The El Niño/La Niña pattern in the Pacific Ocean is notorious for its long-distance effects on weather as far away as Africa and the Midwestern United States. But climate experts also know of several other such patterns, known as "teleconnections," and believe that there are many more to be discovered. The new TRIPODS Climate project, a collaboration among the University of Chicago, University of Wisconsin-Madison and the University of California-Irvine, will develop novel data science tools to sniff out these hidden patterns, improving weather forecasts and scientific understanding of global climate. Researchers will apply data science methods such as machine learning, network analysis and predictive modeling to the growing flood of climate data. "There are fundamental challenges pervasive in data science that are epitomized in the climate science setting, making this collaboration a nice opportunity for advances on a number of fronts," said Rebecca Willett, professor of computer science and statistics at UChicago.

The Artificial Intelligence Week Middle East conference has wrapped up in Dubai, with PwC and Accenture among the sponsors and exhibitors featuring at the two-day event. Covering the banking & finance, government, and healthcare sectors, the Artificial Intelligence Week Middle East conference was held over the 4th and the 5th at the Park Hyatt in Dubai, featuring exhibitions, networking, pitches, and talks from some of the regional leaders in the field, including Xavier Anglada, Accenture Digital Lead for MENAT, and Stephen Anderson, Clients & Markets Leader for PwC Middle East. PwC in the Middle East, the event's official AI Consulting Sponsor & Partner, presented its recent annual AI report for the delegates in attendance, outlining the projected $96 billion boost to the United Arab Emirates' GDP by 2030 through the implementation of AI technologies – part of the $15.7 trillion possible worldwide windfall, and representing a 13.6 percent contribution to the UAE's overall GDP. Accenture – the AI event's Lead Digital Transformation Partner – has itself predicted huge gains for the UAE economy through AI adoption, amounting to some $182 billion in gross value add by 2030, while Accenture and PwC between them point to sizeable potential opportunities in the financial services, utilities, healthcare, education, transport, manufacturing and retail sectors. Unsurprisingly perhaps, consumer goods CEOs in the UAE are among the world's most enthusiastic for AI according to a further recent report by KPMG.And not just consumer goods CEOs in the UAE, but both wider industry and the government and public spheres are ready to embrace artificial intelligence – at least, if the line-up of AI tech conferences being held in the Emirates is anything to go by, with among others the Artelligence Forum having taken place in Dubai in April and the World AI show scheduled again in the city for April of next year.

Toddlers use the same gestures as chimpanzees and gorillas showing they really are just'tiny apes', claim researchers. One to two year olds use 52 limb and body movements to communicate - nine in ten of which are observed in great apes. This is a crucial stage of development when infants are on the cusp of learning language, say Scottish scientists behind the findings. Toddlers use the same gestures as chimpanzees and gorillas showing they really are just'tiny apes', claim researchers. Senior author Dr Catherine Hobaiter, of the School of Psychology and Neuroscience at St Andrews University, said: 'Wild chimpanzees, gorillas, bonobos and orangutans all use gestures to communicate their day-to-day requests.

Hurricane Harvey, shown in 2017. A new data project hopes to sniff out weather patterns. The El Nino and La Nina patterns in the Pacific Ocean are notorious for their long-distance effects on weather as far away as Africa and the Midwestern United States. But climate experts also know of several other such patterns, known as teleconnections, and believe that there are many more to be discovered. The new TRIPODS Climate project, a collaboration among the University of Wisconsin–Madison, the University of Chicago, and the University of California, Irvine, will develop novel data science tools to sniff out these hidden patterns, improving weather forecasts and scientific understanding of global climate.

Imagine there was a simple test to see whether you were developing Alzheimer's disease. You would look at a picture and describe it, software would assess the way you spoke, and based on your answer, tell you whether or not you had early-stage Alzheimer's. It would be quick, easy, and over 90% accurate--except for you, it doesn't work. That might be because you're from Africa. Imagine most of the world is getting healthier because of some new technology, but you're getting left behind.

