Dr. Qichao Hu

Absolutely.

So I'm totally bullish on that.

So with the caveat is that I wouldn't trust the explanation.

I would trust the result.

I give you one example.

So we have lots of the battery test data, charge and discharge, the voltage curves.

And then as a human scientist, so we're all trained in the, for example, Newtonian science, right?

Mm-hmm.

In school, we are taught physics, chemistry, material science, mathematics.

We're taught these theorems, and then you study the theorems, and then you apply these theorems, and then the world must follow these laws, the different laws of physics.

Now with AI, they go beyond that.

They use laws that we are not able to comprehend.

So for example, that voltage and the charge and discharge voltage curve, a trained human scientist would see, would characterize that curve maybe with 20 parameters.

These are typical parameters you will learn in school, in books.

When you give that to an AI model,

it will give you about a thousand parameters.

But most of these parameters, you are not able to explain what they are.

It's not like the human scientists will see 20 parameters.

Okay, this is charge, this is capacity, this is time, this is DQDV.

You can't explain these things.