In 1997, Garry Kasparov famously lost his rematch with IBM's Deep Blue, marking the first time a reigning world champion had been defeated by a program under tournament conditions. Much of the press that followed was predictably hyperbolic, with headlines questioning whether a "Terminator scenario" was just around the corner. Twenty years on, the potential danger posed by powerful AI is in the spotlight once again. It's a concern that leads to the fourth and final question of this mini-series: if we cannot align AI with our own goals and values, do these systems need an off switch? To help explore this issue of AI safety, Ian Sample calls on a trio of experts, including the University of New South Wales's professor of artificial intelligence Toby Walsh, the University of Oxford's Professor Sir Nigel Shadbolt and Dr Yasemin J. Erden from St Mary's University in Twickenham.

A 3D animation has been created of Robert Burns reciting one of his most famous poems. The latest technology was used to recreate the Scottish bard's face from a partial cast of his skull. The words were spoken by modern-day Ayrshire poet, and Burns enthusiast, Rab Wilson. Motion capture was then used to track his facial movements as poem To a Mouse was recited. It was Mr Wilson's idea to use the skull cast to recreate the bard reciting one of his best known works.

The meeting with Kagame comes not long after participants in a White House meeting said Trump had referred to African nations as "shitholes." And Trump has come under fire in Britain after he retweeted videos from a far-right British group and criticized London Mayor Sadiq Khan following a terror attack last year. Trump canceled plans for a recent trip to London to open the new $1 billion U.S. embassy there, a move that avoided protests promised by political opponents. The president said he skipped the trip because he was unhappy with the new embassy's cost and location.

BENGALURU: Infosys President Mohit Joshi today said Industry disruption from Artificial Intelligence (AI) was already on and organisations not using it to amplify their workforce will fall behind or find themselves irrelevant. "Industry disruption from AI is no longer imminent, it is here. The organisations that embrace AI with a clearly defined strategy and use AI to amplify their workforce rather than replace it will take the lead and those that don't will fall behind or find themselves irrelevant," he said. Joshi said this in a statement while releasing the company's global research on the impact of Artificial Intelligence (AI) at Davos, where the world Economic Forum is currently underway. The research findings says enterprises are moving beyond the experimentation phase with AI, deploying AI technologies more broadly and realizing benefits across their business. The research report "Leadership in the Age of AI" surveyed more than 1,000 businesses and IT leaders with decision making power over AI solutions or purchases at large organisations across seven countries.

Researchers from the University of Valladolid (Spain) have created a computer model based on neural networks which provides in which Spanish provinces cases of corruption can appear with greater probability, as well as the conditions that favor their appearance. This alert system confirms that the probabilities increase when the same party stays in government more years. Two researchers from the University of Valladolid have developed a model with artificial neural networks to predict in which Spanish provinces corruption cases could appear with more probability, after one, two and up to three years. The study, published in Social Indicators Research, does not mention the provinces most prone to corruption so as not to generate controversy, explains one of the authors, Ivan Pastor, to Sinc, who recalls that, in any case, "a greater propensity or high probability does not imply corruption will actually happen." The data indicate that the real estate tax (Impuesto de Bienes Inmuebles), the exaggerated increase in the price of housing, the opening of bank branches and the creation of new companies are some of the variables that seem to induce public corruption, and when they are added together in a region, it should be taken into account to carry out a more rigorous control of the public accounts.

Artificial intelligence is starting to have a transformative impact on many industries, healthcare included, as it moves beyond the theoretical and into common practice. "We are no longer on the brink of change resulting from AI -- we are already immersed in a world with software-driven machines learning to process unstructured information in meaningful ways, something that until relatively recently was the domain of humans alone," Infosys researchers wrote in a report released this week at the World Economic Forum in Davos, Switzerland. It's clear that something that seemed sci-fi even five years ago is already changing the landscape in a real and profound way, the study "Leadership in the Age of AI," suggested and include workforces alongside the technology. The report polled more than 1,000 business and IT decision-makers, across nine industries and seven countries, about their AI-related purchases and plans. What it found is that enterprises – healthcare organizations prominent among them, are preparing for fundamental shifts as AI transforms their operations and continues to be deployed more broadly. Industry-wide, nearly three-quarters of respondents (73 percent) said their AI deployments have already changed the way they do business and 90 percent of C-level execs say they've seen "measurable benefits from AI." Infosys researchers said 86 percent of organizations it surveyed have "middle- or late-stage" AI deployments.

The prime minister is to say she wants the UK to lead the world in deciding how artificial intelligence can be deployed in a safe and ethical manner. Theresa May will say at the World Economic Forum in Davos that a new advisory body, previously announced in the Autumn Budget, will co-ordinate efforts with other countries. In addition, she will confirm that the UK will join the Davos forum's own council on artificial intelligence. But others may have stronger claims. Earlier this week, Google picked France as the base for a new research centre dedicated to exploring how AI can be applied to health and the environment.

We may soon have teeny tiny robots crawling throughout our bodies to deliver drugs. That is, if a prototype robot from scientists in Germany ever sees the light of day. A team of researchers from the Max Planck Institute for Intelligent Systems in Stuttgart, Germany have developed a rubbery, worm-like robot that they hope will be used for medicinal purposes in the future. The robot can crawl, walk and roll on land, swim in water and navigate obstacle courses. A team of researchers from the Max Planck Institute for Intelligent Systems in Stuttgart, Germany have developed a rubbery, worm-like robot that they hope will be used for medicinal purposes in the future.

Impulse response estimation has for a long time been at the core of system identification. Up until some five to seven years ago, the generally held belief in the field was indeed that we knew all there was to know about this topic. However, the enlightening work by Pillonetto and De Nicolao [2010] changed this by showing that the estimate can in fact be improved significantly by assuming a Gaussian Process (GP) prior over the impulse response, which acts as a regularizer. This model-driven approach has since then been further refined [Pillonetto et al., 2011, Chen et al., 2012, Pillonetto et al., 2014], where the prior in this case could be interpreted to encode not only smoothness information, but also information about the exponential decay of the impulse response. In this paper we employ deep leaning (DL) to find a suitable regularizer via a method that is driven by data. Deep learning is a fairly new area of research that continues the work on neural networks from the 1990's. To get a brief, but informative, overview of the field of deep learning we recommend the paper by LeCun et al. [2015] and for a more complete snapshot of the field we refer to the monograph by Goodfel-low et al. [2016]. Deep learning has recently revolutionized several fields, including image recognition (e.g.

With the increased availability of large databases of electronic health records (EHRs) comes the chance of enhancing health risks screening. Most post-marketing detections of adverse drug reaction (ADR) rely on physicians' spontaneous reports, leading to under reporting. To take up this challenge, we develop a scalable model to estimate the effect of multiple longitudinal features (drug exposures) on a rare longitudinal outcome. Our procedure is based on a conditional Poisson model also known as self-controlled case series (SCCS). We model the intensity of outcomes using a convolution between exposures and step functions, that are penalized using a combination of group-Lasso and total-variation. This approach does not require the specification of precise risk periods, and allows to study in the same model several exposures at the same time. We illustrate the fact that this approach improves the state-of-the-art for the estimation of the relative risks both on simulations and on a cohort of diabetic patients, extracted from the large French national health insurance database (SNIIRAM), a SQL database built around medical reimbursements of more than 65 million people. This work has been done in the context of a research partnership between Ecole Polytechnique and CNAMTS (in charge of SNIIRAM).