A computer program has been developed that can tell if a person is lying by analysing linguistic cues in emails, texts and even online dating profiles. Researchers from City University in London detailed their findings in a paper set to be published in Journal of Management Information Systems. The paper, titled "Untangling a Web of Lies: Exploring Automated Detection of Deception in Computer-Mediated Communication," describes tell-tale signs that someone is lying. Deceitful emailers have a tendency to avoid personal pronouns--such as "I" and "me"--while also including language that flatters the recipient. The paper's authors say their findings could be used within a business context, to identify corporate deception and spot when a customer might not be telling the truth.

In 2012, Dennis Mortensen had 1,019 meetings, each of which required an average of roughly eight back-and-forth emails to schedule. Every time Mortensen comes across a contact interested in meeting with him, the CEO and founder of New York City-based artificial intelligence firm x.ai simply sends them a return email copying Amy, who takes care of the rest. "In raw numbers, I've saved about an hour every day -- an hour which I would otherwise have to use in really rudimentary work where I add not much value," Mortensen said of Amy's help scheduling meetings. Virtual assistants like Amy are becoming more common. Just as household technology platforms like Apple's "Siri" and Microsoft's "Cortana" has helped consumers navigate their lives more easily, other forms of rudimentary artificial intelligence platforms are starting to proliferate the market, many of them upending traditional business roles.

Society is caught between blind faith in technology and resistance to progress, between technological possibilities and fears that it has a negative impact. Increasingly Artificial Intelligence, the latest buzzword for everything software related, is stirring up much of the fears. In an interesting paper: Is This Time Different? The Opportunities and Challenges of Artificial Intelligence, Jason Furman, Chairman of President Obama's Council of Economic Advisers sets out his belief that we need more artificial intelligence but must find a way to prevent the inequality it will inevitably cause. Despite the labor market challenges we may need to navigate, Furman's bigger worry is that we will not invest enough in AI.

Robot" begins a second season on USA on Wednesday night with a two-part opener broadcast back to back. A conspiracy thriller set in the present day – it's still 2015 on the series' clock – it's science fiction in the sense that it involves technology, but not in the quasi-supernatural manner of flying saucers, Godzillas, time travel or synthetic human or mutant superheroes and such. Still, it shares with much sci-fi a sense of the ordinary world pushed a click toward the uncanny. Into every generation a confused and disaffected hero is born. Robot" it's Elliot Alderson (Rami Malek), a cyberwhiz who was recruited – Season 1 spoilers ahead – to the underground hacking collective fsociety by a person (Christian Slater) who turned out to be his father, who turned out to be dead, a figment of his imagination projected wholly into his world, though invisible to everyone else – a "Sixth Sense" move, dramatically. Robot' season premiere hit online three days early, then got pulled back » Of course, imaginary characters have as much substance in fiction as "actual" ones, so things do get muddled, and I would not be surprised to learn that I have got things in this show upside-down or backward.

Our next meetup will be a series of presentations on hyperparameter optimization and how to use various software packages to find a set of optimal hyperparameters for your machine learning model. Model selection via hyperparameter optimization is an important part of machine learning and we will discuss both the very basic and sophisticated methods for tuning models. Speaker: Erin Craig Title: Hyperparameter Optimization: Grid Search and Bayesian Optimization Abstract: When building a model, how do you select its hyperparameters? Grid search and bayesian optimization are two common methods for hyperparameter optimization; each with its own set of strengths and drawbacks. We begin this talk with a brief overview of these two methods, and then look at a case study to compare results of manual tuning, grid search and Bayesian optimization when predicting 30-day readmission from electronic health records.

Although financial terms of the deal were not revealed, it's said that an undisclosed number of SalesPredict employees will be joining eBay's team, working out of the Israeli development center in Netanya, including SalesPredict chief executive Yaron Zakai-Or, who will be director of product management for technology, and chief technology officer Kira Radinsky, who's been named director of data science and the chief scientist for eBay in Israel. Founded in 2012, SalesPredict specializes in helping businesses grow revenue through analytics that identify ideal potential prospects, thereby improving conversion to actual customers. It follows similar moves, including its pickup of AI startup ExpertMaker in May. In a statement, Zakai-Or explained that by being a part of eBay, "we will help arm eBay sellers with more information about the value of items, ultimately helping to increase customer sales conversions." The inclusion of SalesPredict seems to match the second part of this strategic effort.

Artificial intelligence systems are built by humans using training data that one way or another comes from humans, optimized for goals that humans set. The classifications and actions AI systems take then affect humans. As we build machines to make our lives better and easier, it's always important to ask whose lives it's making better and in which ways. AI systems are not free from ideology and ethics. Most optimistically, working on these systems can teach us more about all of the different ways to be human.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

There are three buckets of jobs right now, and each one will be affected by artificial intelligence.

AlphaGo's uncanny success at the game of Go was taken by many as a death knell for the dominance of the human intellect, but Google researcher David Silver doesn't see it that way. Instead, he sees a world of potential benefits. As one of the lead architects behind Google DeepMind's AlphaGo system, which defeated South Korean Go champion Lee Se-dol 4 games to 1 in March, Silver believes the technology's next role should be to help advance human health. "We'd like to use these technologies to have a positive impact in the real world," he told an audience of AI researchers Tuesday at the International Joint Conference on Artificial Intelligence in New York. With more possible board combinations than there are atoms in the universe, Go has long been considered the ultimate challenge for AI researchers.