Green Algorithms For A Sustainable Future Reducing The Carbon Footprint Of AI And Big Data

Abstract

The compounding growth of Artificial Intelligence (AI) and Big Data analytics has caused an unequaled hunger of computing assets to emerge that has is causing a huge elevation in the utilization of energy and carbon emissions across the globe. Though all of these technologies have brought about revolutionary solutions to the various sectors, their impact on the environment is increasingly becoming a thing of concern. The paper addresses the concepts and application of green algorithms which are energy efficient computational algorithm and are less harmful on the environment. Through the lifecycle of AI models and big data processing pipelines, we can single out the sources of energy wastage that are critical, and the ways of enhancing sustainability. In comparison we will show through comparative analysis how the model architecture optimization, data center management and training practices can be made to reduce carbon emission in a significant way without affecting the performance. The findings support the necessity to consider the principle of sustainability as an essential feature of designing such AI and data-intensive systems in the future.