The Turing test, the quintessential evaluation designed to determine if something is a computer or a human, may have a fatal flaw, new research suggests. The test currently can't determine if a person is talking to another human being or a robot if the person being interrogated simply chooses to stay silent, new research shows. While it's not news that the Turing test has flaws, the new study highlights just how limited the test is for answering deeper questions about artificial intelligence, said study co-author Kevin Warwick, a computer scientist at Coventry University in England. "As machines are getting more and more intelligent, whether they're actually thinking and whether we need to give them responsibilities are starting to become very serious questions," Warwick told Live Science. "Obviously, the Turing test is not the one which can tease them out." The now-famous Turing test was first described by British computer scientist Alan Turing in 1950 to address questions of when and how to determine if machines are sentient.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

The security robots are made by a company called Knightscope, located in Mountain View. The K5 version uses lasers, thermal imaging sensors, 360 video, air quality sensors, a microphone and various other technologies to deter and detect criminal activities. In the event of suspicious activity, the robot alerts local human authorities. Stacy Dean Stephens, Knightscope vice president of marketing and sales, told NBC Bay Area that the company does not think the robots are dangerous. "This is a horrific accident, but we believe the technology and the machines are incredibly safe and we will continue to do our best to make sure that they are," Stephens said.

In this Dec. 17, 2014 file photo, a Pakistan army soldier inspects the Army Public School that was attacked a day before by Taliban gunmen, in Peshawar, Pakistan. The Pakistani army said Wednesday, July 13, 2016 that the mastermind of the 2014 attack on an army-run school has been killed in a U.S. drone strike. A Pakistani military spokesman says that a U.S. Army general confirmed the death of Taliban leader Khalifa Umar Mansoor in a phone call to Pakistan's army chief.

Where we're going we don't need roads, just a large database of pictures. A team at New York University have taught a machine learning system to drive off-road by showing it photos of different landscapes. It's one thing to train driverless cars to navigate city streets or highways. But taking robot drivers off-road is tricky because the surroundings are highly variable, says Karl Iagnemma at the Massachusetts Institute of Technology, who wasn't involved in the work. It is hard to give a robot an exhaustive set of driving rules for every environment.

H2O is the leading open source big data machine learning platform. This talk will cover the distributed parallel in-memory data storage and compute architecture. We will then move on to examples of using H2O from R, Python, Java and Scala. Depending on interest we can also cover Deep Learning in H2O, integration of H2O into smart applications, and/or the optional integration with Spark.

Ben Dickson is a software engineer and freelance writer. He writes regularly on business, technology and politics. The transportation industry is associated with high maintenance costs, disasters, accidents, injuries and loss of life. Hundreds of thousands of people across the world are losing their lives to car accidents and road disasters every year. According to the National Safety Council, 38,300 people were killed and 4.4 million injured on U.S. roads alone in 2015.

Some water utilities have so much data at their disposal it is hard to sift through it all and use it effectively, but software has the potential to change that. "One tool for working with potentially valuable truck loads [of data] is an artificial neural network -- a software system that uses machine learning techniques to process tons of data and intelligently answer questions," Ars Technica reported. OmniEarth, a geographic analytics company, is using IBM's Watson technology to give meaning to water data. Watson, a machine learning system, became a household name when it managed to outdo some formidable Jeopardy contestants. The project has deployed this technology to help water managers understand whether ratepayers are using water efficiently.

Artificial Intelligence is the latest hotness. We've heard how bots are going to be the new apps allowing natural conversational interfaces. Siri, Cortana and Google Now are no longer a gimmick and are becoming more useful every day. Machine Learning sits behind artificial intelligence and on the surface it may seem like a deeply technical, scientific topic. We are here to tell you that it is more accessible than you think.

As a UK-focused venture capital investor, Oxford Capital is fortunate that the UK is a world leader in AI (although to avoid topical accusations of British exceptionalism, it's definitely worth mentioning that there are centres of excellence in AI and machine learning (ML) throughout Europe). We have just completed an as-yet undisclosed investment in the AI space, and we're evaluating several other opportunities. Along with taking an interest in AI companies that approach us for funding, we've mapped out recent activity in the sector across the UK. Innovation starts with talented individuals, and AI is no exception. Many of the UK's most respected universities have AI research groups, such as the Intelligent Systems group within UCL and the joint Oxford-Cambridge Strategic AI Research Centre.