President Donald Trump reportedly spends his nights alone in the White House, watching TV news and yelling at the screen. He wakes up early each morning to watch more television and tweet his anger to the world … or Mika Brzezinski … or CNN. He takes time out of meetings with foreign leaders to brag about his Electoral College win. That all sounds, at the very least, distracting for a person with the weight of the free world on his shoulders. But if his fury at the Russia scandal and insecurity about his election are stealing time from the important decisions of the presidency, Trump is by no means the first commander in chief whose emotions or personality have gotten in the way of the job.

For most people, machines that can think and act on their own have, until now, been futurist fantasy. Fritz Lang's Metropolis (1927), Stanley Kubrick's 2001 A Space Odyssey (1968), Alex Proyas' I, Robot (2004), and Steven Spielberg's Minority Report (2002) have, along with many other creative works, variously portrayed fictive worlds profoundly altered by Artificial Intelligence and, especially, automata. The roots of these vivid tales reach down to a bedrock of Judeo-Christian folklore and Greek mythology from which, at least since the Middle Ages, have grown parables warning of the danger that comes from taking the place of the Creator.[1] Inhabiting Medieval Jewish folklore is one such, the golem, an automaton-protector made from mud which, in one story, prefiguring Mary Shelley's Frankenstein, runs amok.[2] As technology has evolved stories about the ambitions of its creators that end in tragedy have evolved with it -- lasting well into an age where an unchallenged scientific secularism rules our intellectual and moral worlds. Is this a residue of superstition in an enlightened age or a moral symbiosis? And if the latter, is its lesson that science should split the difference with superstition or that the humanities and religion, along with science, should retain this perspective: that good and evil live in man and not in his machines?

In the quarter century since Volvo rolled my ruby-red 240 wagon off an assembly line, its creator has gone from a modest Swedish independent automaker to part of a massive American conglomerate to an arm of a Chinese automaker that's pushing driverless cars and racing to go fully electric in the next two years. It's been a funky journey for a funky automaker, but it's no mere aberration or footnote. If you want to understand the car industry of the past 25 years--and maybe the next 25--study Volvo's journey. For a niche player best known for shuttling liberals and hippies, Volvo has long played an outsized role in the evolution of the auto industry. It invented and made standard the three-point seat belt.

A young Marine reaches out for a hand-launched drone. In science fiction and real life alike, there are plenty of horror stories where humans trust artificial intelligence too much. They range from letting the fictional SkyNet control our nuclear weapons to letting Patriots shoot down friendly planes or letting Tesla Autopilot crash into a truck. As conflict on earth, in space, and in cyberspace becomes increasingly fast-paced and complex, the Pentagon's Third Offset initiative is counting on artificial intelligence to help commanders, combatants, and analysts chart a course through chaos -- what we've dubbed the War Algorithm (click here for the full series). But if the software itself is too complex, too opaque, or too unpredictable for its users to understand, they'll just turn it off and do things manually.

The $711m in value accounted for 44% of the global total, a quadruple increase on the previous year (10%). AI, IoT and analytics and big data propositions collectively accounted for 56% of the total number of deals – around 70% of total value last year. UK market doubles The value of insurtech investments in the UK more than doubled year on year to almost $19m, although the total number of deals remained flat. Accenture said that Brexit had not had a material impact on the investment climate in 2016. After the UK, Germany and France are the next largest markets in Europe.

If you thought human journalists were too biased in their reporting, maybe robots will be better. We rejoiced when automation meant the more efficient production of the Ford Model T. We applauded when artificial intelligence bested humans at games and trivia. We nodded solemnly as machines began to replace fast-food workers and supermarket cashiers. And now, we may not know exactly how to react as computers take over our jobs as news writers. Few jobs these days are truly safe from the rise of AI and the latest industry to be affected is journalism.

Jimmy Causey is seen in this undated photo from authorities in Williamson County, Texas. Authorities said Friday, July 7, 2017, that Causey was on the run more than two days after using wire cutters that were probably dropped from a drone as part of an elaborate escape plan that also included cellphones smuggled into prison, guns and at least $47,000 in cash. Jimmy Causey is seen in this undated photo from authorities in Williamson County, Texas. Authorities said Friday, July 7, 2017, that Causey was on the run more than two days after using wire cutters that were probably dropped from a drone as part of an elaborate escape plan that also included cellphones smuggled into prison, guns and at least $47,000 in cash. This undated photo provided by the South Carolina Department of Corrections shows Jimmy Causey, who authorities continue to search for Thursday, July 6, 2017, after he escaped from Lieber Correctional Institution maximum-security prison in Ridgeville, S.C. (South Carolina Department of Corrections via AP) COLUMBIA, S.C. (AP) -- A South Carolina inmate broke out of a maximum-security prison using wire cutters apparently flown in by drone, officials said Friday, describing a new and devilishly hard-to-stop means of escape.

Recently found a post by Ali Syed on topic; "Europeans unconvinced by big data in general". This study was conducted for the Vodafone Institute for Society and Communications by Kantar-owned market researchers TNS Infratest. It analyses over 8,000 individuals across eight European countries and offers valuable insight into people's perceptions of big data and analytics Still there are people or groups don't believe that we are living in the age of Big Data. Other way round we can say they think Big Data is just a hype created by technology people. To me the concept of Big Data is not new.

Google is giving British journalists more than 700,000 pounds to help them incorporate artificial intelligence into their work. Google awarded the grant to The Press Association (PA), the national news agency for the United Kingdom and Ireland, and Urbs Media, a data driven news startup. It's one of the largest grants handed out by Google's Digital News Initiative Innovation Fund. The funding, announced on Thursday, will specifically go to Reporters And Data And Robots, a news service that aims to create 30,000 local stories a month. "Skilled human journalists will still be vital in the process, but RADAR allows us to harness artificial intelligence to scale up to a volume of local stories that would be impossible to provide manually," Clifton said in a statement.

Deep neural networks (DNNs) have excellent representative power and are state of the art classifiers on many tasks. However, they often do not capture their own uncertainties well making them less robust in the real world as they overconfidently extrapolate and do not notice domain shift. Gaussian processes (GPs) with RBF kernels on the other hand have better calibrated uncertainties and do not overconfidently extrapolate far from data in their training set. However, GPs have poor representational power and do not perform as well as DNNs on complex domains. In this paper we show that GP hybrid deep networks, GPDNNs, (GPs on top of DNNs and trained end-to-end) inherit the nice properties of both GPs and DNNs and are much more robust to adversarial examples. When extrapolating to adversarial examples and testing in domain shift settings, GPDNNs frequently output high entropy class probabilities corresponding to essentially "don't know". GPDNNs are therefore promising as deep architectures that know when they don't know.