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Digital technologies have changed how we shop, work, play, and communicate, reshaping our societies and economies. To understand digital capitalism, we need to grasp how advances in geospatial technologies underpin the construction, operation, and refinement of markets for digital goods and services. In The Map in the Machine, Luis F. Alvarez Leon examines these advances, from MapQuest and Google Maps to the rise of IP geolocation, ridesharing, and a new Earth Observation satellite ecosystem. He develops a geographical theory of digital capitalism centered on the processes of location, valuation, and marketization to provide a new vantage point from which to better understand, and intervene in, the dominant techno-economic paradigm of our time. By centering the spatiality of digital capitalism, Alvarez Leon shows how this system is the product not of seemingly intangible information clouds but rather of a vast array of technologies, practices, and infrastructures deeply rooted in place, mediated by geography, and open to contestation and change.
Consciousness is widely perceived as one of the most fundamental, interesting and difficult problems of our time. However, we still know next to nothing about the relationship between consciousness and the brain and we can only speculate about the consciousness of animals and machines. Human and Machine Consciousness presents a new foundation for the scientific study of consciousness. It sets out a bold interpretation of consciousness that neutralizes the philosophical problems and explains how we can make scientific predictions about the consciousness of animals, brain-damaged patients and machines. Gamez interprets the scientific study of consciousness as a search for mathematical theories that map between measurements of consciousness and measurements of the physical world. We can use artificial intelligence to discover these theories and they could make accurate predictions about the consciousness of humans, animals and artificial systems. Human and Machine Consciousness also provides original insights into unusual conscious experiences, such as hallucinations, religious experiences and out-of-body states, and demonstrates how ‘designer’ states of consciousness could be created in the future. Gamez explains difficult concepts in a clear way that closely engages with scientific research. His punchy, concise prose is packed with vivid examples, making it suitable for the educated general reader as well as philosophers and scientists. Problems are brought to life in colourful illustrations and a helpful summary is given at the end of each chapter. The endnotes provide detailed discussions of individual points and full references to the scientific and philosophical literature.
When a blizzard blows in while the Mystery Gang is skiing, Scooby and Shaggy hide out in a mysterious lodge. Illustrations.
MACHINE OF DEATH tells thirty-four different stories about people who know how they will die. Prepare to have your tears jerked, your spine tingled, your funny bone tickled, your mind blown, your pulse quickened, or your heart warmed. Or better yet, simply prepare to be surprised. Because even when people do have perfect knowledge of the future, there's no telling exactly how things will turn out.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.