Catch this episode on YouTube , Apple , Spotify , Amazon , or Google . You can read the show notes here . The word AI, much like Zero Trust, has come with a lot of baggage in the past few years. It’s a term that’s been misused, slapped on the front of startups’ overpriced booths at RSA and Black Hat, and it feels like every cybersecurity product under the sun now supports it in some flavor or fashion. It's the same cycle we’ve been in the past, but this time everyone is jumping in. This week we are getting in front of the bandwagon and chat with a pioneer in the cybersec AI space who has seen how the technology has been evolving over the past decade, Oliver Tavakoli, the CTO of Vectra AI. “My contemporaneous definition of AI at any given moment in time is there's got to be enough pixie dust in it for people to view it as somewhat magical; so that's my incredibly technical definition. I'd say over the past 10-15 years, that is typically meant neural nets-that has those have been a stand in-and and obviously, neural nets can be used for discrimination [As opposed to a generative AI model]. Again, the example of cat (You search “Cat” on Google images, and it returns results that show images, in theory, of only cats) is an example of how they can be used in a generative sense, which is really the latest revolution that you see. And then the other thing is how broadly applicable they are and how well read they are. Tavakoli’s definition of AI provides the context for how AI is primarily applicable today in cybersecurity. But, in the past, typically these concepts were held back by technology. There is also a stark difference between what has been referred to as AI, or a discriminative AI model, and what is most popular today, or generative AI. It turns out in these large language models, as you make them bigger, there was always kind of the question of if you make them big enough. Will they just plateau or will they take off? It really wasn't a foregone conclusion that if you made them big enough they would take off, but it was a bet that was placed and a bet that turned out to have some merit to it. And that is the crux of today’s interview: what was and will be the past and future impact of AI on cybersecurity? Key Takeaways AI plays a significant role in both offensive and defensive cybersecurity strategies. Threat actors use AI to enhance their attacks, making them more believable and harder to detect. Defensive uses of AI include improving workflow and making SOCs more productive. Organizations must always assume that compromise is possible and focus on minimizing the impact of breaches.
