Zuzanna Stamirowska

So this is fairly simple.

Knowing that physicists, I mean, it looks like a cascade.

Imagine like an epidemic spreading in a graph, right?

So like you have a system, you have an epidemic spreading.

This is how information is spreading, right?

So if you have a very small cascade, very small epidemics, you probably don't care because it wasn't relevant enough for the model.

Yeah.

Potentially.

But if it's small, you can still reverse it.

But if it's big, this is when, you know, also the information is very relevant and you get to a point when you, like, you wouldn't be even able to say where this came from if you were, you know, somewhere in this graph kind of looking around, you wouldn't be able to say where it came from.

I mean, then it's not reversible per se, just from kind of physics point of view.

So, yeah.

Yeah, but you roll back the checkpoint and you could just checkpoint your kind of model over time.

So, you know, if you infuse something you didn't want to have in the data and the model, you take it out.

This is very easy, like generalization.

Yeah.

True generalization.

No, true generalization.

So getting to innovator level.

I mean, I think there is a path towards space exploration for us.