Modern electroplating

By:

Schlesinger, Mordechay (Ed.)

Contributor(s):

Paunovic, Milan [Editor]

Publication details: Hoboken, New Jersey: John Wiley & Sons, 2010.Edition: 5th edDescription: xv, 729p.: ill.; hbk.: 27cmISBN:

9780470167786

Subject(s):

DDC classification:

671.732 SCH

Summary: 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. https://www.wiley.com/en-gb/Modern+Electroplating,+5th+Edition-p-9780470167786

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Books	IIT Gandhinagar	General	671.732 SCH (Browse shelf(Opens below))	1	Available		033450

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Previous	671.52 CAR Modern welding technology, 6th ed.	671.52 GHO Foundation of welding technology	671.52 KOU Welding metallurgy	671.732 SCH Modern electroplating	671.735 MAT Handbook of physical vapor deposition (PVD) processing	672 PAL Process modeling for steel industry	676 JAI Guide to making issues: a handy reference on the subject of paper making	Next

Includes Appendix and Index

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.

https://www.wiley.com/en-gb/Modern+Electroplating,+5th+Edition-p-9780470167786

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