What's Happening?
Researchers at UNC-Chapel Hill have demonstrated that large language models (LLMs) can significantly speed up the georeferencing process in digitizing plant collections. This task, which involves determining the original collection locations of plant specimens,
has traditionally been labor-intensive and costly. The study found that LLMs can perform this task with near-human accuracy, reducing time and costs. This advancement could facilitate the rapid digitization of the estimated 2-3 billion herbarium specimens worldwide, enhancing research capabilities in biodiversity and ecological studies.
Why It's Important?
Digitizing natural history collections is crucial for advancing ecological research and understanding biodiversity. The use of AI to automate georeferencing can unlock vast amounts of data that are currently inaccessible, enabling researchers to track biodiversity changes and species movements more effectively. This technological advancement could accelerate research in areas such as climate change and conservation, providing critical insights into ecosystem dynamics. The study highlights the transformative potential of AI in scientific research, offering new tools to address global environmental challenges.
