Migration crisis, climate change or tax havens: Global challenges need global solutions. But agreeing on a joint approach is difficult without a common ground for discussion. Public spheres are highly segmented because news are mainly produced and received on a national level. Gain- ing a global view on international debates about important issues is hindered by the enormous quantity of news and by language barriers. Media analysis usually focuses only on qualitative re- search. In this position statement, we argue that it is imperative to pool methods from machine learning, journalism studies and statistics to help bridging the segmented data of the international public sphere, using the Transatlantic Trade and Investment Partnership (TTIP) as a case study.

Tall grass hid the advancing cadets from my perch in building 7. The tall grass hid nothing from the drone the defenders flew over their position, a Parrot AR 2.0, a common model used by civilian fliers. A minute later, after the drone pilot filmed the crawling cadets, instructors called in mock artillery fire. The cadets' position was compromised, and while the rest of their platoon advanced to take the buildings, these 10 cadets instead spent an hour in the sun contemplating what they could have done about the drone. The answer was standing right behind them.

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

The FBI maintains a huge database of more than 411m photos culled from sources including driver's licenses, passport applications and visa applications, which it cross-references with photos of criminal suspects using largely untested and questionably accurate facial recognition software. A study from the Government Accountability Office (GAO) released on Wednesday for the first time revealed the extent of the program, which had been queried several years before through a Freedom of Information Act request from the Electronic Frontier Foundation (EFF). The GAO, a watchdog office internal to the US federal government, found that the FBI did not appropriately disclose the database's impact on public privacy until it audited the bureau in May. The office recommended that the attorney general determine why the FBI did not obey the disclosure requirements, and that it conduct accuracy tests to determine whether the software is correctly cross-referencing driver's licenses and passport photos with images of criminal suspects. The Department of Justice "disagreed" with three of the GAO's six recommendations, according to the office, which affirmed their validity.

The Singularity is a term you'll find in science and in science fiction. It was coined by mathematician John von Neumann to define a theoretical moment when the artificial intelligence of computers surpasses the capacity of the human brain. The term is borrowed from physics and quantum mechanics, where the term gravitational singularity is used in the study of black holes. These events are all considered singular because we are unable to predict what happens next; the disruptive degree of change associated with the event is simply too great for our current body of knowledge. While we are far from attaining the goal of artificial intelligence, there was a brief flurry of excitement recently when a computer passed the Turing Test, to mixed reviews.

The FBI has fallen short on assessing the privacy risks and accuracy of a huge facial recognition database used by several law enforcement agencies, a government auditor has said. A new report, released by the U.S. Government Accountability Office Wednesday, shows the FBI's use of facial recognition technology is "far greater" than previously understood, said Senator Al Franken, the Minnesota Democrat who requested the GAO report. The FBI's Next Generation Identification-Interstate Photo System (NGI-IPS), which allows law enforcement agencies to search a database of more than 30 million photos of 16.9 million people, raises serious privacy concerns, Franken added in a press release. "Facial recognition technology is a new and powerful tool that holds great promise for law enforcement," he said. "But if we don't ensure its accuracy and guard against misuse, I am concerned about the risk of innocent Americans being inadvertently swept up in criminal investigations."

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

After almost 10 years of working incognito, former National Aeronautics and Space Administration head Daniel Goldin is finally ready to formally present KnuEdge to the world. KnuEdge is a "neural technology innovation company," an outfit that builds hardware and software based on neural technology, with a main focus on human-machine interaction. While newly revealed publicly, it has been in stealth mode for a decade now, and has already raised 100 million in funding to build its neural chips. The company has revealed its two primary products: KnuVerse, which is a voice authentication technology, and KnuPath, its state-of-the-art neural chip. It has also unveiled Knurld.io, a software development kit with a cloud-based voice recognition and authentication service. Foremost of these offerings is KnuPath.

Before becoming a reality, AlphaBounce had to be shaped by ARAMIS, a motion-capture system that helps determine the amount of strain and tension caused by different materials. ARAMIS, which NASA has used to inspect the outer hull of space shuttles, combines high-speed cameras with flexion sensors to gather information at up to 500 frames per second. Since the software maps skin, bone and muscle, it can give Adidas engineers insight into how they should go about designing a more comfortable running sneaker. ARAMIS can visualize the level of comfort on every area of an individual's foot, from the heel to the toes, as well as indicate when the fabric may be getting in the way of performance. "It's a really versatile tool," said George Robusti, senior design director of global running at Adidas, of the ARAMIS system.

The Monetary Authority of Singapore (MAS) ordered BSI Bank Singapore to shut down recently on 24 May 2016. This serious action is due to their compliance oversight in money laundering which resulted in a criminal case. This is also a stark reminder of the compliance challenges that financial institutions are facing today. They had attracted millions of dollars of regulatory fines in the aftermath of the 2008 Global Financial Crisis. A distinguished law firm, Baker and McKenzie, commissioned a survey of 424 senior executives from financial institutions.