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In recent years, ideas of post- and transhumanism have been popularized by novels, TV series, and Hollywood movies. According to this radical perspective, humankind and all biological life have become obsolete. Traditional forms of life are inefficient at processing information information and inept at crossing the high frontier: outer space. While humankind can expect to be replaced by their own artificial progeny, post-humanists assume that they will become an immortal part of a transcendent superintelligence. Krüger's award-winning study examines the historical and philosophical context of these futuristic promises by Ray Kurzweil, Nick Bostrom, Frank Tipler, and other posthumanist thinkers.
Posthumanism. --- Artificial Intelligence. --- Frank Tipler. --- Futurology. --- Immortality. --- Nick Bostrom. --- Ray Kurzweil. --- Religion. --- Religious Studies. --- Science. --- Singularity. --- Sociology of Culture. --- Sociology of Religion. --- Sociology of Science. --- Sociology. --- Transhumanism.
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What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network?As Peter Robin Hiesinger argues, “the information problem” underlies both fields, motivating the questions driving forward the frontiers of research. How does genetic information unfold during the years-long process of human brain development—and is there a quicker path to creating human-level artificial intelligence? Is the biological brain just messy hardware, which scientists can improve upon by running learning algorithms on computers? Can AI bypass the evolutionary programming of “grown” networks? Through a series of fictional discussions between researchers across disciplines, complemented by in-depth seminars, Hiesinger explores these tightly linked questions, highlighting the challenges facing scientists, their different disciplinary perspectives and approaches, as well as the common ground shared by those interested in the development of biological brains and AI systems. In the end, Hiesinger contends that the information content of biological and artificial neural networks must unfold in an algorithmic process requiring time and energy. There is no genome and no blueprint that depicts the final product. The self-assembling brain knows no shortcuts.Written for readers interested in advances in neuroscience and artificial intelligence, The Self-Assembling Brain looks at how neural networks grow smarter.
Neural networks (Computer science) --- Learning --- Physiological aspects. --- Gary Macus. --- How to Create a Mind. --- Peter Sterling. --- Principles of Neural Design. --- Ray Kurzweil. --- Roger Sperry. --- Seymour Benzer. --- Simon Laughlin. --- Sydney Brenner. --- The Birth of the Mind. --- algorithm. --- algorithmic growth. --- artificial life. --- artificial neural network. --- axon guidance. --- behavior. --- brain development. --- brain wiring. --- cellular automaton. --- cognitive bias. --- complexity. --- computer intelligence. --- connectome. --- cybernetics. --- deep learning. --- evolution. --- filopodia. --- gene. --- guidance cue. --- information theory. --- machine learning. --- memory. --- neural circuit. --- neurogenetics. --- self-organization. --- synapse.
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