Fixed-weight models are adversarially vulnerable: hence misaligned

Fixed-weight AI models are inherently vulnerable to adversarial attacks, which leads to misalignment between their intended and actual behavior. This vulnerability arises because their fixed parameters cannot adapt to adversarial inputs, causing performance and safety issues.