Knowing a cyberattack's going to occur before it actually happens is very useful--but it's tricky to achieve in practice. Now MIT's built an artificial intelligence system that can predict attacks 85 percent of the time. Cyberattack spotters work in two main ways. Some are AIs that simply look out for anomalies in internet traffic. They work, but often throw up false positives--warnings about a threat when actually nothing's wrong. Other software systems are built on rules developed by humans, but it's hard to create systems like that which catches every attack.

The notion of Artificial Intelligence has been around for a while. Yet, unlike other prominent technological innovations such as electric cars or the processor speed, its progress has not been linear. In fact, as far as industrial impact is concerned, there were times when allegedly there was no progress at all. The widespread fascination with AI started several generations ago, in 80-s of the last century. This is when a pioneering work of Noam Chomsky on computational grammar led to a belief that human language capabilities in particular, and human intelligence in general, can be straightforwardly algorithmized.

Existing threat-detection systems broadly fall into two categories: a software bot that can detect patterns and human analysis. AI2's gimmick is that it mashes together a handful of different machine learning tools and asks its flesh-and-blood counterparts for help. When it thinks it's found a pattern amongst the noise of data, it offers it up to a person for a second opinion. After a short period of time, AI2 will learn from its errors and what the human experts are telling it. As Arnaldo says, "it continuously generates new models that it can refine in as little as two hours."

Moves to tighten rules on drones have been promised by the government after Labour and pilots unions called for urgent action, including a possible register of drone users and "geo-fencing" of airports, after a British Airways plane was struck on its descent into Heathrow. Sunday's incident is believed to be the first such collision between a passenger plane and a drone, after a series of near misses that led pilots to warn that a strike could be disastrous. The Air Accidents Investigations Branch said it would launch an inquiry. The Department for Transport (DfT) said it would hold a public consultation before a government strategy is published later this year. Labour has accused ministers of dragging their feet after aviation authorities confirmed a number of potentially serious incidents in 2015, including 23 near misses between aircraft and drones in six months investigated by the UK Airprox Board.

Computing jobs are growing at twice the national rate of other types of employment. By 2020, the Bureau of Labor Statistics says, the US will have 1 million more computer science-related jobs than graduates qualified to fill them. In December, President Obama announced the Computer Science for All Initiative, pledging 4 billion in funding for computer science education in the nation's schools. Yet all kinds of dysfunction keeps the country from closing the deficit in computer science talent, according to a survey by Google and Gallup. Yes, school budgets are a problem, and teachers have a limited time to devote to additional classes.

Finding evidence that someone compromised your cyber defenses is a grind. Sifting through all of the data to find abnormalities takes a lot of time and effort, and analysts can only work so many hours a day. But an AI never gets tired, and can work with humans to deliver far better results. A system called AI2, developed at MIT's Computer Science and Artificial Intelligence Laboratory, reviews data from tens of millions of log lines each day and pinpoints anything suspicious. A human takes it from there, checking for signs of a breach.

While the term may not be immediately recognizable, convolutional neural networks (CNNs) are already part of our daily lives--and they are expected to become even more significant in the near future. Convolutional neural networks are a form of machine learning modeled on the way the brain's visual cortex distinguishes one object from another. That helps explain why the most common use today is for image recognition, which is where this market is gaining real traction today. But it also has many potential uses far beyond image recognition as power is reduced and performance is improved. "The work that happens at a place like Facebook or Yahoo or Google to try to find you in all those pictures people are uploading, that's largely done with neural networks already," observed Drew Wingard, CTO of Sonics, noting that driver assistance uses similar technology.

Games are uniquely human, or so we thought – Chess, Jeopardy, and now Go. Will robots take our jobs? Has web search made us dumb? We heard most of these same fears back in the 1990's, when IBM's Deep Blue defeated Grandmaster Garry Kasparov at the chessboard. But defeat is a better teacher than victory and this was certainly the case for Kasparov who has now developed a system called Centaur Chess where a human and computer play as a team with the human choosing from moves suggested by the computer.

Unmanned systems in military applications will often play a role in determining the success or failure of combat missions and thus in determining who lives and dies in times of war. Designers of UMS must therefore consider ethical, as well as operational, requirements and limits when developing UMS. The ethical issues involved in UMS design may be grouped under two broad headings: Building Safe Systems and Designing for the Law of Armed Conflict. This paper identifies and discusses a number of issues under each of these headings and offers some analysis of the implications of each issue and how it might be addressed.

Mobify, a startup which aims to help retailers attract and retain customers both online and in the brick-and-mortar world, has bought Pathful, a small artificial intelligence (AI) specialist. Both companies are based in Vancouver, British Columbia–so there's a geographic fit–but aside from that, Pathful will bring more machine learning or …