This paper explores the environmental impact of the super-linear growth trends for AI from a
holistic perspective, spanning Data, Algorithms, and System Hardware. We characterize the …

There is great interest in how the growth of artificial intelligence and machine learning may
affect global GHG emissions. However, such emissions impacts remain uncertain, owing in …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

The advent of cloud computing has provided people around the world with unprecedented
access to computational power and enabled rapid growth in technologies such as machine …

Recent years have seen a surge in the popularity of commercial AI products based on
generative, multi-purpose AI systems promising a unified approach to building machine …

The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated
models like OpenAI's ChatGPT, represents a significant advancement in artificial …

Machine learning (ML) requires using energy to carry out computations during the model
training process. The generation of this energy comes with an environmental cost in terms of …

The global energy demand for digital activities is constantly growing. Computing nodes and
cloud services are at the heart of these activities. Understanding their energy consumption is …

Reporting electricity consumption is essential for sustainable AI | Nature Machine Intelligence
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Automated machine learning (AutoML) strives for the automatic configuration of machine
learning algorithms and their composition into an overall (software) solution—a machine …