Q for me. Uh, you mentioned that privacy is a fascinating topic. Um, have you, have you, well, how does that work? So you create an index of the data you get, the privacy rights attached to it, because privacy laws I mean, if you're building a whole history, probably as well, maybe you can believe you're a part of a GDPR, you might exist. A few years ago, nine dollars,
A Yeah, and it's different, different jurisdictions, right? So, and it could be over, weird overlapping things, or different types of things. It's, it's really, really difficult. It's really hard. Ultimately, probably what you want is some sort of, like, privacy as a service, as, as well. So instead of getting the data yourself, um, as an innovator, you might want to keep the data, um, where you, you can't see it, and maybe you can, Like, put your algorithm in a container, run against the data, uh, so you don't have to worry about some sort of these privacy issues. So you'll, uh, I, for instance, everyone, anyone who's ever been, um, like, maybe doing machine learning, there's probably certain, uh, data sets that you salivate over that you wish you could access, because you could really learn a lot. One would be, like, a lot of these hospital, or Medicaid, or other types of data sets would just be, you could just build just incredible innovation, but these are, Have this many, many, you know, huge privacy issues around it. Another one would be the IRS data set. So you could do a longitudinal study of, ah, you know, of the kids of people who were low income. How did those kids do? What happened? What happened? You know, those kids that had, that were in charter schools, that were in low income, that did, you know, you could start to run, like, all these, like, really, really inter…
AI assessment note: “instead of getting the data yourself, um, as an innovator, you might want to keep the data, um, where you, you can't see it”