EP196 AI+TI: What Happens When Two Intelligences Meet?

Guest: Vijay Ganti, Director of Product Management, Google Cloud Security Topics: What have been the biggest pain points for organizations trying to use threat intelligence (TI)? Why has it been so difficult to convert threat knowledge into effective security measures in the past? In the realm of AI, there's often hype (and people who assume "it's all hype"). What's genuinely different about AI now, particularly in the context of threat intelligence? Can you explain the concept of "AI-driven operationalization" in Google TI? How does it work in practice? What's the balance between human expertise and AI in the TI process? Are there specific areas where you see the balance between human and AI involvement shifting in a few years? Google Threat Intelligence aims to be different. Why are we better from client PoV? Resources: Google Threat Intel website "Future of Brain" book by Gary Marcus et al Detection engineering blog (Part 9) and the series Detect engineering blogs by David French The pyramid of pain blog, the classic "Scaling Up Malware Analysis with Gemini 1.5 Flash" and "From Assistant to Analyst: The Power of Gemini 1.5 Pro for Malware Analysis" blogs on Gemini for security

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