Alan Kohler

They're not friends or anything.

They're just doing tasks, right?

So talk us through this difference in the streams.

How do you think that's going to develop?

And productivity.

I don't think I, so I can just interrupt.

I don't think I understand what you mean by context information.

I mean, are you talking about just the amount of tokens, AI tokens that are being used?

And that means it's more expensive to use.

You said before that it's different to electricity because with the adoption of electricity, they had to build power stations and all this and power lines and everything, which was a lot of infrastructure.

But I would have thought it was actually a pretty good analogy because in order to make AI work, you've got to build all these data centers and you need a lot of power.

So to what extent is AI adoption and production being limited by the amount of compute that is available in data centers and the amount of power that's available to do it?

You did some work with Maxim Masenkov, and you introduced an idea you called observed exposure.

which is the gap between what AI can do in theory and what Claude is actually being used for.

So what surprised you about that?

And how long will it take for that gap to be closed?

Why is that?

But that 1.8% productivity growth over 10 years that you talked about before, to what extent is that to do with augmentation?

And to what extent is it displacement?

I mean, obviously, if there's fewer workers doing the same thing, then productivity, labor productivity of the workers increases, right?