Optimization Strategies for Reducing Energy Consumption in AI Model Training

Abstract

The rapid advancement of artificial intelligence (AI) technologies has ushered in significant benefits across various domains, yet it has also led to increased energy consumption. This paper explores the imperative need for energy-efficient AI systems, examining current strategies, challenges, and future directions. We delve into the technologies and methodologies designed to minimize the energy footprint of AI systems, focusing on algorithmic improvements, hardware optimizations, and system-level innovations. Our review highlights recent advancements and offers insights into the future trajectory of energy-efficient AI research.