Model Intelligence Trumps Computing Power in AI-Driven Cybersecurity

Unlike proof-of-work systems where computational resources guarantee eventual success, AI-driven cybersecurity depends fundamentally on model intelligence rather than processing power. This insight challenges conventional assumptions about scaling AI for security: even infinite token consumption cannot compensate for weak model reasoning, as demonstrated by the OpenBSD SACK bug vulnerability that weaker models fail to genuinely understand. Organizations must prioritize access to more capable AI models over raw computing resources to stay ahead in vulnerability detection.