Passengers' baggage is collected by robots, they relax in a luxurious waiting area complete with an indoor garden before getting a face scan and swiftly passing through security and immigration - this could be the airport of the future. It's a vision that planners hope will become reality as new technology is rolled out, transforming the exhausting experience of getting stuck in lengthy queues in ageing, overcrowded terminals into something far more pleasant. The changes also represent major challenges that could upend decades-old business models at major airports, with analysts warning operators may face a hit to their revenues to the tune of billions of dollars. Facial scanning in particular is generating a lot of buzz. Changi in the affluent city-state of Singapore, regarded as among the world's best airports, is set to roll out this biometric technology at a new terminal to open later this year.

Oaxaca, Mexico - The small village of San Pedro Sochiapam, deep in the mountainous region of the southern Mexican state of Oaxaca, is home to the Chinantec people. Here steep footpaths end at chicken coops and cornfields grow on mountainsides, while the villagers clear brush with machetes and children enjoy ice-cream cones from a stall near the town hall. But, in its day to day routines of life, this community is struggling to maintain a unique and important cultural tradition - whistling. "Chinantec whistled speech is a form of communication where people can really whistle whatever they can say in the spoken language, even though there's more ambiguity in the whistled channel," explains Mark Sicoli, a linguistics professor at the University of Virginia, noting that the presence and absence of glottal stops, tones, and stress patterns make it a particularly productive form of communication. The sounds carry across canyons better than a shout in sharp, birdlike chirps that allow people to make plans, negotiate, and chat without ever saying a word.

A new report claims that Facebook is testing out a new feature that appears to be very similar with Tinder. The new Facebook feature encourages users to meet up with their friends in real life, but only if both parties agree to do so. The new Facebook feature was first discovered by Motherboard reporter Jacob Dubé. He claims that while he was using Facebook, a notification popped up saying "[Name redacted] and 15 others may want to meet up with you this week." When Dubé opened the notification, it showed him a page with photos of his Facebook friends.

Machine learning is transforming business. But even as the technology advances, companies still struggle to take advantage of it, largely because they don't understand how to strategically implement machine learning in service of business goals. Hype hasn't helped, sowing confusion over what exactly machine learning is, how well it works and what it can do for your company. Here, we provide a clear-eyed look at what machine learning is and how it can be used today. Machine learning is a subset of artificial intelligence that enables systems to learn and predict outcomes without explicit programming.

The MEKA project provides an open source implementation of methods for multi-label learning and evaluation. In multi-label classification, we want to predict multiple output variables for each input instance. This different from the'standard' case (binary, or multi-class classification) which involves only a single target variable. MEKA is based on the WEKA Machine Learning Toolkit; it includes dozens of multi-label methods from the scientific literature, as well as a wrapper to the related MULAN framework. NEW RELEASE April 12, 2017: Meka 1.9.1 is released.

In October 2013, Lauri Love was drinking coffee in his dressing gown in his bedroom at his parents' house in the village of Stradishall, Suffolk, when his mother called upstairs to say there was a deliveryman at the front door. Love, whose first name is pronounced "Lowry", like the English painter, clomped downstairs. In the front doorway was a man dressed in a UPS uniform. "Are you Lauri Love?" the man asked. In a single motion, the man grabbed Love's arm while presenting, not a package, but a pair of rattling handcuffs. For the next five hours, while dusk turned to evening outside, Love, then 28, and his parents sat in the front room as a dozen or so men from the National Crime Agency, which investigates organised crime and other serious offences, checked the computers in the house. In Love's bedroom, they found two laptops, and a PC tower humming on his desk. Among the bewildering Rolodex of open tabs in Love's internet browsers, the officers found accounts logged into several hacker forums and arcane internet chatrooms. Downstairs, Love, who knew that anything said in these limbo moments of investigation could be later used against him, kept the conversation to small talk about the weather and football. A little before midnight, Love was told that he was being arrested on suspicion of offences under the 1990 Computer Misuse Act, which covers, among other things, criminal hacking. He was not informed of what crimes he had allegedly committed, and was pressed into the back of an unmarked car, and driven to the police investigation centre in Bury St Edmunds. Love's computers, along with USB drives and old computing hardware, much of which belonged to his father, a computing enthusiast, left, too. Love, who was subsequently diagnosed with Asperger syndrome – a form of autism that causes him to fret and obsess – did press-ups in his cell until, in the early hours of the morning, he fell into a brief and fitful sleep.

Chatbots are about to change the world in more ways than we can imagine. Already, bots around the globe can complete a diverse set of varying tasks. From ordering pizza online to mashing faces together in Project Murphy, chatbots are about to become a normal element in everyday life. As the scope of chatbots becomes broader every day, there are new applications popping up constantly. Education has traditionally been known as a sector where innovation moves slowly.

A team of international researchers is urging people to share their selfies in order to help teach computers how to read faces and identify people with rare diseases. The Minerva and Me project - being led by Oxford University with the help of international researchers like WA Health clinical genetist Gareth Baynam - is seeking to use technology to spot rare diseases faster and more accurately. The crowd-sourced research initiative wants to build a database of photographs so the researchers can develop facial recognition software using machine learning algorithms that can identify rare diseases. The software would be able to suggest a disease condition and prompt further tests that could be used to help settle on a diagnosis - potentially reducing the instances of incorrect diagnosis. "We think computers can be used to help diagnose individuals who have particular diseases. To do this we are training computers to look at photographs of peoples' faces to try to identify combinations of subtle changes that might together be indicators of a specific disease," the researchers say.

How did one Harley-Davidson dealership in New York City go from selling one or two bikes a week to selling 15 in a weekend? Owner Asaf Jacobi took a risk on Adgorithms' 'Albert', an artificial intelligence (AI) driven marketing platform that works across digital channels. The results saw the dealership increasing leads by 2930% by the third month and driving Jacobi to set up a new call centre to handle all the new business. Albert can learn as he does and is able to "identify the audiences most likely to convert, eliminate low-value audiences, apply insights gained from one channel to other channels", according to Harley-Davidson NYC. The AI works with campaign creative and KPIs provided by the brand to autonomously execute holistic digital ad and marketing campaigns.

Is the evolution of artificial intelligence a threat to medical practitioners? Far from it, argues Jack Stockert, M.D., in Stat. Rather, A.I. will ease physicians' ever-growing clerical burden, including electronic health record entry, prior authorizations and claims management. That, he asserts, will give doctors more time to "practice medicine, do research, master new technology and improve their skills." Stockert, an executive at a Silicon Valley innovation company, says that "combining human expertise and automated functionality creates an'augmented' physician model that scales and advances the expertise of the doctor."