The carbon footprints of IT shops that train AI models are huge

Artificial intelligence (AI) model training can generate five times more carbon dioxide than a car does in a lifetime, researchers at the University of Massachusetts, Amherst find.

Artificial intelligence model training can generate five times more carbon dioxide than a car
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A new research paper from the University of Massachusetts, Amherst, looked at the carbon dioxide (CO2) generated over the course of training several common large artificial intelligence (AI) models and found that the process can generate nearly five times the amount as an average American car over its lifetime plus the process of making the car itself.

The paper specifically examined the model training process for natural-language processing (NLP), which is how AI handles natural language interactions. The study found that during the training process, more than 626,000 pounds of carbon dioxide is generated.

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This is significant, since AI training is one IT process that has remained firmly on-premises and not moved to the cloud. Very expensive equipment is needed, as are large volumes of data, so the cloud isn’t right for most AI training, and the report notes this. Plus, IT shops want to keep that kind of IP in-house. So, if you are experimenting with AI, that power bill is going to go up.

While the report used carbon dioxide as a measure, that’s still the product of electricity generation. Training involves the use of the most powerful processors, typically Nvidia GPUs, and they are not known for being low-power draws. And as the paper notes, “Model training also incurs a substantial cost to the environment due to the energy required to power this hardware for weeks or months at a time.”

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