Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

In fact, in many countries, the internet, the very thing that was supposed to smash down the walls of authoritarianism like a sledgehammer of liberty, has been instead been co-opted by those very regimes in order to push their own agendas while crushing dissent and opposition. And with the emergence of conversational AI -- the technology at the heart of services like Google's Allo and Jigsaw or Intel's Hack Harassment initiative -- these governments could have a new tool to further censor their citizens. Turkey, Brazil, Egypt, India and Uganda have all shut off internet access when politically beneficial to their ruling parties. Nations like Singapore, Russia and China all exert outsized control over the structure and function of their national networks, often relying on a mix of political, technical and social schemes to control the flow of information within their digital borders. The effects of these policies are self-evident.

The machines haven't taken over. However, they are seeping their way into our lives, affecting how we live, work and entertain ourselves. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies such as behavioral algorithms, suggestive searches and autonomously-powered self-driving vehicles boasting powerful predictive capabilities, there are several examples and applications of artificial intellgience in use today. However, the technology is still in its infancy. What many companies are calling A.I. today, aren't necessarily so.

Artificial intelligence (AI) on its own isn't enough to compete -- companies need industry-specific solutions to business problems. So said Martin Schroeter, IBM Corp. (NYSE: IBM)'s company senior vice president and chief financial officer, on the company's quarterly earnings call Thursday afternoon. Cognitive computing technology (IBM's term for AI) is just "table stakes," said Schroeter, claiming that his company is going the extra mile. IBM is building datasets for Watson to serve specific industries, including healthcare and finance. "You need more than public data or algorithms to solve real-world problems," Schroeter said.

The seminal MMORPG World of Warcraft may have dwindled from its peak of 12 million players back in 2010, but Blizzard's still supporting the 12-year-old game with content and events. To celebrate the latest expansion, Legion, the studio built an elaborate cafe at Germany's Gamescom convention that served themed food and cocktails. But for everyone who couldn't fly out to Europe for some nerd cuisine, they've lined up the next best thing: A cooking show debuting tonight hosted by Choi Hyun-seok, a famous chef known for appearances on South Korean television. The Meal Is Ready, as it's titled, debuts tonight at 11 PM KT. According to GameAbout, Choi a known WoW player, will cook dishes like'Hell Hound Sweet and Sour Fish' and'Murlok Soup' while guests share stories from and about the game.

In this paper, a genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of inter-class distance and intra-class distance. Moreover, the proposed feature search method can additionally search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable, thus, GAFDS exhibits good extensibility. Multiple classic classifiers (i.e., $k$-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Na\"ive Bayes) achieve good results by using the features generated by GAFDS method and the optimized selection. Specifically, the accuracies for the two-classification and three-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in feature extraction for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy.

If you use your credit card to buy a latte in Vancouver and a couple of minutes later that card is making a purchase in Singapore, that's a red flag for fraud. But increasingly sophisticated fraud calls for more sophisticated measures to deal with it, and that is among the challenges behind RBC Research's announcement today that it is launching a new lab to explore the use of artificial intelligence and machine learning in the financial sector. Richard Sutton, a computer scientist and pioneer in artificial intelligence, has been named head academic advisor to RBC Research in machine learning. The new lab will work with the Alberta Machine Intelligence Institute at the University of Alberta, where Sutton is a professor. Foteini Agrafioti, head of RBC Research, which was launched last fall in Toronto, said the announcement will help her organization to play a major role in advancing AI research in the future of banking. Agrafioti said that as the complexity of fraud evolves over time, it becomes increasingly difficult to detect it.

The internet was supposed to become an overwhelming democratizing force against illiberal administrations. It was supposed to open repressed citizens eyes, expose them to new democratic ideals and help them rise up against their authoritarian governments in declaring their basic human rights. It was supposed to be inherently resistant to centralized control. In fact, in many countries, the internet, the very thing that was supposed to smash down the walls of authoritarianism like a sledgehammer of liberty, has been instead been co-opted by those very regimes in order to push their own agendas while crushing dissent and opposition. And with the emergence of conversational AI -- the technology at the heart of services like Google's Allo and Jigsaw or Intel's Hack Harassment initiative -- these governments could have a new tool to further censor their citizens.

The apocalyptic future shown in sci-fi films--the ones where robots have gain consciousness and destroy humanity--is not one you need to worry about according to a report from the United States Department of Defense. The document, produced by JASON--an independent advisory group comprised of scientists and experts that brief the government on matters of science and technology--outlines trends in the field of artificial intelligence as it pertains to the U.S. military. According to the report, most computer scientists believe the possible threats posed by AI to be "at best uninformed" and those fears "do not align with the most rapidly advancing current research directions of AI as a field." It instead says these existential fears stem from a very particular--and small--part of the field of research called Artificial General Intelligence (AGI), which is defined as an AI that can successfully perform any intellectual task that a human can. The report argues we are unlikely to see the reality of an AGI come from the current artificial intelligence research and the concept "has high visibility, disproportionate to its size or present level of success."

Elon Musk was right when he said that Artificial Intelligence (AI) systems and automation will eventually take over most human jobs and, in what can be seen as a first case in India where the country's software giant Infosys has "released" 8,000-9,000 employees in the past one year because of automation of lower-end jobs, which is confirmed by the company's human resources head Krishnamurthy Shankar in a statement to ET. Notably, these released employees are now working on more advanced projects, so its not that automation or AI has stole the human jobs but it actually transforming at least in this case of Infosys. Machine learning and Artificial Intelligence previously required expensive computing machines, but costs have now come down dramatically. As part of its Automation, Artificial Intelligence and machine learning adaptation drive, the company has been releasing about 2,000 people every quarter and also training them in special courses that will help them in their new assignments. In a research report, released by Infosys itself said that the majority -- 85 percent -- plan to train employees about the benefits and use of AI, and 80 percent of companies replacing roles with AI technologies will retrain or redeploy displaced employees. The report also predicts that organizations that have already deployed or have plans to deploy AI technologies expect to see a 39 percent average increase in revenue by 2020, alongside a 37 percent reduction in costs.