Sustainable Artificial Intelligence: Balancing Performance, Energy Consumption, and Applications

Abstract

The last few years have seen AI advance at a frankly dizzying pace. We've gotten better medical diagnostics, smarter climate models, real-time language translation — the works. But here's the uncomfortable part nobody likes to talk about: the systems behind these breakthroughs are enormous, and enormous systems eat enormous amounts of electricity. That electricity, more often than not, still comes from fossil fuels. This paper looks at what people in the field are calling "green AI" — the idea that we can keep pushing the technology forward without quietly burning the planet in the process. We'll go over where all that energy actually goes during machine learning, and what developers can realistically do about it.