Ryan Mallory

speaker

175 appearances 1 recordings 1 series first heard Feb 2026 last heard 10 Feb

Ryan Mallory’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 Feb 2026 with 1.

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Data Center Richness · The State of Enterprise Data Centers in 2026 · 10 Feb 2026 podcast

And what does the data look like coming out of that?

And it's important not to forget that it's a CPU-GPU mix.

And all that data is going to come back into that multi-tenant model that's latency sensitive.

And it also needs to be stored somewhere so that enterprise can interact with it.

So it's making sure you're able to discuss the right tiered architecture with them because they want to embrace AI, but they have to understand how the use case is going to deliver the right impact back into their business, whether it's with efficiencies around, you know, process flows or cost reduction or, you know, some other mechanism that they need to achieve.

And so it's definitely key out there.

And, you know, we're happy to be kind of at the center of that right now.

Well, I think that they feel the need to engage just like they did in 2015, 2016, when all the CIOs were going, hey, we're going cloud first, everything.

And so you have, you know, you have companies that are like, hey, we need AI everything.

And it's like, OK, let's slow down and make sure that we start with, you know, making sure the data is secure and you understand how that model will be trained and then where your data resides.

And so it's no different than

when you need to upload your infrastructure or your data into a public cloud type model.

It's the same thing with AI.

You just have to know and understand, hey, what are the parameters of what and how your data will be interacted with, how it will be trained, then where will it be stored?

And then how do you interact with that post small language model creation interaction?

And so the exact similarities to the public cloud

But they're also, I think, a little bit more forward leaning right now because they've seen this build and this rush, but they're also seeing the real world applications where I don't know that a lot of people understood that the public cloud concept took a couple of years to embrace.

We're definitely in the throes of AI right now, and we see the enterprise leaning in pretty heavy to say, hey, how do I participate and get efficiencies out of using this model?

We see it across a couple of parameters inside the enterprise.

We see it most predominantly with enterprise organizations go to market business because they're able to use some of the tools to help with predictive analytics, selling models, call centers, those types of things.

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