Tom McKenzie

some very significant players like Amazon, who came through the dot-com bubble and, of course, now remain one of the most valuable companies on the planet.

But there was a lot of capital, there was a lot of investment that was burnt in that process.

And so that is another comparison that people are making.

It's the depreciation around the assets and the chips that they're worried about, but also comparisons with what happened during the dot-com era and the pain that was felt by those telecom equipment makers that sunk so much money and to which they accumulated huge losses.

So pushback to the depreciation argument would come from NVIDIA.

And we've heard that recently from the CEO, Jensen Huang.

And he's made the case that, in fact, even their older AI chips, one of their older versions is called Hopper.

has a lifespan of about six years and is very versatile.

So you can use it not just for the training of these large language models, but for the post-training and for the inference.

That's when they're actually being used by us, by consumers and by enterprise.

And so you can move them around.

They have different functions and therefore they actually have a longer lifespan than some of the sceptics are suggesting themselves.

And our own analysis suggests that those hopper chips, those older varieties of chips, have a lifespan of about six years and are fully utilised by most of the companies that own those.

So that does address some of that concern.

The question going forward, to what extent these companies are going to be able to find products...

that match the investments that they are sinking into the AI infrastructure story.

Bain Capital came out with a report recently suggesting that by 2030, the hyperscalers and other AI giants would have to be turning around revenues of about $2 trillion, and that right now there's a huge gap, hundreds of billions of dollars, in terms of the gap between the investments into the AI infrastructure and the actual revenues that are coming about as customers,

and as enterprises and companies use the end product.

So the go-to-market, the product fit is going to be really, really important.

And what the big AI players say, whether that is the hyperscalers, again, the likes of Meta and Alphabet and Amazon say, or the likes of OpenAI and Anthropic, is we're going to be in this world of agentic AI.