A few years back, cloud computing transformed customer management, giving every small and medium business access to unified data and communication platforms without the need to make heavy investments in IT infrastructure and staff. This time around, the next revolution in the space is being driven by artificial intelligence algorithms that help businesses automate customer outreach and make optimal use of data. Beneath the surface of the roiling sea of data we're generating hide exceptional business and sales opportunities. But the problem is there's now more information available than limited human resources and legacy tools can handle. Fortunately, making sense of data, both structured and unstructured, is something that artificial intelligence is becoming increasingly proficient at.

For self-driving cars and other smart transport to be successfully integrated in the real-world, the safety of passengers and pedestrians must be ensured. In the world of intelligent machines, perception answers the question: what is around me? This situational awareness is paramount for safe operation of autonomous vehicles in real-world environments. Scientists working in this field point to robotic perception as fundamental in equipping machines with a semantic understanding of the world, so that they can reliably identify objects and make informed predictions and actions. Michael Milford, Associate Professor at Queensland University of Technology (QUT), is a leading robotics researcher working to improve perception and more in autonomous vehicles, conducting his research at the intersection of robotics, neuroscience and computer vision.

NZTech CEO Graeme Muller says New Zealanders are engaging with artificial intelligence (AI) everyday, probably without even realising it. Muller made the comments on the eve of the launch of the New Zealand AI Forum in Wellington, describing AI as "the fastest growing impactful technology spreading the globe." The forum was announced in February with further details being provided in late May, including the naming of Stu Christie, investment manager at the New Zealand Venture Investment Fund, as its chairman. NZTech says dozens of New Zealand's leading tech companies are joining the forum, which has been initiated via a collaboration between NZTech, the government and AI tech leaders. According to Muller, one of the most recent examples of AI in New Zealand is the chat function on the Air New Zealand website that helps with ticket bookings: users of that function are chatting with AI not a human, Muller said.

Emails are ubiquitous in a modern, globalised workforce. However, a well-crafted email can make the sender appear approachable and competent, while a poorly constructed one is less persuasive, and leaves recipients less willing to comply with the request. Alongside making requests and providing information, emails help us build rapport in the workplace and long-term business relationships. An internet search for "email etiquette" generates 433,000 results, while a search for books on email etiquette fetches 76 titles (on Amazon.com). However, the advice we get is often hazy, lacking justification, and may even be contradictory at times. Emoticons are displayed on the Touch Bar on a new Apple MacBook Pro laptop during a product launch event on Oct. 27, 2016, in Cupertino, California.

Despite the rise in digital banking, an advantage of branch banking continues to be the value of personal interaction. But, could the benefits of face-to-face interaction be incorporated into augmented reality (AR) and virtual reality (VR) solutions? The traditional bank branch network is in a massive state of transition. Offices are shrinking or closing altogether, with digital tools being introduced to support both transactional and advisory roles. But, while more than 8,000 U.S. bank branches have closed over the past decade, and as many as 90% of transactions taking place online, the number of bank employees has remained relatively stable.

A few years back, cloud computing transformed customer management, giving every small and medium business access to unified data and communication platforms without the need to make heavy investments in IT infrastructure and staff. This time around, the next revolution in the space is being driven by artificial intelligence algorithms that help businesses automate customer outreach and make optimal use of data. Beneath the surface of the roiling sea of data we're generating hide exceptional business and sales opportunities. But the problem is there's now more information available than limited human resources and legacy tools can handle. Fortunately, making sense of data, both structured and unstructured, is something that artificial intelligence is becoming increasingly proficient at.

Machines won't become intelligent unless they incorporate certain features of the human brain. Europe's massive €1 billion project has shifted focus from simulation to informatics By Megan Scudellari Large-scale brainlike systems are possible with existing technology--if we're willing to spend the money By Jennifer Hasler Researchers in this specialized field have hitched their wagon to deep learning's star By Lee Gomes Running algorithms that mimic a rat's navigation neurons, heavy machines will soon plumb Australia's underground mines By Jean Kumagai Artificial intelligence might endow some computers with self-awareness.

Summary: This is the second in our multi-part series on Quantum computing. How Fast?" we laid out the case that Quantum computing is commercially available today and that companies are already beginning to use it in operations. We talked a little about who is out in front (D-Wave, IBM) and who is coming soon (Microsoft, Google, University of New South Wales). We also spoke briefly about how it might be applied to deep learning and have an impact on artificial intelligence. In commercial operation today there are two distinct types of Quantum computers and several entirely different types due within a year or two.

Along with the recent advances in scalable Markov Chain Monte Carlo methods, sampling techniques that are based on Langevin diffusions have started receiving increasing attention. These so called Langevin Monte Carlo (LMC) methods are based on diffusions driven by a Brownian motion, which gives rise to Gaussian proposal distributions in the resulting algorithms. Even though these approaches have proven successful in many applications, their performance can be limited by the light-tailed nature of the Gaussian proposals. In this study, we extend classical LMC and develop a novel Fractional LMC (FLMC) framework that is based on a family of heavy-tailed distributions, called $\alpha$-stable L\'{e}vy distributions. As opposed to classical approaches, the proposed approach can possess large jumps while targeting the correct distribution, which would be beneficial for efficient exploration of the state space. We develop novel computational methods that can scale up to large-scale problems and we provide formal convergence analysis of the proposed scheme. Our experiments support our theory: FLMC can provide superior performance in multi-modal settings, improved convergence rates, and robustness to algorithm parameters.

So you think that robots are best suited for menial jobs? You couldn't be far from wrong. The research in artificial intelligence (AI) has moved to an all-new level with scientists at the University of Adelaide in Australia announcing that robots can predict mortality. By analysing CT scans from 48 patients, the deep learning algorithms could predict whether they would die within five years with 69% accuracy, which is broadly similar to the scores from human diagnosticians, the paper says. It will open up new avenues for the application of AI in medical image analysis, offering hope for early detection of serious illness that requires specific medical interventions.