What about the ones that are not being transparent? It's the fact that it, it, it does appear to be happening then that's got people worried.

And I think that's the question with any of these novel and evolving technologies, and I think there's two perspectives you can have on this.

I think the, the first is that, yes, i- in some ways we can see this as a very positive step in transparency from these AI companies.

You know, they've set up these benchmarks, they've set up these protocols.

This, it's this process of red teaming it's called, is where you test these models, um, in this way, and they've published it, right? Um- And it shows that some of these discussed risks are, are real.

Uh, and, and that's important because as we've seen, we live in a world where all of the, the complexity of biological events has caught the attention of the media because of the pandemics and continuous outbreaks that we continue to live through.

I mean, there's also another cynical perspective, which is my own, which is that, you know, we can measure these risks in biological space in the context of AI tools.

But at the same time, if we block the, the sort of nefarious work that could involve many of the same approaches, we prevent that good work in the course of blocking the bad.