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Author: Alf Hornborg Publisher: Rowman Altamira ISBN: 0759116911 Category : Social Science Languages : en Pages : 288
Book Description
Hornborg argues that we are caught in a collective illusion about the nature of modern technology that prevents us from imagining solutions to our economic and environmental crises other than technocratic fixes. He demonstrates how the power of the machine generates increasingly asymmetrical exchanges and distribution of resources and risks between distant populations and ecosystems, and thus an increasingly polarized world order. The author challenges us to reconceptualize the machine—'industrial technomass'—as a species of power and a problem of culture. He shows how economic anthropology has the tools to deconstruct the concepts of production, money capital, and market exchange, and to analyze capital accumulation as a problem at the very interface of the natural and social sciences. His analysis provides an alternative understanding of economic growth and technological development. Hornborg's work is essential for researchers in anthropology, human ecology, economics, political economy, world-systems theory, environmental justice, and science and technology studies. Find out more about the author at the Lund University, Sweden web site.
Author: Alf Hornborg Publisher: Rowman Altamira ISBN: 9780759100671 Category : Business & Economics Languages : en Pages : 296
Book Description
Hornborg argues that we are caught in a collective illusion about the nature of modern technology that prevents us from imagining solutions to our economic and environmental crises other than technocratic fixes. He demonstrates how the power of the machine generates increasingly asymmetrical exchanges and distribution of resources and risks between distant populations and ecosystems, and thus an increasingly polarized world order. The author challenges us to reconceptualize the machine--"industrial technomass"--as a species of power and a problem of culture. He shows how economic anthropology has the tools to deconstruct the concepts of production, money capital, and market exchange, and to analyze capital accumulation as a problem at the very interface of the natural and social sciences. His analysis provides an alternative understanding of economic growth and technological development. Hornborg's work is essential for researchers in anthropology, human ecology, economics, political economy, world-systems theory, environmental justice, and science and technology studies. Find out more about the author at the Lund University, Sweden web site.
Author: Alf Hornborg Publisher: Rowman Altamira ISBN: 0759116911 Category : Social Science Languages : en Pages : 288
Book Description
Hornborg argues that we are caught in a collective illusion about the nature of modern technology that prevents us from imagining solutions to our economic and environmental crises other than technocratic fixes. He demonstrates how the power of the machine generates increasingly asymmetrical exchanges and distribution of resources and risks between distant populations and ecosystems, and thus an increasingly polarized world order. The author challenges us to reconceptualize the machine—'industrial technomass'—as a species of power and a problem of culture. He shows how economic anthropology has the tools to deconstruct the concepts of production, money capital, and market exchange, and to analyze capital accumulation as a problem at the very interface of the natural and social sciences. His analysis provides an alternative understanding of economic growth and technological development. Hornborg's work is essential for researchers in anthropology, human ecology, economics, political economy, world-systems theory, environmental justice, and science and technology studies. Find out more about the author at the Lund University, Sweden web site.
Author: Brian Merchant Publisher: Hachette UK ISBN: 0316487732 Category : Technology & Engineering Languages : en Pages : 545
Book Description
"The most important book to read about the AI boom" (Wired): The "gripping" (New Yorker) true story of the first time machines came for human jobs—and how the Luddite uprising explains the power, threat, and toll of big tech and AI today Named one of the best books of the year by The New Yorker, Wired, and the Financial Times • A Next Big Idea Book Club "Must-Read" The most urgent story in modern tech begins not in Silicon Valley but two hundred years ago in rural England, when workers known as the Luddites rose up rather than starve at the hands of factory owners who were using automated machines to erase their livelihoods. The Luddites organized guerrilla raids to smash those machines—on punishment of death—and won the support of Lord Byron, enraged the Prince Regent, and inspired the birth of science fiction. This all-but-forgotten class struggle brought nineteenth-century England to its knees. Today, technology imperils millions of jobs, robots are crowding factory floors, and artificial intelligence will soon pervade every aspect of our economy. How will this change the way we live? And what can we do about it? The answers lie in Blood in the Machine. Brian Merchant intertwines a lucid examination of our current age with the story of the Luddites, showing how automation changed our world—and is shaping our future.
Author: Paul R. Daugherty Publisher: Harvard Business Press ISBN: 1633693872 Category : Computers Languages : en Pages : 264
Book Description
AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.
