Guests:  Umesh Shankar, Distinguished Engineer, Chief Technologist for Google Cloud Security Scott Coull, Head of Data Science Research, Google Cloud Security Topics: What does it mean to “teach AI security”? How did we make SecLM? And also: why did we make SecLM? What can “security trained LLM” do better vs regular LLM? Does making it better at security make it worse at other things that we care about? What can a security team do with it today?  What are the “starter use cases” for SecLM? What has been the feedback so far in terms of impact - both from practitioners but also from team leaders? Are we seeing the limits of LLMs for our use cases? Is the “LLM is not magic” finally dawning? Resources: “How to tackle security tasks and workflows with generative AI” (Google Cloud Next 2024 session on SecLM) EP136 Next 2023 Special: Building AI-powered Security Tools - How Do We Do It? EP144 LLMs: A Double-Edged Sword for Cloud Security? Weighing the Benefits and Risks of Large Language Models Supercharging security with generative AI  Secure, Empower, Advance: How AI Can Reverse the Defender’s Dilemma? Considerations for Evaluating Large Language Models for Cybersecurity Tasks Introducing Google’s Secure AI Framework Deep Learning Security and Privacy Workshop  Security Architectures for Generative AI Systems ACM Workshop on Artificial Intelligence and Security Conference on Applied Machine Learning in Information Security