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. 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.

Artificial intelligence (AI) is all around us. Unlike the Terminator robots, AI exists in subtle ways, embedded in our daily activities thanks to the rise of big data and machine learning. When Facebook tries to connect users with new friends or businesses, Netflix suggests a new TV series to watch, or Amazon recommends a book, these are all examples of AI presented to people via machine learning – a statistical method that finds patterns and makes predictions based on vast volumes of data. After years of hype, most organisations now have a solid understanding of the potential of big data. In fact, the majority of them are actively pursuing means to capitalise on all the information they capture.

One key buzzword these days is "algorithm," which technically means any computational formula but which has come to mean a formula that predicts our behavior. Amazon and Netflix have algorithms that predict what books a user is likely to want to read or what movies and TV shows he or she is likely to want to watch. Facebook has an algorithm that predicts the news a user is likely to want. Dating sites like Match.com and OkCupid use algorithms to predict with whom we would fall in love. Google, with the most famous algorithm of all, predicts what we want when we type a search term.

It's hard to find someone who isn't a fan of "Game of Thrones." The TV show, which returns Sunday, has reached peaks of popularity that few shows do, and draws in fans of all shapes and sizes -- even computers. Maluuba, a Canadian startup, posted a YouTube video on Friday showing its artificial-intelligence software reading the synopsis for the fifth season of "Game of Thrones'" and immediately knowing all of the show's plot lines. It's the equivalent to a human, let's call him "John" for this example, who knows nothing about the show, has never seen it, takes one look at a Wikipedia page and instantaneously knows everything that's happening. "Who stabbed Jon Snow?" the Maluuba engineer asks the AI software.

A trip to Iceland wouldn't be complete without a dip in the Blue Lagoon, a man-made geothermal pool on Reykjanes peninsula. A trip to Iceland wouldn't be complete without a dip in the Blue Lagoon, a man-made geothermal pool on Reykjanes peninsula. 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. You have storms, you have darkness, but the pool is a place to find yourself again.

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Years ago when I first developed a website that allows for an easy access and reviews of scientific literature one of my long-term goals was to create recommendation system that would actually be useful for the users of this vast literature. Since my primary background is in Physics and not computer science or one of the related fields, this goal had only remained a dream. The technical difficulties seemed overwhelming and daunting, and I did not have either the time or the resources to invest in all the necessary tools and learning. However, it seems that in the intervening years there has been a great progress in developing a set of "consumer" level tools that are relatively easy to implement. "Practical Machine Learning" is a short e-book intended to introduce the readers to some of the latest machine learning tools and packages.

A trip to Iceland wouldn't be complete without a dip in the Blue Lagoon, a man-made geothermal pool on Reykjanes peninsula. A trip to Iceland wouldn't be complete without a dip in the Blue Lagoon, a man-made geothermal pool on Reykjanes peninsula. 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. You have storms, you have darkness, but the pool is a place to find yourself again.

The ability of machines to accurately comprehend written language took another step forward thanks, in part, to Harry Potter. What could this tale provide to the field of artificial intelligence? Artificial language comprehension may be improved by reading Harry Potter, if the results of a new study are developed. Maluuba is a Canadian company centered on teaching machines how to learn, and researchers there now utilize the works of J.K. Rowling. Harry Potter and the Philosopher's Stone was one of the hundreds of books studied by machines designed to study artificial intelligence.

More and more of our experience online is personalized. Search engines, news outlets and social media sites have become quite smart at giving us what we want. Perhaps Ali, one of the hundreds of people I've interviewed about our emotional attachment to technology, put it best: "Netflix's recommendations have become so right for me that even though I know it's an algorithm, it feels like a friend." Personalization algorithms can shape what you discover, where you focus attention, and even who you interact with online. When these algorithms work well, they can feel like a friend. At the same time, personalization doesn't feel all that personal. There can be an uncomfortable disconnect when we see an ad that doesn't match our expectations. When personalization tracks too closely to interests that we've expressed, it can seem creepy. Personalization can create a filter bubble1 by showing us more of what we've clicked on before, rather than exposing us to new people or ideas.