Hackers could one day order sex robots to kill their human lovers, a cyber security expert has warned. Cyber criminals could easily breach the robots' inner defences and turn them against their human owners, lecturer Dr Nick Patterson says. Hacking into modern-day robots would be far simpler than accessing more sophisticated devices like smartphones and computers, he claims. Hackers could one day order sex robots to kill their human lovers, a cyber security expert has warned. Cyber criminals could easily breach the robots' inner defences and turn them against their human owners, lecturer Dr Nick Patterson says (stock image) There are around five makers of sex robots worldwide, with prices ranging from around £4,000 ($5,275) to more than £11,600 ($15,300) for a'deluxe' model.

"From Mary Shelley's Frankenstein's Monster to the classical myth of Pygmalion, through the story of Prague's Golem to the robot of Karel Čapek, who coined the word, people have fantasised about the possibility of building intelligent machines, more often than not androids with human features". This is not an excerpt from a book on the history of robots in literature, but the opening sentence of the brand new European Parliament report on Robotics. Beyond this anecdotal reference, this draft report attempts to answer a question: as the presence of robots in our societies is no longer a science-fiction fantasy, and with people interacting more and more with intelligent machines in their day-to-day lives, is the future of humanity threatened? While the European Commission does currently fund robotics projects, the EU lacks a common regulatory framework in this field. Against this backdrop, the legal affairs committee of the European Parliament, has been entrusted with the task of writing a report on the issue of robotics, and has elaborated policy recommendations for the European Commission.

Popular opinion suggests AI is here to steal our jobs, but research from Capgemini shows an increasing number of roles in firms which are implementing it. Capgemini announced the findings into nearly 1,000 organisations today in its "Turning AI into concrete value: the successful implementer's toolkit" study. Further countering the idea that AI is destroying jobs; more than three in five (63%) of the organisations claim it has not resulted in any losses within their organisations. Many organisations see artificial intelligence as a means to speed up tasks or automate mundane work for employees to spend time doing less routine or administrative tasks. "I think for every job that is lost, there will be many more jobs that are gained," says the CTO of an unnamed large multinational corporation in the report.

The teachers who inspire our children will soon be machines and not humans, according to a leading university vice chancellor. Within 10 years a technological revolution will sweep aside old notions of education and change the world forever, Sir Anthony Seldon says. The vice chancellor of the University of Buckingham believes school teachers will lose their traditional role and effectively one day be little more than classroom assistants. He says they will remain on hand to set up equipment, help children when necessary and maintain discipline. But the essential job of instilling knowledge into young minds will be completely done by artificially intelligent (AI) computers.

The dates are set, the applications are in, the attendee list is finalized, travel plans are made, the curriculum is ready to rock-and-roll and so are we for this week's VSSML17. At BigML, we believe in the power of education when it comes to widening the impact zone of Machine Learning across the global economy. As cliché as it sounds, Machine Learning is truly changing the world in front of our eyes, except it is doing so in few corners of the planet, beige cubicles, and data centers hidden away from our everyday stomping grounds. So what to do to make it mainstream? Easy, just pack all the basics into a 2-day crash course and invite the whole world to it!

Apple is preparing to unveil its most high-tech phone to date – and with a price tag to match. The £1,000 iPhone X will be revealed alongside the iPhone 8 and the iPhone 8 Plus at the tech giant's annual product event tomorrow. Ahead of tomorrow's event, a'disgruntled Apple employee' has released a final version of iOS 11 - the software the new iPhone will run on - which appears to confirm many of the rumours, including wireless charging and an edgeless display. Pictured is Apple's official invite to the reveal of the iPhone at the Steve Jobs Theatre in Cupertino at 10:00 DST (18:00 BST) tomorrow Reports by Apple Insider claim that a'disgruntled employee' has leaked a'Gold Master' (GM) version of iOS 11, that contains a treasure trove of information about the iPhone. The leak confirms many of the rumours that have been circulating for months, and sheds light on other new features we can expect to see in the iPhone.

The Bureau Labor of Statistics estimates that there are 426,310 employed as drivers in the United States. If automation strikes, what happens to these jobs and where can drivers look to next? Developments are well advanced in many logistical areas. Companies are experimenting with new technologies at an accelerating rate. BMW Ford and Mercedes Benz all plan to launch a self-driving taxis in three years.

Predicting and acting upon financial fraud is one of the prime areas of application of advanced big data techniques like machine learning (ML). Earlier this week, a case of money laundering known as the Laundromat was uncovered by the Organized Crime and Corruption Reporting Project (OCCRP) involving a number of global banks active in the UK. Could ML help prevent such incidents? What progress is there on this front, how does it fit in the bigger picture, what are the roadblocks, and what may be the repercussions of adoption? There are many different types of fraud related to the financial industry.

Computing partition function is the most important statistical inference task arising in applications of Graphical Models (GM). Since it is computationally intractable, approximate methods have been used to resolve the issue in practice, where mean-field (MF) and belief propagation (BP) are arguably the most popular and successful approaches of a variational type. In this paper, we propose two new variational schemes, coined Gauged-MF (G-MF) and Gauged-BP (G-BP), improving MF and BP, respectively. Both provide lower bounds for the partition function by utilizing the so-called gauge transformation which modifies factors of GM while keeping the partition function invariant. Moreover, we prove that both G-MF and G-BP are exact for GMs with a single loop of a special structure, even though the bare MF and BP perform badly in this case. Our extensive experiments, on complete GMs of relatively small size and on large GM (up-to 300 variables) confirm that the newly proposed algorithms outperform and generalize MF and BP.

We generalize a support vector machine to a support spinor machine by using the mathematical structure of wedge product over vector machine in order to extend field from vector field to spinor field. The separated hyperplane is extended to Kolmogorov space in time series data which allow us to extend a structure of support vector machine to a support tensor machine and a support tensor machine moduli space. Our performance test on support spinor machine is done over one class classification of end point in physiology state of time series data after empirical mode analysis and compared with support vector machine test. We implement algorithm of support spinor machine by using Holo-Hilbert amplitude modulation for fully nonlinear and nonstationary time series data analysis.