Governments and companies worldwide are investing heavily in artificial intelligence in hopes of new profits, smarter gadgets, and better health care. Financier and philanthropist George Soros told the World Economic Forum in Davos Thursday that the technology may also undermine free societies and create a new era of authoritarianism. "I want to call attention to the mortal danger facing open societies from the instruments of control that machine learning and artificial intelligence can put in the hands of repressive regimes," Soros said. He made an example of China, repeatedly calling out the country's president, Xi Jinping. China's government issued a broad AI strategy in 2017, asserting that it would surpass US prowess in the technology by 2030. As in the US, much of the leading work on AI in China takes place inside a handful of large tech companies, such as search engine Baidu and retailer and payments company Alibaba. Soros argued that AI-centric tech companies like those can become enablers of authoritarianism. He pointed to China's developing "social credit" system, aimed at tracking citizens' reputations by logging financial activity, online interactions, and even energy use, among other things. The system is still taking shape, but depends on data and cooperation from companies like payments firm Ant Financial, a spinout of Alibaba.

Approval ballot based committee formation is concerned with aggregating individual approvals of voters. Voters submit their approvals of candidates and these approvals are aggregated to arrive at the optimal committee of specified size. There are several aggregation techniques proposed in the literature and these techniques differ among themselves on the criterion function they optimize. Voters preferences for a candidate is based on his/her opinion on candidate suitability. We note that candidates have attributes that make him/her suitable or otherwise. Hence, it is relevant to approve attributes and select candidates who have the approved attributes. This paper addresses the committee selection problem when voters submit their approvals on attributes. Though attribute based preference is addressed in several contexts, committee selection problem with attribute approval has not been attempted earlier. We note that extending the theory of candidate approval to attribute approval in committee selection problem is not trivial. In this paper, we study different aspects of this problem and show that none of the existing aggregation rules satisfies Unanimity and Justified Representation when attribute based approvals are considered. We propose a new aggregation rule that satisfies both the above properties. We also present other analysis of committee selection problem with attribute approval.

Capsule Networks envision an innovative point of view about the representation of the objects in the brain and preserve the hierarchical spatial relationships between them. This type of networks exhibits a huge potential for several Machine Learning tasks like image classification, while outperforming Convolutional Neural Networks (CNNs). A large body of work has explored adversarial examples for CNNs, but their efficacy to Capsule Networks is not well explored. In our work, we study the vulnerabilities in Capsule Networks to adversarial attacks. These perturbations, added to the test inputs, are small and imperceptible to humans, but fool the network to mis-predict. We propose a greedy algorithm to automatically generate targeted imperceptible adversarial examples in a black-box attack scenario. We show that this kind of attacks, when applied to the German Traffic Sign Recognition Benchmark (GTSRB), mislead Capsule Networks. Moreover, we apply the same kind of adversarial attacks to a 9-layer CNN and analyze the outcome, compared to the Capsule Networks to study their differences / commonalities.

Chinese telecom giant Huawei is at the centre of an increasingly tense standoff between China and the US. What began as a trade spat and grievances over corporate intellectual property theft has developed into a global standoff involving "hostage diplomacy", death sentences and allegations of Chinese espionage. Huawei's senior executive Meng Wanzhou, was arrested in Canada in December over allegations of sanctions violations, and awaits extradition to the US. Meanwhile, three Canadians remain in police custody in China – with one of them sentenced to death this month. Washington, meanwhile, has said it will file a formal extradition request for Meng by the 30 January deadline.

Yeah, WIRED Transportation loves new car tech. But this week, we were all about alternatives to driving around on four wheels. We thought about what might make public transit more comfortable for more than half of the population--you know, women. We wondered what might happen to the nation's aviation system now that the federal government is open again--and came away depressed. And we took a close look at Amazon's delivery robots.

The price paid by the transferees does not correspond to the software itself, which in itself has little value, but to the secret scientific procedures that the software has implemented in it. These procedures are registered under the formula of industrial secret. The technology to be transferred incorporates an artificial intelligence system that involves a specialized advisory service that adapts case by case to the needs of the client. According to the modalities actually analyzed, in this case a contract has been signed by which the license to use temporarily or permanently a software containing procedures that allow theoretically determine various situations for marketing. In accordance with the case law of the Supreme Court (inter alia, STS of 30 May 2002; of 19 December 2002 or of 2 October 1999), it is essential to distinguish contracts for the assignment or licensing of know-how from contracts for technical assistance, both of which are distinct from contracts for the transfer of technology.

Published by the Royal Society.

It was not long ago thatArtificial Intelligence (AI) was only in the realm of science fiction. Today, it has become a reality and is only growing more prominent in many different industries every day. This includes the internet as AI in search engine technology has been around for a few years. The algorithms used to rank pages have been affected considerably by AI already and that trend will continue into the foreseeable future. How Popular Search Engines Will Evolve in the AI Process Currently, Google's RankBrain, an AI process used help set search engine rankings, is having a major impact which is only expected to expand.

It's going to be interesting to see how society deals with artificial intelligence, but it will definitely be cool. World over, political practices are in decline. I was shocked to see the advertising expenses by political leaders. Just imagine, we work hard, earn money, pay taxes and then, our tax money is used on advertising to tell us that we are doing so great. Come on, we have worked hard and we know that we are doing great.

In fact, it is already here and unfortunately, embedded system engineers have been caught off-guard and snoozing. As you might have guessed, I'm not talking about the internal revenue service but Intelligent Real-time Systems (IRS). Intelligent Real-time Systems are microcontroller-based devices that have the ability to learn to use data by running a resident, artificial intelligence algorithm (AI). There have always been two different ways that teams could leverage artificial intelligence in their products. The first, and the most realistic for the last decade, has been to execute the AI algorithms in the cloud.