A recent project entitled'Your face is big data' saw an art school student photograph people who happened to sit across from him on the subway and then he used FindFace, a facial recognition app that taps neural-network technology, to track them down on Russian social media site VK. The FindFace service was designed for users of the largest Russian social network "Vkontakte" and is based on face recognition technology developed by N-Tech.Lab. According to a report by PC World, the Rodchenko Art School student said it was ridiculously easy to find 60 to 70 percent of the subjects aged between 18 and 35, and, along the way, he said he learned a lot about the lives of complete strangers. "My point in this art project is to show how technology breaks down the possibility of private life," he said. More details and photographs from the art project can be found here.

Turning data into insight is one of the top business challenges today, and it becomes especially tricky when the data in question is unstructured. Artificial intelligence has a mixed track record there, but a young startup aims to get better results by bringing humans back into the picture. Spare5 on Wednesday released a new platform that applies a combination of human insight and machine learning to help companies make sense of unstructured data, including images, video, social media content, and text messages. The result, it says, are "game-changing insights delivered cost-effectively and at scale." The company's technology is now being used by companies including Expedia and Getty Images to enrich, clean and label unstructured data.

Let's say you're scrolling through your favorite social media app and you come across a series of pictures of a man in a tuxedo and a woman in a long white dress. An automated image captioning system might describe that scene as "a picture of a man and a woman," or maybe even "a bride and a groom." But a person might look at the pictures and think, "Wow, my friends got married! As image captioning tools get increasingly good at correctly recognizing the objects in an image, a group of researchers is taking the technology one step further. They are working on a system that can automatically describe a series of images in the same kind of way that a human would, by focusing not just on the items in the picture but also what's happening and how it might make a person feel. "Captioning is about taking concrete objects and putting them together in a literal description," said Margaret Mitchell, a Microsoft researcher who is leading the research project. "What I've been calling visual ...

Pundits opine about how automation technologies will eliminate certain jobs, fueling a rise-of-the-machines kind of fear and loathing among tech workers. Horror story scenarios aside, evidence suggests it's far more likely that automation will augment rather than replace most jobs. Witness the financial services sector, where sophisticated algorithms called "roboadvisors" pair with humans to offer investment advice. The Vanguard Group, a power in mutual and exchange-traded funds with 3.2 trillion in global assets, has written custom software that offers clients tailored investment advice, a new but crowded market for a company whose clients are largely self-directed. But while many roboadvisors act alone, Vanguard pairs them with humans, creating a hybrid model that marries algorithmic portfolio planning and relies on human financial advisors to provide a white-glove touch.

Digital engagement is once again shifting, as we can see from the main discussions at Facebook's F8 conference this week about the new release of Messenger and its smart chatbots, or when we look at what's happening with popular team messaging services like Slack, which is being "overrun by friendly, wonderful bots." While bots seem like a minor improvement to digital user experience, some believe -- including myself -- that a combination of today's latest technologies will transform this what's-old-is-new-again technology into a major new force in contemporary digital experience and social engagement. Over the last couple of years, conversing in everyday language with our digital devices has become relatively commonplace with the advent of widely used digital concierge services like Siri, Google Now, and Amazon Echo. Known more formally as'conversational user experiences (UXs)', this dialogue-based interaction model actually has quite a long history going way back to command-line programs like Eliza and Zork (both of which yours truly spent far too much time with when younger), the first commercial expert systems in the 1980s, IRC bots, and other early examples. While there's always been an assumption that bots had a bit code behind them with a little situated intelligence -- from performing simple services like scheduling reminders via IM all the way up to the first textual AI-based systems such as MYCIN for helping doctors diagnose infections -- most conversational interfaces tend to be relatively simple affairs with a little bit of basic natural language processing connected to a decision tree.

Facebook has seemingly positioned artificial intelligence as one of the catalysts for innovation for the company over the next 10 years. Outlining its technology roadmap for the next 10 years, the company highlighted artificial intelligence, as well as virtual and augmented reality, as technologies to drive new features and user experience. New features highlighted include translation, photo image searches, 'talking pictures' and real-time video classification. "Artificial Intelligence will power all kinds of different services with better than human level perception and we'll see the emergence of the next major computing platform in virtual and augmented reality," said Facebook founder Mark Zuckerberg during his opening keynote at F8. "These are all elements of our 10 year roadmap to connect the world and each of these elements is in service of our mission. It's about bringing people together, that's what we do here."

Japan's Sharp will launch in May a smartphone that's built into a humanoid robot. Or is it a humanoid robot with a built-in smartphone? The Robohon is said to be the world's first mobile robotic phone -- and judging from the price and slightly unwieldy form factor could also be the last. It's 19.5 centimeters (7.7 inches) tall and weighs 390 grams (13.8 ounces), making it several times the size and weight of a conventional smartphone, and it will cost 198,000 yen, which is just over US 1,800 and more than double the price of a high-end iPhone. But those shortcomings are more than made up in cuteness.

Machine learning often involves a trade-off between accuracy and interpretability. Models that are easy to understand perform poorly, while models that perform well tend to be hard to understand. This can be a show-stopper in many contexts. It can be risky or legally dubious to deploy a model you don't understand in a commercial environment. Interpreting a model is often the whole point of using machine learning in science.

Microsoft has developed a new artificial intelligence (AI) system capable of analysing and describing pictures automatically. The program, now available to try on the company's website, has been named CaptionBot by the Microsoft Cognitive Services team, and it works surprisingly well. Users can upload any image to CaptionBot and have it return a description in seconds. It manages this by using image and face analysing programs, as well as a language processor which returns descriptions in understandable English. The program isn't entirely spot-on all the time, but it's generally close enough to be impressive.

The biggest leak in history has connected more than 70 current and former world leaders to tax evasion schemes that channel billions of pounds into secretive off-shore accounts. This is how the data was analysed. The Panama Papers show that law firm Mossack Fonseca helped hundreds of clients, with connections to some of the most powerful people in the world, launder money, dodge tax and potentially avoid sanctions. The papers themselves were leaked to news organisations by an unknown person and have been shared with more than 100 news organisations and 400 journalists – the investigation has been ongoing for almost a year. The process of making the raw data accessible for journalists involved converting it to digital formats, high-performance computers, and algorithms to find well known names among the thousands of details. While the actual leaked documents have not been published -– the International Consortium of Investigative Journalists (ICIJ) say the full list of companies linked to the papers will be revealed in May – how much data they contain is known.