I'm wondering how much more data do you think needs to be generated? And would that be considered a good thing for the demand trends for a lot of the life science tools industry, do you think?

In a lot of ways, I think of biology as the ultimate big data problem.

I mean, if you sort of think about the variables that are involved, the diversity of humanity, the inputs that affect biology, There are just so many variables and just so much complexity that needs to be unraveled.

And to be able to get to that, I can't possibly even imagine the volume of data that's needed.

So think about it this way.

And if you think about like, you know, how much data, even like, I don't mean to diminish them, but like LLMs have to be trained on to be able to tell you what the next word in a sentence ought to be, or, you know, how to sort of search for a particular match of an image that you're looking for.

That volume is already like just extraordinary, well-structured, easily accessible.

So what was the most important leadership lesson you learned from Jay that still influences how you run companies today?