AI sped up James Webb Space Telescope data analysis from years to days. What can it do for the groundbreaking Rubin Observatory?
- Apr 30
- 1 min read
SPACE.com — The researchers trained the generative model, called Neo, using images taken by the Subaru Telescope in Japan and snaps of the same sections of the sky captured by the Hubble Space Telescope.
The task for the model was to learn how to fill the details missing in the images taken from Earth. The results were impressive. The researchers said in a paper that the Neo model "improves the accuracy of measured morphological parameters by factors of 2-10."
In practice, that means an increased resolution that reveals a vast quantity of individual stars and precise shapes of galaxies where before one would find only vague smudges.
