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Sustainable AI - Raghavendra Selvan

Sustainable AI

tools for moving towards green AI
Buch | Softcover
250 Seiten
2025 | 1. Auflage
O'Reilly Media (Verlag)
978-1-0981-5551-3 (ISBN)
CHF 109,95 inkl. MwSt
Author Raghavendra Selvan exposes the high costs—both environmental and economic—traditional DL methods and presents practical solutions that pave the way for a more sustainable AI.
In the era of big data and even bigger machine learning models, the environmental footprint of these technologies can no longer be ignored. This much-needed guide confronts the challenge head-on, offering a groundbreaking exploration into making deep learning (DL) both efficient and accessible. Author Raghavendra Selvan exposes the high costs—both environmental and economic—of traditional DL methods and presents practical solutions that pave the way for a more sustainable AI.This essential read is for anyone in the machine learning field, from the academic researcher to the industry practitioner, who wants to make a meaningful impact on both their work and the world. This book enables readers to be agents of change toward a more sustainable and inclusive technological future. In this book, you will:



Learn strategies to significantly reduce the energy consumption, carbon footprint, and hardware demands of DL models
Examine ways to break down barriers and foster a more inclusive future in AI development
Explore strategies for cutting costs and minimizing ecological impact
Learn how to balance performance with efficiency in model development
Gain proficiency in cutting-edge tools that enhance the sustainability of your AI projects

Raghavendra Selvan (Raghav) is currently an Assistant Professor at the University of Copenhagen, with joint responsibilities at the Machine Learning Section (Dept. of Computer Science), Kiehn Lab (Department of Neuroscience) and the Data Science Laboratory. He received his PhD in Medical Image Analysis (University of Copenhagen, 2018). Raghavendra Selvan was born in Bangalore, India. His current research interests broadly pertain to Resource Efficient ML, Medical Image Analysis with ML, Quantum Tensor Networks and Graph Neural Networks. An overarching theme of his current research interests lies at the intersection of sustainability and ML where he is interested in investigating sustainability with ML, and also the sustainability of ML.

Erscheinungsdatum
Verlagsort Sebastopol
Sprache englisch
Maße 178 x 232 mm
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 1-0981-5551-3 / 1098155513
ISBN-13 978-1-0981-5551-3 / 9781098155513
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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