Iraqi Special Forces soldiers celebrate after reaching the bank of the Tigris river as their fight against Islamic State militants continues in parts of the Old City of Mosul, Iraq, Sunday, July 9, 2017. Iraqi Special Forces soldiers celebrate after reaching the bank of the Tigris river as their fight against Islamic State militants continues in parts of the Old City of Mosul, Iraq, Sunday, July 9, 2017. In this Thursday, July 6, 2017 photo, Sumaya Farooqi, 14, left, practices robotics with her colleagues, at the Better Idea Organization center, in Herat, Afghanistan. Six female students from war-torn Afghanistan who had hoped to participate in an international robotics competition July 16-18 in Washington D.C will have to watch via video link after the U.S. denied them visas -- not once, but twice. Of 162 teams participating, the Afghan girls are the only nation's team to be denied visas.

The field of AI is going through a period of rapid progress, with improvements in processor design and advances in machine learning, deep learning, and natural language processing. The reports recommended increased expenditure on machine learning research and enhanced collaboration between the U.S. government and tech industry leaders to unlock the potential of AI. But despite these efforts, 91 percent of the 1,268 tech founders, CEOs, investors, and developers surveyed at the international Collision tech conference in New Orleans in May 2017 believed that the U.S. government is "fatally under-prepared" for the impact of AI on the U.S. ecosystem. Research firm CB Insights found that Chinese participation in funding rounds for American startups came close to $10 billion in 2016, while recent figures indicate that Chinese companies have invested in 51 U.S. AI companies, to the tune of $700 million.

In the battle of technology innovation between East and West, artificial intelligence (AI) is on the frontline. And China's influence is growing. AI is seen as a key to unlocking big data and the Internet of Things. It allows us to make better decisions faster, and will soon enable smarter cities, self-driving cars, personalized medicines and other new commercial applications to potentially help solve various global problems. The AI field is going through a time of rapid progress, with improvements in processor design and advances in machine learning, deep learning and natural language processing.

Artificial intelligence is helping the Army keep its Stryker armored vehicles in fighting shape. Army officials are using IBM's Watson AI system in combination with onboard sensor data, repair manuals and 15 years of maintenance data to predict mechanical problems before they happen. IBM and the Army's Redstone Arsenal post in Alabama demonstrated Watson's abilities on 350 Stryker vehicles during a field test that began in mid-2016. The Army is now reviewing the results of that test to evaluate Watson's ability to assist human mechanics, and the early insights are encouraging. The Watson AI enabled the pilot program's leaders to create the equivalent of a "personalized medicine" plan for each of the vehicles tested, said Sam Gordy, general manager of IBM U.S. Federal.

A Master Algorithm would allow machines to learn anything from data, and has applications in fields from marketing to medicine. But to do that we need a deeper understanding of learning in our own brains. This helmet of sensors is part of a brain scanner. We may not be aware of it, but machine learning is already an integral part of our daily lives, from the product choices that Amazon offers us to the surveillance of our data by the National Security Agency. Few of us understand it or the implications, however.

Every year at the United Nations, member states deliver statements during the General Debate discussing major issues in world politics. These speeches provide invaluable information on governments' perspectives and preferences on a wide range of issues, but have largely been overlooked in the study of international politics. This paper introduces a new dataset consisting of over 7,701 English-language country statements from 1970-2016. We demonstrate how the UN General Debate Corpus (UNGDC) can be used to derive country positions on different policy dimensions using text analytic methods. The paper provides applications of these estimates, demonstrating the contribution the UNGDC can make to the study of international politics.

Mark Waser, for instance, a longtime artificial intelligence researcher who works for a think tank called the Digital Wisdom Institute, says that once we fix some key kinks in artificial intelligence, robots will make much better decisions than humans can. Another big technical problem to solve before computers could run the country: Robots don't know how to explain themselves. In an approach called machine learning, the computer analyzes mountains of data and searches for patterns--patterns that might make sense to the computer but not to humans. In a variant approach called deep learning, a computer uses multiple layers of processors: One layer produces a rough output, which is then refined by the next layer, and that output, in turn, is refined by the next layer.

As the demand for advanced security solutions grows, organizations are gradually realizing the need to go beyond perimeter based defences. They need to detect unknown threats, despite weak signals, in real-time. Only solution to this problem is to analyse user traffic, identify relevant patterns, and gain a clear insight on potential threats. Spotting this as an opportunity--as well as a challenge--Reveelium, the American subsidiary of a European-based cybersecurity provider, decided to develop a solution with advanced threat detection techniques. Rigorous R&D and collaboration with specialized labs allowed professionals at the company to launch in 2012 a behavioral analysis platform-- Reveelium AI.

In a post Snowden world, would you be happy with politicians setting their sights on artificial intelligence as a tool set? Of course there are already many implementations of machine learning used by government and bodies surrounding it, but to actually start using it as a political platform? This is what I saw just a few moments ago, shared by a friend of a friend on Facebook. Mike Tolking, who really wants to be mayor of New York, is using an affinity for modern technology (or at least its buzzwords) to convince people to vote for him. While first of all I am not American, so I care a little less, and secondly not interested so much in politics (who can find the time these days), so I don't really care at all, I am very interested in the way he is portraying the current state of artificial intelligence.

Around midnight one Saturday in January, Sarah Jeong was on her couch, browsing Twitter, when she spontane ously wrote what she now bitterly refers to as "the tweet that launched a thousand ships." The 28-year-old journalist and author of The Internet of Garbage, a book on spam and online harassment, had been watching Bernie Sanders boosters attacking feminists and supporters of the Black Lives Matter movement. In what was meant to be a hyper bolic joke, she tweeted out a list of political carica tures, one of which called the typical Sanders fan a "vitriolic crypto racist who spends 20 hours a day on the Internet yelling at women." The ill-advised late-night tweet was, Jeong admits, provocative and absurd--she even supported Sanders. But what happened next was the kind of backlash that's all too familiar to women, minorities, and anyone who has a strong opinion online. By the time Jeong went to sleep, a swarm of Sanders supporters were calling her a neoliberal shill. By sunrise, a broader, darker wave of abuse had begun. She received nude photos and links to disturbing videos. One troll promised to "rip each one of [her] hairs out" and "twist her tits clear off." The attacks continued for weeks. "I was in crisis mode," she recalls. So she did what many victims of mass harassment do: She gave up and let her abusers have the last word.