the nubbin like me
Lasso the buckle bunnies if ya don't hail from tha tenderloin
I'm a celebrated mudsill of the first water, acknowledge the corn
I boast ducky notions, I'm fine as cream gravy

10 karats on my earlobes
BBS on my wrist
20 karats on my neck
While y'all slidin' in tha little bit '06 vette
I'm waitin' on tha runway for my G4 jet

Got much specie "˜neath mah hat (these ain't prarie-pancakes)
Bonanza "˜round my hand
Like Neil Young, I'm afta the gold rush
Though y'all squeeze the biscuit on that crowbait jackass
I hang fire on the trail for mah widowmaker

I'm ahead of tha game
You see you boys got next
Did a lil' bit of actin' just ta stack a few chips
I ain't gotta remind y'all how tha game go
I'm tha youngest widda clothin' line, first widda TV show

Won't catch me suckin' hind tit
Cool yer heels, you shave-tails'll soon absquatulate
Strung a few whizzers just to earn ma grubstake
But I needn't stretch the blanket for ya
I'm a button wit' a concern o' bib and tucker, big bug wit' a bill show

I do it big, I guess you say I'm jus' the best at it
Made a mil early, man, I done learned my mathematics
Boy stop stuntin', if I wanted I could have your chick
Don't get it twisted, Richey Rich, so gutta!
You'z a momma's boy, I'm tha son of a hustla!

I'm the biggest toad in the puddle; I'm the rip-snortin' sockdolager
Got my poke o' plunder as a shaver, twigged tha numerical palaver
Enough ballyhoo, pilgrim, don'cha kick up a row; should I take a notion I could cut a rusty wit' yer soiled dove!
Don't get it honey-fuggled, I'm a dude what's hit pay-dirt
Yer a tenderfoot desperado, I'm a bunko artist's guttersnipe!

See me, I'm so fly I'm diff'rent from them otha brothas
Only 16 and I don't live at home wit motha
Kids poppin' they grillz in, they think they gettin' tougher
They tryna take off they shirts, think they gettin' buffa
I'm benchin 180 and that just wit one muscle

Lookee here, I'm a huckleberry 'bove a persimmon
Between hay and grass but don't bunkroll with momma
Whipper-snappers think they been through tha mill
They strip off their long johns, fancy they cut a swell
But I c'n take a rag off the bush six ways from Hell

I see dudes tryna act like me, be like me, dogg even dress like me
No, ya not me and there won't be anotha
So many rocks on my hand I'm a certified hustla
Got a wizard on ya hands, kinda like Ron Butler

Greenhorns playin' to tha gallery, even wear my union-suit and hat
Horsefeathers! You'll catch a weasel asleep "˜fore you cap my climax
Many nuggets in the sluice box, I'm a jo-fired hornswoggla'
Hot as a whorehouse on nickel night, I'm a dandy conjura'

I jus' learn from da best
Hoodstar down South wit a mansion on the West, yes
I got a Bentley that I don't even drive
And I bought a Phantom just to see how it ride!

I suckled from the boss teat
Cattle baron tenderfeet wit' a lean-to on the rollin' plain
Got a broomtailed mare I don't even ride, bayin'
An' I dickered a bangtail just to burn the breeze, sayin'
Can I get two whoops an' a holla?

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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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Stephen Missal
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]