Original image
Wikimedia Commons

The Bad Quartos: What Shakespeare Could’ve Been

Original image
Wikimedia Commons

It’s the best-known soliloquy in the world. Hamlet: To be or not to be! The chances are you know it already, and it’s likely that when you’re seated in the stalls of your local theater, after the stage clears and the actor playing the young prince steps into the spotlight, you’re able to mouth along with him: 

“To be or not to be. Aye, there’s the point. To die, to sleep—is that all? Aye, all.”


For a full year, from 1603 to 1604, if you went into a bookseller’s shop in London and asked for a copy of The Tragicall Historie of Hamlet, Prince of Denmark, to give the play its full name, you’d be given a bound copy of a text that had “Aye, there’s the point” as the totemic speech of the whole play. Today we call that edition a bad quarto, which was eventually replaced by a better good quarto, before the definitive edition of Shakespeare’s plays that we tend to read today—the first folio—was released in 1623 after his death.

What’s gone wrong? Where’s “Whether 'tis nobler in the mind to suffer the slings and arrows of outrageous fortune”? What could the world have been like if we hadn’t been gifted Hamlet shuffling off his mortal coil?

It’s quite simple. Just as today pirates walk into cinemas around the world and record movies from the screen to sell as knock-off DVDs before a major release, so back in the 1600s unscrupulous businessmen would walk into the pit at plays and commit an equivalent act of piracy: They’d scribble down what they could remember, go back to their printing presses and put out a version cobbled together from their notes. 

If You Know Not Me, You Know Nobody

How do we know that plays of the time were reconstructed from memory and issued by booksellers? Well, by a contemporary play, of course. Thomas Heywood was a friend and rival of Shakespeare, writing plays for Elizabethan and Jacobean audiences. One such play was If You Know Not Me, You Know Nobody, performed some time around July 1605. In the prologue to the first part, a character in the play utters the following lines: 

Your skilless tongue doth make our well-tun’d words
Jar in the Prince’s ears; and of our text
You make a wrong construction.

The key words there? “And of our text you make a wrong construction.” Heywood’s calling out a character for misconstruing his words, and directly referencing the people turning up to his plays to pirate his text. But as with all things, there are complications.

Of course, scholarship changes, and there’s no way of definitively knowing one way or the other whether a particular text is true to the one Shakespeare intended to be performed. Indeed, nowadays some scholars believe that many texts previously described as bad quartos are in fact just earlier versions of a play, and the so-called good quartos—that is, the ones taken as canon—are composites of one or more earlier versions. 

What’s in a phrase?

Romeo and Juliet is one such play where people are no longer so sure about the difference between good and bad. The supposed malignant text was first published in 1597; the good version two years later. For centuries, that was the accepted wisdom. But elements of the bad quarto have made their way into the texts in our classrooms and on our bookshelves: almost all the stage directions we see are from the 1597 quarto, which appears to have been used as an actor’s crib sheet (much abridged and paraphrased, but with the important stage movements a player would need to recall). 

Take one of Juliet’s most famous speeches: “What’s in a name?” 

The text most of us know goes as follows: 

What's Montague? it is nor hand, nor foot,
Nor arm, nor face, nor any other part
Belonging to a man. O, be some other name!
What's in a name? that which we call a rose
By any other name would smell as sweet;
So Romeo would, were he not Romeo call'd,
Retain that dear perfection which he owes
Without that title. Romeo, doff thy name,
And for that name which is no part of thee
Take all myself.

But the bad 1597 quarto is slightly shorter:

What’s Montague? It is nor hand nor foote,
Nor arme nor face, nor any other part ,
What’s in a name? That which we call a rose,
By any other name would smell as sweet.

Your host and guide

It wasn’t just actors’ versions and audience recall that created our bad quartos: Some actors, likely in Shakespeare’s company, were responsible for some of the texts. We owe the hypothesis of memorial reconstruction being the cause of so-called bad quartos to Sir Walter Wilson Greg. In 1909, aged 34, he sat down with two versions of Shakespeare’s Merry Wives of Windsor—one early quarto and the later folio edition (the terms refer to the way in which the texts were printed and bound; a folio page was 12 inches by 15 inches, a quarto 9½ inches by 12 inches). Not only did he find discrepancies between the two versions, but he felt that this version of Shakespeare’s story wasn’t dashed down by groundlings in the audience. 

Greg was sure that this quarto edition was pieced together from memory by an actor. In fact, Greg believed that he could pin down which role the actor played. To his eyes, the thespian playing the Host in the play was responsible for the bad quarto—mainly because his scenes were the fullest fleshed out. 

Canonical copies

We could well have been performing poor imitations of Shakespeare’s plays were it not for John Heminges and Henry Condell, two of Shakespeare’s friends and contemporaries. Eighteen bad copies of Shakespeare’s plays were floating around among London’s literati in the seven years after his death in 1616. Heminges and Condell wanted to change that, believing they were bringing down Shakespeare’s reputation as a playwright.

So they mustered together the best and most canonical versions of his plays they could find, often direct from the source, and put them out in a 900-page folio. That folio—with a few changes, thanks to modern scholarship—forms the basis for the texts we know and love today. And we’ve got a lot to thank Heminges and Condell for. Without them we’d be quoting “To be or not to be. Aye, there’s the point.”

Original image
iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
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!

Original image
Scientists Think They Know How Whales Got So Big
May 24, 2017
Original image

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]