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18 Famous Literary First Lines Perfectly Paired With Rap Lyrics

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Are you an aspiring rap lyricist? Have I got the tool for you! RapPad is a site where you can compose your raps with the help of rhyme lookups, syllable counters, and a library of beats. It also puts you in touch with a community for discussion, feedback, and online rap battles.

But even if you’re not planning on writing raps, it offers a unique kind of linguistic fun. With the “Generate Line” feature, you can give RapPad a line, and it will write the next line for you by pulling from a library of successful rap songs. I entered a bunch of famous first lines from literature, and got RapPad to give me back some gems. Are they literature? Are they rap? Let’s call it raperature. Or maybe literatrap? Anyway, here are 18 literary first lines paired with rap lyrics.

1. Ernest Hemingway/Wale

He was an old man who fished alone in a skiff
With an impending mixtape that only seems like a myth
(The Old Man and The Sea and “New Soul”)

2. William Butler Yeats/Run-D.M.C.

Turning and turning in the widening gyre
I won’t stop rockin’ till I retire
(“The Second Coming” and “King of Rock”)

3. Samuel Taylor Coleridge/J. Cole

In Xanadu did Kubla Khan
Pay dues like a hair salon
(“Kubla Khan”and “The Last Stretch”)

4. Founding fathers/Earl Sweatshirt

We hold these truths to be self-evident
Say hi to the Ritalin regiment
(“Declaration of Independence” and “Pigions”)

5. Gertrude Stein/Cam’ron

Rose is a rose is a rose is a rose
Sorta like drano...you know how the game goes
(“Sacred Emily” and “Spend the Night”)

6. Jane Austen/Black Cobain

It is a truth universally acknowledged
That a single man in possession of a good fortune must be in want of a wife
I’m in your head like a mnemonic device
(Pride and Prejudice and “Busy Now”)

7. Leo Tolstoy/Cam’ron

All happy families are alike
Each unhappy family is unhappy in its own way
Drinking sake on a Suzuki, we in Osaka Bay
(Anna Karenina and “Down and Out”)

8. George Orwell/Kendrick Lamar

It was a bright, cold day in April, and the clocks were striking thirteen
And if you hard then wreck your car and walk up to my crime scene
(1984 and “Ignorance is Bliss”)

9. Robert Frost/2Pac

Whose woods these are I think I know
Creep with me through that immortal flow
(“Stopping by Woods on a Snowy Evening” and “Thug Passion”)

10. Virginia Woolf/Wale

Mrs. Dalloway said she would buy the flowers herself
Fall in love with defeat, throw my endeavors on the shelf
(Mrs. Dalloway and “The Artistic Integrity”)

11. Allen Ginsberg/2Pac

I saw the best minds of my generation
Destroyed by madness, starving hysterical naked
See me and hope I'm intoxicated or slightly faded
(“Howl” and “Ain’t Hard 2 Find”)

12. Emily Dickinson/Wale

Because I could not stop for death, he kindly stopped for me
In the face of adversity, I prepared a verse to see
(“Because I Could Not Stop for Death” and “DC or Nothing”)

13. William Shakespeare/J. Cole

If music be the food of love, play on
At dinner with Hov, hoping that he pass the baton
(Twelfth Night and “Beautiful Bliss”)

14. Dylan Thomas/Ace Hood

Do not go gentle into that good night
Tell by your handbag that boy don't do you right
(“Do Not Go Gentle Into That Good Night” and “Body 2 Body”)

15. Charles Dickens/Schoolboy Q

It was the best of times, it was the worst of times
Daylight saving times all the time on this block of mines
(A Tale of Two Cities and “Live Again”)

16. Lewis Carroll/Kendrick Lamar

Twas brillig and the slythy toves
Wayne told me that, and that's just how it goes
(“Jabberwocky” and “Michael Jordan”)

17. William Blake/Lil Wayne

Tyger tyger burning bright, in the forests of the night
I’m off the hook like cordless phones, my identity so right
(“The Tyger” and “My Weezy”)

18. Walt Whitman/Big Sean

O captain, my captain, our fearful trip is done
Rolling in more green than a hole in one
(“Oh Captain! My Captain!” and “Life Should Go On”)

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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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Nick Briggs/Comic Relief
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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]

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