And how does that translate into what you're seeing with AI, right? And the similarities and differences there.

Yeah.

First thing when I think of AI and we call it machine learning.

When, you know, I had my edge fund was really the amount of talent that was at my fingertips as a professor that I wish I wasn't, you know, slinging solar panels and had focused more on some of, some of what they're doing now.

Um, but I'm very happy for them.

And, you know, some of my former students are, uh, whether, you know, a lot of them went to like the Citadels, Jumps, Geckos of the world.

Um, but also a lot went to Google and, um, Anthropic, OpenAI, Microsoft, because they have a, you know, you know, it wasn't like their Python trait, you know, abilities, it was their abilities to look at complex systems that have multi layers and multiple, multiple inputs, and how to aggregate that data into decision making for trading, you know, but also risk, you know, how managing risk is really a huge commodity that a lot of traders have.

And that person's they're the one defining what these agents need to do.