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What are common mistakes to avoid with Adversarial Examples & Attacks

Intermediate

Answer

A common mistake with Adversarial Examples & Attacks is applying it without fully understanding the underlying data or problem, which often leads to weak or misleading results. Skipping proper testing before relying on it in a real project is another frequent error.
Real-world example Researchers showed that adding tiny, almost invisible changes to a stop sign image could trick a self driving car's AI into misreading it.

Common follow-ups: What is AI Security & Adversarial Attacks, How is Adversarial Examples & Attacks evaluated in practice, What tools are commonly used for Adversarial Examples & Attacks