Rafael Francis

speaker

248 appearances 1 recordings 1 series first heard Jul 2026 last heard 31 Jul

Rafael Francis’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.

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Heavy Networking · HN836: Optimize AI Traffic on the WAN with Ciena’s Integrated IP Networking (Sponsored) · 31 Jul 2026 podcast

And that's where the consumption of these models comes into play from enterprises and consumers.

And that's what AI inference is all about, right?

How do we now interact with these models to...

to gain insights and predictions and answers for things.

And obviously that inference for the end users, consumers, enterprises, has to traverse metro and last mile networks to reach those end users.

And that's where the service providers become a big part of that value chain.

And so that's where things are now focused.

Now, in terms of how AI inference is different,

Certainly, you know, compared to just traditional broadband networks, enterprise, residential, et cetera, consumers, certainly bandwidth is going to be increased, right?

You know, especially with multimodal AI, you know, more video-rich AI and imaging.

That's one way it's going to change.

And a lot of that is, some of that is also more upstream, right?

So now I'm providing a lot of context, which could also be multimodal.

And so where traditional networks were very downstream oriented, I need some more upstream capacity perhaps now too, right?

Latency is important, obviously, with inference.

And network latency can matter more than compute latency, right?

It's about that time to first token.

et cetera.

So latency is going to, we'll talk more about that and some of the tools and things that we have for latency and also always on, right?

So now with agentic AI, it's not just, you know, it's going to be 24 seven.

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