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The history of modern art is often told through aesthetic breakthroughs that sync well with cultural and political change. From Courbet to Picasso, from Malevich to Warhol, it is accepted that art tracks the disruptions of industrialization, fascism, revolution, and war. Yet filtering the history of modern art only through catastrophic events cannot account for the subtle developments that lead to the profound confusion at the heart of contemporary art. In Industry and Intelligence, the artist Liam Gillick writes a nuanced genealogy to help us appreciate contemporary art's engagement with history even when it seems apathetic or blind to current events. Taking a broad view of artistic creation from 1820 to today, Gillick follows the response of artists to incremental developments in science, politics, and technology. The great innovations and dislocations of the nineteenth and twentieth centuries have their place in this timeline, but their traces are alternately amplified and diminished as Gillick moves through artistic reactions to liberalism, mass manufacturing, psychology, nuclear physics, automobiles, and a host of other advances. He intimately ties the origins of contemporary art to the social and technological adjustments of modern life, which artists struggled to incorporate truthfully into their works.
Artificial Intelligence and Industry 4.0 by Aboul Ella Hassanien,Jyotir Moy Chatterjee,Vishal Jain Pdf
Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT. Explores artificial intelligence applications within the industrial manufacturing and communications sectors Presents a wide range of machine learning, computer vision, and digital twin applications across the IoT sector Explores how deep learning and cognitive computing tools enable processing vast data sets, precise and comprehensive forecast of risks, and delivering recommended actions
Regulating Artificial Intelligence in Industry by Damian M. Bielicki Pdf
Artificial Intelligence (AI) has augmented human activities and unlocked opportunities for many sectors of the economy. It is used for data management and analysis, decision making, and many other aspects. As with most rapidly advancing technologies, law is often playing a catch up role so the study of how law interacts with AI is more critical now than ever before. This book provides a detailed qualitative exploration into regulatory aspects of AI in industry. Offering a unique focus on current practice and existing trends in a wide range of industries where AI plays an increasingly important role, the work contains legal and technical analysis performed by 15 researchers and practitioners from different institutions around the world to provide an overview of how AI is being used and regulated across a wide range of sectors, including aviation, energy, government, healthcare, legal, maritime, military, music, and others. It addresses the broad range of aspects, including privacy, liability, transparency, justice, and others, from the perspective of different jurisdictions. Including a discussion of the role of AI in industry during the Covid-19 pandemic, the chapters also offer a set of recommendations for optimal regulatory interventions. Therefore, this book will be of interest to academics, students and practitioners interested in technological and regulatory aspects of AI.
Artificial Intelligence in Industry 4.0 by Alexiei Dingli,Foaad Haddod,Christina Klüver Pdf
This book is intended to help management and other interested parties such as engineers, to understand the state of the art when it comes to the intersection between AI and Industry 4.0 and get them to realise the huge possibilities which can be unleashed by the intersection of these two fields. We have heard a lot about Industry 4.0, but most of the time, it focuses mainly on automation. In this book, the authors are going a step further by exploring advanced applications of Artificial Intelligence (AI) techniques, ranging from the use of deep learning algorithms in order to make predictions, up to an implementation of a full-blown Digital Triplet system. The scope of the book is to showcase what is currently brewing in the labs with the hope of migrating these technologies towards the factory floors. Chairpersons and CEOs must read these papers if they want to stay at the forefront of the game, ahead of their competition, while also saving huge sums of money in the process.
Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.
Artificial Intelligence in Industrial Applications by Steven Lawrence Fernandes,Tarun K. Sharma Pdf
This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. In the past few decades there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in industrial domain. The versatility of these techniques have made them a favorite among scientists and researchers working in diverse areas. The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying computational intelligence and their applications. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems. This book will be a useful resource for researchers, academicians as well as professionals interested in the highly interdisciplinary field of Artificial Intelligence.
Author : Harold L. Wilensky Publisher : Quid Pro Books Page : 226 pages File Size : 50,5 Mb Release : 2015-02-14 Category : Political Science ISBN : 9781610272889
Organizational Intelligence by Harold L. Wilensky Pdf
The prize-winning book Organizational Intelligence focuses on the structural and ideological roots of intelligence (informational and analytical) failures in government, industry, and other institutions. It provides groundbreaking theory and structure to the analysis of decision-making processes and their breakdowns, as well as the interactions among experts and the organizations they inform. In this book, both "organization" and "intelligence" are taken to their larger meanings, not just focused on the military meaning of intelligence or on one set of institutions in society. Astute illustrations of intelligence failures abound from real-world cases, such as foreign policy (the Bay of Pigs, Soviet predictions in the Cuban missile crisis), military (civilian bombing of Germany, Pearl Harbor), financial (AmEx's investment in a vegetable oil guru), economics (the Council of Economic Advisers) and industrial production (Ford's Edsel), as well as many other telling arenas and disciplines. Economic, cultural, legal, and political contexts are considered, as well as the more known institutions of government and commerce. The new Classics of the Social Sciences edition from Quid Pro Books features a 2015 Foreword from Neil J. Smelser, University Professor Emeritus at Berkeley and former chair of its sociology department. He writes that the book remains "one of the classics in organizational studies, and—in ways I will indicate—it is still directly relevant to current and future problems of organizational life. ... What makes this book a classic? It is a disciplined, intelligent, and elegant model of applied social science. ... The text itself, richly documented empirically, yields an informed and balanced account of the decision-making process as this is shaped by the quality of information available (and unavailable) to and used (and not used) by organizational leaders." Reviews of the book at the time it was written similarly attest to the originality and breadth of its interdisciplinary analysis. Amitai Etzioni wrote in the American Sociological Review: "This book opens a whole new field — the macrosociology of knowledge. It is as different from the traditional sociology of knowledge as the study of interaction is from that of the structure of total societies." He adds, "The power of Wilensky's contribution is further magnified by his historical perspective. He studies structures and processes, but not in a vacuum." Gordon Craig wrote in The Reporter that the book's examples from organizations "show a similar tendency to believe what they want to believe, to become the victims of their own slogans and propaganda, and to resist or to silence warning voices that challenge their assumptions.... In his fascinating analysis of intelligence failures and their causes ... in the public and private sectors, Wilensky finds that the most disastrous miscalculations are those which have occurred in the field of governmental operations, especially foreign policy and national security." The book explains how such highly institutionalized actors are vulnerable to informational pathologies. The new digital edition features active Contents, a fully linked Index, linked notes, and proper ebook formatting. It is a modern, quality, and authorized re-presentation of a classic work in social science and organizational studies.
