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Analysis Study Research Paper | Computer Science & Engineering | India | Volume 13 Issue 8, August 2024 | Rating: 5.4 / 10
Achieving Energy Efficiency in AI: Balancing Performance in Machine Learning Models
Tara Prasad, Jeevan Kumar
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are transforming many areas of our lives, from healthcare to transportation. However, these technologies require significant computational power, leading to high energy consumption. This can be bad for the environment. This paper talks about how to make AI more sustainable by balancing how well it performs with how much energy it uses. Sustainable AI means creating and using AI systems that are not only powerful but also energy - efficient. We look at different ways to make AI models use less energy without losing their ability to work well. One method is to design algorithms that need less computer power. Another method is to use better hardware that uses less energy. We also talk about using renewable energy sources to power AI systems. Additionally, we consider the importance of reusing and recycling computer parts to reduce waste. This paper discusses the necessity of achieving sustainability in AI by balancing the performance and energy consumption of machine learning models. It explores various strategies, including optimizing algorithms, using specialized hardware, and integrating renewable energy sources, to reduce the environmental impact of AI systems without compromising their effectiveness. The study emphasizes the importance of developing energy efficient AI technologies to ensure that the benefits of advanced AI systems do not come at the expense of environmental sustainability.
Keywords: Sustainable AI, Energy Efficiency, Machine Learning, Environmental Impact, Renewable Energy
Edition: Volume 13 Issue 8, August 2024
Pages: 1066 - 1072