CLOSE
Original image
HBO

Learn the Art of Language Creation From the Guy Who Created the Game of Thrones Languages

Original image
HBO

When David Peterson was in middle school, he had no particular interest in language and never dreamed he would one day create languages for wildly successful TV shows—but when he watched Return of the Jedi he noticed that something was not quite right about the scene where Princess Leia, disguised as a bounty hunter, speaks in an unknown language to Jabba the Hutt. She basically repeats what sounds like yaté and yotó a few times, and that somehow, according to the subtitles, stands for both “I have come for the bounty on this Wookie,” “50,000, no less,” and a few other things. That didn't seem like something a language should do. Peterson didn’t know it at the time, but this sense of unease about what he was seeing was an early glimmer of the particular artistic sensibility of the language inventor, the ability to distinguish an intelligent, well-crafted creation, from a lazy jumble of nonsense syllables.

He eventually developed an intense love of language, studying several of them and creating even more. His professional language creations (heard in Game of Thrones, Defiance, and Thor: The Dark World) as well as the personal projects he has been working on since 2000 are of the intelligent and well-crafted type. They have complicated, learnable grammars, extensive vocabularies, and features consistent with fully-imagined cultural practices. In an era where we can watch, re-watch, and pick apart on the internet to our heart’s content, fans demand no less. Yaté yotó just doesn’t cut it anymore.

But what makes a good constructed language (or conlang, for those in the know)? And for those who want to try their hand at language creation for their fantasy novel, secret club, thought experiment, or plain personal enjoyment, where is a good place to begin? Since the early 90s, conlangers have been sharing their ideas and strategies and evaluating each other’s work on listservs and forums and sometimes even at in-person conferences. A sort of technique and artistic standard has emerged, but it can be difficult for a newbie to figure out what it is. Peterson asks,

Where is the collected wisdom of the early conlang community? Why is it not written down somewhere that if you’re creating a naturalistic ergative language, it will most likely be split ergative, and that those splits will happen in one of a small number of likely places in the grammar? This is something that every conlanger knows or eventually learns, but the information is only passed via word of mouth—it’s like we’re living in the 1300s, but we also have the internet and indoor plumbing!

If you are a budding language inventor now thinking “yikes! What’s an ergative language?” Peterson has written the book for you. Full of examples from both natural and constructed languages, The Art of Language Invention will take new conlangers through “the nuts and bolts of language creation so they can focus on the more important question: What do I want to say with this new language that I can’t say in my native language —or any other language that currently exists?”

Even if you have no plans to build your own language, the book is a lively introduction to the important concepts of linguistics, from consonants and vowels, to stress and tone, to verb agreement and case, to how grammar evolves over time. There’s also a section on writing systems with some beautiful examples of invented scripts. And if you’re a fan of HBO’s Game of Thrones or Syfy’s Defiance the “case studies” of the languages Peterson created for those shows will give you a deeper appreciation for just how far we’ve come from the days of yaté yotó.

Read some fun facts about Dothraki or Valyrian, and if you want to know more, check out The Art of Language Invention.

Original image
iStock // Ekaterina Minaeva
arrow
technology
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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
iStock
arrow
technology
Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
Original image
iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

SECTIONS
BIG QUESTIONS
arrow
BIG QUESTIONS
WEATHER WATCH
BE THE CHANGE
JOB SECRETS
QUIZZES
WORLD WAR 1
SMART SHOPPING
STONES, BONES, & WRECKS
#TBT
THE PRESIDENTS
WORDS
RETROBITUARIES