SYDNEY (Reuters) - Australia's military will be more readily deployed to respond to "terrorist incidents" on home soil under proposed changes to laws announced by the government on Monday. The government said in a statement that state and territory police forces remained the best first response, but the military could offer additional support to enhance their capabilities. Australia has seen a series of "lone wolf" Islamist-inspired attacks, prompting a review of police tactics and the powers of state and federal authorities. "The key thing we need is the most flexible possible arrangements -- the threat's changed very significantly," Justice Minister Michael Keenan told the Australian Broadcasting Corporation on Monday. Under the proposed law changes, state and territory governments would be able to call for military aid before the ability to respond to an incident exceeds the capabilities of their police forces.

The subjugation of humanity by a race of super-smart, artificially intelligent beings is something that has been theorized by everyone from generations of moviemakers to New Zealand's fourth-most-popular folk-parody duo. But the latest prophet of our cyber-fueled downfall must realize why people would be inclined to take his warnings with a grain of silicon. He is, after all, the same guy who's asking us to turn over control of our cars -- and our lives -- to a bunch of algorithms. Elon Musk, who hopes that one day everyone will ride in a self-driving, electric-powered Tesla, told a group of governors Saturday that they needed to get on the ball and start regulating artificial intelligence, which he called a "fundamental risk to the existence of human civilization." When pressed for better guidance, Musk said the government must get a better understanding of the latest achievements in artificial intelligence before it's too late.

"How are you doing today?" "What's going on in your world right now?" "How do you feel?" These might seem like simple questions a caring friend would ask. However, in the present day of mental health care, they can also be the start of a conversation with your virtual therapist. Innovative technology is offering new opportunities to millions of Americans affected by different mental health conditions. Advancements in artificial intelligence (AI) are bringing psychotherapy to more people who need it.

Tennis - Wimbledon - London, Britain - July 16, 2017 Switzerland's Roger Federer celebrates winning the final against Croatia's Marin Cilic REUTERS/Toby Melville Reuters From 1877 to 1921 the men's singles was decided on a challenge-round system with the previous year's winner automatically qualifying for the final (British unless stated): Winner of all-comers' final declared champion. Not all U.S. presidents are missed once they leave the White House. The Tesla and SpaceX CEO urged governors to regulate artificial intelligence before it's too late. Administration officials traveled to Providence to gain support from key players like Gov. Brian Sandoval. Prime Minister Justin Trudeau and other foreign leaders reached out to U.S. governors ahead of slated talks.

Lots of algorithms go bad unintentionally. Some of them, however, are made to be criminal. Algorithms are formal rules, usually written in computer code, that make predictions on future events based on historical patterns. To train an algorithm you need to provide historical data as well as a definition of success. We've seen finance get taken over by algorithms in the past few decades. Trading algorithms use historical data to predict movements in the market. Success for that algorithm is a predictable market move, and the algorithm is vigilant for patterns that have historically happened just before that move.

We consider the problem of approximating the set of eigenvalues of the covariance matrix of a multivariate distribution (equivalently, the problem of approximating the "population spectrum"), given access to samples drawn from the distribution. The eigenvalues of the covariance of a distribution contain basic information about the distribution, including the presence or lack of structure in the distribution, the effective dimensionality of the distribution, and the applicability of higher-level machine learning and multivariate statistical tools. We consider this fundamental recovery problem in the regime where the number of samples is comparable, or even sublinear in the dimensionality of the distribution in question. First, we propose a theoretically optimal and computationally efficient algorithm for recovering the moments of the eigenvalues of the population covariance matrix. We then leverage this accurate moment recovery, via a Wasserstein distance argument, to show that the vector of eigenvalues can be accurately recovered. We provide finite--sample bounds on the expected error of the recovered eigenvalues, which imply that our estimator is asymptotically consistent as the dimensionality of the distribution and sample size tend towards infinity, even in the sublinear sample regime where the ratio of the sample size to the dimensionality tends to zero. In addition to our theoretical results, we show that our approach performs well in practice for a broad range of distributions and sample sizes.

Microsoft has launched an app that'narrates the world' to people who are blind or visually impaired using AI. The app can, for example, recognize friends' faces and guess their emotions, read text out loud when it comes into view and even has experimental features that can describe scenes - for example, it identified a young girl throwing a frisbee in the park. The app, which is free and available on iOS-only, relies on holding up one's smartphone camera to hear information about the world. The app can also describe strangers around you. In a video demonstrating the app's abilities, the app described a young woman with glasses (left) by saying: '28-year-old female, wearing glasses, looking happy' (right) To use the app, the user must point their phone's camera, select a channel and hear a description of their surroundings.

When Swedbank customers face a problem, they reach out to Nina, the bank's virtual assistant. Visitors to Mizuho Bank are greeted by Pepper, a humanoid robot standing four feet tall. Santander allows payments to be activated by voice, and JP Morgan Chase now uses machine learning to review commercial loan agreements in seconds, a task that used to take 3,60,000 manhours every year. Wherever you look in the world of financial services, you will find some form of artificial intelligence (AI) at work. AI technologies such as machine learning and speech recognition are quietly working behind the scenes to improve lending decisions and prevent fraud.

Here are the slides I gave recently as member of panel Sci-Fi Dreams: How visions of the future are shaping the development of intelligent technology, at the Centre for the Future of Intelligence 2017 conference. I presented three short stories about robot stories. The FP7 TRUCE Project invited a number of scientists – mostly within the field of Artificial Life – to suggest ideas for short stories. Those stories were then sent to a panel of writers, who chose one of the stories. I submitted an idea called The feeling of what it is like to be a robot and was delighted when Lucy Caldwell contacted me.

Engineers are studying human behaviour in great detail in order to make robots that not only look like us, but can also understand us and interact with us in socially acceptable ways. These studies are teaching us many things about our own human nature, as my recent paper explains. The robots in films like Blade Runner are very humanlike, with thoughts and feelings, motives and desires. But making robots that are just like us is a huge challenge. Technical limitations make it currently impossible to make robots identical to humans, although Hiroshi Ishiguru has made a geminoid (a humanlike robot that looks like himself), and David Hanson has made a number of impressive android heads.