Alex Lintner

That's not math.

It doesn't do the calculation.

It just recognizes it.

Human oversight through data scientists.

Uh, you know, you, you, I think we're too early in the journey that we can let it run on its own.

I think we need to all practice responsible use for a data company.

It means we lean on some of the strongest human assets that we have.

And as our data scientists, they need to look at the output and they need to look whether it's accurate or not.

And if, if it's not accurate, you know, we turn it off and we fix it.

Or if it's not fixable, we would throw it away.

Have you run across that by the way, but we would do that.

Oh, yeah, because we test everything before we put it in production.

So it happens all the time.

Nothing goes into production without going through that kind of process.

We have synthetic data, and we have depersonalized data that we use for testing new models, new agents.

And we don't put anything into production until we know it works.

Nobody should, right?

I think it has to do with the interaction of AI to the human.

The way I look at AI, and I think a lot of people do, is it's a digital teammate or a digital workforce.

If it is that, then that teammate or that team would perform a certain task, and it would contribute it to the work of the overall team.