U.S. drone strikes against suspected al-Qaida targets have been commonplace in the years since the Sept. 11, 2001 attacks on New York and Washington, as a retaliatory measure against the group. The use of unmanned aircraft as well as air strikes in the Arab world's poorest country rose dramatically under President Barack Obama, with data from the Britain-based Bureau of Investigative Journalism showing spikes in attacks, especially in 2012 and 2016.

Despite spending more money on security than ever, organisations struggling with a widespread cybersecurity skills gap are often told how technologies like big data, analytics, machine learning, and artificial intelligence can aid them in protecting their data or critical infrastructure from attackers. Organisations ranging from startups to established large corporations are investing in the building of AI systems to bolster defences by analysing vast amounts of data and helping cybersecurity professionals identify far more threats than would be possible if they were left to do it manually. But the same technologies that improve corporate defences could also be used to attack them. It's the simplest method of cyberattack available -- and there are schemes on the dark web which put all the tools required to go phishing into anyone's hands. It's simply a case of taking an email address, scraping some publicly available personal data to make the phishing email seem convincing, then sending it to the victim and waiting for them to bite.

SANAA, Yemen – Yemeni security and tribal officials say suspected U.S. drone strikes have killed three alleged al-Qaida operatives in the country's southwestern Bayda province. They say the two Saturday strikes killed Abu Anis al-Abi, an area field commander, and two others. They spoke on condition of anonymity as they were not authorized to release the information. U.S. drone strikes against suspected al-Qaida targets have been commonplace in the years since the Sept. 11, 2001 attacks on New York and Washington as a retaliatory measure. Saturday's strikes were the first to be reported since Donald Trump assumed office as Barack Obama's successor.

The Tesla Model S is an extraordinary machine. As part of my research into the regulation of self-driving cars, I've had the privilege of driving one. Or more accurately, I've had the privilege of being driven by one. On a Colorado highway in July, with some trepidation, I flicked the lever to engage Autopilot mode. I told the representative from Tesla that I was worried about handing over control, taking my feet off the pedals and my hands off the wheel.

Artificial Intelligence (AI), machine learning and automation are technology trends dominating discussions in many different industries at the moment and cyber security is no exception. As cyber criminals become more advanced and the threat landscape continues to develop, businesses are looking to new technologies that can help secure their organisation in a more proactive way. According to Dave Palmer, director of technology at Darktrace, this move to the so-called "age of automation" is an inevitable and much needed one: "When you think about networks getting faster and big data, it's been just as useful for the bad guys as it has for the good guys, but machine learning changes that. This whole era of automation and machine learning is going to be about handing complex problems off to the machines to do some of that solving for us and bringing humans out. "Not that the attackers won't benefit in some ways from that, but on balance, overwhelmingly this is an area of science that is much more of benefit to defenders than attackers and that is really the first time we've seen that." What's clear is that the traditional model of endpoint protection through the likes of antivirus software is no longer enough, as Palmer explained: "People are falling out of love with the idea that year on year generation of improved perimeter defenses is making a difference.

Our analysis includes companies applying AI algorithms to verticals like healthcare, security, advertising, and finance as well as those developing general-purpose AI tech. Our analysis includes all equity funding rounds and convertible notes. In addition, auto tech company and unicorn Zoox raised $200M in Series A in Q2'16 and cybersecurity startup StackPath raised a $180M private equity round in Q3'16. Last quarter also saw 4 mega-rounds: $130M Series B round raised by life science startup Zymergen, $120M Series B round raised by computer vision startup SenseTime, $100M Series C round raised by facial recognition startup Face, and a $100M round raised by Israel-based Voyager Labs.

The capabilities of artificial intelligence and machine learning are accelerating, and many cybersecurity tasks currently performed by humans will be automated. There will still be plenty of work to go around so job prospects should remain good, especially for those who keep up with technology, broaden their skill sets, and get a better understanding of their company's business needs. Cybersecurity jobs won't go the way of telephone operators. Take, for example, Spain-based antivirus company Panda Security. When the company first started, there were a number of people reverse-engineering malicious code and writing signatures.

"The Automatic Emergency Braking (AEB) or Autopilot systems may not function as designed, increasing the risk of a crash." It's a simple sentence, delivered with the calm finality of bureaucratic certainty. It is a literal post-mortem, the bottom-line-up-front from the National Highway Traffic Safety Administration's investigation into the first fatal crash of an autonomous car--one made by Tesla Motors. The investigation into the crash closed today, and it will likely cast a long shadow over the future of self-driving cars, which have long been heralded as potentially life-saving devices. There was no particularly unique flaw to the Tesla that Joshua Brown, of Canton Ohio, was driving on May 7th, 2016.

Photo taken on Jan. 17, 2017 shows Xuewei Qi, a leading researcher at the University of California, Riverside, is using vehicle connectivity and evolutionary algorithms to improve the efficiency of Plug-In Hybrid Electric Vehicles.

One of the highlights at this year's Consumer Electronics Show (CES) was the parade of new connected vehicle technologies. Automakers and their suppliers rolled out a number of innovative capabilities that promise to shape the next generation of driving, make transportation safer and more efficient, revitalize our cities, and reduce air pollution. Often lost amidst the "oohs" and "ahhs" these new capabilities inspire, however, is their dependence on radio spectrum and the policies that govern its use. The new connected vehicle capabilities come in decidedly different flavors. Some, for example, seek to enhance the automobile user's experience.