Min-Liang Tan

And that's how we design it.

And there are particular problems that we need to solve that the models don't provide for us.

You know, context.

So that's one of the things that, you know, our AI scientists do really well.

We've got, you know, advanced RAG.

We've got context.

We really focus on that.

Persistent memory is something that we are very good at also at the same time.

And these are fundamental things.

problems that AI scientists need to solve.

So these are the things that our team does.

So we work with the best models out there.

And we also have the capabilities of creating physical representations.

And that's something that we've got a huge advantage at.

So that's, I think, where our angle is, I think, from a software perspective, that we believe that we can bring enough value of persistence across to the user.

And progressively, we will see even more users that will say, look, this is what I want to be able to go from one model to another, for example.

Or if I'm happy with just a single model, and if I'm a techie and I'm happy to just go directly and play around with it, we provide that open platform.

So being open is one of the things that we truly believe in.

Well, I think the entire tech industry has always been, you know, rappers, you know, for that matter.

Not necessarily from an AI perspective, but it's the question of when you build a rapper,