Rise of frontier technologies like Artificial Intelligence has caused fears of robots taking over blue-collar jobs, but a UN expert says mass unemployment is not expected as humans still have the upper hand given their creative abilities. Ekkehard Ernst, Chief of Macro-economic policies and job unit at the UN International Labour Organization (ILO), says the manufacturing sector does not stand to profit most from AI, at least not in developed countries, and will not suffer the forecast demise. The jobs more likely to be impacted are in service sectors such as construction, health care and business. "It is not so much about losing jobs but about how jobs are being transformed and employees in these sectors will add new tasks to their profile while being supported by computers and robots in others," Ernst said. The type of tasks that are being replaced by AI algorithms are routine, repetitive tasks that take a lot of time and can be more easily and more effectively performed by machines and by robots – leaving people to focus on interpersonal, social, emotional skills.

That the modern world is a complex place will not have escaped your notice. We are all dimly, unsettlingly aware that our lives are enmeshed in systems we can't fully comprehend. The last meal you ate probably contained produce grown in another country that was harvested, processed, packaged, shipped, then sold to you. The phone in your hand is the end-product of an even more convoluted chain; one that relies on human labor from mines in Africa, assembly lines in China, and standing desks in San Francisco. Explaining how these systems connect and the effect they have on the world is not an easy task.

A world renowned pioneer in social robotics, Cynthia Breazeal splits her time as an Associate Professor at MIT, where she received her PhD and founded the Personal Robots Group, and Founder and Chief Scientist of Jibo, a personal robotics company with over $85 million in funding. While Breazeal's work has won numerous academic awards, industry accolades, and media attention, she had to fight early skepticism in the 1990s from other experts in robotics and AI. At the time, robots were seen as physical and industrial tools, not social or emotional companions. Her first social robot, Kismet, was unfairly called out in popular press as "useless". Breazeal bucked the trend with a very different vision: "I wanted to create robots with social and emotional intelligence that could work in collaborative partnership with people. In 2-5 years, I see social robots helping families with things that really matter, like education, health, eldercare, entertainment, and companionship." She hopes her work and influence will inspire others to create robots "not only with smarts, but with heart, too."

There used to be only three ways off of a kidney transplant waiting list. The first was to find a healthy person from within one's own pool of friends and family, who perfectly matched both the recipient's blood and tissue types, and possessed a spare kidney he or she was willing to part with. The second was to wait for the unexpected death of a stranger who was a suitable physical match and happened to have the organ-donor box checked on their driver's license. The third was to die. But then it occurred to doctors: given enough kidney patients, and enough healthy, willing donors, they could form a pool big enough to facilitate far more matches than the one-to-one system of the past. As long as patients could procure a donor--any donor, even one that wasn't a fit with the patient themselves--they could get a matching kidney. At first, this required doctors to spend brain-searing hours poring over the details of blood types and tissue variations in patients' and potential donors' charts. Then computer scientists and economists got involved. They built algorithms that performed these complicated matches more elegantly than human brains ever could.

Abstract--Meta-graph is currently the most powerful tool for similarity search on heterogeneous information networks, where a meta-graph is a composition of meta-paths that captures the complex structural information. However, current relevance computing based on meta-graph only considers the complex structural information, but ignores its embedded meta-paths information. To address this problem, we propose MEta-GrAph-based network embedding models, called MEGA and MEGA, respectively. The MEGA model uses normalized relevance or similarity measures that are derived from a meta-graph and its embedded meta-paths between nodes simultaneously, and then leverages tensor decomposition method to perform node embedding. The MEGA further facilitates the use of coupled tensor-matrix decomposition method to obtain a joint embedding for nodes, which simultaneously considers the hidden relations of all meta information of a meta-graph. Extensive experiments on two real datasets demonstrate that MEGA and MEGA are more effective than state-of-the-art approaches.