When the engineers had at last finished their work, Eugenia Kuyda opened a console on her laptop and began to type. "This is your digital monument." It had been three months since Roman Mazurenko, Kuyda's closest friend, had died. Kuyda had spent that time gathering up his old text messages, setting aside the ones that felt too personal, and feeding the rest into a neural network built by developers at her artificial intelligence startup. She had struggled with whether she was doing the right thing by bringing him back this way. At times it had even given her nightmares. But ever since Mazurenko's death, Kuyda had wanted one more chance to speak with him. A message blinked onto the screen. "You have one of the most interesting puzzles in the world in your hands," it said. Born in Belarus in 1981, Roman Mazurenko was the only child of Sergei, an engineer, and Victoria, a landscape architect. They remember him as an unusually serious child; when he was 8 he wrote a letter to his descendents declaring his most cherished values: wisdom and justice. In family photos, Mazurenko roller-skates, sails a boat, and climbs trees. Average in height, with a mop of chestnut hair, he is almost always smiling.

It seems like everyone including the U.S. government is getting hacked on a regular basis. Like the British broadband provider TalkTalk recently found out, we can all do more to protect ourselves. But fighting against cyber threats seems futile as staying a step ahead of criminals seems almost impossible. So it begs the question, is Machine Learning (ML) the answer we have all been waiting for? The amount of data that's being generated individually and collectively is multiplying rapidly.

Any future war with Russia or China would be "extremely lethal and fast" and produce violence on the scale not seen for 60 years, according to US generals. Artificial intelligence and automated weapons systems will accelerate any future conflict, Major General William Hix has warned. "A conventional conflict in the near future will be extremely lethal and fast," he told a future-of-the-Army panel on Tuesday, Defense One reports. "And we will not own the stopwatch." General Hix described his vision of accelerated future warfare: "The speed of events are likely to strain our human abilities.

To Baldi, scientists should embrace deep learning without being "too anal" about the black box.

Stocks extended their winning streak to a fourth session on the Tokyo Stock Exchange on Thursday, backed by the yen's further drop against the dollar and a brighter U.S. economic outlook. The Nikkei average rose 79.86 points, or 0.47 percent, to finish at 16,899.10. On Wednesday, it gained 83.59 points. The Topix index closed up 6.12 points, or 0.45 percent, at 1,353.93, after climbing 7.60 points the previous day. The Tokyo market opened sharply higher thanks to the weaker yen and gains on Wall Street.

Jin Kawaguchiya gave up a career in finance to help revive Japan's ailing dairy industry, one robot at a time. In a country that relies increasingly on imported foods like cheese and butter, Japan's milk output tumbled over two decades, touching a 30-year low in 2014. Costs rose faster than prices as the economy stagnated, eroding profit, and aging farmers quit the business because they could not find enough young people willing to take on the hard labor of tending to cows every day. But technology is altering that dynamic. On Hokkaido, Japan's top dairy-producing region, Kawaguchiya transformed the 20-cow farm he inherited from his father-in-law 16 years ago into Asia's largest automated milking factory.

"Sandia National Laboratories researchers are drawing inspiration from neurons in the brain, such as these green fluorescent protein-labeled neurons in a mouse neocortex, with the aim of developing neuro-inspired computing systems to reboot computing. "Summary: Researchers explore neural computing to extend Moore's Law. Sandia explores neural computing to extend Moore's Law. Computation is stuck in a rut. The integrated circuits that powered the past 50 years of technological revolution are reaching their physical limits.

Dean Pomerleau can still remember his first tussle with the black-box problem. The year was 1991, and he was making a pioneering attempt to do something that has now become commonplace in autonomous-vehicle research: teach a computer how to drive. This meant taking the wheel of a specially equipped Humvee military vehicle and guiding it through city streets, says Pomerleau, who was then a robotics graduate student at Carnegie Mellon University in Pittsburgh, Pennsylvania. With him in the Humvee was a computer that he had programmed to peer through a camera, interpret what was happening out on the road and memorize every move that he made in response. Eventually, Pomerleau hoped, the machine would make enough associations to steer on its own.

Dean Pomerleau can still remember his first tussle with the black-box problem. The year was 1991, and he was making a pioneering attempt to do something that has now become commonplace in autonomous-vehicle research: teach a computer how to drive. This meant taking the wheel of a specially equipped Humvee military vehicle and guiding it through city streets, says Pomerleau, who was then a robotics graduate student at Carnegie Mellon University in Pittsburgh, Pennsylvania. With him in the Humvee was a computer that he had programmed to peer through a camera, interpret what was happening out on the road and memorize every move that he made in response. Eventually, Pomerleau hoped, the machine would make enough associations to steer on its own.

After graduating with a law degree from the University of Saskatchewan, Andrew identified a problem amid the legal hierarchy – by experiencing it first-hand. "I worked at a small law firm to pay my way through university and law school. When I started out I did a lot of the grunt work that senior lawyers don't do. Legal research takes about 30% of a lawyer's time. Currently legal research works by inputting keywords to search a massive databases of cases – you type in a query and get thousands of results, which a lawyer has to trawl through to pick out key meanings. I was doing that, and I can tell you that it's a mess and takes a long time".