The African smartphone market is gaining rapid traction. According to predictions, smartphones sold this year will outnumber feature phone sales, and mobile penetration is far higher than line-based internet access. Currently, most people in Africa use text messages to send money with a service called M-Pesa from the largest tech start-up in Kenya. Now, chatbots could potentially replace text-based transactions altogether. Budapest-based Hungarian start-up UXstudio has created a chatbot called Nuru.

A healthcare revolution is being predicted after the Edinburgh Centre for Robotics (ECR) received new funding. Researchers there are using artificial intelligence to create robots that will learn from their environment, each other - and us. The ECR is a joint initiative between Heriot-Watt University and the University of Edinburgh. Its new Robotarium will open later this year thanks to £8m of support from the UK's Engineering and Physical Sciences Research Council (EPSRC). Now the EPSRC is giving almost £1m more to develop four new robots that will use Artificial Intelligence (AI) to transform healthcare and emergency response.

Your consumers spend a lot of time exploring and analyzing suitable information―which books to study, which news articles to read, which songs to play, which movies to watch, which games to play, and so on. Imagine, what their experience would be like, if they don't need to pick anything on their own, but are presented with options of their liking―be it in education or media or entertainment. Here are some of the things they can be offered: • Adaptive text-books, in which content changes based on the pace of learning and comfort level of the reader. Such advancements reduce the overall time spent on information discovery, and increase the scope of effective information consumption (or learning). Domains such as education, publishing, entertainment, and advertisement mostly deal with granular digital assets (text, images, audio, video, multi-media, and so on), and are better prepared to enhance personalization even without creating new content from scratch.

THE RISE OF THE INTERNET has led to the rise of e-commerce websites. With the mushrooming of the number of e-commerce sites today there is surge in demand by customers. In order to provide the most relevant recommendations to the visitors, ecommerce websites regularly rely on recommendation engines, which are complex data applications fueled by data ingestion, data preparation and machine learning processes. In addition to building machine learning models, recommendation engines require the ingestion and storage of user data in real-time, the training and storing of the models and their results, as well as the monitoring and improvement of the model performance. This webinar showcases the ways and means to use the Cask Data Application Platform (CDAP), a unified integration platform for big data, to operationalize Machine Learning models for your ecommerce website by simplifying data collection, testing and continuous improvement. About the Speaker:Russ Savage is leading the application engineering team at Cask, focusing on building end to end big data applications using the Cask Data Application Platform (CDAP).

Do you ever find yourself in this situation of having to speak to a personal assistant? The second I hear the words personal assistant, I immediately think wow this company must be important. Personal assistants have an association with very high up, powerful people within an organization. Or does having a personal assistant just seem more professional and established? The answer could be either, but the one thing I do know is that personal assistants are becoming easier to come by than ever before.

Artificial intelligence (AI) has promised to relieve us of our dullest tasks and improve almost every aspect of our lives, from transportation to health care. But, by their very nature, the best tech ideas lead to incredible efficiencies, and if those efficiencies touch on people's jobs, it will take those jobs away. The Industrial Revolution replaced entire job descriptions, but more highly skilled and better-paying jobs eventually followed. That may not necessarily end up the case with AI, as deep learning helps machines replace people further up the talent chain. How many jobs could be affected?

HBO's Westworld features a common plot device--synthetic hosts rising up against their callous human creators. But is it more than just a plot twist? After all, smart people like Bill Gates and Steven Hawking have warned that artificial intelligence may be on a dangerous path and could threaten the survival of the human race. They're not the only ones worried. The Committee on Legal Affairs of the European Parliament recently issued a report calling on the EU to require intelligent robots to be registered, in part so their ethical character can be assessed.

My mother waited two months for her Amazon Echo to arrive. Then, she waited again -- leaving it in the box until I came to help her install it. Any device that requires vocal instructions makes my mother skeptical. She has bad memories of Siri. "She could not understand me," my mom told me.

SirionLabs, a startup providing vendor management software to enterprises, is adding a US headquarters to its footprint. The company was initially founded in India and has raised $16.95 million from Sequoia Capital India, Canopy Ventures and Qualgro VC to extract data from contracts to ensure transparency and accountability. The establishment of a US presence represents a strategic shift in the company's growth plans. Last year, SirionLabs told TechCrunch that it was looking to hire and relocate workers from Silicon Valley to India. While the startup has had offices in the UK, Germany, Denmark and Singapore, it has been slow to establish a permanent US team.

During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical systems are still built through significant engineering and expert knowledge. Nevertheless, several recent results suggest that data-driven approaches are feasible and quite promising. To facilitate research in this area, we have carried out a wide survey of publicly available datasets suitable for data-driven learning of dialogue systems. We discuss important characteristics of these datasets, how they can be used to learn diverse dialogue strategies, and their other potential uses. We also examine methods for transfer learning between datasets and the use of external knowledge. Finally, we discuss appropriate choice of evaluation metrics for the learning objective.