Dylan Patel

Here's something that the model spit out.

You can do it in like all the like CAD type programs, not exactly CAD, but like computer aided design programs and test it, simulators and test it.

But then you also want to test it in the real world and then feed that feedback back into the model.

And so you do this like chain of, instead of purely being

digital, which is why RL is really hard because you need to generate a bunch of responses, test, and then train the model.

So the flywheel is so freaking fast.

The flywheel in the physical world is so slow.

You mean I need to make a chemistry?

I need to try this?

I need to test the thing?

I need to input it back in and keep calibrating and keep doing this?

It's so much more expensive.

It's so much harder to do.

But actually, there's a ton of low-hanging fruit there, I bet, in terms of large-scale experiments, whether it's

Drug discovery is one angle, right?

But design of like, what most complicated chemistry ecosystem in the world is semiconductors.

There are tons of things that we know are the next thing to build.

And now the next five years of work is actually building it, right?

And it's like next five years is actually getting the chemistry to work, getting it to be a low enough yield, a low enough defectivity.

Or it's, we can't, we don't know what material could do this.