vulnerability detection AI News & Updates
AI Security Firm Irregular Secures $80M to Test and Secure Frontier AI Models Against Emergent Risks
AI security company Irregular raised $80 million led by Sequoia Capital to develop systems that identify emergent risks in frontier AI models before they are released. The company uses complex network simulations where AI agents act as both attackers and defenders to test model vulnerabilities and security weaknesses.
Skynet Chance (-0.08%): The development of robust AI security testing and vulnerability detection systems reduces the probability of uncontrolled AI deployment by creating better safeguards and early warning systems for dangerous capabilities.
Skynet Date (+0 days): Investment in AI security infrastructure may slightly slow deployment timelines as more rigorous testing becomes standard practice, though this represents a minor deceleration in the overall pace.
AGI Progress (+0.01%): The focus on securing increasingly sophisticated AI models indicates continued advancement in frontier model capabilities, and the security testing itself may contribute to understanding AI behavior and limitations.
AGI Date (+0 days): Enhanced security requirements and testing protocols may add minor delays to model development and deployment cycles, slightly decelerating the pace toward AGI achievement.