Leseprobe
* Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
The Self-Assembling Brain
Peter Robin Hiesinger
* Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
Naturwissenschaften, Medizin, Informatik, Technik / Naturwissenschaften allgemein
Beschreibung
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.
Kundenbewertungen
Equipotentiality, Neuron, Scientist, Biological neural network, Action potential, Algorithm, Brain, Retina, Self-assembly, Organism, Iteration, Behavior, Algorithmic information theory, Gene product, Deep learning, Gene, Synaptic weight, Wiring (development platform), Self-organization, Phenotype, Biology, Developmental biology, Neocortex, Artificial life, Biologist, Machine learning, Netrin, Addition, Filopodia, Genetic code, Probability, Molecule, Mutation, Robotics, Wiring diagram, Enzyme, Metabolism, Cell surface receptor, Prediction, Artificial general intelligence, Perceptron, Artificial neural network, Information theory, Cell type, Artificial neuron, Axon, Rule 110, Cybernetics, Neurotransmission, Penetrance, Analogy, Nucleic acid sequence, Autonomous agent, Cellular automaton, Backpropagation, Protein, Result, Thought, Neuromodulation, Chemical synapse, Bit, Simulation, Axon guidance, Evolutionary programming, Synapsis, Geneticist, Transcription factor, Computation, Interaction, Growth cone