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Will the use of artificial intelligence (AI), algorithms, and smart machines be the end of journalism as we know it—or its savior? In Newsmakers, Francesco Marconi, who has led the development of the Associated Press and Wall Street Journal’s use of AI in journalism, offers a new perspective on the potential of these technologies. He explains how reporters, editors, and newsrooms of all sizes can take advantage of the possibilities they provide to develop new ways of telling stories and connecting with readers. Marconi analyzes the challenges and opportunities of AI through case studies ranging from financial publications using algorithms to write earnings reports to investigative reporters analyzing large data sets to outlets determining the distribution of news on social media. Newsmakers contends that AI can augment—not automate—the industry, allowing journalists to break more news more quickly while simultaneously freeing up their time for deeper analysis. Marshaling insights drawn from firsthand experience, Marconi maps a media landscape transformed by artificial intelligence for the better. In addition to considering the benefits of these new technologies, Marconi stresses the continuing need for editorial and institutional oversight. Newsmakers outlines the important questions that journalists and media organizations should consider when integrating AI and algorithms into their workflow. For journalism students as well as seasoned media professionals, Marconi’s insights provide much-needed clarity and a practical roadmap for how AI can best serve journalism.
This bestselling book gives business leaders and executives a foundational education on how to leverage artificial intelligence and machine learning solutions to deliver ROI for your business.
This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems. Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images. The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.
Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.
Knowledge Processing and Applied Artificial Intelligence discusses the business potential of knowledge processing and examines the aspects of applied artificial intelligence technology. The book is comprised of nine chapters that are organized into five parts. The text first covers knowledge processing and applied artificial intelligence, and then proceeds to tackling the techniques for acquiring, representing, and reasoning with knowledge. The next part deals with the process of creating and implementing strategically advantageous knowledge-based system applications. The fourth part covers intelligent interfaces, while the last part details alternative approaches to knowledge processing. The book will be of great use to students and professionals of computer or business related disciplines.
This comprehensive reference to all areas of expert systems and applications, plus advanced related topics, lets you spend your time reading expert systems literature rather than searching for it. It gives you a source of historical perspectives and outlooks on the future of the field. Whether you are a manager, a developer or an end user or researcher, Expert Systems and Related Topics: Selected Bibliography & Guide to Information Sources puts all the sources of expert systems literature at your fingertips.
“Intelligent systems must perform in order to be in demand. ” Intelligent systems technology is being applied steadily in solving many day-to-day problems. Each year the list of real-world deployed applications that inconspicuously host the results of research in the area grows considerably. These applications are having a significant impact in industrial operations, in financial circles, in transportation, in education, in medicine, in consumer products, in games and elsewhere. A set of selected papers presented at the seventeenth in the series of conferences on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2004), sponsored by the International Society of Applied Intelligence, is offered in this manuscript. These papers highlight novel applications of the technology and show how new research could lead to new and innovative applications. We hope that you find these papers to be educational, useful in your own research, and stimulating. In addition, we have introduced some special sessions to emphasize a few areas of artificial intelligence (AI) that are either relatively new, have received considerable attention recently or perhaps have not yet been represented well. To this end, we have included special sessions on e-learning, bioinformatics, and human-robot interaction (HRI) to complement the usual offerings in areas such as data mining, machine learning, intelligent systems, neural networks, genetic algorithms, autonomous agents, natural language processing, intelligent user interfaces, evolutionary computing, fuzzy logic, computer vision and image processing, reasoning, heuristic search, security, Internet applications, constraint satisfaction problems, design, and expert systems.