Their work, which is yet to be peer reviewed, shows that while training massive AI models is incredibly energy intensive, it’s only one part of the puzzle.
For each of the tasks, such as text generation, Luccioni ran 1,000 prompts, and measured the energy used with a tool she developed called Code Carbon.
Generating 1,000 images with a powerful AI model, such as Stable Diffusion XL, is responsible for roughly as much carbon dioxide as driving the equivalent of 4.1 miles in an average gasoline-powered car.
AI startup Hugging Face has undertaken the tech sector’s first attempt to estimate the broader carbon footprint of a large language model.
The generative-AI boom has led big tech companies to integrate powerful AI models into many different products, from email to word processing.
Luccioni tested different versions of Hugging Face’s multilingual AI model BLOOM to see how many uses would be needed to overtake training costs.
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Their work, which is yet to be peer reviewed, shows that while training massive AI models is incredibly energy intensive, it’s only one part of the puzzle.
For each of the tasks, such as text generation, Luccioni ran 1,000 prompts, and measured the energy used with a tool she developed called Code Carbon.
Generating 1,000 images with a powerful AI model, such as Stable Diffusion XL, is responsible for roughly as much carbon dioxide as driving the equivalent of 4.1 miles in an average gasoline-powered car.
AI startup Hugging Face has undertaken the tech sector’s first attempt to estimate the broader carbon footprint of a large language model.
The generative-AI boom has led big tech companies to integrate powerful AI models into many different products, from email to word processing.
Luccioni tested different versions of Hugging Face’s multilingual AI model BLOOM to see how many uses would be needed to overtake training costs.
The original article contains 1,021 words, the summary contains 153 words. Saved 85%. I’m a bot and I’m open source!