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I spoke with Lee Caswell, SVP of Product and Solutions Marketing at Nutanix, about how AI can enable new levels of application portability in a distributed computing environment.
Below are some of the key quotes from the interview:
Scroll down for a video and a podcast version of the interview.
On Large Language Models and the Cloud:
“What we’re finding is there’s actually relatively few companies that can afford to build what we call large language models. Those are naturally suited for the public cloud, right? 180 billion parameters for example, and hordes of data scientists.
“Not every company can afford that, but those large language models are now being made available to enterprises across the world. And now those enterprises want to go and do two things. They want to basically customize them, introduce their own domain expertise so it’s specific to their industry. So that’s a tuning model. They also want to make sure their data is protected and that their data is now a core asset. And so that model all of a sudden looks like, ‘Hey, I’m going to go and customize that data probably in a data center some place.’
“And then finally I want to go and run what we call inferencing. So there’s a training model and then your inferencing is actually running on the model. And so we’re probably going to run that now closer to where the data is being ingested. So it could be a retail store, for example, where you’re using generative AI to manage theft and shrink, or it could be a manufacturing facility where you’d be looking at how you would do maintenance procedures. So we see this as a natural distributed data problem and a real value for a common cloud platform across those different endpoints.”
Nutanix, the Cloud and AI:
“So the way Nutanix works, our cloud platform software aggregates standard servers together, servers you can add GPUs to, those are all qualified today from all of our major hardware partners and then our software then takes artificial intelligence as the next application.
“Turns out the way our software has been used in the past, virtual desktops was a big landing spot. Then people brought in databases and performing databases, then they brought analytics like Splunk for example, and now the latest application is AI. And so by adding GPUs and helping size and configure what your application would look like, we’re helping customers get started saying AI is the next application you’d run on the Nutanix cloud platform.”
The Future is Multi-cloud:
“I think everyone is wrestling with predictability and how to forecast the future. It’s an unpredictable world right now, right? Economic changes all over. You’ve got global geopolitical events and you started thinking about skill shortage as well.
“And so customers are looking for how to apply their scarce skills in new creative areas and stop doing things that are actually less value. And so what I see is, going forward, everyone acknowledges this is going to be a multi-cloud world. You’re going to have resources across different clouds. The on-prem data center is not going away and the edge is growing where 50% of data is forecasted to be at the edge.
“So where does it go? I think what happens is you start thinking, how can I get this portability platform in place and tap into the power of servers? So a server-based architecture gives you the flexibility to have the degrees of freedom. [This allows you to have options] over time without locking you into deciding today.”
Listen to the podcast:
Also available on Apple Podcasts
Watch the video: