You can't just think your way to a solution. The universe is so complicated that in order to actually push the frontier of knowledge and to make progress, you need to create these conjectures and then actually see whether or not it holds.

Our data comes from our physical labs. And this is sort of our ultimate truth. It's not enough just to do optimization against some answers that were known in some papers or textbooks, because we're going beyond that.

We feel like simulations will never be enough by themselves, but in the loop of simulations, AI and experiments, I think we can make progress much faster than before.

Broadly the way that we think about this is it is a lab in the loop with amortized latency. So it's like go out, you record the thing once and then you can have a huge number of rollouts through that thing.

But even a slight pause or a halt of research can put that research back for months or years or decades, depending on what needs to be rebuilt to start the research again.

If something is unpredictable, unstable, then every aspect of that scientific enterprise is shaken. And in the case of NIH funded research, it's not just what's happening at the nih.

I would encourage more research labs around the country or the world, as a matter of fact, to invest in this type of research. It's very important.

The problem comes first and you should be flexible in terms of your solution space. You should try both things. You should try to understand what is the problem that you're trying to solve.