Google uses "deep learning" to generate captions for images, Facebook uses it to recognize faces and Tesla uses it to train self-driving cars. Now astronomers have caught on to deep learning, a form of machine learning in which a computer can be trained to identify or classify particular objects in images. The newest telescopes, such as the Dark Energy Survey, which uses a 4-meter telescope in northern Chile and covers about one quarter of the southern sky, take millions of images of a variety of celestial objects. These often include visual distortions, cosmic rays and satellite trails that make them difficult to interpret. Deep learning could help process this deluge of data quickly.

Deloitte Global predicts that over 300 million smartphones, or more than one fifth of units sold in 2017, will have machine learning capabilities within the device in the next 12 months. Mobile devices will be able to perform machine learning tasks even without connectivity which will significantly alter how humans interact with technology across every industry, market and society, notes Deloitte Global in its 16th Technology, Media & Telecommunications (TMT) Predictions. Over time, machine learning on-the-go will not just be limited to smartphones, the report states. These capabilities are likely to be found in tens of millions (or more) of drones, tablets, cars, virtual or augmented reality devices, medical tools, Internet of Things (IoT) devices and unforeseen new technologies. "Machine learning is fascinating as it will revolutionise how we conduct simple tasks like translating content, but it also has major security and health consequences that can improve societies around the world," says Paul Sallomi, Deloitte Global TMT industry leader, in a statement.

The World Economic Forum's "Global Risks Report 2017″ says tech firms must take responsibility for the disruption caused by their innovations. A new report by the World Economic Forum lists IoT hacking and weaponized AI among what they say will be the top security threats in 2017. The Global Risks Report 2017 surveyed business executives in the US, Germany, Japan, Switzerland, Australia, Singapore, Malaysia, UEA and other countries across the globe. Those executives cited cyberattacks as the biggest risk facing their businesses. The report pointed out the risks involved with letting decision-making be taken over by AI applications and said both AI and robotics can be serious risks without proper regulation and governance.

The objective of this paper is to present the process of building a Deep Learning Model for optimising the output for a Production Process from a Training sample using Weka Multilayer Perceptron. The scope is limited to implementation only and does not cover the theory behind Artificial Neural Networks. This work is the outcome of a comprehensive prototyping and proof-of-concept exercise conducted at Turing Point (http://www.turing-point.com/) a consulting company focused on providing genuine Enterprise Machine Learning solutions based on highly advanced techniques such as 3D discrete event simulation, deep learning and genetic algorithms. Predictive Analytics is the process of extracting information from the data for predicting future trends. There are a number of Machine Learning approaches available to model the behaviour.

MEPs have warned European countries must "seriously" consider introducing a general basic income to prepare for wide scale unemployment that could come as a result of robots taking over manual jobs. A draft report, tabled by a socialist MEP Mady Delvaux-Stehres, warns preparations must be made for what it describes as the "technological revolution" currently taking place, including provisions for the "possible effects on the labour market of robotics". The report, which passed by 17 votes to two and will be put in front of the entire European Parliament in February, urges member states to consider a general basic income in preparation for robots taking over people's jobs. It states: "In the light of the possible effects on the labour market of robotics and AI a general basic income should be seriously considered, and invites all Member States to do so." The resolution also suggests that a system of reporting on how robotics are affecting the economic results of companies should be established "for the purpose of taxation and social security contributions".

Now is the time of the year when every marketer should well reflect on the achievements of 2016 and holistically examine what the New Year is going to mean for marketing, branding, and business. With this article I proceed with a good tradition by following-up on my previous and related articles for 2016, 2015, and 2014. As we all know, paying attention to what's on the horizon does offer valuable insights. Knowing the below-listed 16 marketing trends which I consider as highly relevant for 2017, should help you to build, expand, and keep strong brands. Although this should have been ingrained in every marketer s DNA for years, however, with all the data, tech, and buzzwords flying around, one of the biggest marketing challenges of 2017 will be to stay calm, focused, and to be obsessed with the only one that matters: Your customer! How to identify her, to reach her, to engage her, to make her purchase, to have her stay loyal, to make her to recommend you, and to have her even re-purchase more of your products in the future? There is a certain risk that (marketing) managers – more than ever – get confused and fall into the trap of mixing up data-driven insights with a real customer-centric business philosophy. Therefore successful companies and brands don t worship the data gods for the sake of it; instead they have a comprehensive and deeply rooted digital transformation strategy in place which is flanked by a crystal clear marketing action plan. Enhanced and lived by every employee of the organization and not only by a chief digital officer who very often is floating around the company in search for a home base.

We've all been warned about the upcoming machine takeover in the world of work. Studies have shown that 47 percent of jobs in the United States are expected to be replaced by smart machines and other forms of automated systems in the next decade or so. In Southeast Asia, about 137 million workers are bound to lose their jobs to automation in the next 20 years. In fact, it's already happening for some companies including Walmart, Barclays, and a life insurance firm in Japan -- not to mention Amazon Go, the retail store of the future. Automation is going to be a problem as far as employment is concerned.

Many current fears around AI and automation center around the idea that superintelligence could somehow "take over," turning streets around the globe into scenes from The Terminator. While there is much to be gained from discussing the safe development of AI, there's another more imminent danger: Autonomous weapons. On Friday, after three years of negotiations, the UN unanimously agreed to take action. At the Fifth Review Conference of the UN Convention on Certain Conventional Weapons, countries around the world agreed to begin formal discussions--which will take place for two weeks at the 2017 UN convention in Geneva--on a possible ban of lethal, autonomous weapons. Talks will begin in April or August, and 88 countries have agreed to attend.

Clarifai: graphic design: 0.99% no person: 0.98% isolated: 0.97% symbol: 0.97% stripe: 0.95% Our Image Recognition API can block all images that have no relation with real estate. With restb's solution, all images containing spam, unrelated or restricted content are immediately blocked and tagged as non_related. Meanwhile the other solutions on the market will just keep giving you tags describing what's inside each image. Another big problem that property portals have is related with the publication of logos and watermarks in the images. Watermarks from your competitors or real estate agencies reduce the quality of the listings and the search experience overall. We have developed a solution that identifies all logos and watermarks that appear within an image and return the position of each one.

Most online daters prefer to contact people with the same level of education as them, but a new study suggests that as people grow older they become less picky about it. Researchers based at Queensland's University of Technology, Australia, analyzed the online dating behaviors of 41,000 Australians aged between 18 and 80. The researchers said that humans usually look for similar characteristics and traits in a partner in areas such as age, attractiveness and culture, however, the internet has changed this process. Researchers based at Queensland's University of Technology, Australia, analyzed the online dating behaviors of 41,000 Australians aged between 18 and 80 The researchers analyzed the behaviors of people using the online dating website'RSVP' during a four month period in 2016. Mr Stephen Whyte, a behavioural economist and co-author of the study, said: 'Selecting a mate can be one of the largest psychological and economic decisions a person can make and has long been the subject of social science research across a range of disciplines.