Generative AI and sustainability

In recent years, interest in artificial intelligence (AI) has significantly increased. The availability of vast amounts of data, advancements in computing power, and the development of new methods and algorithms have enabled the training of more accurate and reliable models that can be effectively applied in real-world contexts. This growing interest has surged further with the emergence of new generative AI (GenAI) methods, which can synthesize text, images, video, audio, or code based on user input. The popularity of GenAI, along with the introduction of increasingly sophisticated versions that require more resources to create and run, has sparked debate about its long-term scalability. In this article, we will examine GenAI from a sustainability perspective, assessing its current impact and future projections, while identifying the most promising trends and technologies to enhance the long-term sustainability of GenAI.