Don't trust vendors' marketing materials to help you find a workable, accurate definition. "It's almost criminal, the use of these terms by the vendors today," says Kris Lovejoy, CEO of security firm BluVector. "Pretty much anybody that has analytics embedded in their system is calling it a form of AI. It's confusing the marketplace, and frankly, I think it's incredibly unfair to the consumer." So what exactly is artificial intelligence?

When Google unveiled its $249 Clips camera back in October 2017, it was easy to question Google's motives. Lifelogging cameras weren't a new idea, nor were they particularly successful, and given the rise in smartphone imaging and video quality, it was a tough ask to let a wearable camera automatically capture important moments. With Clips expected to debut in the coming weeks, Google has penned a blog post (first detailed by The Verge) detailing how it's trained its algorithms to identify the best shots. In order to do that, its AI needed to learn from something or someone, so Google called in photography experts from various different backgrounds and supplied their model with some of the best photography available. "We ended up discovering--through trial and error and a healthy dose of luck--a treasure trove of expertise in the form of a documentary filmmaker, a photojournalist, and a fine arts photographer," said Josh Lovejoy, Senior Interaction Designer at Google.

"We ended up discovering--through trial and error and a healthy dose of luck--a treasure trove of expertise in the form of a documentary filmmaker, a photojournalist, and a fine arts photographer," said Josh Lovejoy, Senior Interaction Designer at Google. "Together, we began gathering footage from people on the team and trying to answer the question, 'What makes a memorable moment?'" Some of that learning comes down to principles that you may have learnt as you've struggled to get to grips with a new smartphone camera or point-and-shoot. Understanding focus, particularly depth of field, and the rule of thirds are key, but so are some more "common sense" suggestions. Everybody knows to keep fingers out of the shot and to not make quick movements, but machine learning algorithms have no such understanding.

A new exhibition at Science Gallery Dublin is exploring what an automated world might look like. There's a lot of discussion around the future of work, particularly when it comes to AI and robotics becoming more integrated into the workplace. Many experts are confident that advances in AI will, contrary to popular belief, actually create more jobs than it will get rid of. Those experts have also quelled our fears about certain elements of human behaviour being usurped by intelligent, human-like bots. Sure, they can analyse data at the drop of a hat and a lot of monotonous administration can be automated, but robots don't have the level of creativity or emotional intelligence that humans have, right?

August saw the Defense Advanced Research Projects Agency (DARPA) host its first Cyber Grand Challenge – the first hacking competition not involving people. During this event, teams left their systems alone to single-handedly find, diagnose and fix software flaws in real time. Elsewhere, researchers at MIT are not only developing machine learning systems that automatically mine dark web marketplaces for vulnerabilities and zero-day attacks and reports them back as well as software that automatically fixes buggy code, but also a platform that can predict 85% of cyber-attacks. Machine learning, deep learning, and Artificial Intelligence (AI) are hot topics at the moment, and while there's plenty of research going on, there's also some practical applications that can be deployed right now to make life easier for cybersecurity professionals. A glut of new start-ups, from the likes of Darktrace, Cylance, Deep Instinct, and HackerONE, plus established player such as FireEye, IBM, and Forcepoint, are all working on bringing self-learning systems into the world of security.