The Digital Press

A self-taught high school student, Matteo Paz, developed a machine learning algorithm that identified 1.5 million previously uncatalogued variable space objects by analyzing decade-old NASA infrared data.

Why it matters: The discovery significantly expands our cosmic catalog and showcases AI's power in processing vast astronomical datasets.

The big picture: This breakthrough highlights how young scientists merging computer science with astrophysics can accelerate space research.

The stakes: Verification and peer review are needed to confirm these 1.5 million objects as genuine variable phenomena in space.

Commenters say: Many admire the achievement and youth involvement, while some emphasize the importance of independent validation and peer review.