What is the current reality for AI automation in Cybersecurity? Caleb and Ashish spoke to Edward Wu,  founder and CEO of Dropzone AI about the current capabilities and limitations of AI technologies, particularly large language models (LLMs), in the cybersecurity domain. From the challenges of achieving true automation to the nuanced process of training AI systems for cyber defense, Edward, Caleb and Ashish shared their insights into the complexities of implementing AI and the importance of precision in AI prompt engineering, the critical role of reference data in AI performance, and how cybersecurity professionals can leverage AI to amplify their defense capabilities without expanding their teams.

Questions asked:
‍00:00 Introduction
‍05:22 A bit about Edward Wu
‍08:31 What is a LLM?
‍11:36 Why have we not seen entreprise ready automation in cybersecurity?
‍14:37 Distilling the AI noise in the vendor landscape  
‍18:02 Solving challenges with using AI in enterprise internally
‍21:35 How to deal with GenAI Hallucinations?
‍27:03 Protecting customer data from a RAG perspective
‍29:12 Protecting your own data from being used to train models
‍34:47 What skillset is required in team to build own cybersecurity LLMs?
‍38:50 Learn how to prompt engineer effectively