AI Carbon Footprint
and what we can do for sustainable AI
What’s the problem
Everybody loved ChatGPT, but not so many people are aware of the tremendous damage from the point of view of the environment. Indeed, to train the model extensive use of computer was required which means electricity, which means CO2 to generate this electricity (502 Tons C02). We are talking of about the same footprint of 600 flights between New York and San Francisco, according to the AI Index report from Stanford University.
And this is only taking into account ChatGPT, other models or AWS services are not better. AI is largely dependent on the infrastructure that supports it, including data centers, cloud networks, and edge devices, all of which use up a lot of energy and resources. Given the exponential growth of data and the requirement for ever-more-powerful computer resources with the creation of ever-larger neural networks or large language models (LLM), the energy consumption of AI is a serious concern. AI’s energy needs are substantial in terms of carbon emissions as well as the resources needed to create and maintain the essential infrastructure.
Numerous studies have examined the carbon footprint of AI, emphasizing the severe negative environmental effects of this technology. “Energy and Policy Considerations for Deep Learning…
