Editor's note: The following article contains the conclusions reached from research on the feasibility and implication of swarming weapons for use in the future operating environment. For a copy of the full monograph, please contact the author directly at sean.williams.3.sw@gmail.com. Unless otherwise annotated, images are author's original work. Swarm weapons are feasible within the next decade and those swarm weapons could have a significant impact on the battlefield providing operational advantages through employment concepts like swarm parallel warfare, cooperative survival, pulsing, and adaptive area reconnaissance. To some extent, swarms are already starting to emerge on a small scale.

Automated sentiment classification (SC) on short text fragments has received increasing attention in recent years. Performing SC on unseen domains with few or no labeled samples can significantly affect the classification performance due to different expression of sentiment in source and target domain. In this study, we aim to mitigate this undesired impact by proposing a methodology based on a predictive measure, which allows us to select an optimal source domain from a set of candidates. The proposed measure is a linear combination of well-known distance functions between probability distributions supported on the source and target domains (e.g. Earth Mover's distance and Kullback-Leibler divergence). The performance of the proposed methodology is validated through an SC case study in which our numerical experiments suggest a significant improvement in the cross domain classification error in comparison with a random selected source domain for both a naive and adaptive learning setting. In the case of more heterogeneous datasets, the predictability feature of the proposed model can be utilized to further select a subset of candidate domains, where the corresponding classifier outperforms the one trained on all available source domains. This observation reinforces a hypothesis that our proposed model may also be deployed as a means to filter out redundant information during a training phase of SC.

Most work in machine reading focuses on question answering problems where the answer is directly expressed in the text to read. However, many real-world question answering problems require the reading of text not because it contains the literal answer, but because it contains a recipe to derive an answer together with the reader's background knowledge. One example is the task of interpreting regulations to answer "Can I...?" or "Do I have to...?" questions such as "I am working in Canada. Do I have to carry on paying UK National Insurance?" after reading a UK government website about this topic. This task requires both the interpretation of rules and the application of background knowledge. It is further complicated due to the fact that, in practice, most questions are underspecified, and a human assistant will regularly have to ask clarification questions such as "How long have you been working abroad?" when the answer cannot be directly derived from the question and text. In this paper, we formalise this task and develop a crowd-sourcing strategy to collect 32k task instances based on real-world rules and crowd-generated questions and scenarios. We analyse the challenges of this task and assess its difficulty by evaluating the performance of rule-based and machine-learning baselines. We observe promising results when no background knowledge is necessary, and substantial room for improvement whenever background knowledge is needed.

BOSTON – The slaying of two competitors at a Florida video game tournament on Sunday has stirred the long-simmering gun rights debate in the state on the eve of its hotly contested state and federal primary elections. With Florida voters scheduled to pick candidates for governor and Congress on Tuesday, some Democratic contenders said the shooting on Sunday in Jacksonville was further evidence of the need for stricter gun legislation, while other hopefuls canceled campaign appearances. The violence, which also wounded 11 people, was the latest in a series of high-profile shootings in the state, following the killing of 17 students and educators at a high school in February and of 49 people at an Orlando nightclub in 2016. The Jacksonville Sheriff's Office identified the suspected shooter as David Katz, 24, of Baltimore. Witnesses told local media Katz was angry because he lost the tournament.

By rendering artificial cognition to computers, AI has broadened the scope of application for machines. Machines are, as a result, not only performing tasks, they're making decisions. Applications like data aggregation from nation-wide databases, practice tools for training troops, bioinformatics, and the security options that AI technology offers can be optimized with these intelligent computers. It is due to this competency the technology offers, that scientists have started applying AI in the defense sector to make up for the limitations that humans have. With giant leaps in the domains of AI and robotics, drones, robots, and intensive hacking systems for a country's defense are no longer limited to sci-fi movies.

Imagine what would happen if all 55,000 of America's hard-working coal miners were laid off tomorrow. The American workforce would suffer a tragic blow. Wall-to-wall 24-hour news coverage would ensue. Whole swaths of the American Southeast would be economically devasted. Now imagine something even worse -- 3.5 million people being laid off.

Workshop 18 is designated by Chinese industry officials as a model demonstration facility for Beijing's plan to upgrade its corporate champions so they can better compete in the world, a policy known as "Made in China 2025." The adoption of robots, big data and other technological advancements is seen by Chinese leaders as key to developing domestic giants in areas such as power equipment, electric cars, marine products and chips--sectors it aims to become largely self-sufficient by the middle of the next decade. Sany, one of China's three big heavy machinery makers, said the integration of technology has increased capacity, shortened order-delivery times and slashed operational costs, all by at least 20%. The company is also betting that the technology will enable it to build a reputation for innovation and quality, rather than for lower prices for copycat products that made Sany a big player domestically. "The future of the heavy-equipment industry will rely as much on software and data as it does on hardware," Sany's Chief Information Officer Pan Ruigang said. The "Made in China 2025" strategy has drawn criticism in Washington, with members of President Trump's administration accusing Beijing of using subsidies and protectionism to unfairly bolster Chinese companies.

Sky News understands that Pointr, a fast-growing "scale-up" which helps retail and transport businesses improve performance by navigating customers more efficiently, is close to finalising its Series-A fundraising. The deal with Livingbridge, which is expected to involve it injecting several million pounds in return for a sizeable equity stake in Pointr, is designed to fuel the technology company's international expansion. It will mark the latest purchase by Livingbridge of a stake in an earlier-stage business, reflecting the growing attractiveness to mainstream buyout firms of companies whose share registers have typically been dominated by venture capital funds. Pointr's technology has been installed at King's Cross Station and Gatwick Airport, as well as in Harrods, Sainsbury's and Virgin Trains. Its use of AI and augmented reality technology to provide pinpoint tracking and orient ation services is designed to help clients better understand their customers' interaction with their environment.

Killer robots must be banned to prevent unlawful killings, injuries and other violations of human rights'before it's too late', according to Amnesty International. The human rights non-profit is calling upon the United Nations to place tough new restraints on the development of autonomous weapon systems ahead of key negotiations in Geneva this week. The development of automated weapons, which can pick out and eliminate targets without input from a human being, has proliferated over the past decade. Countries including the UK, France, Israel and the US are known to be developing the technology for use in military and police operations. Amnesty International argues humans should remain'at the core of critical decisions' on the use of deadly force, such as the selection and engagement of targets.

There is a "real danger to humanity" if there is no ban on so-called killer robots, says professor of artificial intelligence (AI) and robotics Noel Sharkey. The long-time campaigner against killer robots told Verdict in an exclusive video interview about the dangers of lethal autonomous weapons (LAWS), which are being developed by militaries to kill without human oversight. He made the warning ahead of the UN's 6th meeting on LAWS, taking place in Geneva today and lasting throughout the week. The most recent meeting was in April and saw Austria and China join the list of countries calling for a prohibition on LAWS. This meeting will see more than 70 governments from around the world meet under the auspices of the Convention of Certain Conventional Weapons (CCW).