The Self-Assembling Brain : How Neural Networks Grow Smarter /
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....
Clasificación: | Libro Electrónico |
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Autor principal: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Princeton, NJ :
Princeton University Press,
[2021]
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Temas: | |
Acceso en línea: | Texto completo Texto completo |
MARC
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100 | 1 | |a Hiesinger, Peter Robin, |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
245 | 1 | 4 | |a The Self-Assembling Brain : |b How Neural Networks Grow Smarter / |c Peter Robin Hiesinger. |
264 | 1 | |a Princeton, NJ : |b Princeton University Press, |c [2021] | |
264 | 4 | |c ©2021 | |
300 | |a 1 online resource (384 p.) : |b 49 b/w illus. | ||
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505 | 0 | 0 | |t Frontmatter -- |t Contents -- |t Acknowledgments -- |t Prologue -- |t The self-assembling brain -- |t Introduction -- |t The Present and the Past -- |t 1 Algorithmic growth -- |t 2 Of players and rules -- |t 3 Brain development and artificial intelligence -- |t Epilogue -- |t Glossary -- |t References -- |t Index |
506 | 0 | |a restricted access |u http://purl.org/coar/access_right/c_16ec |f online access with authorization |2 star | |
520 | |a 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. | ||
538 | |a Mode of access: Internet via World Wide Web. | ||
546 | |a In English. | ||
588 | 0 | |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 01. Dez 2022) | |
650 | 0 | |a Artificial intelligence. | |
650 | 0 | |a Learning |x Psysiological aspects. | |
650 | 0 | |a Neural circuitry |x Adaptation. | |
650 | 0 | |a Neural networks (Computer science) | |
650 | 0 | |a Neural networks (Computer science). | |
650 | 7 | |a SCIENCE / Life Sciences / Neuroscience. |2 bisacsh | |
653 | |a Gary Macus. | ||
653 | |a How to Create a Mind. | ||
653 | |a Peter Sterling. | ||
653 | |a Principles of Neural Design. | ||
653 | |a Ray Kurzweil. | ||
653 | |a Roger Sperry. | ||
653 | |a Seymour Benzer. | ||
653 | |a Simon Laughlin. | ||
653 | |a Sydney Brenner. | ||
653 | |a The Birth of the Mind. | ||
653 | |a algorithm. | ||
653 | |a algorithmic growth. | ||
653 | |a artificial life. | ||
653 | |a artificial neural network. | ||
653 | |a axon guidance. | ||
653 | |a behavior. | ||
653 | |a brain development. | ||
653 | |a brain wiring. | ||
653 | |a cellular automaton. | ||
653 | |a cognitive bias. | ||
653 | |a complexity. | ||
653 | |a computer intelligence. | ||
653 | |a connectome. | ||
653 | |a cybernetics. | ||
653 | |a deep learning. | ||
653 | |a evolution. | ||
653 | |a filopodia. | ||
653 | |a gene. | ||
653 | |a guidance cue. | ||
653 | |a information theory. | ||
653 | |a machine learning. | ||
653 | |a memory. | ||
653 | |a neural circuit. | ||
653 | |a neurogenetics. | ||
653 | |a self-organization. | ||
653 | |a synapse. | ||
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