Joanne Feeney

Well, they seem to be doing a really excellent job of that.

And what's interesting about what Matt just said is they're going to let customer demand drive how they build out these different capabilities for AI applications, which tells us that there are going to be different models purposed to different types of workloads.

So everybody's thinking, oh, NVIDIA is the market-dominant player right now.

They have massive market share.

And they're treating it like it's one sort of big thing that's homogenous.

And I think what people are going to realize over time is that there are going to be different types of models for different workloads.

And different chips will be useful for developing such different models and for running those models, for doing the inference.

So I think there's a lot of room for different chip players here.

And we should expect more of the in-house chips like what Amazon does in collaboration with Marvell or what Google does in collaboration with Broadcom to continue to rise in prominence, as we've been seeing in the recent news coverage.

Well, no company likes any kind of competition, right?

So I'm sure NVIDIA would just be happier if they didn't exist.

But clearly, look, ASICs are very powerful.

That stands for application-specific integrated circuit, right?

So I believe these kind of XPUs or TPUs are going to be designed and going to be put to use for the type of applications in AI for which they're best designed.

So...

It's clearly the case that NVIDIA is going to lose share over time in the big world of AI compute.

But nobody should be surprised by that.

And the pie is still growing so massively.

They can't meet demand.

They're unlikely to be able to meet demand for some years to come.