Green AI Engineering Designing Energy-Efficient, Low-Carbon Machine Learning Systems for a Sustainable Future

Free Download Green AI Engineering: Designing Energy-Efficient, Low-Carbon Machine Learning Systems for a Sustainable Future
English | December 11, 2025 | ASIN: B0G6GCRGXP | 123 pages | Pdf | 1.23 MB
Green AI Engineering is a groundbreaking, practical, and forward-thinking guide for engineers, developers, cloud architects, machine learning practitioners, and technology leaders who want to design AI systems that are not only powerful-but sustainable. As AI adoption accelerates globally, its energy footprint is growing faster than the models themselves. Training and deploying large models now consumes megawatts of power, generates massive emissions, and strains data centers worldwide. The next era of AI innovation is clear: efficiency, sustainability, and carbon-aware engineering will define the future of intelligent systems. This book provides a comprehensive, hands-on roadmap for building energy-efficient, low-carbon machine learning systems using modern tools, best practices, and engineering patterns. From optimizing data pipelines to reducing model size, selecting greener cloud regions, building low-power inference systems, and applying AI to real climate-tech problems, this guide equips you with the tools to build scalable, planet-friendly AI solutions. Whether you're an ML engineer improving your workflow, a climate-tech innovator building solutions for decarbonization, or a leader shaping sustainable technology strategies, Green AI Engineering offers the technical clarity and practical frameworks needed to reduce compute cost, improve performance, and minimize environmental impact-all without sacrificing accuracy. This is the playbook for the next generation of AI professionals: engineers who want to build an intelligent world the planet can afford.