Machine Learning Reveals Evolutionary Paths of Animals Returning to Aquatic Life

Yale scientists have employed machine learning and extensive fossil measurements to uncover new insights into how terrestrial animals evolved to return to aquatic environments. This research illuminates the specific factors and pathways driving such significant evolutionary shifts, enhancing our understanding of life's adaptability.