With over 144,370,000 square miles of surface terrain, Mars has a lot of places where signs of potential life could hide. Factor in the ultra-valuable time of current and future rovers, and it makes it even more challenging to scour for evidence of potential ancient microbes and organisms in an efficient way. To even the playing field a bit, SETI is turning again to artificial intelligence and machine learning in an effort to calculate the most likely and promising places for rovers--and, perhaps one day, astronauts--to look for clues of life. And as first detailed on Monday in Nature Astronomy, the team's new AI machine learning modeling is already showing potential to speed up humanity's search for alien life. To build their AI, the interdisciplinary project led by SETI Institute Senior Research Scientist Kim Warren-Rhodes trained a program on datasets drawn from a region called Salar de Pajonales.