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6 Early Theories About the Origin of Language

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How did language begin? Words don’t leave artifacts behind—writing began long after language did—so theories of language origins have generally been based on hunches. For centuries there had been so much fruitless speculation over the question of how language began that when the Paris Linguistic Society was founded in 1866, its bylaws included a ban on any discussions of it. The early theories are now referred to by the nicknames given to them by language scholars fed up with unsupportable just-so stories.

1. The bow-wow theory

The idea that speech arose from people imitating the sounds that things make: Bow-wow, moo, baa, etc. Not likely, since very few things we talk about have characteristic sounds associated with them, and very few of our words sound anything at all like what they mean.

2. The pooh-pooh theory

The idea that speech comes from the automatic vocal responses to pain, fear, surprise, or other emotions: a laugh, a shriek, a gasp. But plenty of animals make these kinds of sounds too, and they didn't end up with language.

3. The ding-dong theory

The idea that speech reflects some mystical resonance or harmony connected with things in the world. Unclear how one would investigate this.

4. The yo-he-ho theory

The idea that speech started with the rhythmic chants and grunts people used to coordinate their physical actions when they worked together. There's a pretty big difference between this kind of thing and what we do most of the time with language.

5. The ta-ta theory

The idea that speech came from the use of tongue and mouth gestures to mimic manual gestures. For example, saying ta-ta is like waving goodbye with your tongue. But most of the things we talk about do not have characteristic gestures associated with them, much less gestures you can imitate with the tongue and mouth.

6. The la-la theory

The idea that speech emerged from the sounds of inspired playfulness, love, poetic sensibility, and song. This one is lovely, and no more or less likely than any of the others.

These Days

About a century after banishment of the language origin question, scientists started to consider it again, but this time using evidence from paleontology about the likely brain and vocal tract features of early humans and hominids. Rather than speculate about which kinds of vocalizations gave rise to speech sounds, they consider which physical, cognitive, and social factors must first be in place in order for there to be language.

This doesn't make the question of how language started any easier to answer, but it does make you appreciate that whatever those necessary factors are, we got all of 'em. Phew! La la la la. Ta ta!

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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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]

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