Cloud and Edge Computing for Generative AI
Bibliographic Data
| ID | 23587221 |
|---|---|
| Authors | Ishneet Kaur Dua (0009-0002-2928-8282), Parth Patel (0000-0001-8105-0031), Parth Girish Patel (0009-0003-7800-9486) |
| Year | 2024 |
| Pages | 203-231 |
| Publication date | 2024-01-01 |
| Open Access | Yes |
| Type | CHAPTER |
| Venue | Optimizing Generative AI Workloads for Sustainability (SOURCE_BOOK) |
| Publisher | Apress (PUBLISHER • US) |
| DOI | 10.1007/979-8-8688-0917-0_7 |
| OpenAlex | W4404481205 |
| ISBN | 9798868809170 |
| Language | EN |
Cloud computing and edge computing both offer significant potential for enhancing the environmental sustainability of generative AI systems. By consolidating computational resources in centralized, energy-efficient data centers, cloud computing allows using renewable energy sources, advanced cooling technologies, and energy-efficient hardware, thereby minimizing environmental impact. However, the substantial energy requirements of training large language models and other generative AI systems in the cloud highlight the need for more sustainable practices.
Cloud computing · Edge computing · Enhanced Data Rates for GSM Evolution · Generative grammar · Operating system · Artificial Intelligence · Cognitive Computing and Networks · Computer Science · Neural Networks and Applications · Robotics and Automated Systems
| Highly cited | No |
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