Q Maybe this transitions to the business side. How close is this to problems that, you know, you guys do consulting, right? Effectively. I don't know if that's the hacker word for it. Like how is this, does this match what you do for work?
A Yeah, I'll, I'll, I'll take this one. In a sense. Yeah. There's been some partnerships, you know, plenty, obviously being sort of the poster boy for AI machine learning hackers, the world over, but we get some interesting opportunities that come across the desk. And oftentimes, you know, we, we have an ethos in our hacker collective. Which is radical transparency and radical open source. And what that basically means is if it comes down to, you know, us being an emerging technology is like red team doing like ethical hacking and research and development. If an organization that's on the frontier says, well, we really want you to test this or check this out, kick the tires, give us feedback, poke holes in it, whatever. But in the contract, it says you can't kiss and tell. And we said, well, we really want you to open source the data. And then they say, well, then we don't really want you to come kick the tires anymore. Well, if it's between us touching the latest and greatest tech to explore it and push the limits, right. Then we're going to do that. So we're open source up until we can't be, that's the best way I describe it. We, but we often push for open source data sets. And you can see this with some of the partnerships that we've had in the past. Right. So Yeah. I try to think of it like this. It's like you have these, these multi-billion dollar companies and they're build…
AI assessment note: “In a sense. Yeah. There's been some partnerships”