Venezuela's interior minister says six people have been arrested, after what President Nicolas Maduro says was an assassination attempt against him. The president accuses Colombia and a group of US financiers of trying to kill him. Venezuela's opposition fears the government will launch a crackdown. Colombia's Foreign Affairs Ministry called that accusation absurd, and in Washington, President Donald Trump's national security adviser John Bolton strongly denied any US role.

Robots have fascinated and preoccupied human minds for centuries - from ancient tales of stone golems, to modern science fiction. Though the word "robot" was only officially penned in 1921 by Karel Čapek, mankind has endeavored to create autonomous machines since as far back as the 4th Century BCE. Today, robots are widely used across a variety of industries, aiding in the manufacturing of vehicles and more. According to the International Federation of Robotics, in 2015 there were as many as 1.63 million industrial robots in operation worldwide, and that number continues to grow steadily each year. Here's a brief history of how robotics have evolved and grown from the early imaginings of 400 BCE, to the global resource they are today. The earliest beginnings of robotics can be traced back to Ancient Greece. Aristotle was one of the first great thinkers to consider automated tools, and how these tools would affect society at large.

Microsoft is warning investors that artificial intelligence technology as well as any changes to trade policies around the world may present risks to its business. In a regulatory filing Friday, the tech powerhouse said that "AI algorithms may be flawed. Datasets may be insufficient or contain biased information. Inappropriate or controversial data practices by Microsoft or others could impair the acceptance of AI solutions." It's the first time the company has specifically mentioned AI technology in such detail in its 10-K filing as part of its standard list of potential risk factors.

CARACAS – Authorities detained six people suspected of using explosives-laden drones in a failed bid to assassinate Venezuelan President Nicolas Maduro, officials said Sunday, in what one witness described as a terrifying attack that shook her apartment building. The government alleged that opposition factions conspired with assailants in Miami and Bogota, although they offered no specific evidence. Opposition leaders decried Maduro for broadly singling out his political opponents, and they warned he may use it to further suppress his critics. The thwarted attack comes as Venezuela is reeling from a worsening economic and humanitarian crisis and Maduro has grown increasingly isolated. Foreign nations, including the United States, are slapping economic sanctions against a growing list of high-ranking officials and decrying his government as an autocratic regime.

Missing data imputation can help improve the performance of prediction models in situations where missing data hide useful information. This paper compares methods for imputing missing categorical data for supervised classification tasks. We experiment on two machine learning benchmark datasets with missing categorical data, comparing classifiers trained on non-imputed (i.e., one-hot encoded) or imputed data with different levels of additional missing-data perturbation. We show imputation methods can increase predictive accuracy in the presence of missing-data perturbation, which can actually improve prediction accuracy by regularizing the classifier. We achieve the state-of-the-art on the Adult dataset with missing-data perturbation and k-nearest-neighbors (k-NN) imputation.

Deep neural networks (DNNs) are known to be vulnerable to adversarial perturbations, which imposes a serious threat to DNN-based decision systems. In this paper, we propose to apply the lossy Saak transform to adversarially perturbed images as a preprocessing tool to defend against adversarial attacks. Saak transform is a recently-proposed state-of-the-art for computing the spatial-spectral representations of input images. Empirically, we observe that outputs of the Saak transform are very discriminative in differentiating adversarial examples from clean ones. Therefore, we propose a Saak transform based preprocessing method with three steps: 1) transforming an input image to a joint spatial-spectral representation via the forward Saak transform, 2) apply filtering to its high-frequency components, and, 3) reconstructing the image via the inverse Saak transform. The processed image is found to be robust against adversarial perturbations. We conduct extensive experiments to investigate various settings of the Saak transform and filtering functions. Without harming the decision performance on clean images, our method outperforms state-of-the-art adversarial defense methods by a substantial margin on both the CIFAR-10 and ImageNet datasets. Importantly, our results suggest that adversarial perturbations can be effectively and efficiently defended using state-of-the-art frequency analysis.

Their argument is essentially, "If everyone else is doing the same thing in their respective areas, why should we be the ones to start to change?" Consequently, the situation has become chronic, and no solution is reached. Not even some of the most important public agencies that fund this kind of research in the United States take this requirement seriously. Even authors of academic or commercial studies that use data on health, find ways to get around administrative restrictions such as those imposed by the Family Educational Rights and Privacy Act (FERPA), the Health Insurance Portability and Accountability Act (HIPAA), and other regulatory legislation. The complaints of Kalev Leetaru--who has worked for Yahoo!, Google, Georgetown University, and the World Economic Forum Global Agenda Council on the Future of Government--are applicable to technicians and managers of various related activities: big data, data mining, machine learning, artificial intelligence, the internet of things, etc. At the head of these activities are professionals who come from disciplines such as information technology, who, due to their experience and position, are more accustomed to answering questions than to asking them, Leetaru says.

DARPA's Artificial Intelligence Exploration (AIE) program will speed up AI development. It will streamline the contracting procedures and funding mechanisms to achieve a start date within three months of an opportunity announcement. Researchers will then work to establish the feasibility of new AI concepts within 18 months of award. Through this nimble approach to exploring new AI concepts, DARPA aims to outpace competing, global AI science and technology discovery efforts. DARPA wants to use short-term efforts to accelerate AI advancements.

Minister of Science and Technology, Ogbonnaya Onu said President Muhammadu Buhari has approved the establishment of an agency on robotics and artificial intelligence, AI, for the South East. Mr Onu revealed this at a grand rally of the All Progressives Congress in Abakaliki, capital of Ebonyi state. The rally which received defectors from the Peoples Democratic Party, was attended by the national chairman of the party, Adams Oshiomhole. Some of the defectors who were received include, Sonni Ogbuoji, former Minister of Power and Steel, Goddy Ogbaga, former Secretary to the State Government, Bernard Odoh and former attorney general and commissioner for justice, Augustine Nwankwegu. Mr Onu told the rally that in 2015 he pleaded with South-East not to put its eggs in one basket but his pleadings fell on deaf ears.

This is a very serious, looming threat that we are currently unprepared to confront,