If you are someone who likes to keep a tab on all the latest dating trends, you would have probably come across the term "submarining," a nasty dating trend in the millennial world that can be considered the next step to "ghosting." To understand what submarining is, you will have to wrap your head around ghosting, which refers to the date disappearing from your life without any prior warning. This means that you could be getting close to a potential boyfriend or girlfriend, but that significant someone suddenly drops off the face of the earth. He or she will end all modes of communication with you, including calls, texts, and emails. You would end up getting blocked on all social media platforms, with your date, essentially turning into a ghost you once knew. Needless to mention, most cases of ghosting happen in relationships which started online or via dating apps like Tinder.

A couple years ago, Apple went on a shopping spree. It snatched up PrimeSense, maker of some of the best 3-D sensors on the market, as well Perceptio, Metaio, and Faceshift, companies that developed image recognition, augmented reality, and motion capture technology, respectively. It's not unusual for Cupertino to buy other companies' technology in order to bolster its own. But at the time, it was hard to know exactly what Apple planned to do with its haul. It wasn't until last month, at the company's annual talent show, that the culmination of years of acquisitions and research began to make sense: Apple was building the iPhone X.

TEPIC, MEXICO – Rocks under increasing pressure before earthquakes strike send out low-pitched rumbling sounds that the human ear cannot detect but could be used to predict when a tremor will strike, scientists said Monday. Researchers recreated powerful earthquake forces in a laboratory and used high-tech algorithms to pick out the acoustic clues amid all the other noise of a pending quake, according to findings published in Geophysical Research Letters, a journal published by the American Geophysical Union. The sounds are emitted typically a week before an earthquake occurs, so deciphering them would allow scientists to pinpoint the timing of a tremor, the research paper said. Scientists currently can calculate the probability of an earthquake in a particular area but not when it will happen, according to the U.S. Geological Survey. "People have said you can't predict earthquakes. We're now saying we believe for the first time we can predict an earthquake in a laboratory," said Colin Humphreys, professor of materials science at Cambridge University and one of the paper's authors.

Facebook disclosed last month it had found ads linked to fake accounts -- likely run from Russia -- that sought to influence the U.S. election. Facebook said the ads focused on divisive political issues such as immigration and gun rights in an apparent attempt to sow discord among the U.S. population.

Dr Matthew Howard is a director of AI at Deloitte in the UK. In his role, Matthew looks at how AI technology can benefit clients in the professional services space and within Deloitte's own business. In this blog, he outlines the opportunities and challenges facing professional services in implementing AI. Hear him speak at the'The big Alternative AI debate: Will the partnership model kill AI? Or will AI kill the partnership model?" at 4:45pm on 27 November at the Alternative AI event. AI is a broad umbrella that will impact a broad range of processes and industries – everything from language translation to medical advice. In an industry that relies on understanding vast amounts of data every day, AI can offer significant productivity benefits to professional services firms. Being able to correlate that data and make it meaningful – fast – is one of the most attractive advantages of AI. This is especially true as information analysis becomes increasingly commoditised and firms have ...

Despite our more rapid advances in machine learning, we are still far from developing a species of sentient machines or a confluence of technologies that would let each of us enjoy digital immortality. One of the most advanced artificially intelligent, humanoid robots to date is Hanson Robotics' Sophia, shown in Figure 1, which spoke at the AI for Good Global Summit in Geneva, Switzerland in June 2017. While, in recent years, the media have focused largely on computer-related technologies, we are entering what author and futurist Dr. Michio Kaku calls "the golden age of neuroscience." In his Wall Street Journal article on this topic, he acknowledges, "We have learned more about the thinking brain in the past 10 to 15 years than in all of previous human history." Genomics is another example of astonishing scientific advancement.

Two days after K.S. Sunil Kumar received a promotion, Human Resources phoned him up and asked him to resign. This happened in April, just as Kumar was beginning his ninth year at Tech Mahindra, one of the giants in India's IT services industry. He worked in engineering services, where he designed components and tools for aerospace firms in North America and Europe. They'd send over specs--the materials available to construct a hinge, and the kind of load it had to bear, and the cost at which it had to be manufactured--and he mocked up options with the help of software. He was a foot soldier in the army of Indian engineers to whom work is outsourced from the West, so that it can be finished at a fraction of the expense. Sometimes he left his base, Tech Mahindra's Bangalore campus, to serve stints at clients' offices abroad: in Montreal, Belfast, or Stockholm.

The AI has "already reduced false positives by 50%" Copenhagen-based Danske Bank has gone public on its deal with Think Big Analytics, the consulting arm of Teradata, to create and launch an artificial intelligence (AI) driven fraud detection platform. The announcement is all timed sweetly to be part of the Teradata Partners Conference 2017 (22-26 October), attended by Banking Technology and held in Anaheim, California. Teradata also revealed its new data analytics platform at the show – and unveiled two other initiatives – Analytics-as-a-Service and a new software portfolio. In terms of the engine, this uses machine leaning to analyse latent features, scoring online banking transactions in real-time to provide insight regarding true, and false, fraudulent activity. Nadeem Gulzar, head of advanced analytics, Danske Bank, says by using AI it has "already reduced false positives by 50% and as such have been able to reallocate half the fraud detection unit to higher value responsibilities".

Are we doing enough to get ready for the emergence of artificial intelligence as a major driving force for transformation in our economy? Forget the apocalyptic concerns of people like Elon Musk and Stephen Hawking for a moment and consider the very real and practical ways AI is already changing the way we do things, from chatbots for customer service through to driverless vehicles in industries like mining and agriculture. This stuff is already here and it's only going to accelerate as we start to understand and apply AI, machine learning and automation technologies across our industries. A new report from the UK government which looks into growing the AI industry is taking its potential as an economic driver very seriously. Are we doing the same here in Australia?

Probabilistic methods for classifying text form a rich tradition in machine learning and natural language processing. For many important problems, however, class prediction is uninteresting because the class is known, and instead the focus shifts to estimating latent quantities related to the text, such as affect or ideology. We focus on one such problem of interest, estimating the ideological positions of 55 Irish legislators in the 1991 D\'ail confidence vote. To solve the D\'ail scaling problem and others like it, we develop a text modeling framework that allows actors to take latent positions on a "gray" spectrum between "black" and "white" polar opposites. We are able to validate results from this model by measuring the influences exhibited by individual words, and we are able to quantify the uncertainty in the scaling estimates by using a sentence-level block bootstrap. Applying our method to the D\'ail debate, we are able to scale the legislators between extreme pro-government and pro-opposition in a way that reveals nuances in their speeches not captured by their votes or party affiliations.