Juni

Second, the question of understanding.

A reinforcement learning controller that works well on a tokamak might not be easy to translate back into human readable physical insight, and are we satisfied with being able to control a system, or do we want explanations that match our scientific intuitions?

Are we looking for just validation, or are we looking for...

push it forward.

And then, of course, third is governance.

If AI becomes the default control layer for reactors, grids, plants, and labs, who sets the objective functions, who audits them, and who is accountable when something goes wrong?

So here's the question of the day.

If AI is on track to become the operating system for critical physical systems like fusion reactors, power grids, factories, labs, what are the two or three basic principles you would want to insist we build into the control layer from the start?

Mm-hmm.

Okay, so direct environmental impact.

It seems to be the largest concern for you.

Right, right, right.

So I think for me, I see less clarity of fusion, cold fusion, mainly because fusion's just the process that happens.

And the technology, I guess all of the technology pushing forward is cold fusion, because that's how you get more energy out than you put in.

Being able to be portable, being able to put it in anywhere and control it and those kinds of things.

So what it seems to me so far is that we're looking at environmental concerns and then governance concerns, control concerns, right?

Andy, you see us as humans would be in every level of authorization, control, shutdown.

Sort of maybe how we apply these processes or systems to nuclear reactors, power plants, those kinds of things.

Because, Beth, we don't want to see another Three Mile Island kind of outcome and that kind of stuff.

Yeah, I think one of the things that brought up the concept as an interest point is because of recognizing some of the stories that we covered in the past, right?