#NPRreads: 3 Stories To Soak Up This Weekend
#NPRreads is a weekly feature on Twitter and on The Two-Way. The premise is simple: Correspondents, editors and producers from our newsroom share the pieces that have kept them reading, using the #NPRreads hashtag. Each weekend, we highlight some of the best stories.
From engagement editor Carol Ritchie:
You have storms, you have darkness, but the pool is a place to find yourself again. Iceland’s Water Cure https://t.co/GrrOWlfN31 #NPRreads— Carol Ritchie (@LCarolRitchie) April 19, 2016
The irony was irresistible: The same week NPR went to Greenland to look at high suicide rates, The New York Times Magazine went to Greenland's neighbor, Iceland — but for a story on high rates of happiness and how that contentedness is partly powered by the country's vulcanic geology.
Iceland came in second on a list of world's happiest countries, despite its arctic weather. It has no public plazas or pubs, but it does have public pools, heated geothermically to hot-tub temperatures. Every town and city has one; some have many. The famously reserved Icelandic people live most of their days separated from fellow Icelanders by layers of down and wool and darkness, but they come together to forge a connection in the pool. "In the hot tub, you must interact," the mayor of Raykjavik told writer Dan Kois. "There's nothing else to do."
In Greenland, native communities have lost village livelihoods and been moved to cities, where they lost their sense of community, self and meaning. Iceland has a water cure. "It's not exactly like you're happy," said a pool dipper. "It's that you know how to be in the swimming pool."
From science desk reporter Angus Chen:
How did our languages evolve and gain complexity? New sign languages may offer answers #nprreads https://t.co/twf77dC29z @NewsfromScience— Angus Rohan Chen (@angRchen) April 22, 2016
This story by journalist Catherine Matacic for Scienceshows how new sign languages weave new words and grammar into their structure over time. It's exciting to read about the progression, in this case, of Israeli Sign Language and to see how other languages have evolved in the same way. I like imagining a hypothetical signer first learning to wave her dominant hand for basic signs, then tilting her head for a question, then squinting out a relative clause, and swaying her body to sign "by the way."
The questions underneath this story are even more intriguing to me, and Matacic brings some of them up. Did the first human languages build from the ground up in the same way, starting with simple nouns and verbs and then on to topics and questions?
But I also wonder what it's like to live without a way to say "about." How do you make a word for something that has no word and be understood? I want to find the first person to come up with the first "about" and ask her why she chose to move her head in that particular way. What was it like? Was it a relief?
From digital editor Steve Mullis:
Inside Facebook’s biggest artificial intelligence project ever via @FortuneMagazine https://t.co/i8mdkxsGx6 #NPRreads— Steve Mullis (Semi-Pro Social Distancer) (@stevemullis) April 18, 2016
The ubiquity and sheer size of Facebook is not really a story anymore. Whether or not you like the social media giant doesn't detract from the fact that in just over a decade it has become a massive entity: now serving more than 1.5 billion users. What is equally parts fascinating and terrifying is how they actually manage to deal with the likes, photos and interactions of about one-fifth of the world's population. The answer, as Fortune magazine explains, is machine learning and artificial intelligence. Facebook's machine learning platform – called FBLearner Flow – basically studies the habits and data of the billion+ users and uses that data to feed us posts, ads and everything else and also fills the workload gap that even Facebook's 13,000 employees can't handle. The computational weight of that is stunning. Now, the terrifying part:
"The company's use of machine learning has since grown more advanced. ... At the product's launch, Facebook said that its image recognition models could recognize human faces with 98% accuracy, even if they weren't directly facing the camera. It also said it could identify a person in one picture out of 800 million in less than five seconds."
I don't know where I will be when Facebook's AI becomes self-aware, but Facebook certainly will.
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