Neural networks, machine-learning systems, predictive analytics, speech recognition, natural-language understanding and other components of what's broadly defined as'artificial intelligence' (AI) are currently undergoing a boom: research is progressing apace, media attention is at an all-time high, and organisations are increasingly implementing AI solutions in pursuit of automation-driven efficiencies. The first thing to establish is what we're not talking about, which is human-level AI -- often termed'strong AI' or'artificial general intelligence' (AGI). A survey conducted among four groups of experts in 2012/13 by AI researchers Vincent C. Müller and Nick Bostrom reported a 50 percent chance that AGI would be developed between 2040 and 2050, rising to 90 percent by 2075; so-called'superintelligence' -- which Bostrom defines as "any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest" -- was expected some 30 years after the achievement of AGI (Fundamental Issues of Artificial Intelligence, Chapter 33). This stuff will happen, and it certainly needs careful consideration, but it's not happening right now. What is happening right now, at an increasing pace, is the application of AI algorithms to all manner of processes that can significantly affect peoples' lives -- at work, at home and as they travel around. Although hype around these technologies is approaching the'peak of expectation' (sensu Gartner), there's a potential fly in the AI ointment: the workings of many of these algorithms are not open to scrutiny -- either because they are the proprietary assets of an organisation or because they are opaque by their very nature.

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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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Nvidia cofounder Chris Malachowsky is eating a sausage omelet and sipping burnt coffee in a Denny's off the Berryessa overpass in San Jose. It was in this same dingy diner in April 1993 that three young electrical engineers--Malachowsky, Curtis Priem and Nvidia's current CEO, Jen-Hsun Huang--started a company devoted to making specialized chips that would generate faster and more realistic graphics for video games. East San Jose was a rough part of town back then--the front of the restaurant was pocked with bullet holes from people shooting at parked cop cars--and no one could have guessed that the three men drinking endless cups of coffee were laying the foundation for a company that would define computing in the early 21st century in the same way that Intel did in the 1990s. "There was no market in 1993, but we saw a wave coming," Malachowsky says. "There's a California surfing competition that happens in a five-month window every year. When they see some type of wave phenomenon or storm in Japan, they tell all the surfers to show up in California, because there's going to be a wave in two days. We were at the beginning."

The'Netflix AI' set to hunt for aliens: Machine learning algorithm developed for online recommendations will scour the skies for systems that could sustain life Researchers are using machine learning to find stable planetary systems It uses techniques developed for Google's and Netflix recommendations The tool will also reveal the mass and how elliptical an exoplanet's orbit is Will be used to analyse data from NASA planet hunting mission It uses techniques developed for Google's and Netflix recommendations The tool will also reveal the mass and how elliptical an exoplanet's orbit is Machine learning software (pictured) that pull inspiration from Google and Netflix's algorithms could soon discover alien life in outer space. Did HALLUCINOGENS spark the Salem witch trials? Experts say... Iron Man suits, X ray detectors and a fake Facebook and... Hello there! Chimps can recognise friends with a single... How Donald Trump's administration could change the internet:... Did HALLUCINOGENS spark the Salem witch trials? Experts say... Iron Man suits, X ray detectors and a fake Facebook and... Hello there!

A focal point of president-elect Donald Trump's campaign, that manufacturing jobs have left the US in droves as a result of bad trade deals, could be based on a faulty premise. "America has lost nearly one-third of its manufacturing jobs since Nafta and 50,000 factories since China joined the World Trade Organization," says Mr Trump's official site, citing research from 2007 by the Economic Policy Institute. According to this narrative, the US's trade policies, growing trade deficits with Mexico and Canada, and China's "unfair subsidy behaviour" are to blame for the US's "deindustrialisation" and its disappearing middle class. The US did indeed lose about 5.6m manufacturing jobs between 2000 and 2010. But according to a study by the Center for Business and Economic Research at Ball State University, 85 per cent of these jobs losses are actually attributable to technological change -- largely automation -- rather than international trade.

Artificial intelligence and increasing automation is going to decimate middle class jobs, worsening inequality and risking significant political upheaval, Stephen Hawking has warned. In a column in The Guardian, the world-famous physicist wrote that "the automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining." He adds his voice to a growing chorus of experts concerned about the effects that technology will have on workforce in the coming years and decades. The fear is that while artificial intelligence will bring radical increases in efficiency in industry, for ordinary people this will translate into unemployment and uncertainty, as their human jobs are replaced by machines. Technology has already gutted many traditional manufacturing and working class jobs -- but now it may be poised to wreak similar havoc with the middle classes.

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Appier, a Taipei-based artificial intelligence company, closed US$ 19.5m in additional Series B funding. In total, this round of funding brings Appier's Series B total to US$ 42.5m and total funding to date to USD 49.5m. Backers included Pavilion Capital International Pte Ltd (a member of Temasek Holdings), WI Harper Group, FirstFloor Capital, and Qualgro. The company will use the funding for AI-powered product research and development and to support continued hiring and market expansion in Asia. Led by Chih-han Yu, co-founder and CEO, Appier provides companies with Aixon, an artificial intelligence platform to collect and analyze user data to generated insights to inform their marketing business decisions.