Tom McKenzie

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.

We're going to have AI agents booking our holidays, checking up on our health care, finding good schools and universities for our students.

All those kind of things are going to come together.

enterprises are going to be embedding AI much more than they already are.

We're only in the first opening stages of that would be the argument.

And then there's the sovereign AI story where different countries, and we're seeing that in the Middle East, but also in Europe as well, and Japan are investing heavily to ensure that they have their own AI infrastructure and AI clouds that will be very early in that story as well.

Those are all the cases that the big AI players would underscore in terms of why this is going to be driving momentum going forward, at least through 2026.

Our own team at Bloomberg Intelligence say the end of 2026 is going to be a question mark as to whether or not investors continue to have patience.