"Britons on way to France risk quarantine" is the front page headline in the Times, as it reports that Whitehall officials have placed the country on a list of destinations to be closely monitored. A senior aviation source is quoted saying France is "bubbling" with cases and that travellers should only book trips which can be re-arranged at 24 hours' notice. The Daily Telegraph also reports the close monitoring of France as cases there overtake the numbers for Portugal, which has reduced its infection rate. The paper says about 450,000 Britons are currently holidaying in France, a scale which would make any new restrictions a logistical nightmare. The Guardian leads with an exclusive warning from doctors' leaders that shutting down non-Covid NHS services to deal with any second wave will leave thousands of patients unacceptably "stranded", risking more deaths.
Arrangements for the OECD's role as host will be finalised in the coming days. The GPAI will bring together experts from industry, government, civil society and academia to conduct research and pilot projects on AI. Its objective, as set out by founding members Australia, Canada, the European Union, France, Germany, India, Italy, Japan, Korea, Mexico, New Zealand, Singapore, Slovenia, the United Kingdom and the United States, is to bridge the gap between theory and practice on AI policy. An example would be looking at how AI could help societies respond to and recover from the Covid-19 crisis. Basing its Secretariat at the OECD will allow the GPAI to create a strong link between international policy development and technical discourse on AI, taking advantage of the OECD's expertise on AI policy and its leadership in setting out the first international standard for trustworthy AI – the OECD Principles on Artificial Intelligence.
Since COVID-19 was first identified in December 2019, various public health interventions have been implemented across the world. As different measures are implemented at different countries at different times, we conduct an assessment of the relative effectiveness of the measures implemented in 18 countries and regions using data from 22/01/2020 to 02/04/2020. We compute the top one and two measures that are most effective for the countries and regions studied during the period. Two Explainable AI techniques, SHAP and ECPI, are used in our study; such that we construct (machine learning) models for predicting the instantaneous reproduction number ($R_t$) and use the models as surrogates to the real world and inputs that the greatest influence to our models are seen as measures that are most effective. Across-the-board, city lockdown and contact tracing are the two most effective measures. For ensuring $R_t<1$, public wearing face masks is also important. Mass testing alone is not the most effective measure although when paired with other measures, it can be effective. Warm temperature helps for reducing the transmission.
ECMWF is organising a series of seminars given by international experts to explore aspects of the use of machine learning in weather prediction and climate studies. The first will take place on 28 April and will be live-streamed. Sherman Lo and Ritabrata Dutta from the University of Warwick will present a statistical methodology to predict precipitation at 0.1 resolution using lower-resolution model fields of air temperature, geopotential, specific humidity, total column water vapour and wind velocity. On 9 June, Annalisa Bracco from the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology will talk about spatiotemporal complexity and time-dependent networks in mid- to late Holocene simulations. In subsequent seminars, Maxime Taillardat (Météo-France) will present examples of operational ensemble post-processing using machine learning; Alberto Arribas (UK Met Office) will talk about work at the Met Office Informatics Lab; and Nal Kalchbrenner (Google) will talk about now-casting applications at Google.
Hogan, Aidan, Blomqvist, Eva, Cochez, Michael, d'Amato, Claudia, de Melo, Gerard, Gutierrez, Claudio, Gayo, José Emilio Labra, Kirrane, Sabrina, Neumaier, Sebastian, Polleres, Axel, Navigli, Roberto, Ngomo, Axel-Cyrille Ngonga, Rashid, Sabbir M., Rula, Anisa, Schmelzeisen, Lukas, Sequeda, Juan, Staab, Steffen, Zimmermann, Antoine
In this paper we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After a general introduction, we motivate and contrast various graph-based data models and query languages that are used for knowledge graphs. We discuss the roles of schema, identity, and context in knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We summarise methods for the creation, enrichment, quality assessment, refinement, and publication of knowledge graphs. We provide an overview of prominent open knowledge graphs and enterprise knowledge graphs, their applications, and how they use the aforementioned techniques. We conclude with high-level future research directions for knowledge graphs.
The European Union's leading tech regulator has thrown her weight behind the British government's plans to press ahead with a digital tax despite threats from Donald Trump. Margrethe Vestager, the EU competition commissioner recently promoted to take charge of Europe's digital policy as well, said she was a "strong supporter" of national digital taxes in order to advance the chances of an international agreement. She said the EU would revive plans for a digital tax within a year if international efforts to find a solution failed. "I think it is very important that we keep up the momentum. Because of this very fundamental injustice that most people and businesses pay their taxes and they are competing with businesses who create value but do not pay taxes," she said in an interview with the Guardian and other European newspapers.
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations.
Artificial Intelligence (AI) is opening up a new frontier by combining human creativity with technology to drive progress in our society and bring governments closer to their constituents. According to the 2018 United Nations (UN) e-Government Survey all 193 Member States have e-government systems in place, at different maturity levels, to deliver digital services and experiences to citizens. The three most commonly used e-government services are paying utilities (140 countries), submitting income taxes (139 countries), and registering a new business (126 countries). Denmark is heading the top 10 e-government development ranking, followed by Australia, the Republic of Korea, United Kingdom, Sweden, Finland, Singapore, New Zealand, France and Japan. The next phase of e-government will use AI to go beyond digitized and automated services and deliver better experiences to citizens.
With leaders increasingly seeing artificial intelligence (AI) as helping to drive the next great economic expansion, a fear of missing out is spreading around the globe. Numerous nations have developed AI strategies to advance their capabilities, through investment, incentives, talent development, and risk management. As AI's importance to the next generation of technology grows, many leaders are worried that they will be left behind and not share in the gains. There is a growing realization of AI's importance, including its ability to provide competitive advantage and change work for the better. A majority of global early adopters say that AI technologies are especially important to their business success today--a belief that is increasing. A majority also say they are using AI technologies to move ahead of their competition, and that AI empowers their workforce. AI success depends on getting the execution right. Organizations often must excel at a wide range of practices to ensure AI success, including developing a strategy, pursuing the right use cases, building a data foundation, and cultivating a strong ability to experiment. These capabilities are critical now because, as AI becomes even easier to consume, the window for competitive differentiation will likely shrink. Early adopters from different countries display varying levels of AI maturity. Enthusiasm and experience vary among early adopters from different countries. Some are pursuing AI vigorously, while others are taking a more cautious approach.
DAVOS, SWITZERLAND – The star who stole the stage at the annual meeting of the World Economic Forum, which just ended here yesterday, wasn't the stuff of flesh and blood but of data-driven algorithms. US President Donald Trump, China's Xi Jinping, India's Narendra Modi, France's Emmanuel Macron and Great Britain's Theresa May were no shows at this gathering of global movers and shakers, occupied with more pressing matters at home. That left hundreds of global business executives with less distraction as they turned their attention to Artificial Intelligence (AI), a term few of them knew even a couple of years ago and a technology they still don't fully comprehend. Yet in one session after another, they shared what they were (or weren't) doing about it and learned how AI would transform their industries, their societies and international relations, perhaps as no technology before it. Not even news late in the week from Venezuela shifted the conversation all that much.