Since Theresa May invoked Article 50, there has been a mystifying surge in video games set in Britain. They come in all shapes and sizes, from Nintendo's Pokémon Sword and Shield, which riffs on the architecture of Oxbridge and London, to PanicBarn's anti-Brexit polemic Not Tonight. Most began development long before the EU referendum, but they are useful explorations of national identity at a time when what Britain stands for is hotly contested. Gary Younge has described the Brexit debate as a clash between stories about Britain's past and our ideas of Britishness. How, then, might these video games help us think about what Britain is today? In the 9th-century, Britain was not one but several nations, a mass of warring Anglo-Saxon, Celtic and Viking kingdoms.

The fashion industry is forever being accused of using models that have unrealistic standards of beauty -- but in the future, the models themselves could be unreal, too. All of the realistic-looking people in the video below are actually fakes -- dreamed up by a pair of AI developed by researchers from Kyoto University in Japan. The AI were first trained on real-life pictures of humans models. From this, one AI was tasked with repeatedly trying to dream up images of replica models that its counterpart could not distinguish form the real thing. This model-creating technology could one day be used to create fake models for use in advertisements and by the clothing and fashion industries.

Following warnings from the FTC, both Apple and Google have removed several dating apps from their platforms that they say allowed children to join. According to a letter sent by the FTC to Ukraine-based Wildec LLC, which owns FastMeet, Meet24 and Meet4U, the trio of dating apps allowed children as young as 12 to participate in the service and communicate with adults. In an FTC investigation of the app, the organization says they were also able to identify and confirm multiple children within the service using a built-in age filter that allows users to search by age. A trio of dating apps was removed by Google and Apple for allowing children under 13-years-old to participate. The FTC says the apps have already been used by sexual predators.

Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of evolving threats, data deluge, and rapid courses of action. Developing an end-to-end artificial intelligence system involves parallel development of different pieces that must work together in order to provide capabilities that can be used by decision makers, warfighters and analysts. These pieces include data collection, data conditioning, algorithms, computing, robust artificial intelligence, and human-machine teaming. While much of the popular press today surrounds advances in algorithms and computing, most modern AI systems leverage advances across numerous different fields. Further, while certain components may not be as visible to end-users as others, our experience has shown that each of these interrelated components play a major role in the success or failure of an AI system. This article is meant to highlight many of these technologies that are involved in an end-to-end AI system. The goal of this article is to provide readers with an overview of terminology, technical details and recent highlights from academia, industry and government. Where possible, we indicate relevant resources that can be used for further reading and understanding.

These authors contributed equally to this work. Artificial intelligence (AI) researchers claim that they have made great'achievements' in clinical realms. However, clinicians point out the so-called'achievements' have no ability to implement into natural clinical settings. The root cause for this huge gap is that many essential features of natural clinical tasks are overlooked by AI system developers without medical background. In this paper, we propose that the clinical benchmark suite is a novel and promising direction to capture the essential features of the real-world clinical tasks, hence qualifies itself for guiding the development of AI systems, promoting the implementation of AI in real-world clinical practice. AI researchers claim that they have obtained many significant'achievements' in various However, in practice, most of the AI products fail to obtain approval from the Food and Drug Administration (FDA). AI devices are not qualified handling high-risk tasks such as clinical diagnosis .

Check out part one of this series for what the next five to fifteen years looks like in AI. In part two we get super sci-fi and see if our crystal ball can reach 50 years into the future. Once dumb objects have woken up. Your shirt is babbling away with your shades and having a conversation with your girlfriend's pearl earrings when she's traveling to give a talk in Brazil. Everything from our houses, to weapons, to planes, trains and automobiles, to roads, clothes, jewelry, headphones, glasses, and eye contacts are wild with thoughts. The dynamic new algorithms that pushed us past deep learning and powered the fourth wave of the intelligence revolution sprang from world wide efforts to map every single neuron and connection in the human brain. Eventually the processors and biotechnology caught up with our ambitions and scientists succeeded beyond our wildest expectations.

AstraZeneca announced a long-term collaboration deal with BenevolentAI, a UK-based company focused on combining computational medicine and advanced artificial intelligence. The two companies will focus on using AI and machine learning to discover and develop new drugs for chronic kidney disease (CKD) and idiopathic pulmonary fibrosis (IPF). "The vast amount of data available to research scientists is growing exponentially each year," stated Mene Pangalo, AstraZeneca's executive vice president and president BioPharmaceuticals R&D. "By combining AstraZeneca's disease area expertise and large, diverse datasets with BenevolentAI's leading AI and machine learning capabilities, we can unlock the potential of this wealth of data to improve our understanding of complex disease biology and identify new targets that could treat debilitating diseases." No financial details were disclosed.

StartupBlink, a Swiss interactive platform for startups, has released its 2019 Ecosystem Ranking Report, with Canada holding on to the third position, boasting five cities in the top 100 startup ecosystems globally. "Canada's major strength lies in the distribution of strong startup hubs scattered throughout the country." Along with Canada, the US, UK, and Israel all held on to the top four spots for countries with the strongest startup ecosystems. However, Canada's typical tech hubs fell in the rankings compared to 2017. This year, Toronto ranked 15, after dropping four spots, while Vancouver dropped six places to 24.

More? Check out the book! Discover a correlation: find new correlations. Go to the next page of charts, and keep clicking "next" to get through all 30,000. Or for something totally different, here is a pet project: When is the next time something cool will happen in space? Discover a correlation: find new correlations.

Encouraging sustainable mobility patterns is at the forefront of policymaking at all scales of governance as the collective consciousness surrounding climate change continues to expand. Not every community, however, possesses the necessary economic or socio-cultural capital to encourage modal shifts away from private motorized vehicles towards active modes. The current literature on `soft' policy emphasizes the importance of tailoring behavior change campaigns to individual or geographic context. Yet, there is a lack of insight and appropriate tools to promote active mobility and overcome transport disadvantage from the local community perspective. The current study investigates the promotion of walking and cycling adoption using a series of focus groups with local residents in two geographic communities, namely Chicago's (1) Humboldt Park neighborhood and (2) suburb of Evanston. The research approach combines traditional qualitative discourse analysis with quantitative text-mining tools, namely topic modeling and sentiment analysis. The analysis uncovers the local mobility culture, embedded norms and values associated with acceptance of active travel modes in different communities. We observe that underserved populations within diverse communities view active mobility simultaneously as a necessity and as a symbol of privilege that is sometimes at odds with the local culture. The mixed methods approach to analyzing community member discourses is translated into policy findings that are either tailored to local context or broadly applicable to curbing automobile dominance. Overall, residents of both Humboldt Park and Evanston envision a society in which multimodalism replaces car-centrism, but differences in the local physical and social environments would and should influence the manner in which overarching policy objectives are met.