This image, from a 1962 internal General Electric document, conveyed the idea of random access storage using a set of "pigeon holes" in which data could be placed. Fifty-three years ago a small team working to automate the business processes of the General Electric Company built the first database management system. The Integrated Data Store--IDS--was designed by Charles W. Bachman, who won the ACM's 1973 A.M. Turing Award for the accomplishment. Before General Electric, he had spent 10 years working in engineering, finance, production, and data processing for the Dow Chemical Company. He was the first ACM A.M. Turing Award winner without a Ph.D., the first with a background in engineering rather than science, and the first to spend his entire career in industry rather than academia.

Bots (short for software robots) have been around since the early days of computers. One compelling example of bots is chatbots, algorithms designed to hold a conversation with a human, as envisioned by Alan Turing in the 1950s.33 The dream of designing a computer algorithm that passes the Turing test has driven artificial intelligence research for decades, as witnessed by initiatives like the Loebner Prize, awarding progress in natural language processing.a Many things have changed since the early days of AI, when bots like Joseph Weizenbaum's ELIZA,39 mimicking a Rogerian psychotherapist, were developed as demonstrations or for delight. Today, social media ecosystems populated by hundreds of millions of individuals present real incentives--including economic and political ones--to design algorithms that exhibit human-like behavior. Such ecosystems also raise the bar of the challenge, as they introduce new dimensions to emulate in addition to content, including the social network, temporal activity, diffusion patterns, and sentiment expression. A social bot is a computer algorithm that automatically produces content and interacts with humans on social media, trying to emulate and possibly alter their behavior. Social bots have inhabited social media platforms for the past few years.7,24

After great promise in the 1960s that machines would soon think like humans, progress stalled for decades. Only in the past 10 years or so has research picked up, and now there are several popular products on the market that do a decent job of at least recognizing spoken speech. For Björn Schuller, full professor and head of the chair of Complex and Intelligent Systems at the University of Passau, Germany, who grew up watching Knight Rider--a television show about a car that could talk--this is the fulfillment of a childhood fantasy. Schuller is a World Economic Forum Young Scientist who will speak at the World Economic Forum's Annual Meeting of the New Champions in Tianjin, China, from June 26 to 28.He recently spoke about the possibility of machines soon tuning in to human language quirks, behavior and emotion. How did you get interested in machine intelligence and speech recognition?

Stress is actually a bit of a buzzword. The initial definition was "the reaction to changes", which is why you get stressed also when good things happen, hence the distinction between good stress, eustress, and bad stress, distress. Since the 90's, stress has become a synonym of the everyday hustling, describing a life style. We focus on the original definition, evaluating the user autonomic balance that can be estimated from heart rate variability (HRV). The autonomic nervous system (the sympathetic and parasympathetic systems) has a direct influence over most of our internal organs.

Pedro Domingos speaks on the future of the Information Age. Machine learning not only affects computers, but it will also change our lives. Pedro asks "what will the ultimate learning algorithm look like?" and discusses how future technology will change how we model many parts of our lives. Pedro Domingos is a professor of computer science at the University of Washington and the author of "The Master Algorithm". He is a winner of the SIGKDD Innovation Award, the highest honor in data science.

Outcomes Based Healthcare and Big Data Partnership have won an Innovate UK grant for a 1m project to change healthcare's approach to diabetes. In partnership, these two organisations will be creating "a dashboard and software product for doctors to predict and pre-treat for complications of diabetes." The press release explains that this will utilise health and non-health data in conjunction with advanced Machine Learning and analytics techniques to develop a system that can identify the progression of the disease. This will come from a local London population. The reason this Big Data and Machine Learning approach is interesting though, is it offers a top-line independent perspective on a difficult disease.

The first spark of the idea that would go on to become Tech City, surfaced on the last night of a UK trade mission to India in July 2010. At a British Government-hosted reception in Delhi, Matt Webb, then CEO and cofounder of design consultancy BERG, struck up a conversation with Rohan Silva, then a senior special advisor to the prime minister. Their chat soon turned to London and the best way to get the small cluster of startups that were scattered around Old Street to take off, and ultimately become a viable ecosystem. "Matt said there [wasn't] a Silicon Valley-type ethos in Old Street, where you can all come together," Silva told Wired magazine at the time. "So he asked for our help." A few months later, the Prime Minister delivered a speech in which he declared that "something [was] stirring in east London", which could one day "be one of the world's great technology centres".

From TechCrunch: "NEW YORK, NY - MAY 09: CEO and co-founder of Viv Dag Kittlaus speaks onstage during TechCrunch Disrupt NY 2016 at Brooklyn Cruise Terminal on May 9, 2016 in New York City." Dag Kittlaus co-created Apple's Siri, and now he's looking to disrupt the personal assistant market again--this time with Viv. While Siri may only respond to certain commands and doesn't remember the last thing you ask, you can make extremely specific requests of Viv, like "Will it be hotter than 70 degrees after 5PM tomorrow in San Francisco" or "pay David 20 dollars," and Viv can answer follow up questions. We caught up with Kittlaus to ask a few questions about how he's disrupting the virtual personal assistant market. Popular Science: You helped start Siri and you've got a deep understanding of how most assistants work.

Physicists are putting themselves out of a job, using artificial intelligence to run a complex experiment. The experiment, developed by physicists from The Australian National University (ANU) and UNSW ADFA, created an extremely cold gas trapped in a laser beam, known as a Bose-Einstein condensate, replicating the experiment that won the 2001 Nobel Prize. "I didn't expect the machine could learn to do the experiment itself, from scratch, in under an hour," said co-lead researcher Paul Wigley from the ANU Research School of Physics and Engineering. "A simple computer program would have taken longer than the age of the Universe to run through all the combinations and work this out." Bose-Einstein condensates are some of the coldest places in the Universe, far colder than outer space, typically less than a billionth of a degree above absolute zero.

What if computers could take the words we type on the internet and convert them into a language that describes what they actually mean? Analyzing data pulled from social media would reveal insights into the deeper questions about our real motives and feelings, instead of mere statistics. Pierre Lévy, a French philosopher who's been writing about cyberspace since the 1990s and who is the Canada research chair in collective intelligence at the University of Ottawa, is working on software that can do just this. He's done the math and annotated the entire French dictionary with a language--or, as he calls it, a hyper-language, since it describes words that already form a language of their own--that he calls IEML, or the Information Economy MetaLanguage. All that's left is to do the actual coding to turn it into an automatic system.