AE Natarajan

You still have to do certain things in the factory to build from raw materials to goods.

So you have the data coming in and you have models to train.

You have to do all of that stuff that goes into the center of the factory and generations of it.

And then you have to also scale it up so that the edge becomes intelligent.

The edge architectures become intelligent.

so that the end product gets delivered in a very quick fashion to the end user.

So the consumers, when they look at it, when they're consuming AI, which is where the biggest thing is, the user experience really matters.

So you want the edge to be there with the capabilities to deliver the lowest latency, predictable response times for anything and everything that you do.

And that is important, as well as the rest of it in the core for building it and doing it is also important.

You cannot move everything to the edge

When you look at it as a service provider and you look at these products and solutions,

There are multiple aspects of this AI.

First and foremost is the products and the solutions and the architecture that you build is most efficient in handling inter-GPU communications of the data center interconnects so that the GPUs can work really, really efficiently.

Second, on the edge, your architecture is defined in such a way that the consumers have a user experience that is really good and have an excellent experience.

Last but not the least, it is constantly growing.

You're going to get the next generation of GPUs and the next generation of applications and the next generation of agentic AI.

that is going to impose more and more demands and throughputs of it?

Can you build a system that can seamlessly migrate from one step to another and provide you that longevity?

Good.

We actually announced those products that today, which are 800 gig, can easily move over to 1.60 and above.