9783030183370-3030183378-NANO-CHIPS 2030: On-Chip AI for an Efficient Data-Driven World (The Frontiers Collection)

NANO-CHIPS 2030: On-Chip AI for an Efficient Data-Driven World (The Frontiers Collection)

ISBN-13: 9783030183370
ISBN-10: 3030183378
Edition: 1st ed. 2020
Author: Boris Murmann, Bernd Hoefflinger
Publication date: 2020
Publisher: Springer
Format: Hardcover 615 pages
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Book details

ISBN-13: 9783030183370
ISBN-10: 3030183378
Edition: 1st ed. 2020
Author: Boris Murmann, Bernd Hoefflinger
Publication date: 2020
Publisher: Springer
Format: Hardcover 615 pages

Summary

NANO-CHIPS 2030: On-Chip AI for an Efficient Data-Driven World (The Frontiers Collection) (ISBN-13: 9783030183370 and ISBN-10: 3030183378), written by authors Boris Murmann, Bernd Hoefflinger, was published by Springer in 2020. With an overall rating of 3.6 stars, it's a notable title among other Economic Policy & Development (Economics, Microprocessors & System Design, Hardware & DIY, Materials & Material Science, Engineering, Nanostructures, Physics, Nanotechnology, Technology) books. You can easily purchase or rent NANO-CHIPS 2030: On-Chip AI for an Efficient Data-Driven World (The Frontiers Collection) (Hardcover) from BooksRun, along with many other new and used Economic Policy & Development books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

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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