Brandon McBee

And there's no question of what is gold and not gold, et cetera.

Compute really isn't, right?

And especially GPU compute.

GPU compute today is not...

And I think that this is well understood by our client base, by our suppliers, by third-party consultants like CineAnalysis.

And it's this idea that an H100 deployed in one cloud doesn't have the same performance of an H100 deployed in another cloud.

And the metrics that people use are things like good put or model flop utilization, MFUs.

And there are these measurements of how much more performant is the exact same GPU, by the way, versus another GPU deployed in another facility.

And so in order for something to be commoditized, it has to be fungible.

Right.

Otherwise, there's just too much murkiness and there isn't like an exact data point in there.

It could be in some part configuration, right?

We build everything to DGX reference spec, which is the most...

outlined by nvidia it's the most performant way to build operate and deliver okay gpus but but the rest of it honestly is just how you operate the the gpus and that is the core weave software stack that is how do you keep these gpus online right like what happens if a gpu fails can you predict if a gpu is about to fail and swap in other infrastructure so that the client doesn't

have downtime on that component and there's there's an immense suite of software solutions that and infrastructure management solutions that we have built to have the best good put to have the best mfus in the industry and that's none of that is is off the shelf right and so

I wouldn't say it comes down to the strict components.

That's kind of like a bare minimum starting point, right?

Like you have to start in DJX reference spec, but where's differentiation come from there?

I mean, that's the core product you're describing right there.

Yes.