A couple in the US has been charged with voyeurism by electronic equipment, having been caught using a drone to spy on neighbours. One victim claims to have chased the drone in his truck after spotting it outside his window, seizing it when it landed in a car park and handing it over to police in December. "The citizen who located the drone was familiar with drones and had a similar one himself," reads a search warrant unsealed this week in court, according to Deseret News. "There [were] multiple videos recording individuals inside their residences through windows. Some of the recordings were multiple stories high in apartment complexes."

An official German watchdog has told parents to destroy an internet-connected doll because hackers can use it to spy on children. My Friend Cayla was found to be equipped with an insecure Bluetooth device, which cybercriminals could hijack, in order to steal personal data and listen and talk to the child playing with it. Germany's Federal Network Agency, the regulatory office for electricity, gas, telecommunications, post and railway markets, has now warned parents to destroy it. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar. Japan's On-Art Corp's CEO Kazuya Kanemaru poses with his company's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' and other robots during a demonstration in Tokyo, Japan Japan's On-Art Corp's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' performs during its unveiling in Tokyo, Japan Singulato Motors co-founder and CEO Shen Haiyin poses in his company's concept car Tigercar P0 at a workshop in Beijing, China A picture shows Singulato Motors' concept car Tigercar P0 at a workshop in Beijing, China Connected company president Shigeki Tomoyama addresses a press briefing as he elaborates on Toyota's "connected strategy" in Tokyo.

Growing numbers of successful Silicon Valley entrepreneurs are'microdosing' on LSD at work each day. The drug has been shown to make users more relaxed, creative and focused. But is running the risk of arrest or mental health issues worth the reported benefits? In this piece for The Conversation, University of Cambridge scientists Barbara Sahakian, Camilla d'Angelo and George Savulich how the trend could be putting lives at risk. Researchers in Germany and the UK carried out trials in which participants were asked to name a number of pictures, either under the influence of acid or taking a placebo.

The reality will lie between these two extremes. Based on research gathered from surveying Asian business leaders and human resources and AI professionals, this report argues that AI's future will cleave much more closely to the positive outcome. Moreover, this future appears to be approaching quickly: advances in deep learning and the rapid expansion of process automation in such diverse sectors as manufacturing, transportation, and financial services mean that AI's impact is growing exponentially with each passing year. Decision makers in all organizations must now begin to understand how AI will alter their own operational processes and those of suppliers, partners, and customers. Asia's business landscape is poised not only to benefit greatly from AI's rise, but also to define it.

Scientists have worked for years to incorporate robotics into delicate medical procedures. They've given us tiny devices that can inject drugs into a person's eye or bend to operate on hard-to-reach areas. Now, they've come up with a way to potentially fight cancer using a magnetized swarm of microscopic robots. Researchers at Phillips Innovative Technologies in Hamburg, Germany have created a way to manipulate each robot in a swarm individually and assign them specific tasks using magnetic fields. The scientists presented their findings on Feb. 15th in the Journal Science Robotics.

The technology industry is facing up to the world-shaking ramifications of artificial intelligence. There is now a recognition that AI will disrupt how societies operate, from education and employment to how data will be collected about people. Machine learning, a form of advanced pattern recognition that enables machines to make judgments by analysing large volumes of data, could greatly supplement human thought. But such soaring capabilities have stirred almost Frankenstein-like fears about whether developers can control their creations. Failures of autonomous systems -- like the death last yearof a US motorist in a partially self-driving car from Tesla Motors -- have led to a focus on safety, says Stuart Russell, a professor of computer science and AI expert at the University of California, Berkeley.

In a setting befitting the opening scene of a sci-fi thriller at the recently opened Leverhulme Center for the Future of Intelligence at Cambridge University, Professor Stephen Hawking cautions that the future of artificial intelligence could potentially be "either the best, or worst thing to ever happen to humanity." Reiterating his 2014 statement to the BBC, Hawking urges that if done wrong, "the development of full AI could spell the end of the human race" –– think Terminator, I, Robot, or WestWorld. But on the other hand, Hawking believes that amplifying our minds through utilization of artificial intelligence can transform every aspect of our lives. The overarching concern surrounding AI is machine morality and whether it is safe for society. If people do not have proper ethical guidelines or fully comprehend the risks AI could play on mankind, is the expansion of functionalities and the powering of complex self-evolving capabilities – as Hawking would put it – the'worst thing to happen to humanity?'

