O2 has announced plans to introduce an AI capable of performing the same job as customer service staff. The voice recognition system, which is called Aura, was unveiled by the mobile operator's parent company Telefonica at MWC this week. It's expected to launch in the UK next year, and will enable the company to cut customer service costs. Aura would be able to deal with customers' issues over the phone, such as questions about bills and requests to make changes to existing mobile plans. Telefonica also believes that Aura will help it boost customer loyalty, by allowing the firm to hand customers' data back to them.

Although we're still far away from a sci-fi world where we interact with human-like computers, the artificial intelligence industry has made massive strides in recent years. "AI is literally all around us all the time," said Pritzker Group Venture Capital associate David Vandegrift. "When you use Google search, the rankings use AI. Your Facebook feed is ordered by AI. When you get Amazon or Netflix recommendations, that's AI. When you see translations in your Twitter and Facebook feeds, that's AI."

The legend is that Almon Strowger invented automatic telephone switching in order to stop human operators deliberately or accidentally misdirecting phone calls. This was an early (patented 1891) example of using machinery to improve security and reliability in the telecommunications network. However, it was primarily the need to manage growth that drove automation of the phone system. And since then, through various stages of electromechanical, electronic and computer driven developments, the telecommunications networks of the world have benefited from increasingly high levels of automation. Most of this time, the underlying pattern of advancement stayed the same.

Machine learning is taking on Hollywood's gender bias. Technology that automatically detects how often men and women appear on screen reveals that in recent popular films, men have had almost twice as much screen time as women. The software uses algorithms for face and voice recognition that have been trained on annotated video to identify whether a character is male or female, and can measure how long they are on screen to a fraction of a second. It was developed by Shri Narayanan at the University of Southern California, Los Angeles, in partnership with the Geena Davis Institute on Gender in Media and Google.org, the search engine's charitable arm. In an analysis of the 100 highest-grossing live-action films from each of the past three years, the software found that women appear on average for just 36 per cent of the total time that characters are on screen.

Precision medicine promises a paradigm shift in care delivery, one that removes the need for guesswork, variable diagnoses and treatment strategies based on generalized demographics. Precision medicine approaches are enabled by data leveraged from direct and indirect sources to provide a more holistic view of an individual patient. Applying precision medicine into mainstream clinical workflow will eventually facilitate more predictive and preventive care by bringing better targeted therapies. By augmenting the process for differential diagnosis, clinicians can mitigate many of the inefficiencies that currently encumber care optimization. Those inefficiencies such as false positives, false negatives, unnecessary treatments and over- or under-medication all have financial and quality-of-care ramifications.

The CIA had a special programme allowing it to trick people into thinking they had been hacked by other countries, according to WikiLeaks. The agency was cataloguing the hacking methods of outside cyber attackers, including those from Russia, according to files published by the organisation. Once it had them catalogued, it could use them to break into other countries or people's computers or phones – making it look like a different country had done so. WikiLeaks made specific reference to the Russian Federation. Tensions between the US and Russia have escalated in recent months, in particular since American intelligence agencies blamed the hack of Democratic emails – credited with swaying the election of Donald Trump – on the country.

Feedzai, a leading data science company shaping the future of fraud detection in commerce, and BayPay Forum, a leading business and event network for payment, commerce and Fintech executives, hosted an engaging evening at Wells Fargo to discuss the real world application of AI across payments and banking. According to Tim Sloan, Wells Fargo CEO and President, AI is featured as one of the five areas of innovation that will shape the future of banking. Feedzai's REAL MACHINE series brings together data scientists from leading payments companies to learn about AI and machine learning and their application in the fintech industry. The AI deep dive strives to share best practices and exchange ideas for solving issues with moving modern money. The subject matter experts on the AI/ML panel discussed the impact that AI and deep learning methodologies would have on the future of business.

Tedious administrative tasks have long been the bane of the HR professional's job. Updating paperwork, sending out benefits reminders and plowing through hundreds of resumes can eat up hours every day, preventing HR leaders from focusing on more strategic tasks related to workforce planning and development. But the days of drudgery may soon be over, at least according to some vendors. Over the past year, HR software providers have trumpeted the fact that their technologies automate all of the manual and repetitive tasks that few want to do. Industry tech experts say your job is safe.

The insideBIGDATA Guide to Deep Learning & Artificial Intelligence is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting area of technology. In this guide, we take a high-level view of AI and deep learning in terms of how it's being used and what technological advances have made it possible. We also explain the difference between AI, machine learning and deep learning, and examine the intersection of AI and HPC. We present the results of a recent insideBIGDATA survey that reflects how well these new technologies are being received. Finally, we take a look at a number of high-profile use case examples showing the effective use of AI in a variety of problem domains.