What is different about how AI is handling that? And then what are the boundaries and how have those boundaries changed over the last couple of years? Is that a fair question?

Yeah.

So, yeah, it's a great question.

It's to really historically we've been focused on humans or the complete factor that they're the ones deciding on on is this should this alert be valid? Is this something I should investigate? And then they come to a conclusion on the alert.

So is this a threat? Is this not a threat? Did they look at the right source to make sure that their their validation was appropriate? Now we have AI doing a lot of that.

So what has shifted is we went from doing the work to supervising the work, right? And so now AI is going and making a lot of the preemptive decisions.

It's evaluating a lot of logs.

So talk a little bit about how you did that and did you anticipate the efficiencies at the start? Did you gain more efficiencies as you went? How did that kind of evolve?

So from your perspective, what do you think the new international standards for AI security and data protection will look like the next few years without holding back innovation? What are you seeing here? How do you see this planning out?

I actually do think that for AI regulation specifically, that's going to move faster than cybersecurity regulation has.

And that's because of a couple reasons.

But one of those is because as different nation states, we all have different priorities on the state of our AI models, the state of the companies that lead the charge on our models.

on our GDP related to AI.

And so we are kind of in an arms race of sorts with data.

And so I know here in the US, we worry a lot about nation states like China and Russia and such that they're building their own LLMs.

So what should they be doing?