Two years ago, our ambitious team of data scientists, engineers and visualisation experts set out to tackle the challenging problem of interconnecting the entire universe of research. Using this incredibly powerful knowledge graph, we aimed to provide breakthrough insights about the past and present of research, and by applying predictive techniques we sought to outline the future of research at a global scale. Using big data analytics, machine learning and artificial intelligence, our team worked determinedly for two years piecing together the world's most comprehensive and continuously updating knowledge graph. Today, we are excited to introduce wizdom.ai, Our goal is to utilise this powerful research graph, representing the collective knowledge of human civilisation to answer the most fundamental questions for researchers, research institutions, publishers, funding organisations, businesses and governments – explore the extensive range of questions addressed by our team on the wizdom.ai

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

Will a robot one day win a Lion? That was the central question of PHD Worldwide's panel. CANNES, France--Many workers around the world have legitimate concerns about being replaced by automation. And, at least according to a show of hands, a large majority of attendees at a Cannes panel called "Will a Robot Win a Lion?" don't think advertising creative directors are exempt. But the panel of marketing and tech professionals organized by Omnicom's PHD Worldwide wasn't so sure. "We think our own creativity is really special or mystical, but there are lots of mechanical aspects to it," said Wired magazine co-founder Kevin Kelly.

The artificial intelligence (AI) system is "based on deep learning, a machine-learning algorithm used for a range of applications including speech recognition and image recognition," explains Andrew Beck, an associate professor in pathology at Harvard Medical School, who heads the team developing the new system at Beth Israel Deaconess Medical Center (BIDMC), in Boston, MA. Prof. Beck and colleagues demonstrated the new AI system in a competition held at the annual meeting of the International Symposium of Biomedical Imaging (ISBI 2016) in Prague in April. He and his colleagues are developing AI methods that train computers to interpret pathology images to improve the accuracy of diagnoses. The approach they are using teaches computers to interpret the complex patterns seen in such images by "building multi-layer artificial neural networks," says Prof. Beck. The process is thought to be similar to the way learning takes place in the layers of neurons in the neocortex of the brain, the region where thinking occurs.

This paper deals with prediction of anopheles number, the main vector of malaria risk, using environmental and climate variables. The variables selection is based on an automatic machine learning method using regression trees, and random forests combined with stratified two levels cross validation. The minimum threshold of variables importance is accessed using the quadratic distance of variables importance while the optimal subset of selected variables is used to perform predictions. Finally the results revealed to be qualitatively better, at the selection, the prediction , and the CPU time point of view than those obtained by GLM-Lasso method.

IN JULY 2011 Sebastian Thrun, who among other things is a professor at Stanford, posted a short video on YouTube, announcing that he and a colleague, Peter Norvig, were making their "Introduction to Artificial Intelligence" course available free online. By the time the course began in October, 160,000 people in 190 countries had signed up for it. At the same time Andrew Ng, also a Stanford professor, made one of his courses, on machine learning, available free online, for which 100,000 people enrolled. Both courses ran for ten weeks. Such online courses, with short video lectures, discussion boards for students and systems to grade their coursework automatically, became known as Massive Open Online Courses (MOOCs).

It has been the dream of science fiction fans since they first saw Captain Kirk and Spock disappear from the deck of the Enterprise, only to reappear on a planet in a haze of light. Now scientists in Russia are on a mission to bring Star Trek-style teleportation to life as part of a multi-trillion Rouble research and development drive. Russian investors say the plan isn't as far-fetched as it may seem, with much of the common technology used today inspired by sci-fi of decades gone by. The Russian government could develop the technology by 2035 as part of a 2.1 trillion ( 1.4 trillion) research and development drive. Investors say the plan isn't as far-fetched as it may seem, with much of the common technology used today inspired by sci-fi of decades gone by.

MUNICH (Reuters) – Europe's growing army of robot workers could be classed as "electronic persons" and their owners liable to paying social security for them if the European Union adopts a draft plan to address the realities of a new industrial revolution. Robots are being deployed in ever-greater numbers in factories and also taking on tasks such as personal care or surgery, raising fears over unemployment, wealth inequality and alienation. Their growing intelligence, pervasiveness and autonomy requires rethinking everything from taxation to legal liability, a draft European Parliament motion, dated May 31, suggests. Some robots are even taking on a human form. Visitors to the world's biggest travel show in March were greeted by a lifelike robot developed by Japan's Toshiba and were helped by another made by France's Aldebaran Robotics.

Gone are the days when tossing a mattress in the back of a truck was the only way to get it home from the store. The booming'boxed bed' business has taken over the mattress industry, allowing consumers to purchase their bedding online and have it shipped to their doorstep compressed inside of a box. And a new video shows the monstrous Auto-Pac 1390HCA system using a 60-ton hydraulic press and highly consistent rolling to neatly fold your mattress to be bagged and sealed for delivery. A new video shows the monstrous Auto-Pac 1390HCA system using a 60-ton hydraulic press and highly consistent rolling to neatly fold a mattress to be bagged and sealed for delivery. The first step of preparing a mattress for shipping is to cover it in a protective plastic wrap.

Google is ringing in 2014 with a spending spree, first dropping 3.2 billion to acquire Nest Technologies and now spending a reported 400 million (or more) on the UK-based artificial intelligence outfit DeepMind. It's no secret that Google has an interest in artificial intelligence; after all, technologies derived from AI research help fuel Google's core search and advertising businesses. AI also plays a key role in Google's mobile services, its autonomous cars, and its growing stable of robotics technologies. And with the addition of futurist Ray Kurzweil to its ranks in 2012, Google also has the grandfather of "strong AI" on board, a man who forecasts that intelligent machines may exist by midcentury. If all this sounds troubling, don't worry: Google's acquisition of DeepMind isn't about fusing a mechanical brain with faster-than-human robots and giving birth to the misanthropic Skynet computer network from the Terminator franchise.