Dr. Qichao Hu

And the second is idea filtering stage.

You have this idea and then you have lots of candidates, candidate materials, and they have to filter.

This could be millions and then billions down to hundreds.

And then third is validation.

So you're down to a couple hundred, but you have to test this.

And then in drug discovery, you go through trials, clinical phase one, phase two, and then approval.

And then for battery, depending on the application, you have to do room temperature cycling, low temperature cycling, high temperature cycling.

And in some applications, for example, EV, you buy a car and that battery needs to last at least eight years.

A lot of times the warranty is for 15 years.

So that means you actually test the battery for at least eight years.

And there's no good way to accelerate that testing.

Testing process just takes a long time.

So again, it's still the same three phases, idea creation, candidate filtering, and then validation.

So for each one, idea creation in the traditional human process, that takes about on average a month to come up with a really good idea.

And also the horizon of a human scientist is limited.

On average, a human scientist reads three to five papers because human scientists also have to eat, have to drink coffee, and then get sick and tired.

It's inefficient.

I know.

And then an AI agent can process several tens of thousands of papers a day and then has perfect memory of all the content.

So that can be reduced from a month to on the order of...