In recent years, the significant breakthroughs in protein discovery that have led to a Nobel Prize have gradually highlighted the potential of Fundamental Models (FMs) in exploring large combinatorial spaces, signaling a possible revolution in multiple scientific fields. Despite this, the field of Artificial Life (ALife) has yet to fully utilize these fundamental models, presenting a tremendous opportunity for development. To this end, the research team has introduced a method called 'Automatic Search for Artificial Life' (ASAL), which utilizes visual language foundational models to effectively alleviate the long-standing reliance in the field of artificial life.