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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...
Autores principales: | Murmann, Boris, Hoefflinger, Bernd |
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Lenguaje: | eng |
Publicado: |
Springer
2020
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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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