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A recent study conducted by Hugging Face and Carnegie Mellon University has revealed that generating AI images has a comparable carbon footprint to charging a smartphone.
The researchers discovered that the process of generating images from text consumes a significantly higher amount of energy compared to other generative AI tasks. Notably, AI-generated text was found to utilize energy equivalent to 16% of a smartphone's full charge.
Key Points from the Study:
- - The study involved testing 88 models across 30 datasets, with the researchers noting that large, multipurpose models like ChatGPT were particularly energy-demanding when compared to task-specific models.
- - Across 13 tasks, including summarization and text classification, the researchers measured carbon dioxide emissions per 1,000 grams, highlighting the environmental impact of different AI tasks.
- - The most energy-intensive tasks for AI were those involving the generation of new content, such as text, summarization, image captioning, and image generation, with image generation being the highest for emissions and text classification the lowest.
Implications and Recommendations:
The study's findings underscore the environmental implications of AI model usage, particularly in tasks involving content generation. The researchers have urged machine learning experts to be transparent about the environmental impacts of their models, emphasizing the need for increased awareness and accountability in the development and deployment of AI technologies.
This study sheds light on the energy consumption and environmental impact of AI tasks, prompting a call for greater transparency and consideration of sustainability in the development and use of AI models.