The Defense Department is likely within 18 months of introducing autonomous cybersecurity tools that will be capable of augmenting human analysts by predicting threats, including insider activity, and dynamically isolating parts of the network that may come under attack, the department's outgoing chief information officer said Thursday. Terry Halvorsen, speaking to reporters during his last media roundtable before retiring at the end of the month, said as the department continues deployment of its 12 Joint Regional Security Stacks--a $1.6 billion effort to eliminate hundreds of disparate firewalls with centrally managed commercial security appliances and network monitoring tools--the next major step will be the deployment and testing of AI-based security applications. "Given the volume [of attacks] and where I see the threat moving it will be impossible for humans by themselves to keep pace. We can and we're very close to being able to put more autonomy into the security tools, and we will get to the point within the next 18 months where AI is becoming a key factor in augmenting the human analyst in making those decisions about what to do," Halvorsen said. Halvorsen recently hosted a special meeting of the Five Eyes alliance (Australia, Canada, New Zealand, the United Kingdom, and the United States), plus Germany, Japan, and NATO, at which AI-based cybersecurity was discussed in detail. "This is very real inside the department.

Gaussian processes are used as flexible models for these functions and estimates are calculated directly from dense data sets using Gaussian process regression. We also develop an approximate expectation maximization algorithm to deal with the unobserved, latent dynamics between sparse observations. The posterior over states is approximated by a piecewise linearized process of the Ornstein-Uhlenbeck type and the maximum a posteriori estimation of the drift is facilitated by a sparse Gaussian process approximation. I. INTRODUCTION Dynamical systems in the physical world evolve in continuous time and often the (noisy) dynamics is described naturally in terms of (stochastic) differential equations [1]. However, due to missing information and/or the complexity of a system it may be difficult to derive such a model from first principles. Instead, the goal often is to fit it to observations of the state at discrete points in time [2]. So far most inference approaches for these systems have dealt with the estimation of parameters contained in the drift function (e.g. Assumptions for the stochastic part were often simple: additive noise with the diffusion constant as the only parameter to estimate. But as both drift and diffusion can be nonlinear functions of the state vector, a nonparametric estimation would be a natural generalization, when a large number of data points is available. Previous nonparametric approaches were based on solving the adjoint Fokker-Planck equation [5] and on kernel estimators [6] and are effectively restricted to one-dimensional models. An alternative would be a Bayesian nonparametric approach, where prior knowledge on the unknown functions--such as smoothness, variability, or periodicity--can be encoded in a probability distribution. A recent result by [7, 8] presented an important step in this direction. The authors have shown that Gaussian processes (GPs) provide a natural family of prior probability measures over drift functions. If a path of the stochastic dynamics is observed densely, the posterior process over the drift is also a GP. Unfortunately, this simplicity is lost, when observations are not dense, but separated by larger time intervals. In [7] the case of sparse observations has been treated by a Monte Carlo approach, which alternates between sampling complete diffusion paths of the stochastic differential equation (SDE) and sampling from GP for the drift given a philipp.batz@tu-berlin.de

Being an unsupervised machine learning and data mining technique, biclustering and its multimodal extensions are becoming popular tools for analysing object-attribute data in different domains. Apart from conventional clustering techniques, biclustering is searching for homogeneous groups of objects while keeping their common description, e.g., in binary setting, their shared attributes. In bioinformatics, biclustering is used to find genes, which are active in a subset of situations, thus being candidates for biomarkers. However, the authors of those biclustering techniques that are popular in gene expression analysis, may overlook the existing methods. For instance, BiMax algorithm is aimed at finding biclusters, which are well-known for decades as formal concepts. Moreover, even if bioinformatics classify the biclustering methods according to reasonable domain-driven criteria, their classification taxonomies may be different from survey to survey and not full as well. So, in this paper we propose to use concept lattices as a tool for taxonomy building (in the biclustering domain) and attribute exploration as means for cross-domain taxonomy completion.