
Recent developments in artificial intelligence (AI) have showcased remarkable advancements and impressive capabilities, yet a concerning trend is emerging: the collapse of AI models when faced with real-world data. This phenomenon sheds light on the gaps between controlled experimental success and practical failure. As AI models grow increasingly complex, they encounter significant challenges outside of their controlled training environments, raising










