Machine learning can "hallucinate" data features in images during training, known as adversarial examples, leading models to misclassify objects in seemingly nonsensical ways. This reveals a profound gap between human and AI perception, underscoring that algorithms don't "see" as we do; they process patterns that can be deceptively manipulated. Understanding this helps in hacking-proofing AI systems. Share your own ML insights—isn't it fascinating how different the world looks through the eyes of an algorithm?