Dr. Qichao Hu

So there's two parallel approach on the database, the raw data from the lab, dry data and wet data.

We use that to teach a foundation model, no large language model.

And then in parallel to build that intelligence,

we take all the books, all the papers about this domain, and then we teach that large language model to learn how to search for it.

So one is, so think of the database as the map, and that's not LLM.

And then think of the LLM as the search engine.

That is LEM.

So we don't feed that large database into the LEM.

We feed that into the map, into the foundation model.

And then to the LEM, we only feed a more limited list of properties.

Yeah, so it's really to improve lithium metal and then develop the battery so that it's ready to be deployed in vehicles.

And of course, that technology development, that product development can also be used for drones or energy storage for data centers, for lots of other applications.

One thing we have seen in the electrification industry

effort, the EV industry has been sort of the pioneer of the technology and product that develop in EV are now used in other industries as part of the electrification.

That makes sense.

Cost, duration.

Yeah, so there are technical specs you have to meet.

Range, high temperature, low temperature, performance, safety, a lot of safety.

The safety test is no joke.

And then also the scale.