... regardless.

You know, because you still need some training in f- so some training in a compute, yeah.

Um, look, the, the main difference is clearly a, a closed model or a commercial model is just that.

Some company has been funded themselves and they've built a model and now they are selling it, and the way in which they sell it is one token at a time.

Um, you know, hello, ChatGPT, Claude, Mistral, all of those.

Then there's a group of people that are building open weight models, and what that means is when you, when you build a model, it has weights and it has representations.

The representations, if you like, are the data, and the weights are how that data is connected together, right? So as a very simple example, the dog chased the...

Hmm.

What's your response to that? Is there a different perspective we should be taking here?

Look, I'm a little bit pro data centre and I get that they might look ugly in your suburb if you're in your suburb.

And occasionally when they need to fire up their generators, that is a diesel generator that's running.

But they're doing a lot of work in renewables.

They're building data centers with water treatment plants.

But the very much publicized power and data usage for me is a little bit of a furphy, to use another good Aussie phrase.

There was a study just done recently by Mandela, and they discovered that we use more electricity in Australian shopping centers than we do in Australian data centers.

or

And then I speak it back in English and it's got to do the opposite to get

to.

It's got to do the opposite.

And actually, that's the harder piece right now.

So you have to kind of Franken stack a bit because I'm working with a client that wants to.

Franken stack.

Yeah.

Yeah, exactly.