SAFEGUARDING AI: DEFENDING AGAINST ADVERSARIAL ATTACKS

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

The burgeoning domain of artificial intelligence (AI) presents both unprecedented opportunities and substantial risks. As advanced AI systems become increasingly integrated into our lives, it is imperative to establish robust safeguards to mitigate potential harms. One crucial aspect of this endeavor involves tackling the risk of AI maliciousapplic