Researchers in Nebraska tested a new tool on Friday that could eventually help in fighting grass fires -- drones. A team from the University of Nebraska-Lincoln flew an unmanned aircraft over the prairie at the Homestead National Monument of America on Friday, dropping ping pong-like balls filled with a chemical mixture to ignite brush-clearing grass fires. Local and federal officials are interested in the technology because it could help clear overgrown vegetation in rugged, hard-to-reach terrain, said Michael Johnson, a spokesman for the National Park Service. The balls are filled with a chemical powder, potassium permanganate, before they're loaded into the drone. During flight, the aircraft pierces the ball with a needle and injects it with another chemical, glycol, before releasing it.

Ben Dickson is a software engineer and freelance writer. He writes regularly on business, technology and politics. Computers and mobile devices running rich operating systems have a plethora of security solutions and encryption protocols that can protect them against the multitude of threats they face as soon as they become connected to the Internet. Such is not the case with IoT. Of the billions of IoT devices presently in use, a considerable percentage are sporting low-end processing power and storage capacity and don't have the capability to become extended with security solutions.

Isn't it cool if we could predict cyber attacks before it happens? Predicting cyber attacks before it happens can help to prevent it. A Scientist team at Massachusetts Institute of Technology have developed an Artificial Intelligence system that can detect and stop almost 85% of cyber attacks with a little human help. This Advanced intelligent system is known as AI2. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the machine-learning startup ParrernEx have demonstrated an artificial intelligence platform knows AI2.

Michael Kropp typically spends his days behind the wheel of a big, freight-hauling truck, navigating the high-speed curves, offramps, and stop-and-go traffic typical of European highways. On a recent trip to Rotterdam, he was able to relax and take in the sights. Kropp was one of about 30 drivers participating in a test of a new automated driving technology called platooning, which links trucks via Wi-Fi, GPS, sensors, and cameras so they can travel semiautonomously behind one another. The leading rig dictates speed and direction, while the rest automatically steer, accelerate, and brake in a closely spaced convoy. "It was a little eerie to hand over part of my role as driver," says Kropp, a 55-year-old test driver for Daimler who piloted the second vehicle in the caravan.

The future of cyber-security looks part human and part machine, according to MIT's Computer Science and Artificial Intelligence Laboratory but what does the broader industry think? According to researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), working with machine-learning startup, PatternEx, the future of cyber-security could be part-human and part-bot. A newly published paper from MIT suggests that the prototype AI2 system it has developed combines machine learning with human analysis to end up with an 85 per cent successful cyber-attack prediction rate. The MIT researchers maintain that analyst-driven security systems miss too many attacks as they rely upon humans to create rules that have to be matched. On the other hand, machine-learning solutions rely upon anomaly-detection which is prone to triggering false positives and so lead to mistrust.

San Diego Brayan Valle was looking to buy some marijuana. When he reached out to a business associate of his uncle's, a drug connection, Valle became involved in a much more serious -- and novel -- offense. Rather than sell him the marijuana, the associate asked for Valle's help to smuggle drugs over the U.S.-Mexico border by drone. The case signals the first drone drug-smuggling seizure along the Southwest border. On Thursday, Valle, now 21, was sentenced to three years in prison for his role in operating the drone remote control and loading up 30 pounds of heroin dropped into a Calexico-area field on April 28.

The most realistic risks about the dangers of artificial intelligence are basic mistakes, breakdowns and cyber attacks, an expert in the field says – more so than machines that become super powerful, run amok and try to destroy the human race. Thomas Dietterich, president of the Association for the Advancement of Artificial Intelligence and a distinguished professor of computer science at Oregon State University, said that the recent contribution of 10 million by Elon Musk to the Future of Life Institute will help support some important and needed efforts to ensure AI safety. But the real risks may not be as dramatic as some people visualize, he said. "For a long time the risks of artificial intelligence have mostly been discussed in a few small, academic circles, and now they are getting some long-overdue attention," Dietterich said. "That attention, and funding to support it, is a very important step."

These use cases–and so many more–all owe a debt to machine learning. By automatically discovering patterns that lead to insights and creating predictive models that drive actions, the technology has proven its value many times, and to many industries. More recently, machine learning has begun to make a name for itself in the field of cybersecurity. There are multiple reasons that manual cybersecurity practices on their own are no longer sufficient to protect businesses, governments and other organizations. All of these issues are further aggravated by the fact that threats are growing in scale and complexity.

Predicting cyber attacks before they happen have two conventional approaches. One uses a set of indicators specified by an expert, and the other uses machines to detect abnormal activity. The problem with these approaches is that rules are often broken by criminals, and there is just too much abnormal activity flagged, even when these are not attacks. AI² is a collaboration between MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and PatternX, a machine learning startup with a focus on information security and threat prediction. The hybrid platform combines Artificial Intelligence, with Analyst Intuition, to give AI².

A program designed by MIT to battle hackers is example of effective artificial intelligence and human collaboration. South Korean professional Go player Lee Sedol puts the first stone against Google's artificial intelligence program, AlphaGo.