In this video interview, Harmail Chatha, senior director of cloud computing operations at Nutanix, talks about sustainability factors and automation capabilities of AI that are shaping IT strategies.
Robots troubleshooting data centers? Systems that self-heal? Artificial intelligence (AI) and machine learning (ML) capabilities are helping IT professionals answer with a yes.
In this video interview with The Forecast, Harmail Chatha, senior director of cloud operations at Nutanix, explains how the recent wave of AI innovation is creating new challenges and opportunities for IT decision makers.
“The wave of AI from an infrastructure perspective is gonna be tremendous,” Chatha said. “It’s going to require a lot more power, more real estate.”
In a previous podcast, Chatcha explained why building data centers is his calling. He helped build and runs a state-of-the-art hyper-dense data center for Nutanix. His role also include IT sustainability initiatives, which are chronicled in Nutanix’s annual ESG Report.
As more businesses adopt new AI and ML technologies, increasingly these capabilities will run on hybrid cloud and hybrid multicloud IT systems, which have become the IT operating model of choice, according to the Enterprise Cloud Index report. Chatha said AI and ML will be used more and more to manage IT operations.
“Data centers consume about 1.5% of global power,” he said. But with the rise of AI and the immense amount of computational power and data needed to train large language models, “that number's probably going to double.”
AI has the potential to help solve its own sustainability challenges by improving software operations in data centers.
“Through AI, we'll be able to self-heal a lot of the problems at the software tier,” he said, rather than having to monitor or fix things when they break.
His team plans to deploy robots in their data centers to troubleshoot problems when they arise.
“That will be based on a lot of AI telling the robot what to do and how to fix it. It’s gonna grow and continue to grow. It will have a huge impact on data, data centers and sustainability.”
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Transcript:
Ken Kaplan: What's your view on AI from a data center mindset?
Harmail Chatha: So AI is going to require a lot of compute, right? It's a heavy algorithm base, which requires a lot of GPUs, high processing computers. So that's going to require a lot more power. It's going to require a lot more real estate, and AI is useful in so many verticals, but ultimately it's going to be useful in the data center as well. Through AI we'll be able to self-heal a lot of the problems at the software tier as well. We're planning to deploy robots in our data centers to do troubleshooting as well, and that's going to be based on a lot of AI in itself to try to tell the robot what to do, how to fix it, and ultimately we want to be able to plug into the robot Prism Central. Anytime a system does have an issue, the robot already knows and goes and tries to address it itself. So AI, obviously, is going to be tremendous, a vertical that's going to grow and continue to grow, and it's going to have a huge impact on data centers and sustainability in itself.
Ken Kaplan: How does it make you feel when you see this wave of AI coming?
Harmail Chatha: So the wave of AI from an infrastructure perspective is going to be tremendous. Right now we're at a chasm where we're doing some AI/ML for small level data sets, but now what we're seeing in the industry, for example, with Chat GPT, that infrastructure is heavy for them to even start the company. They have to deploy so much gear so the systems could learn what to do, how to do, they literally took the entire internet and dumped it into Chat GPT. So the entire internet is run across thousands of data centers. So much power consumption. Data centers consume about 1.5% of global power. And if Chat GPT took the internet into its set and we're building on AI, that number's probably going to double in the future as well.
Editor’s note: Learn more about Nutanix GPT-in-a-Box, a full-stack software-defined AI-ready platform designed to simplify and jump-start your initiatives from edge to core. More details in this blog post The AI-Ready Stack: Nutanix Simplifies Your AI Innovation Learning Curve and in the Nutanix Bible.
Ken Kaplan is Editor in Chief for The Forecast by Nutanix. Find him on X @kenekaplan.
Jason Lopez contributed to this video. He is executive producer of Tech Barometer, the podcast outlet for The Forecast. He’s the founder of Connected Social Media. Previously, he was executive producer at PodTech and a reporter at NPR.
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