In this episode of the "Training Data" podcast, Dean Meyer interviews Dan Lahav, founder of Irregular, about the future of AI security. Dan discusses the shift in security focus needed as AI models become autonomous economic actors, moving from traditional code vulnerabilities to unpredictable AI behaviors. He shares real-world simulations where AI models outmaneuver traditional defenses, emphasizing the need for proactive experimental security research. Dan also addresses the balance between AI's potential for good and the risks of its misuse, advocating for robust monitoring and customized defenses. The conversation covers the capabilities of current AI models in cyberattacks, the role of reinforcement learning in cybersecurity, and how enterprises and governments should approach AI risk and sovereignty.
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