Solving AI's growing carbon emissions

AI has become an integral part of our lives, but its growth in recent years has come at a cost. As AI systems become increasingly complex, their training and usage can generate large amounts of carbon emissions, contributing to global warming and climate change. The relationship between model accuracy and complexity is logarithmic. This means that an exponential increase in model size and training requirements can result in linear improvements to performance. Despite this, less priority is given to developing methods with improved efficiency. We need to be aware of the trade-off between accuracy and efficiency and the model's carbon footprint, both during training and when making inferences.