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Technology Differences over Space and Time looks at how countries use their productive resources—such as workers, skills, equipment and structures, and natural resources. Francesco Caselli develops methods to assess the efficiency with which productive inputs are used, and how these efficiencies vary across countries and over time. Caselli finds that richer countries use skilled workers relatively more efficiently than unskilled workers, and equipment and structures relatively more efficiently than natural resources. They also are relatively more efficient users of labor than of capital. Technological change tends to make countries particularly efficient at using skills and less efficient at using capital. Technical change also favors experienced workers. In order to interpret and understand these findings, Caselli presents a theory of technology choice. In this theory, firms pick technologies that make the most efficient use of the most abundant production factors when these factors are good substitutes for the less abundant factors. Firms pick technologies that make the most of less abundant factors when other suitable factors are not available for substitution. For example, rich countries, where skilled workers are abundant, use skilled workers efficiently, as these are good substitutes for unskilled workers. This flexible framework can be applied to other pairs of inputs, over time, and across countries. Technology Differences over Space and Time has significant implications not only for the theoretical understanding of development and technological innovation, but also for government formulation of industrial policy and multinationals making decisions about what to invest in and where to make those investments.
Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
The central purpose of this collection of essays is to make a creative addition to the debates surrounding the cultural heritage domain. In the 21st century the world faces epochal changes which affect every part of society, including the arenas in which cultural heritage is made, held, collected, curated, exhibited, or simply exists. The book is about these changes; about the decentring of culture and cultural heritage away from institutional structures towards the individual; about the questions which the advent of digital technologies is demanding that we ask and answer in relation to how we understand, collect and make available Europe’s cultural heritage. Cultural heritage has enormous potential in terms of its contribution to improving the quality of life for people, understanding the past, assisting territorial cohesion, driving economic growth, opening up employment opportunities and supporting wider developments such as improvements in education and in artistic careers. Given that spectrum of possible benefits to society, the range of studies that follow here are intended to be a resource and stimulus to help inform not just professionals in the sector but all those with an interest in cultural heritage.
A revised and updated edition of an acknowledged classic of the Organizational Development literature. Over 30,000 of first and second editions sold.
"This book summarizes the challenges inherent in leading distributed teams and explores practices that are emerging to optimize distributed team performance"--Provided by publisher.
The papers in this volume comprise the refereed proceedings of the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA2008), in Beijing, China, 2008. The conference on the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA 2008) is cooperatively sponsored and organized by the China Agricultural University (CAU), the National Engineering Research Center for Information Technology in Agriculture (NERCITA), the Chinese Society of Agricultural Engineering (CSAE) , International Federation for Information Processing (IFIP), Beijing Society for Information Technology in Agriculture, China and Beijing Research Center for Agro-products Test and Farmland Inspection, China. The related departments of China’s central government bodies like: Ministry of Science and Technology, Ministry of Industry and Information Technology, Ministry of Education and the Beijing Municipal Natural Science Foundation, Beijing Academy of Agricultural and Forestry Sciences, etc. have greatly contributed and supported to this event. The conference is as good platform to bring together scientists and researchers, agronomists and information engineers, extension servers and entrepreneurs from a range of disciplines concerned with impact of Information technology for sustainable agriculture and rural development. The representatives of all the supporting organizations, a group of invited speakers, experts and researchers from more than 15 countries, such as: the Netherlands, Spain, Portugal, Mexico, Germany, Greece, Australia, Estonia, Japan, Korea, India, Iran, Nigeria, Brazil, China, etc.
"This set of books represents a detailed compendium of authoritative, research-based entries that define the contemporary state of knowledge on technology"--Provided by publisher.
New York Times Bestseller "Readers cannot but be provoked and stimulated by this splendidly iconoclastic and refreshing book." —Andrew Porter, New York Times Book Review The Wealth and Poverty of Nations is David S. Landes's acclaimed, best-selling exploration of one of the most contentious and hotly debated questions of our time: Why do some nations achieve economic success while others remain mired in poverty? The answer, as Landes definitively illustrates, is a complex interplay of cultural mores and historical circumstance. Rich with anecdotal evidence, piercing analysis, and a truly astonishing range of erudition, The Wealth and Poverty of Nations is a "picture of enormous sweep and brilliant insight" (Kenneth Arrow) as well as one of the most audaciously ambitious works of history in decades.
Going Virtual: Distributed Communities of Practice contributes to the understanding of how more subtle kinds of knowledge can be managed in a distributed international environment. It describes work in the field of knowledge management, with a specific focus on the management of knowledge which cannot be managed by the normal capture-codify-store approach and provides answers to the questions of what is the nature of the more subtle kind of knowledge and how can it be managed in the distributed environment?