The Faculty of Engineering and Information Technologies has attracted high-profile researcher, Professor Dacheng Tao, who will join the School of Information Technologies on 5 December. In 2015 and 2016 he was ranked by Thomson Reuters as a Highly Cited Researcher for Engineering and Computer Science. In 2015 he received the Australian Scopus -Eureka Prize, and in the same year obtained the ACS Gold Disruptor Award. His research predominantly covers artificial intelligence (AI), with a focus on computer vision, deep learning, and statistical learning, as well as their applications to robotics, neuroscience, medical informatics, and video surveillance. Professor Tao is excited to be joining the university as he believes "it has a history of achieving research excellence, passing frontier knowledge on to students, and for building the base to change lives for the better."

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With technology governing almost every aspect of our lives, industry experts are defining these modern times as the "platinum age of innovation"; verging on the threshold of discoveries that could change human society irreversibly, for better or worse. At the forefront of this revolution is the field of artificial intelligence (AI), a technology that is more vibrant than ever due to the acceleration of technological progress in machine learning – the process of giving computers with the ability to learn without being explicitly programmed – as well as the realisation by big tech vendors of its potential. One major tech behemoth fuelling the fire of this fast-moving juggernaut is Intel, a company that has long invested in the science and engineering of making computers more intelligent. The Californian company held an "AI Day" in San Francisco showcasing its new strategy dedicated solely to AI, with the introduction of new AI-specific products, as well as investments for the development of specific AI-related tech. And Alphr was in town to hear all about it.

My academic background is in computer science and philosophy. My work has been about the relationship between those two fields. What do we learn about being human by thinking about the quest to create artificial intelligence? What do we learn about human decision making by thinking of human problems in computational terms? The questions that have interested me over the years have been, on the one hand, what defines human intelligence at a species level? And secondly, at an individual level, how do we approach decision making in our own lives, and what are the problems that the world throws at us? I find myself interested at the group level, the society level, and the civic level in a couple of different ways. I've been encouraged by what I've seen over the last few years in terms of the norms of the sciences changing. It used to be that people were scared to publish their models because that was the secret sauce; that was their advantage over other research groups.

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Artificial intelligence (AI) and machine learning have emerged as a major talking point for the likes of IBM, Google and Microsoft, with all keen to talk up the work they are doing to help enterprises make the most of these technologies. What to move, where and when. Corporate E-mail Address: This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. Corporate E-mail Address: This email address is already registered.

When Bill McDermott, CEO of SAP, the world's largest business software provider, believes the next five to 10 years will be far more disruptive than the five to 10 we just lived through, it's time to sit up and pay attention. "I believe very strongly that intelligent applications will fundamentally change the way you do work in the enterprise and the way you collaborate with your trading partners," said McDermott. Take a closer look at what this technology is capable of doing in the examples below. There's a good reason the below machine learning demo has over three million views on YouTube – it's a brilliant example of how this technology learns and predicts in a classic video game environment.

In-memory data store Redis recently acquired a module architecture to expand functionality. The latest module is a machine learning add-on that accelerates delivery of results from trained data rather than training itself. Redis-ML, or the Redis Module for Machine Learning, comes courtesy of the commercial outfit that drives Redis development, Redis Labs. It speeds the execution of machine learning models while still allowing those models to be trained in familiar ways. Redis works as an in-memory cache backed by disk storage, and its creators claim machine learning models can be executed orders of magnitude more quickly with it.

Humans are on the cusp of augmenting their lives in extraordinary ways with AI. At IBM Research Labs around the globe, we envision and develop next-generation systems that work side-by side with humans, accelerating our ability to create, learn, make decisions and think. We also architect the future of Watson, which has evolved from an IBM Research project to the world's first and most-advanced AI platform. Whether exploring new technical capabilities, collaborating on ethical practices or applying Watson technology to cancer research, financial decision-making, oil exploration or educational toys, IBM Research is shaping the future of AI.

The newest prime number is more than 22 million digits long Watch This Robot Solve a Rubik's Cube in Less Than 2 Seconds Thanks to a $28 million grant, Harvard is researching artificial in... The world has lost one of its greatest minds in science.