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Feynman Lectures on Computation
Anniversary Edition
Udgivet af Taylor & Francis Ltd
ISBN
9780367857332
Om denne bog
The last lecture course that Nobel Prize winner Richard P. Feynman gaveto students at Caltech from 1983 to 1986 was not on physics but on computerscience. The first edition of the Feynman Lectures on Computation, publishedin 1996, provided an overview of standard and not-so-standard topics incomputer science given in F…
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Bogdetaljer
Forlag
Taylor & Francis Ltd
Kategori
Biovidenskab: generelt
ISBN-13
9780367857332
EAN
9780367857332
Format
Hæftet
Sprog
Engelsk
sider
402
Undertitel
- Anniversary Edition
Produktbeskrivelse
The last lecture course that Nobel Prize winner Richard P. Feynman gaveto students at Caltech from 1983 to 1986 was not on physics but on computerscience. The first edition of the Feynman Lectures on Computation, publishedin 1996, provided an overview of standard and not-so-standard topics incomputer science given in Feynmans inimitable style. Although nowover 20 years old, most of the material is still relevant and interesting, andFeynmans unique philosophy of learning and discovery shines through. For this new edition, Tony Hey has updated the lectures with an invitedchapter from Professor John Preskill on Quantum Computing 40 YearsLater. This contribution captures the progress made toward building aquantum computer since Feynmans original suggestions in 1981. The last25 years have also seen the Moores law roadmap for the IT industrycoming to an end. To reflect this transition, John Shalf, Senior Scientistat Lawrence Berkeley National Laboratory, has contributed a chapteron The Future of Computing beyond Moores Law. The final updatefor this edition is an attempt to capture Feynmans interest in artificialintelligence and artificial neural networks. Eric Mjolsness, now a Professorof Computer Science at the University of California Irvine, was a TeachingAssistant for Feynmans original lecture course and his research interestsare now the application of artificial intelligence and machine learningfor multi-scale science. He has contributed a chapter called Feynmanon Artificial Intelligence and Machine Learning that captures the earlydiscussions with Feynman and also looks toward future developments. This exciting and important work provides key reading for students andscholars in the fields of computer science and computational physics.
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