A couple of weeks ago, I went looking for a competitive moat for AI, and among other candidates, I suggested that compute probably wasn’t it:

If Oracle can build a datacenter stuffed with Nvidia chips and lease it to OpenAI, that leaves Anthropic high and dry: no datacenter, no chips available to buy, and no finance to buy them with. In that case, the datacenter is worth almost any amount of money, because the value is not just positive ownership of the datacenter and its contents, but also the negative value to competitors of keeping the resources out of their hands (digits?).

The problem is that anyone advocating this view is arguing against some trends that have been stable over periods of time that are very long, in tech-industry terms at least. For this sort of investment to work out, there needs to be a window of time when the datacenter is operational but not yet obsolete, and that window needs to be long enough for the datacenter to recoup the costs of its construction and ideally generate some surplus profit for its operators.

A stately home surrounded by a moat

Of course the big frontier labs are also frantically searching for a moat to avoid getting commoditised and letting someone else capture all of the value at a different level of the stack. Now The Verge has published OpenAI’s latest internal memo about beating the competition — including Anthropic, which contains this nugget:

Our compute advantage sets us up to deliver continuous leaps in capability. Customers already feel it in real product terms: higher token limits, lower latency, and more reliable execution of complex workflows. Every step forward in compute lets us train stronger models, serve more demand, and lower the cost per unit of intelligence. That is durable business leverage.

I understand why OpenAI would want their massive investment in compute capacity to constitute “durable business leverage”, but it’s far from clear that it actually does. The Stargate datacenter that Oracle was building for OpenAI in Texas is dead, and according to this toot by Mark Newton, the UK datacenter is even worse off:

Nscale is the Australian company that can’t build an OpenAI datacenter in England because it didn’t apply for planning approval.

… And doesn’t own the land it earmarked.

… And can’t buy it because it’s currently in productive use as a scaffolding yard.

… And because they don’t have any money; because the $2 billion they raised on a $14 billion valuation is denominated in IOUs for Nvidia GPUs.

… And because they don’t know how to build datacenters because they’ve never done it before, not even once, not ever.

But apparently they’ve suffered a “blow to their ambitions,” according to the AFR.

… Which is too stupid and uninformed to even mention any of the other stuff.

Nick Clegg is on their board, and Kier Starmer’s govt has given them heaps of favorable treatment because they’re the biggest thing happening in the British AI scene. Which is quite funny when you think about what the next six months will look like.

https://www.afr.com/technology/openai-pauses-stargate-uk-data-centre-citing-energy-costs-20260410-p5zmq8 @davidgerard

Other datacenter builds might also be in trouble, as according to the Wall Street Journal, We’re Using So Much AI That Computing Firepower Is Running Out. I don’t have access to the WSJ, so I am once again relying on the excerpt from Charles Arthur’s invaluable The Overspill:

Token use in OpenAI’s API—a platform where mostly enterprise users access its software—rose from six billion a minute in October to 15 billion a minute in late March.

In my evaluation quoted at the top of this post, I had assumed that the bottleneck would be that deployed hardware would become obsolete faster than it would depreciate. However, it looks like the choke point may come far sooner, when not even OpenAI can get hold of enough compute to run its models on.

🖼️  Photos by Colin Watts on Unsplash