
AI Uncovers Hundreds of Hidden Cosmic Oddities in the Hubble Archive
Researchers used AnomalyMatch, an AI-driven neural network, to scan nearly 100 million Hubble Legacy Archive image cutouts in about 2.5 days, identifying roughly 1,400 anomalous objects, with around 800 new-to-science discoveries. The haul includes merging galaxies, gravitational lenses, jellyfish galaxies, and unusual edge-on disks, plus a number of objects that defy easy classification, highlighting AI’s power to unlock archival data for future surveys like Euclid and the Vera C. Rubin Observatory.












