Craig Scroggie

So Australia has actually really punched above its weight, Alan, in our role in cloud computing and will now, because of the abundance of land and the ability to grow and scale renewable energy, solar, wind, battery, we will have an outsized opportunity for Australia to be a global leader in the development of digital infrastructure for artificial intelligence.

uh when when these tokens are created and the extent of power and so on that's required yeah let's go back in history just to touch alan to give context to digital infrastructure so traditionally computers were hosted in office buildings so if you're a bank or a telco you ran your own systems over the course of the last decade we've moved those computers out of on-premise office buildings

into specialized data centers that allowed us to improve energy efficiency and to improve sustainability outcomes.

And that's been really the role of data centers over the last decade.

Most recently, the emergence of artificial intelligence has meant that we moved from CPUs predominantly to GPUs.

So those GPUs from companies like Nvidia

Yeah, the central processing unit or the graphics processing unit, essentially the difference between linear transactions.

So in a CPU, like in your laptop, it was linear transactions, lots of them very quickly.

In the NVIDIA world for GPUs,

you're able to do parallel processing.

And that came predominantly from their history in the gaming industry, where rendering graphics was a very, very memory and system intensive use.

And so the design of these GPUs was to allow parallel processing of information in real time.

And as it turns out, the parallel processing of information was highly relevant and useful for artificial intelligence systems for large language models.

So when we go from the traditional data center, its role was largely to store and protect information and to share it.

It has security classifications.

It's a physical perimeter, not just a digital perimeter as well.

But when we move into the IR world, we're moving into the production of tokens.

And essentially, that is the GPU producing a word.

That token is essentially the economic unit of output.

And for AI to scale, we need more GPU computing capacity so that more tokens can be produced for people who are using large language models like ChatGPT or Claude from Anthropic.