The Self-Assembling Brain : How Neural Networks Grow Smarter

Peter Robin Hiesinger

ISBN 10: 0691241694 / ISBN 13: 9780691241692

Edité par Princeton Univers. Press Dez 2022, 2022

A propos de cet article

Neuware - 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.

N° de réf. du vendeur 9780691241692

Détails bibliographiques

• Titre: The Self-Assembling Brain : How Neural Networks Grow Smarter
• Éditeur: Princeton Univers. Press Dez 2022
• Date de parution: 2022
• Langue: anglais
• ISBN à 10 chiffres: 0691241694
• ISBN à 13 chiffres: 9780691241692
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 231 L x 151 H x 24 P (en millimètres) 231 millimètres de largeur par 151 millimètres de hauteur par 24 millimètres de profondeur
• Poids: 614 grammes

A propos de ce titre

Synopsis

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.

À propos de l?auteur

Peter Robin Hiesinger is professor of neurobiology at Freie Universität Berlin, where he teaches undergraduate and graduate students and leads a research laboratory and a multilab research consortium on neural networks.