Author: Liam Gillick
Publisher: Columbia University Press
ISBN: 0231540965
Category : Art
Languages : en
Pages : 209
Book Description
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.
Industry and Intelligence
Author: Liam Gillick
Publisher: Columbia University Press
ISBN: 0231540965
Category : Art
Languages : en
Pages : 209
Book Description
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.
Publisher: Columbia University Press
ISBN: 0231540965
Category : Art
Languages : en
Pages : 209
Book Description
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
Author: Aboul Ella Hassanien
Publisher: Academic Press
ISBN: 0323906397
Category : Technology & Engineering
Languages : en
Pages : 264
Book Description
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
Publisher: Academic Press
ISBN: 0323906397
Category : Technology & Engineering
Languages : en
Pages : 264
Book Description
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
Artificial Intelligence in Industry 4.0
Author: Alexiei Dingli
Publisher: Springer Nature
ISBN: 3030610454
Category : Technology & Engineering
Languages : en
Pages : 248
Book Description
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.
Publisher: Springer Nature
ISBN: 3030610454
Category : Technology & Engineering
Languages : en
Pages : 248
Book Description
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.
Artificial Intelligence in Industrial Applications
Author: Steven Lawrence Fernandes
Publisher: Springer Nature
ISBN: 3030853837
Category : Technology & Engineering
Languages : en
Pages : 203
Book Description
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.
Publisher: Springer Nature
ISBN: 3030853837
Category : Technology & Engineering
Languages : en
Pages : 203
Book Description
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.
Regulating Artificial Intelligence in Industry
Author: Damian M. Bielicki
Publisher: Routledge
ISBN: 1000509796
Category : Law
Languages : en
Pages : 255
Book Description
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.
Publisher: Routledge
ISBN: 1000509796
Category : Law
Languages : en
Pages : 255
Book Description
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.
New Trends in the Use of Artificial Intelligence for the Industry 4.0
Author: Luis Romeral Martinez
Publisher: BoD – Books on Demand
ISBN: 1838801413
Category : Technology & Engineering
Languages : en
Pages : 214
Book Description
Industry 4.0 is based on the cyber-physical transformation of processes, systems and methods applied in the manufacturing sector, and on its autonomous and decentralized operation. Industry 4.0 reflects that the industrial world is at the beginning of the so-called Fourth Industrial Revolution, characterized by a massive interconnection of assets and the integration of human operators with the manufacturing environment. In this regard, data analytics and, specifically, the artificial intelligence is the vehicular technology towards the next generation of smart factories.Chapters in this book cover a diversity of current and new developments in the use of artificial intelligence on the industrial sector seen from the fourth industrial revolution point of view, namely, cyber-physical applications, artificial intelligence technologies and tools, Industrial Internet of Things and data analytics. This book contains high-quality chapters containing original research results and literature review of exceptional merit. Thus, it is in the aim of the book to contribute to the literature of the topic in this regard and let the readers know current and new trends in the use of artificial intelligence for the Industry 4.0.
Publisher: BoD – Books on Demand
ISBN: 1838801413
Category : Technology & Engineering
Languages : en
Pages : 214
Book Description
Industry 4.0 is based on the cyber-physical transformation of processes, systems and methods applied in the manufacturing sector, and on its autonomous and decentralized operation. Industry 4.0 reflects that the industrial world is at the beginning of the so-called Fourth Industrial Revolution, characterized by a massive interconnection of assets and the integration of human operators with the manufacturing environment. In this regard, data analytics and, specifically, the artificial intelligence is the vehicular technology towards the next generation of smart factories.Chapters in this book cover a diversity of current and new developments in the use of artificial intelligence on the industrial sector seen from the fourth industrial revolution point of view, namely, cyber-physical applications, artificial intelligence technologies and tools, Industrial Internet of Things and data analytics. This book contains high-quality chapters containing original research results and literature review of exceptional merit. Thus, it is in the aim of the book to contribute to the literature of the topic in this regard and let the readers know current and new trends in the use of artificial intelligence for the Industry 4.0.
Deep Natural Language Processing and AI Applications for Industry 5.0
Author: Tanwar, Poonam
Publisher: IGI Global
ISBN: 1799877302
Category : Computers
Languages : en
Pages : 240
Book Description
To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.
Publisher: IGI Global
ISBN: 1799877302
Category : Computers
Languages : en
Pages : 240
Book Description
To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.
Organizational Intelligence
Author: Harold L. Wilensky
Publisher: Quid Pro Books
ISBN: 1610272889
Category : Political Science
Languages : en
Pages : 313
Book Description
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.
Publisher: Quid Pro Books
ISBN: 1610272889
Category : Political Science
Languages : en
Pages : 313
Book Description
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.
Machine Learning in Industry
Author: Shubhabrata Datta
Publisher: Springer Nature
ISBN: 3030758478
Category : Technology & Engineering
Languages : en
Pages : 202
Book Description
This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.
Publisher: Springer Nature
ISBN: 3030758478
Category : Technology & Engineering
Languages : en
Pages : 202
Book Description
This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.
Automation and Autonomy
Author: James Steinhoff
Publisher: Springer Nature
ISBN: 3030716899
Category : Political Science
Languages : en
Pages : 259
Book Description
This book argues that Marxist theory is essential for understanding the contemporary industrialization of the form of artificial intelligence (AI) called machine learning. It includes a political economic history of AI, tracking how it went from a fringe research interest for a handful of scientists in the 1950s to a centerpiece of cybernetic capital fifty years later. It also includes a political economic study of the scale, scope and dynamics of the contemporary AI industry as well as a labour process analysis of commercial machine learning software production, based on interviews with workers and management in AI companies around the world, ranging from tiny startups to giant technology firms. On the basis of this study, Steinhoff develops a Marxist analysis to argue that the popular theory of immaterial labour, which holds that information technologies increase the autonomy of workers from capital, tending towards a post-capitalist economy, does not adequately describe the situation of high-tech digital labour today. In the AI industry, digital labour remains firmly under the control of capital. Steinhoff argues that theories discerning therein an emergent autonomy of labour are in fact witnessing labour’s increasing automation.
Publisher: Springer Nature
ISBN: 3030716899
Category : Political Science
Languages : en
Pages : 259
Book Description
This book argues that Marxist theory is essential for understanding the contemporary industrialization of the form of artificial intelligence (AI) called machine learning. It includes a political economic history of AI, tracking how it went from a fringe research interest for a handful of scientists in the 1950s to a centerpiece of cybernetic capital fifty years later. It also includes a political economic study of the scale, scope and dynamics of the contemporary AI industry as well as a labour process analysis of commercial machine learning software production, based on interviews with workers and management in AI companies around the world, ranging from tiny startups to giant technology firms. On the basis of this study, Steinhoff develops a Marxist analysis to argue that the popular theory of immaterial labour, which holds that information technologies increase the autonomy of workers from capital, tending towards a post-capitalist economy, does not adequately describe the situation of high-tech digital labour today. In the AI industry, digital labour remains firmly under the control of capital. Steinhoff argues that theories discerning therein an emergent autonomy of labour are in fact witnessing labour’s increasing automation.