In the era of big data and even bigger machine learning models powering the current generative AI revolution, the environmental footprint of these developments 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.
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
