Clare Kanazawa is a student at Holy Names Academy in the United States. She is a member of the National Honor Society and has received the Sr. Ann Book Award and a varsity robotics letter. Beyond academics, Clare contributes to her school’s robotics programming team. She also serves as a Youth Ocean Advocate at the Seattle Aquarium through its Leadership Pod. In addition, she studies calculus through the Art of Problem Solving programme. She also leads a section in her school orchestra, where she plays piano and percussion.
At CCIR Academy, Clare’s research paper, Source Attribution vs. Non-Source Attribution in Large Language Models: An Analysis of Which Technique Is More Environmentally Friendly, was accepted at the Sustainable AI Conference. Her study compares the environmental costs of two approaches to large language models: source attribution and non-source attribution. She fine-tuned LLaMA models and measured their energy use and carbon emissions. The results showed that source attribution increased computational energy consumption and emissions. Therefore, reducing attribution may help lower the environmental footprint of large language models.
The Sustainable AI Conference is hosted by the Bonn Sustainable AI Lab and the Institute for Science and Ethics at the University of Bonn. It brings together researchers, policymakers, and industry leaders to examine the environmental and societal impacts of artificial intelligence. Through these discussions, participants explore ways to develop and use AI more sustainably and responsibly.
Congratulations to Clare on this achievement!
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