An article published in “The Astrophysical Journal” reports the identifications of 335 new gravitational lens candidates discovered using machine learning software trained for this task. A team of astrophysicists led by Xiaosheng Huang of the University of San Francisco submitted images from the DECaLS investigation obtaining 335 possible gravitational lenses so far unknown. The verification will be carried out by humans, and 60 candidates have been included in the group that has the most chances of being confirmed. Gravitational lenses help astronomers in observing very far objects behind them, so the more are known the more likely they can be useful in some research.