Jon Parrella

I'll say it.

But like PJM can't get out of their own way.

They can't get anything through the interconnection queue fast enough, right?

And that's – there's no reason for that, especially not with AI now.

Like you should be able to accelerate the speed of feasibility studies leveraging AI's capacity to look at the network of the grid and look at it and say, is there room here or not and how do we do it?

The other thing I'll mention that's interesting is if you look at what happened in Virginia recently,

There's a misalignment or misunderstanding of certain key terms that the grids are reacting to.

And it's scary because I think you're going to see a lot of like regulatory reaction and you're starting to see moratoriums because they're like, OK, we need to slow everything down a little bit and pump the brakes to make sure we fully understand what this means.

In Virginia, they had a situation where it wasn't a fault of the data centers, but the grid faulted.

And like nine data centers went offline or they went to backup power.

And when the grid came back up, the grid was expecting the data centers to be there, and they weren't.

They were still running off backup power.

It's called low-voltage ride-through.

And what happened is the grid then had an over-frequency event because it's all real-time supply and demand.

So you had generators online running.

for the grid that were expecting a load and the load wasn't there when the grid came back.

And so there was way more power available than needed being.

What can happen in situations like that and or if you connect one of these data centers directly to the grid, when you have that much volatility that quickly, you can shunt airbreakers or trip airbreakers at substations and cause a rolling blackout.

Right.

And so when you start building data centers that are gigawatt scale, it scares the hell out of me if they don't have the right infrastructure in place because they're not designed.