In this episode of the AI Cybersecurity Podcast, Caleb and Ashish sat down with Vijay Bolina, Chief Information Security Officer at Google DeepMind, to explore the evolving world of AI security. Vijay shared his unique perspective on the intersection of machine learning and cybersecurity, explaining how organizations like Google DeepMind are building robust, secure AI systems.

We dive into critical topics such as AI native security, the privacy risks posed by foundation models, and the complex challenges of protecting sensitive user data in the era of generative AI. Vijay also sheds light on the importance of embedding trust and safety measures directly into AI models, and how enterprises can safeguard their AI systems.

Questions asked:

(00:00) Introduction

(01:39) A bit about Vijay

(03:32) DeepMind and Gemini

(04:38) Training data for models

(06:27) Who can build an AI Foundation Model?

(08:14) What is AI Native Security?

(12:09) Does the response time change for AI Security?

(17:03) What should enterprise security teams be thinking about?

(20:54) Shared fate with Cloud Service Providers for AI

(25:53) Final Thoughts and Predictions