Artificial Intelligence for Digitising Industry – Applications by Ovidiu Vermesan Pdf
This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.
Computational Sciences and Artificial Intelligence in Industry by Tero Tuovinen,Jacques Periaux,Pekka Neittaanmäki Pdf
This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors.
Impact and Opportunities of Artificial Intelligence Techniques in the Steel Industry by Valentina Colla,Costanzo Pietrosanti Pdf
This book collects perceptions and needs expectations and experiences concerning the application of Artificial Intelligence (AI) and Machine Learning in the steel sector. It contains a selection of themes discussed within the Workshop entitled “Impact and Opportunities of Artificial Intelligence in the Steel Industry” organized by the European Steel Technology Platform as an online event from October 15 until November 5, 2020. The event aimed at analyzing the diffusion of AI technologies in steelworks and at providing indications for future research, development and innovation actions addressing the sector demands. The chapters treat general analyses on transversal themes and applications for process optimization, product quality enhancement, yield increase, optimal exploitation of resources and smart data handling. The book is devoted to researchers and technicians in the steel or AI fields as well as for managers and policymakers exploring the opportunities provided by AI in industry.
Artificial Intelligence and the Fourth Industrial Revolution by Utpal Chakraborty,Amit Banerjee,Jayanta Kumar Saha,Niloy Sarkar,Chinmay Chakraborty Pdf
This book presents the overall technology spectrum in artificial intelligence (AI) and the Fourth Industrial Revolution, which is set to revolutionize the world. It discusses their various aspects and related case studies from industry, academics, administration, law, finance, and accounting as well as educational technology. The contributors, who are experts in their respective fields and from industry and academia, focus on a gesture-recognition prototype for specially abled people; jurisprudential approach to AI and legal reasoning; automated chatbot for autism spectrum disorder using AI assistance; Big Data analytics and Internet of Things (IoT); role of AI in advancement of drug discovery; development, opportunities, and challenges of the Fourth Industrial Revolution; legal, ethical, and policy implications of AI; Internet of Health Things for smart healthcare and digital wellbeing; machine learning and computer vision; computer vision-based system for automation and industrial applications; AI-IoT in home-based healthcare; and AI in super-precision human brain and spine surgery. Buttressed with comprehensive theoretical, methodological, well-established, and validated empirical examples, the book covers the interests of a broad audience from basic science to engineering and technology experts and learners. It will be greatly helpful for CEOs, entrepreneurs, academic leaders, researchers, and students of engineering, biomedicine, and master’s programs in science as well as the vast workforce and students with technical or non-technical backgrounds. It also serves common public interest by presenting new methods to improve the quality of life in general, with a better integration into society.
Manufacturing Intelligence for Industrial Engineering: Methods for System Self-Organization, Learning, and Adaptation by Zhou, Zude,Wang, Huaiqing,Lou, Ping Pdf
"This book focuses on the latest innovations in the process of manufacturing in engineering"--Provided by publisher.
Artificial Intelligence and Industrial Applications by Tawfik Masrour,Ibtissam El Hassani,Anass Cherrafi Pdf
This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA’2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
Artificial Intelligence and Industrial Applications by Tawfik Masrour,Ibtissam El Hassani,Noureddine Barka Pdf
Amid the dynamic growth of artificial intelligence, this book presents a collection of findings and advancements from the second edition of the A2IA-Artificial Intelligence and Industrial Applications conference. The conference, hosted by ENSAM-Meknès at Moulay Ismail University, Morocco, fosters knowledge exchange in AI, focusing primarily on its industrial applications. Covering a wide range of topics, the book highlights the adaptable nature of AI and its increasing impact on industrial sectors. It brings together contributions from an international cohort of researchers, discussing themes such as intelligent manufacturing and maintenance, intelligent supply chain management, various modes of learning including supervised, unsupervised, reinforcement, semi-supervised, and graph-based, as well as neural networks, deep learning, planning, and optimization. A defining feature of this edition is its extensive scope and emphasis on the practical applications of AI, along with its foundational elements. It facilitates an understanding of AI's current state and potential future direction, showcasing recent developments that bridge the gap between theory and practice. Designed for a diverse readership, this book is of interest to AI practitioners, academics, and enthusiasts, as well as to those new to the field. It provides an opportunity to explore AI's critical role in industrial applications, and the practical insights it offers are likely to be beneficial for decision-making within industrial settings.
