The IEEE publishes an annual list of the Top 10 Technology Trends for each upcoming year. Making the list for 2018 are multiple topics surrounding artificial intelligence and machine learning. Deep learning comes in as the IEEE hottest trend for 2018. Neural networks extract features through a concept of layers. By combining the output from these multiple layers, deeper layers are able to construct more advanced insight from data.

We are interested in the development of surrogate models for uncertainty quantification and propagation in problems governed by stochastic PDEs using a deep convolutional encoder-decoder network in a similar fashion to approaches considered in deep learning for image-to-image regression tasks. Since normal neural networks are data intensive and cannot provide predictive uncertainty, we propose a Bayesian approach to convolutional neural nets. A recently introduced variational gradient descent algorithm based on Stein's method is scaled to deep convolutional networks to perform approximate Bayesian inference on millions of uncertain network parameters. This approach achieves state of the art performance in terms of predictive accuracy and uncertainty quantification in comparison to other approaches in Bayesian neural networks as well as techniques that include Gaussian processes and ensemble methods even when the training data size is relatively small. To evaluate the performance of this approach, we consider standard uncertainty quantification benchmark problems including flow in heterogeneous media defined in terms of limited data-driven permeability realizations. The performance of the surrogate model developed is very good even though there is no underlying structure shared between the input (permeability) and output (flow/pressure) fields as is often the case in the image-to-image regression models used in computer vision problems. Studies are performed with an underlying stochastic input dimensionality up to $4,225$ where most other uncertainty quantification methods fail. Uncertainty propagation tasks are considered and the predictive output Bayesian statistics are compared to those obtained with Monte Carlo estimates.

We tackle the problem of classifying Electrocardiography (ECG) signals with the aim of predicting the onset of Paroxysmal Atrial Fibrillation (PAF). Atrial fibrillation is the most common type of arrhythmia, but in many cases PAF episodes are asymptomatic. Therefore, in order to help diagnosing PAF, it is important to be design a suitable procedure for detecting and, more importantly, predicting PAF episodes. We propose a method for predicting PAF events whose first step consists of a feature extraction procedure that represents each ECG as a multi-variate time series. Successively, we design a classification framework based on kernel similarities for multi-variate time series, capable of handling missing data. We consider different approaches to perform classification in the original space of the multi-variate time series and in an embedding space, defined by the kernel similarity measure. Our classification results show state-of-the-art performance in terms of accuracy. Furthermore, we demonstrate the ability to predict, with high accuracy, the PAF onset up to 15 minutes in advance.

The world's biggest carmaker Volkswagen said Friday it would stuff even more technology into the next generation of its top-selling Golf model, bringing so-called "connected driving" deeper into the mainstream. Slated for release in 2019, the updated cars will be constantly connected to the internet, with greater self-driving capabilities and "more software than ever before on board," VW compact cars chief Karlheinz Hell said in a statement. Existing Golf models have a range of driver assistance features, including parking aids, staying in lane and maintaining safe distance in traffic jams and emergency braking. But they remain far removed from visions of completely hands-free self-driving cars dangled by industry executives. Some 34 million people have bought a Golf, the successor to the iconic Beetle, since the first model rolled off production lines in 1974, VW says, and the range accounted for almost one in 10 of the vehicles sold by the VW group in 2016.

On January 30th let's celebrate the European Tech Night of the International VivaTour in NYC with today's innovations and tomorrow's possibilities. We are going to talk about "How are European Artificial Intelligence startups disrupting industry?" Don't miss a tremendous meet up gathering the European and American Tech ecosystems.

Conventional wisdom decrees that this dual-track approach isn't sustainable, and that low- to middle-skilled workers will eventually make way for robots. A landmark 2013 study by Carl Frey and Michael Osborne of Oxford University suggests that, in the coming decades, 47% of total US employment will be at risk of automation. Similarly, the International Labour Organization (ILO) has warned that 56% of total employment in Cambodia, Indonesia, the Philippines, Thailand, and Vietnam is "at high risk of displacement due to technology over the next decade or two."

You may not realise it, but we all rely on artificial intelligence (AI) as we go about our normal daily lives. Let's take just one example: Keeping 1.7 billion journeys safeAI is used to protect the UK's rail passengers as they take 1.7 billion journeys (that's more than 66 billion passenger kilometres) every year. But before we even think about taking a train journey, AI is keeping us safe. Thales's Predict and Prevent technology uses a variety of sensors to monitor the real-time performance of more than 42,000 assets on thousands of kilometres of track, and at stations, platforms, signals, bridges, tunnels, crossings, cuttings, embankments and viaducts. Each component that is being monitored has a known profile – how much current it draws in normal use, for example, and the typical length of its operating life.

Editor's Note: TensorFlow, our open source machine learning library, is just that--open to anyone. Companies, nonprofits, researchers and developers have used TensorFlow in some pretty cool ways, and we're sharing those stories here on Keyword. Today we hear from Yasir Khokhar and Saad Ansari, founders of Connecterra, who are applying machine learning to an unexpected field: dairy farming. We formed the company based on a simple thesis: if we could use technology to make sense of data from the natural world, then we could make a real impact in solving the pressing problems of our time. It all started when Yasir moved to a farm in the Netherlands, near Amsterdam.

Britain and France's leading tech sectors will be brought closer together with plans for a digital conference – or digital colloque – to promote deeper integration in the digital economy, the Digital, Culture, Media and Sport Secretary Matt Hancock has announced. The UK tops the list in Europe for global tech investors, with its tech firms attracting more venture capital funding than any other European country in 2017. In December it was named by Oxford Insights as the best prepared country in the world for artificial intelligence (AI) implementation. France has made big strides in creating new tech businesses and encouraging entrepreneurs, with Paris's newly built Station F, a former railway station hosting startups, multinationals and investors, symbolising the country's ambition. "The UK and France are strengthening ties in technology and innovation," explained Hancock.

THE UK AND FRANCE have teamed up in the name of artificial intelligence (AI) and cybersecurity in a bid to boost future developments in these areas. Ministers from the two county's governments made the decision to join forces on Thursday in hope that the arrangement will foster cross-Channel collaboration between academics, industry and government and thus "help both countries seize the economic and social benefits of fast-developing tech such as AI". The UK's Digital, Culture, Media and Sport Secretary minister, Matt Hancock pioneered the initiative and to get the ball rolling on the deal, met his French counterpart, Françoise Nyssen, at the UK France Summit. It was hosted by the prime minister and the French president, Emmanuel Macron, at Royal Military Academy in Sandhurst. Hancock said the two countries will establish "cutting-edge digital conference" as part of the new pact, which will take place later this year and "see our world-leading experts in cybersecurity, digital skills, artificial intelligence, data and digital government share their talent and knowledge".