In H. G. Wells's classic The War of the Worlds, the narrator pauses a moment to rue the fact that he didn't react sooner to the arrival of an "intelligence greater than man's"--in his case, Martians landing on earth. Comparing himself to a comfortable dodo in its nest, he imagined those ill-fated birds also dithering as hungry sailors invaded their island: "We will peck them to death tomorrow, my dear." As intelligent technologies take over more and more of the decision-making territory once occupied by humans, are you taking any action? Are you sufficiently aware of the signs that you should? To help you get the head start you may need, here are the signs that it's time to fly the nest.

Before Chris White could help disrupt Jihadi finance networks, crush weapons markets, and bust up sex-slave rings with search tools that mine the dark Web, he first had to figure out how to stop himself from plummeting through the open gun door of a banking Black Hawk helicopter. White was on his way to a forward operating base outside Kabul headquarters, as part of a secret intelligence cell to help confront the Taliban and al-Qaida, smash their encrypted online money stream, and win over the hearts and minds of the Afghanistan population. Slight and lanky and 28, White felt Dukakis-ridiculous in his unwieldy body armor and bulbous helmet with "Dr. White" scrawled in marker on duct tape across the front, and with the dust from liftoff, he was finding it hard to breathe. He was still struggling with the unfamiliar seat straps when the pilot hit the stick, sending White sliding toward the hot square of the door and the desert 200 feet below. Down there, Afghanistan was a messy, dangerous place for pretty much everybody. After nearly a decade of U.S.-led war, the American body count had hit 1,000, and civilian casualties were beyond calculation, as President Obama's 30,000-troop surge intensified the fighting that spring. Many feared the situation was only going from bad to worse. The U.S. was escalating drone strikes across the border in Pakistan. And U.S. command was under assault after Gen. Stanley McChrystal, the surge's architect, found himself without a job after he and his staff made disparaging remarks about the commander in chief in some music magazine. It is hard to imagine that only a few weeks earlier, White had been just another impossibly young-looking Harvard postdoc in flip-flops looking forward to a Cambridge summer. Helicopter gunships and war zones weren't on the radar; there were lattes in the square and rock climbing, and on the other side of campus, a prestigious fellowship in the School of Engineering and Applied Sciences, where he was working at the intersection of big data, statistics, and machine learning. He had earned academic pole position and had every expectation it would continue that way forever -- becoming a professor, building a lab, and sniping out white papers from a tenured ivory tower.

The car company announced last week that it would no longer use a vision system provided by MobileEye, an Israeli company that supplies technology to many automakers. This comes a few weeks after the National Highway Traffic Safety Administration announced that it was investigating a fatal accident that occurred while one of Tesla's cars was operating in Autopilot mode, a system designed to enable automated driving under a driver's supervision. It is unclear why Tesla is dropping MobileEye, but one reason may be the emergence of newer approaches to automated driving. MobileEye provides what amounts to an advanced image-recognition system, capable of identifying road signs or obstacles, such as other cars or pedestrians, on the road ahead. The company has said that it uses deep learning, a popular machine-learning technique based on training a many-layered network of simulated neurons to recognize input using a large number of training examples.

This article was originally published by the World Economic Forum. The doomsday scenarios spun around this theme are so outlandish--like The Matrix, in which human-created artificial intelligence plugs humans into a simulated reality to harvest energy from their bodies--it's difficult to visualize them as serious threats. Meanwhile, artificially intelligent systems continue to develop apace. Self-driving cars are beginning to share our roads; pocket-sized devices respond to our queries and manage our schedules in real-time; algorithms beat us at Go; robots become better at getting up when they fall over. It's obvious how developing these technologies will benefit humanity. But, then, don't all the dystopian sci-fi stories start out this way?

Any business that sells goods or services online is vulnerable to attack by fraudsters. This can be using stolen credit card details for purchases online, creating false accounts and even voucher code abuse. The cost of this fraud can be calculated in the multi millions, with chargebacks and related costs plaguing online businesses. In the UK it is the most common crime of all, with 2.47M offences in 2015/16 alone. The traditional approach to tackling this problem is to use heuristic rules and business logic to try to'predict' whether a new transaction that the business is seeing is fraudulent or not.

No company is immune to cyber criminal activity. In 2013, Target was hacked despite receiving as many as 10,000 security alerts per day. While Target is a Fortune 100 retailer, even medium-sized companies have to sift through hundreds of thousands of alerts each year. Alerts are investigated before being categorized as false positives and ultimately ignored, but most alerts are idiosyncratic to a product or application with little context of the overall business impact. To prevent financial and reputational loss, security teams are driven to find the most critical needles in an ever-growing haystack of security information.

Intel just announced a pending acquisition of Movidius, a chip manufacturer focusing on integrated system-on-chip solutions for machine learning and computer vision. It could be a key part towards building a standalone VR headset, and more. Cylance is an innovator, and they realise one thing most cybersecurity providers don't - most new malware is just a variant of everything currently on the scene. With that in mind, and with so many different combinations of the same thing, the question becomes: how do you manage this massive amount of data?

William Santana Li imagines a future where robots will keep Americans safe. Communities, he dreams, will take security into their own hands by investing in wheeled machines that patrol streets, sidewalks and schools -- instantly alerting residents via a mobile app of intruders or criminal behavior. "What if we could crowd-source security?" said Li, co-founder and chief executive of a robotics company, Knightscope, that hopes to eventually do just that. His question is like many posed by Silicon Valley entrepreneurs seeking to modernize, privatize and monetize services once entrusted to the government -- and it's one that has intrigued venture capitalists who have pumped 14 million into his start-up. Already, Knightscope robots are edging into the private security industry, patrolling parking lots, a shopping center and corporate campuses in California.

The next president will have a range of issues on their plate, from how to deal with growing tensions with China and Russia, to an ongoing war against ISIS. But perhaps the most important decision they will make for overall human history is what to do about autonomous weapons systems (AWS), aka "killer robots." The new president will literally have no choice. It is not just that the technology is rapidly advancing, but because of a ticking time bomb buried in US policy on the issue. In 2012, the Obama administration created Department of Defense Directive 3000.09, which sets policy on how the Pentagon handles the questions of this new technology.

Based on the disturbing number of successful data breaches over the past few years, it's pretty evident that organizations are being overwhelmed by the growing number of threats. However, a new breed of security solution has sprung up, offering to apply machine learning to enterprise security. These tools deliver the ability to analyze networks, learn about them, detect anomalies and protect enterprises from threats.