This webpage introduces the discoveries locked in returned luanr samples, aiming to explore how to use diverse scientific data to explore how AI supports lunar science, museums and mineral galleries, youth engagement, and public understanding by using these discoveries as the motivating context throughout. Since 2019, We have mentored over seventy high school students and university undergrads in building (1) a dataset of petrographic images of returned lunar samples; (2) a PDF corpus of lunar olivine research; (3) a multimodal dataset for a foundation model of the Moon.
Archive
Acknowledgement
This work is developed by PI Ping Wang who is a Research Scientist at the Planetary Science Institute. This work is supported by the National Science Foundation under Grant No. DRL-2620566. Any opinions, findings, and conclusions or recommendations expressed are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Contact
pwang@psi.edu