SAFEGUARDING AI: DEFENDING AGAINST ADVERSARIAL ATTACKS

Adversarial attacks pose a significant threat to the stability of AI systems. These attacks involve introducing input data in subtle ways to induce undesirable outputs. Safeguarding against such attacks demands a multi-faceted approach that encompasses {robust{design principles, rigorous testing methodologies, and ongoing monitoring strategies. By

The burgeoning sector of artificial intelligence (AI) presents both unprecedented opportunities and substantial risks. As sophisticated AI systems become increasingly integrated into our lives, it is imperative to implement robust safeguards to mitigate potential harms. One essential aspect of this endeavor involves addressing the risk of AI malici