The study, titled Conditional Adversarial Fragility in Financial Machine Learning under Macroeconomic Stress, published as a ...

Artificial intelligence (AI) safety has turned into a constant cat-and-mouse game. As developers add guardrails to block ...

Adversarial AI exploits model vulnerabilities by subtly altering inputs (like images or code) to trick AI systems into misclassifying or misbehaving. These attacks often evade detection because they ...

As AI applications and capabilities continue to progress rapidly, so do efforts into exploiting its vulnerabilities, mainly through the Adversarial AI research field. As these trends persist, AI ...

We’ve touched previously on the concept of adversarial examples—the class of tiny changes that, when fed into a deep-learning model, cause it to misbehave. In March, we covered UC Berkeley professor ...

Generative adversarial networks, or GANs, are deep learning frameworks for unsupervised learning that utilize two neural networks. The two networks are pitted against each other, with one generating ...

A five-year “adversarial collaboration” of consciousness theorists led to a stagy showdown in front of an audience. It crowned no winners — but it can still claim progress. Science routinely puts ...