How far apart are humans from animals--even the "vampire squid from hell"? Playing the scientist/philosopher/provocateur, Vilem Flusser uses this question as a springboard to dive into a literal and a philosophical ocean. "The abyss that separates us" from the vampire squid (or vampire octopus, perhaps, since Vampyroteuthis infernalis inhabits its own phylogenetic order somewhere between the two) "is incomparably smaller than that which separates us from extraterrestrial life, as imagined in science fiction and sought by astrobiologists," Flusser notes at the outset of the expedition.
Part scientific treatise, part spoof, part philosophical discourse, part fable, Vampyroteuthis Infernalis gives its author ample room to ruminate on human--and nonhuman--life. Considering the human condition along with the vampire squid/octopus condition seems appropriate because "we are both products of an absurd coincidence . . . we are poorly programmed beings full of defects," Flusser writes. Among other things, "we are both banished from much of life's domain: it into the abyss, we onto the surfaces of the continents. We have both lost our original home, the beach, and we both live in constrained conditions."
Thinking afresh about the life of an "other"--as different from ourselves as the vampire squid/octopus--complicates the linkages between animality and embodiment. Odd, and strangely compelling, Vampyroteuthis Infernalis offers up a unique posthumanist philosophical understanding of phenomenology and opens the way for a non-philosophy of life.
Автор: Commandeur, Jacques J.F.; Koopman, Siem Jan Название: An Introduction to State Space Time Series Analysis ISBN: 0199228876 ISBN-13(EAN): 9780199228874 Издательство: Oxford Academ Рейтинг: Цена: 7681.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text provides an introduction to time series analysis using state space methodology to readers who are neither familiar with time series analysis, nor with state space methods. This is the first in a series of books designed to provide practitioners, researchers, and students with practical introductions to various topics in econometrics.
Автор: Dainton Barry Название: Time and Space ISBN: 1844651916 ISBN-13(EAN): 9781844651917 Издательство: Taylor&Francis Рейтинг: Цена: 6123.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This fully revised edition of this standard work on the philosophy of time and space includes two new chapters on Zeno`s paradoxes, new material on dynamic time, speculative contemporary developments in physics, and time and consciousness, making the second edition, once again, unrivalled in its breadth of coverage.
Автор: Walker Название: From Matter to Life ISBN: 1107150531 ISBN-13(EAN): 9781107150539 Издательство: Cambridge Academ Рейтинг: Цена: 5069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent advances suggest that the concept of information might hold the key to unravelling the mystery of life`s origins. This book provides fresh insights from experts in philosophy, biology, chemistry, physics, and cognitive and social sciences to provide a unique cross-disciplinary perspective on the problem. It will be of interest to students and researchers in these fields.
Автор: Marius Leordeanu Название: Unsupervised Learning in Space and Time ISBN: 3030421279 ISBN-13(EAN): 9783030421274 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field. Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video.
The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts. Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way.
Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines.
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