Q on a variety of different chips. And once people, once these labs train their models and they're happy with their models, most of the computing is going to go to these inference chips. And therefore, even if Nvidia has a bet there, there's not going to be able to sustain their dominance. Is that what do you think about that? Is that a potential flaw in the armor for Nvidia?
A I think it is a flaw, and I think there is, if anyone's going to sort of attack NVIDIA's dominance, they're going to do it on inference, like you said, and there is sort of a massive effort underway right now to make all inference chips under the sun work well, and so every single company that buys NVIDIA chips and is spending a lot of money on NVIDIA chips is trying really hard to make these other, other chips work, whether it's in-house chips from Google or Amazon or even in OpenAI's case and potentially Anthropik's case. You know, do we make our own inference chip? Um, so I'd have a hard time, you know, believing that none of those chips are going to pan out. But, you know, they might not tackle the bulk of the inference workload even. But then again, even if they do 10% of your inference, maybe you're saving enough money that you think the effort is worth it. And it gives you negotiating leverage with Nvidia. If they know that you have an in-house chip team, you know, Jensen's going to be a little bit worried when negotiating with you when you're playing hardball with him. So I think everyone's going to have to have an inference chip Answer to Nvidia. But when I talk to data center companies about what they're seeing, you know, some data center companies don't really care what chip goes inside of their data center, but they try to get hints from the companies that they're w…
AI assessment note: “I think it is a flaw, and I think there is, if anyone's going”