DUBAI: When it comes to man versus machine, many industries, including medical science, are at a critical juncture. Advancements in technology are creating a world where robots are performing tasks with speed and efficiency unmatched by their human counterparts. Increasingly, robots are becoming a familiar presence in operating theaters, especially in the Gulf. Experts predict that the region could become the leader in the field of robotic surgery. In June, Johns Hopkins Aramco Healthcare (JHAH) -- the result of a joint venture between Saudi Aramco and Johns Hopkins Medicine -- became the first hospital in the Kingdom to perform a robot-assisted hysterectomy.

People will be able to get expert health advice using Amazon Alexa devices under a partnership with the NHS, the government has announced. From this week, the voice-assisted technology is automatically searching the NHS Choices website when UK users ask for health-related advice. Previously the device provided information from a range of sources. The Department of Health in England said it could provide valuable support and even reduce demand on the NHS. The partnership was first announced last year and now talks are under way with other companies, including Microsoft, to set up similar arrangements.

Should your Roomba need a W-2? Probably not, but it's an amusing thought when debating the more serious topic of whether or not a robot should have to pay taxes -- and how to do it. During the June MIT Technology Review EmTech Next event, two experts argued both sides of the question before an audience at the MIT Media Lab in Cambridge, Massachusetts. Ryan Abbott, professor of law and health sciences at the University of Surrey, argued in favor of taxing robots, while Ryan Avent, economics columnist for The Economist, argued against the idea. Both agreed there needs to be a shift in tax burden from labor to capital. Avent, however, carried the most audience votes by the end of the debate. Here are some highlights from each of the men's arguments.

India's space agency is preparing to launch its ambitious Chandrayaan-2 mission next week which is set to land near the currently unexplored south pole of the moon. Chandrayaan-2 will blast off from the Satish Dhawan Space Center at Sriharikota on the country's south west coast at 2.51am (10.21pm It is the Indian Space Research Organisation's (ISRO) second lunar probe, and the first one destined to land on the moon, and is scheduled to land on September 6. India will become only the fourth country, after the US, Russia and China, to reach Earth's satellite if successful. The ISRO has said it chose to explore the south pole as it is possible there is water in the permanently shadowed areas, which could pave the way for future lunar habitation.

According to one futurist, the next frontier for human innovation is the body itself. In a talk at Fast Company's European Innovation Festival, historian and international bestselling author, Yuval Noah Harari, said that the human body is on a crash course with technology. 'It's increasingly hard to tell where I end and where the computer begins,' Harari said, as reported by Fast Company. In the future, humans and technology will be impossible to differentiate from one another says one prominent futurist. Yuval Noah Harari (pictured, file photo) spoke recently during Fast Company's European Innovation Festival'In the future, it is likely that the smartphone will not be separated from you at all,' Harari said.

The Nintendo Switch has a couple of ways to back-up, archive, and delete your games. You don't have to truly delete titles you may be bored of as you may want to play again at a later time. Nintendo is moving some production of its Switch video game console out of China. The Kyoto, Japan-headquartered game company, which until now has produced all Nintendo Switch consoles in China, said the move was not because of concern for potential U.S. tariffs on products made in China. "For the past several years, we have been exploring options for assembling product in Vietnam to diversify our manufacturing options," the company said in a statement to USA TODAY.

In this paper, we argue that competitive pressures could incentivize AI companies to underinvest in ensuring their systems are safe, secure, and have a positive social impact. Ensuring that AI systems are developed responsibly may therefore require preventing and solving collective action problems between companies. We note that there are several key factors that improve the prospects for cooperation in collective action problems. We use this to identify strategies to improve the prospects for industry cooperation on the responsible development of AI.

One shirt size cannot fit everybody, while we cannot make a unique shirt that fits perfectly for everyone because of resource limitation. This analogy is true for the policy making. Policy makers cannot establish a single policy to solve all problems for all regions because each region has its own unique issue. In the other extreme, policy makers also cannot create a policy for each small village due to the resource limitation. Would it be better if we can find a set of largest regions such that the population of each region within this set has common issues and we can establish a single policy for them? In this work, we propose a framework using regression analysis and minimum description length (MDL) to find a set of largest areas that have common indicators, which can be used to predict household incomes efficiently. Given a set of household features, and a multi-resolution partition that represents administrative divisions, our framework reports a set C* of largest subdivisions that have a common model for population-income prediction. We formalize a problem of finding C* and propose the algorithm as a solution. We use both simulation datasets as well as a real-world dataset of Thailand's population household information to demonstrate our framework performance and application. The results show that our framework performance is better than the baseline methods. We show the results of our method can be used to find indicators of income prediction for many areas in Thailand. By increasing these indicator values, we expect people in these areas to gain more incomes. Hence, the policy makers can plan to establish the policies by using these indicators in our results as a guideline to solve low-income issues. Our framework can be used to support policy makers to establish policies regarding any other dependent variable beyond incomes in order to combat poverty and other issues.

Deep learning architectures have demonstrated state-of-the-art performance for object classification and have become ubiquitous in commercial products. These methods are often applied without understanding (a) the difficulty of a classification task given the input data, and (b) how a specific deep learning architecture transforms that data. To answer (a) and (b), we illustrate the utility of a multivariate nonparametric estimator of class separation, the Henze-Penrose (HP) statistic, in the original as well as layer-induced representations. Given an $N$-class problem, our contribution defines the $C(N,2)$ combinations of HP statistics as a sample from a distribution of class-pair separations. This allows us to characterize the distributional change to class separation induced at each layer of the model. Fisher permutation tests are used to detect statistically significant changes within a model. By comparing the HP statistic distributions between layers, one can statistically characterize: layer adaptation during training, the contribution of each layer to the classification task, and the presence or absence of consistency between training and validation data. This is demonstrated for a simple deep neural network using CIFAR10 with random-labels, CIFAR10, and MNIST datasets.

NASA's Insight lander got one step closer to extricating a crucial device that has been wedged in Martian soil since February. In the first of several planned maneuvers, NASA's Insight lander carefully moved part of its support structure which was obscuring the agency's view, using the lander's robotic arm. The successful move puts a probe called the'mole' within NASA's view for the first time since it was ordered to stop drilling earlier this year. NASA's Insight Lander carefully moved part of its support structure which was obscuring the agency's view, using the lander's robotic arm. 'We've completed the first step in our plan to save the mole,' said Troy Hudson of a scientist and engineer with the InSight mission at NASA's Jet Propulsion Laboratory in a statement.