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"But the answer to how he was chosen is actually an algorithm, a computer program that crunched through reams of data, looking at how much each passenger had paid for their ticket, what time they checked in, how often they flew on United, and whether they were part of a rewards program. The algorithm likely determined that Dr. Dao was one of the least valuable customers on the flight at the time."

""No-limit Texas Hold'em is a game of incomplete information where the AI must infer a human player's intentions and then act in ways that incorporate both the direct odds of winning and bluffing behaviour to try to fool the other player." The designers said their computer didn't "bluff" the human players. But by learning from its mistakes and practising its moves at night between games, the AI was working out how to defeat its human opponents."

"Brain scans, however, are quite telling, especially when analyzed with an algorithm, Brent and his colleagues discovered. "We're trying to figure out what's going on in somebody's brain when they're thinking about suicide," says Brent.  These scans, taken using fMRI, or functional magnetic resonance imaging, show that strong words such as 'death,' 'trouble,' 'carefree,' and 'praise,' trigger different patterns of brain activity in people who are suicidal, compared with people who are not. That means that people at risk of suicide think about those concepts differently than everyone else-evidenced by the levels and patterns of brain activity, or neural signatures."

""Could teaching be trumped by a learning machine? Are we beginning to glimpse the possibility of machines that teach themselves to teach? They learn what works, what doesn't and deliver ever better performance. We see the embryonic evidence for this in adaptive learning systems, that are truly algorithmic, and do use machine learning, to improve as they deliver. The more students they teach, the better they get. They even tech themselves. This is not science fiction. This is real AI, in real software, delivering real courses, in real institutions." - Donald Clark"

"An algorithm has no tastebuds; a neural net never gets the munchies. So can a robot brain really tell us what we'll want to eat? The question is whether AI systems will be able to excel in the sensual, creative work of tasting and developing new foods - and what we stand to gain or lose by inventing foods that really have our number."

"Rather than being "taught" medical knowledge, the AI was asked to learn using unsupervised deep neural networks, known as autoencoders, without being given any medical knowledge. The researchers developed a method for translating the features found by the AI-only numbers initially-into high-resolution images that can be understood by humans."

"According to tweets from DeepMind founder Demis Hassabis, however, this time AlphaGo really did make mistakes. The AI "thought it was doing well, but got confused on move 87," Hassabis said, later clarifying that it made a mistake on move 79 but only realized its error by 87. AlphaGo adjusts its playing style based on its evaluation of how the game is progressing."

"For now, however, Hammond tries to reassure journalists that he's not trying to kick them when they're down. He tells a story about a party he attended with his wife, who's the marketing director at Chicago's fabled Second City improv club. He found himself in conversation with a well-known local theater critic, who asked about Hammond's business. As Hammond explained what he did, the critic became agitated. Times are tough enough in journalism, he said, and now you're going to replace writers with robots? "I just looked at him," Hammond recalls, "and asked him: Have you ever seen a reporter at a Little League game? That's the most important thing about us. Nobody has lost a single job because of us.""

"This algorithm uses a recurrent neural network to predict sound features from videos and then produces a waveform from these features with an example-based synthesis procedure. We show that the sounds predicted by our model are realistic enough to fool participants in a "real or fake" psychophysical experiment, and that they convey significant information about material properties and physical interactions."

"Facebook announced late Friday that it had eliminated jobs in its trending module, the part of its news division where staff curated popular news for Facebook users. Over the weekend, the fully automated Facebook trending module pushed out a false story about Fox News host Megyn Kelly, a controversial piece about a comedian's four-letter word attack on rightwing pundit Ann Coulter"

"Generally, it questions the advance of computing in the absence of a deeper knowledge of how the human brain perceives the world to be computed. We want computers to have perception, yet we know little about the workings of our own human perception."

"From a computer science perspective, learning the behaviour of a single user is tough. This is the small data problem; unlike big data, where patterns and trends easily emerge, individual human beings can be unpredictable and can change behaviour, which is not helpful for pattern-hunting algorithms."

"Unskilled manual laborers have felt the pressure of automation for a long time - but, increasingly, they're not alone. The last few years have been a bonanza of advances in artificial intelligence. As our software gets smarter, it can tackle harder problems, which means white-collar and pink-collar workers are at risk as well. Here are eight jobs expected to be automated (partially or entirely) in the coming decades. Call Center Employees call-center Telemarketing used to happen in a crowded call center, with a group of representatives cold-calling hundreds of prospects every day. Of those, maybe a few dozen could be persuaded to buy the product in question. Today, the idea is largely the same, but the methods are far more efficient. Many of today's telemarketers are not human. In some cases, as you've probably experienced, there's nothing but a recording on the other end of the line. It may prompt you to "press '1' for more information," but nothing you say has any impact on the call - and, usually, that's clear to you. But in other cases, you may get a sales call and have no idea that you're actually speaking to a computer. Everything you say gets an appropriate response - the voice may even laugh. How is that possible? Well, in some cases, there is a human being on the other side, and they're just pressing buttons on a keyboard to walk you through a pre-recorded but highly interactive marketing pitch. It's a more practical version of those funny soundboards that used to be all the rage for prank calls. Using soundboard-assisted calling - regardless of what it says about the state of human interaction - has the potential to make individual call center employees far more productive: in some cases, a single worker will run two or even three calls at the same time. In the not too distant future, computers will be able to man the phones by themselves. At the intersection of big data, artificial intelligence, and advanced

"The really significant thing about AlphaGo is that it (and its creators) cannot explain its moves. And yet it plays a very difficult game expertly. So it's displaying a capability eerily similar to what we call intuition - "knowledge obtained without conscious reasoning". Up to now, we have regarded that as an exclusively human prerogative. It's what Newton was on about when he wrote "Hypotheses non fingo" in the second edition of his Principia: "I don't make hypotheses," he's saying, "I just know.""

"The Bank of England has previously highlighted the impact of trading algorithms. "Some markets appear to have become more fragile, as evidenced by episodes of short-term volatility and illiquidity over the past couple of years," Threadneedle Street said last December, warning of a move towards "fast, electronic trading." "

"Automated decision-making is appealing to businesses as it can save time and eliminate human emotional volatility. "People have a bad day and it then colors their perception of the world and they make different decisions. In a hedge fund that's a big deal," he added."

"A robot that can decide whether or not to inflict pain has been built by roboticist and artist Alexander Reben from the University of Berkeley, California. The basic machine is capable of pricking a finger but is programmed not to do so every time it can."

"As the miles grow, the odds shrink. At some point, a car driving autonomously or semi-autonomously will cause a fatal accident. If their performance is remotely comparable to a human's, that moment could come within the next 18-24 months. If so, by the law of averages it will probably involve a Tesla Model 3. Self-driving cars may be about to have their Driscoll moment."