Intro

Dr. Dan Shiebler, Head of ML at Abnormal Security, joins Jon Krohn this week and unveils the intricacies of cybercrime detection and email protection, and the role of AI in future challenges.

This episode is brought to you by Grafbase, the unified data layer, by ODSC, the Open Data Science Conference,  and by Modelbit, for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• The heuristic and “intermediate” ML models that they develop at Abnormal Security [07:08]
• How Dan uses LLMs at Abnormal Security [15:46]
• How false negatives are individually the biggest classification error to avoid in cybersecurity [20:49]
• How head-to-head competitor analysis helps refine models [34:34]
• Resilient ML in cybersecurity [38:36]
• Abnormal Security’s routine for updating their models [52:37]
• AI's impact on the urban world [1:09:57]
• How to stay updated in data science and AI [1:13:46]

Additional materials: www.superdatascience.com/717