Author: Patrick Bangert Publisher: Elsevier ISBN: 0128226005 Category : Technology & Engineering Languages : en Pages : 276
Book Description
Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. - Provides best practices on how to design and set up ML projects in power systems, including all nontechnological aspects necessary to be successful - Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how the data must be prepared for them - Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems - Accompanied by numerous supporting real-world case studies, providing practical evidence of both best practices and potential pitfalls
Author: Dean Buonomano Publisher: W. W. Norton & Company ISBN: 0393247953 Category : Science Languages : en Pages : 357
Book Description
"Beautifully written, eloquently reasoned…Mr. Buonomano takes us off and running on an edifying scientific journey." —Carol Tavris, Wall Street Journal In Your Brain Is a Time Machine, leading neuroscientist Dean Buonomano embarks on an "immensely engaging" exploration of how time works inside the brain (Barbara Kiser, Nature). The human brain, he argues, is a complex system that not only tells time, but creates it; it constructs our sense of chronological movement and enables "mental time travel"—simulations of future and past events. These functions are essential not only to our daily lives but to the evolution of the human race: without the ability to anticipate the future, mankind would never have crafted tools or invented agriculture. This virtuosic work of popular science will lead you to a revelation as strange as it is true: your brain is, at its core, a time machine.
Author: Hubert Dreyfus Publisher: Simon and Schuster ISBN: 0743205510 Category : Philosophy Languages : en Pages : 256
Book Description
Human intuition and perception are basic and essential phenomena of consciousness. As such, they will never be replicated by computers. This is the challenging notion of Hubert Dreyfus, Ph. D., archcritic of the artificial intelligence establishment. It's important to emphasize that he doesn't believe that AI is fundamentally impossible, only that the current research program is fatally flawed. Instead, he argues that to get a device (or devices) with human-like intelligence would require them to have a human-like being in the world, which would require them to have bodies more or less like ours, and social acculturation (i.e. a society) more or less like ours. This helps to explain the practical problems in implementing artificial intelligence algorithms.
Author: Brittany Ackerman Publisher: ISBN: 9781597096911 Category : BIOGRAPHY & AUTOBIOGRAPHY Languages : en Pages : 152
Book Description
Inspired by a brother's high school science project--a perpetual motion machine that could save the world-- The Perpetual Motion Machine is a memoir in essays that attempts to save a sibling by depicting the visceral pain that accompanies longing for some past impossibility. The collection has been a science project in its study of memory, in the calculation and plotting of the moments that make up a childhood. The preparation has been "in the field" in that it is built upon the gathering of lived experience; the evidence is photo albums, family interviews, and anecdotes from friends. The project has been one giant experiment--to see if they can all make it out alive.
Author: Mr. Om Prakash Singh Publisher: Xoffencerpublication ISBN: 8119534158 Category : Computers Languages : en Pages : 212
Book Description
Intelligent machines, also known as artificial intelligence (AI) systems, are a fascinating area of study and development that integrates computer science, mathematics, and cognitive science to create machines that can simulate human-like intellect and conduct. This field of study and development aims to produce machines that can create intelligent machines that can simulate human-like intelligence and behavior. These computers are programmed to perceive, learn, reason, and make judgments in a manner that is either comparable to or superior to the cognitive powers of humans. Machine learning is a subsection of artificial intelligence that focuses on the development of algorithms and models that enable computers to learn from and make predictions or judgments based on data. Intelligent machines are constructed on top of this foundation, which is the basis of machine learning. Intelligent machines are able to analyze huge amounts of data, recognize patterns in that data, and make decisions based on that analysis through the use of machine learning techniques such as neural networks, decision trees, and reinforcement learning. The capacity to learn new things and advance themselves over time is one of the most distinguishing features of intelligent machines. They are able to gain knowledge from their experiences and modify either their behavior or their models in order to get better results. This skill is frequently referred regarded as "artificial intelligence" since these machines can demonstrate features that we generally associate with human intellect, such as problem-solving, the ability to grasp plain language, and visual perception. The applications for intelligent machines are quite diverse and can be found in a variety of domains. They are used in a variety of industries, including the healthcare sector, the financial sector, the transportation sector, and the manufacturing sector, to automate processes, improve decision-making, and increase efficiency. In the field of medicine, for instance, intelligent robots can be of assistance in the process of disease diagnosis, the analysis of medical imaging, and the development of individualized treatment regimens.
Author: Alf Hornborg
Author: Alf Hornborg
Author: Alf Hornborg
Author: Brian Merchant
Author: Paul R. Daugherty
Author: Patrick Bangert
Author: Dean Buonomano
Author: Hubert Dreyfus
Author: Brittany Ackerman
Author: Mr. Om Prakash Singh
Author: Lee Fang