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Nano-chips 2030: on-chip AI for an efficient data-driven world

In this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent...

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Detalles Bibliográficos
Autores principales: Murmann, Boris, Hoefflinger, Bernd
Lenguaje:eng
Publicado: Springer 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-030-18338-7
http://cds.cern.ch/record/2720392
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author Murmann, Boris
Hoefflinger, Bernd
author_facet Murmann, Boris
Hoefflinger, Bernd
author_sort Murmann, Boris
collection CERN
description In this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent reviews of the status quo, as presented in CHIPS 2020 (Springer), have prompted the need for an urgent reassessment of opportunities in nanoelectronic information technology. As such, this book explores the foundations of a new era in nanoelectronics that will drive progress in intelligent chip systems for energy-efficient information technology, on-chip deep learning for data analytics, and quantum computing. Given its scope, this book provides a timely compendium that hopes to inspire and shape the future of nanoelectronics in the decades to come. .
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institution Organización Europea para la Investigación Nuclear
language eng
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spelling cern-27203922021-04-21T18:07:49Zdoi:10.1007/978-3-030-18338-7http://cds.cern.ch/record/2720392engMurmann, BorisHoefflinger, BerndNano-chips 2030: on-chip AI for an efficient data-driven worldComputing and ComputersIn this book, a global team of experts from academia, research institutes and industry presents their vision on how new nano-chip architectures will enable the performance and energy efficiency needed for AI-driven advancements in autonomous mobility, healthcare, and man-machine cooperation. Recent reviews of the status quo, as presented in CHIPS 2020 (Springer), have prompted the need for an urgent reassessment of opportunities in nanoelectronic information technology. As such, this book explores the foundations of a new era in nanoelectronics that will drive progress in intelligent chip systems for energy-efficient information technology, on-chip deep learning for data analytics, and quantum computing. Given its scope, this book provides a timely compendium that hopes to inspire and shape the future of nanoelectronics in the decades to come. .Springeroai:cds.cern.ch:27203922020
spellingShingle Computing and Computers
Murmann, Boris
Hoefflinger, Bernd
Nano-chips 2030: on-chip AI for an efficient data-driven world
title Nano-chips 2030: on-chip AI for an efficient data-driven world
title_full Nano-chips 2030: on-chip AI for an efficient data-driven world
title_fullStr Nano-chips 2030: on-chip AI for an efficient data-driven world
title_full_unstemmed Nano-chips 2030: on-chip AI for an efficient data-driven world
title_short Nano-chips 2030: on-chip AI for an efficient data-driven world
title_sort nano-chips 2030: on-chip ai for an efficient data-driven world
topic Computing and Computers
url https://dx.doi.org/10.1007/978-3-030-18338-7
http://cds.cern.ch/record/2720392
work_keys_str_mv AT murmannboris nanochips2030onchipaiforanefficientdatadrivenworld
AT hoefflingerbernd nanochips2030onchipaiforanefficientdatadrivenworld