I believe that the answer to that question is hidden behind what Google and Facebook have been showing us recently. It began when Facebook opened their Messenger platform to Chatbots. While huge amount of developers are currently playing with this new toy, it's still very much pre-mature. But it's growing rapidly, as Facebook is clearly taking the "move fast, keep shipping" approach, by continuously iterating and improving the platform. In my previous post, I wrote about my very own experiment and ended up with my wish list, mainly about ways Facebook should enable developers to improve the User Experience, Discovery and Distribution of their Chatbots.

Imagine receiving a phone call from your aging mother seeking your help because she has forgotten her banking password. The voice on the other end of the phone call just sounds deceptively like her. It is actually a computer-synthesized voice, a tour-de-force of artificial intelligence technology that has been crafted to make it possible for someone to masquerade via the telephone. Such a situation is still science fiction -- but just barely. It is also the future of crime.

Driverless cars are the most pressing AI-related consideration for the insurance industry, with recent advances from the likes of Google, Uber, and Volvo making it likely they will dominate the roads within the next decade. In June, British insurance company Adrian Flux began offering the first policy specifically geared towards autonomous and partly automated vehicles. The policy covers typical car insurance staples such as damage, fire, and theft, as well as accidents specific to AI - loss or damage as a result of malfunctions in the car's driverless systems, interference from hackers who have got into a car's operating system, failure to install vehicle software updates and security patches, satellite failure or outages affecting navigation systems, or failure of the manufacturer's vehicle operating system or other authorised software.

While you likely have at least a vague sense that artificial intelligence is the future of the devices and services around you, you may or may not know much about the specific technologies that enable machines to process data and react intelligently -- such as by recognizing objects or translating speech in real-time. The concept of deep learning, a technology that MIT Technology Review reports "attempts to mimic the activity in layers of neurons in the neocortex, the wrinkly 80 percent of the brain where thinking occurs" -- can be especially difficult to wrap your head around. Curious about deep learning, and what you need to know about it? Here's exactly how the stuff of science fiction films is coming to life. Deep learning software learns to recognize patterns in digital representations of sounds, images, and other data.

The judicial decisions of the European Court of Human Rights (ECtHR) have been predicted to 79% accuracy using an artificial intelligence (AI) method developed by researchers at UCL, the University of Sheffield and the University of Pennsylvania. The method is the first to predict the outcomes of a major international court by automatically analysing case text using a machine learning algorithm. The study behind it was published today in PeerJ Computer Science. "We don't see AI replacing judges or lawyers, but we think they'd find it useful for rapidly identifying patterns in cases that lead to certain outcomes. It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights," explained Dr Nikolaos Aletras, who led the study at UCL Computer Science.

A series of algorithms dubbed the Nightmare Machine is an effort to find the root of horror by generating ghoulish faces, and then relying on user feedback to see which approach makes the freakiest images. MIT also used Google's DeepDream method to create ghastly portraits of famous locations around the world, just in time for Halloween. It's easiest to think of the fear-generating AI as a complex black box that draws a best fit line. When given the task of creating something, it generates an image based on everything it has seen before: in this case, scary faces. Each "scary" or "not scary" vote in MIT's game pulls the best fit line slightly in some direction: more teeth, paler skin, darker background.

Artificial intelligence (AI), which many experts predict will have an enormous impact on the travel industry, is becoming a reality not in the form of blockbuster apps but as a slow, steady trickle of apps, features and technological innovations. The pace of its progress was measured recently by a London School of Economics study, which identified AI and big data as "key disruptive factors shaping the travel distribution industry over the next decade." But the resulting report also noted that those factors have yet to spark major changes. More and more companies are developing and using AI technology today, and experts agree that a recognizable impact isn't too far off; it will begin trickling into agents' workflows over the next several months. "It's definitely not going to be like a flip switch -- one day there's no AI and the next day there's AI," said Paul English, co-founder of the travel agency Lola, where agents use AI to augment their workflows on a daily basis.

In spite of warnings from some of the world's smartest people, engineers at the Massachusetts Institute of Technology have developed a very scary AI. To be more specific, they've built a deep learning algorithm to teach an AI what various kinds of spooky image look like, so that it can tweak other images to make them look spookier. They call it the'Nightmare Machine'. It's learnt a number of styles, from'Fright night' to'Inferno', which the team has applied to a bunch of famous landmarks from around the world. There are a bunch more examples over on the team's Instagram account.

While IBM has invested heavily in Watson, and the artificial intelligence technology is paying off in innovations within healthcare and other sectors, it's performing less brilliantly for the company's bottom line, at least so far. "IBM has pursued big, bespoke moonshot initiatives that can take years and are extremely expensive," Gartner research fellow Tom Austin told The New York Times. "It seems like they're swimming upstream with that." According to the article, the company believes more lucrative times lie ahead. IBM points to a collaboration announced Oct. 18 with Quest Diagnostics, Memorial Sloan Kettering Cancer Center and the Broad Institute of MIT and Harvard as an example.