Singapore has announced a new partnership with Microsoft to create a digital government services platform that will shift towards conversational computing. Announcing the initiative at the World Cities Summit in the city-state on 12 July, Dr Vivian Balakrishnan, Minister for Foreign Affairs and Minister-In-Charge of the Smart Nation Initiative, said the new medium, conceptually referred to as "Conversations as a Platform" will use chatbots -- intelligent software programmes that simulate human behaviour. "I believe there are more intuitive ways for government services to be delivered to our citizens," Dr Balakrishnan said. The chatbots, which combine human language, artificial intelligence and machine learning, are envisioned to make public and business transactions simpler, more efficient, and more consistent. "Everybody expects responsive and personalised interactions in real time. The recent quantum improvement of natural language processing means that'conversations' will be the new medium," he said.

In the future, the development of artificial intelligence (AI) will accelerate beyond anything we have previously imagined. It will offer limitless possibilities – changing our experiences, transforming every area of life and redefining how we interact with technology. Yet AI is not just future fantasy. It is here and now, gaining momentum through advances in machine learning, neural networks and big data. These are exciting times and the UK is right at the heart of it.

Helen of Troy may have had the face that launched a thousand ships, but even the best facial recognition algorithms may have had trouble finding her face in a crowd of one million strangers. The first benchmark test based on one million faces has shown how facial recognition algorithms from Google and other research groups around the world can still fall short in accurately identifying and verifying faces. Facial recognition algorithms that had previously performed with more than 95 percent accuracy on a popular benchmark test involving 13,000 faces saw significant drops in accuracy when faced with the new MegaFace Challenge involving one million faces. The best performer on one test, Google's FaceNet algorithm, dropped from near-perfect accuracy on five-figure datasets to 75 percent on the million-face test. Other top algorithms dropped from above 90-percent accuracy on the small datasets to below 60 percent on the MegaFace Challenge.

Deploying the most innovative technologies alone will not ensure Singapore can succeed in its smart nation ambition, as this will require a population that is willing to embrace change in the way it interacts with its government. Since the launch of its smart nation initiative in 2014, the Singapore government has been rolling out various pilots and programmes to put in place the supporting infrastructure and systems. These centred around key objectives, among others, to enable safer and greener urban living, provide more transport options, facilitate better healthcare, and deliver more responsive public services and citizen engagement. Several initiatives had focused on a range of technologies including data analytics, Internet of Things (IoT), and cloud computing. Microsoft earlier this week announced it was working with the Singapore government to explore the use of machine learning and chatbots to deliver more interactive online citizen services.

Functional Magnetic Resonance Imaging (fMRI) is a noninvasive technique for studying brain activity, which receives an increasing attention in the last decade or so. During an fMRI experiment, a series of brain images is acquired, while the subject possibly performs a set of tasks responding to external stimuli. Changes in the measured blood-oxygen-level dependent (BOLD) signal are used to examine different types of activation in the brain. There are several objectives in the analysis of fMRI data, the most common of which are the localization of regions of the brain, that are activated by a task, and the determination of the functional brain connectivity [1, 2]. The localization of the activated areas in the human brain is a challenging "cocktail party" problem, where several people are talking (areas activated) simultaneously behind a wall (skull). Our goal is to distinguish those areas (spatial maps) as well as activation patterns (time courses) through some blind source separation (decomposition) method [3, 4]. Each source is the outcome of a combination of a time course with a spatial map. In fMRI studies of the brain function, the structure of the data involves multiple modes, such as trial, task condition, subject, in addition to the intrinsic dimensions of time and space [5].

It was a worrying refusal that does not bode well for the future of humanity. In New York to help Mastercard launch its rebrand and a new mobile payment service, the machine answered several questions - but refused to reveal its ultimate ambitions, simply flashing its eyes. 'I was named Pepper as I'm here to spice up your life, and my nickname is Pepperoni,' the robot then told us. Pepper also revealed it knows the three laws of robots, which include not harming humans, adding'I think robots should love humans.' However, it also refused to answer whether is was looking to take our reporter's job, simply waving and saying goodbye at that point, cutting the interview short. Betty DeVita of Mastercard reveal the Pepper unit normally works in a Pizza restaurant.

Are (All) Players Worth the Trouble?

LONDON: Understanding the hierarchical structure of biological networks like human brain -- a network of neurons -- could be useful in creating more complex, intelligent computational brains in the fields of artificial intelligence and robotics, says a study. Like large businesses, many biological networks are hierarchically organised, such as gene, protein, neural, and metabolic networks. This means they have separate units that can each be repeatedly divided into smaller and smaller subunits. Apple to sell solar energy now Apple is now planning to sell excess solar energy produced at its solar farms in Cupertino and Nevada. To understand as to why biological networks evolve to be hierarchical, researchers from the University of Wyoming and the French Institute for Research in Computer Science and Automation (INRIA) simulated the evolution of computational brain models, known as artificial neural networks, both with and without a cost for network connections.

BOSTON, MA--(Marketwired - Jul 5, 2016) - Jibo Inc., creator of the world's first social robot for the home, is pleased to announce the addition of Professor Michael I. Jordan to the company's advisory board. Jordan is renowned in the scientific community as an expert and leading researcher in the fields of artificial intelligence and machine learning. "Jibo is breaking new ground by bringing a human element to the robot experience -- something I believe the world needs and will benefit from embracing," said Michael I. Jordan, advisory board member of Jibo Inc. "My background and research in AI is uniquely suited to help in advancing Jibo's learning capabilities and developing his role and relationships within the home environment." Currently the Pehong Chen distinguished professor in electrical engineering, computer science and statistics at the University of California, Berkeley, Jordan has developed a wide range of novel methods in machine learning, natural language processing and signal processing. Jibo Inc. will apply artificial intelligence and machine learning techniques to the field of social rapport and relationships.

If robots that mimic animal or human behavior are your nightmare fuel, turn away now. Researchers at the Tokyo Institute of Technology went one step further with a skeleton robot, giving it human-like muscles to help with movement. The microfilament muscle "tissues" connect to joints and expand/contract just like the real thing. In fact, the robot has the same number of muscles in its legs as we do. At this point, they're not very strong and though the strands help with smoother movements, the skeleton still requires assistance to walk.