Journal of Parallel and Distributed Computing 104, 19-35.

In the last years, deep learning algorithms have highly revolutionized several areas including speech, image and natural language processing. The specific field of Machine Translation (MT) has not remained invariant. Integration of deep learning in MT varies from re-modeling existing features into standard statistical systems to the development of a new architecture. Among the different neural networks, research works use feedforward neural networks, recurrent neural networks and the encoder-decoder schema. These architectures are able to tackle challenges as having low-resources or morphology variations. This manuscript focuses on describing how these neural networks have been integrated to enhance different aspects and models from statistical MT, including language modeling, word alignment, translation, reordering, and rescoring. Then, we report the new neural MT approach together with a description of the foundational related works and recent approaches on using subword, characters and training with multilingual languages, among others. Finally, we include an analysis of the corresponding challenges and future work in using deep learning in MT.

Ascott Limited, a mid-market serviced apartments provider with 40,000 residences across the US, Asia, Europe and the Middle East, is in discussions with two Dubai-based robotics firms as it looks to use robots to conduct basic services at its properties, such as bringing clean towels to its guests. "Ascott is exploring new technologies across the serviced residence sector as automation becomes an integral part of business," said Vincent Miccolis, Ascott's regional general manager for the Middle East, Africa and Turkey. If a deal is reached with one of the firms – unlikely to happen until next year, Mr Miccolis told The National – Ascott would start commissioning the production of small-scale robots to deploy across its portfolio. "The idea is not to replace our staff," he added, during the ATM travel conference in Dubai, "but to complement their work and make operations even more efficient." Ascott has been orchestrating tests in China in conjunction with a Chinese robotics firm, which have shown that the proposed type of robots it would use can move around independently within the properties, including in elevators.

Artificial Intelligence (AI) is quickly finding a place at the heart of the enterprise, with it set to affect 25 percent of technology spend going forward, according to Accenture. Enabling better-informed decisions by augmenting human intelligence with powerful computing and precise data analysis, and then automating the tasks that follow, AI and automation – like an AA battery – have the power to energise business and help them drive towards success. Their rapid emergence has been driven by three factors. The cloud has made huge amounts of computing and processing power available, on demand. The data deluge – where 90 percent of the world's data has been created in just the last two years – has brought the critical mass needed to power the smart algorithms that drive these new capabilities.

"Hakuna matata" may very well be the only Swahili phrase that many people outside of East Africa have ever heard (thanks, Lion King), but a 4-foot-tall humanoid robot named Pepper is working to change that. The National Museum of African Art in Washington, D.C.--part of the Smithsonian Institution's network--is using Pepper to explain the meaning of Swahili words and phrases that appear in its artworks. The Smithsonian says it's the first museum complex in the world to use this particular robot, which was developed by SoftBank Robotics in 2014, made available to Japanese consumers in 2015, and later released to a wider market. Considered to be the world's first robot capable of reading emotions, Pepper is multi-talented. He has already found a home in several different Smithsonian sites, where he interacts with visitors, answers questions, plays games, tells stories, and even dances.

Globally, there are large disparities in access to health, education, etc. and the UN's Sustainable Development Goal No. 10 is aimed at reducing inequalities for the world's most vulnerable. For example, according to global association of mobile operators (GSMA), although eighty percent of the population in developing countries owns a mobile phone, still more than 1.7 billion women do not own one, according to a recent report on the subject. Anecdotally, there are more mobile phones in the developing world than adults. We see an increasing number of apps and services that are now being offered digitally. Moreover, cheap alternatives to text messaging and social networking platforms have enabled more people to communicate information with each other in the last decade than anything has in over a century since the discovery of the telephone.

As a follow-up to Artificial Intelligence is Coming for Your Clothes, Boots, Harley, and Job – Part 1, this article is but a brief segue for the brainiacs before the final transmission in Part 3 that will discuss changes and potential opportunities in the workforce of our future. "Medieval philosophers were right, man is the center of the Universe" – Fantastic Voyage (1966) "AI is software that takes on the task of writing itself autonomously, manifesting its own updates in order to renew itself, and it develops its own way of thinking through generative processes. AI is beginning to run things so much that we have become incapable of understanding how its decisions are made. The machines are'machine learning' themselves and improving their algorithms, making it so that we are unable to trace back to the algorithms that brought the AI to the decisions it makes. We tend to think of software as a system of codes that humanity creates, where the machines do what we tell them to do and we own it. That paradigm is no longer necessarily true."

Neanderthals may have died out because they lacked part of the human brain that helps us adapt to change and be sociable. Our ancient cousins had less grey matter in an area vital for memory, thinking and communication skills, suggests a new study. This would have affected their social and cognitive abilities, and could have been a major factor in their demise, scientists said. Neanderthals would have been less able than humans to adapt to climate change by innovating, for example. Researchers scanned the skulls of Neanderthals to assess their brain matter.

On a fine early afternoon in late March a young German-Iranian friend and I walked into the Garage Gallery at the Fire Station in Doha, Qatar - and we wondered. We were there to see the famous Chinese artist Ai Weiwei's "Laundromat": "A traveling installation", as the official description of the exhibition says, "that brings the current European migrant crisis into sharp focus." We had read before that "the work is centered around a vast makeshift camp near the village of Idomeni, on the border with the Republic of Macedonia. As part of his recently released documentary Human Flow, Ai Weiwei has borne witness to the brutal plight of refugees worldwide." Does the brutal plight of refugees worldwide - those from Syria in particular - need a witness?

Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it.1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations. Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance. In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values.2 Although there is no uniformly agreed upon definition, AI generally is thought to refer to "machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention."3 According to researchers Shubhendu and Vijay, these software systems "make decisions which normally require [a] human level of expertise" and help people anticipate problems or deal with issues as they come up.4 As such, they operate in an intentional, intelligent, and adaptive manner. Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.