Less about Models; More about Architecture

**SPEAKER_1** (0:02)
Welcome to the Practical AI Podcast, where we break down the real world applications of artificial intelligence and how it's shaping the way we live, work and create. Our goal is to help make AI technology practical, productive and accessible to everyone. Whether you're a developer, business leader, or just curious about the tech behind the buzz, you're in the right place.
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**Daniel Whitenack** (0:41)
Welcome to another episode of the Practical AI podcast. This is Daniel Whitenack. I am CEO at Prediction Guard, and I'm joined as always by my co-host, Chris Benson, who is a principal AI and autonomy research engineer at Lockheed Martin. How you doing, Chris?

**Chris Benson** (0:57)
Doing great today, Daniel. Looking forward to a conversation here.

**Daniel Whitenack** (1:01)
Yeah. Excited to chat about all sorts of things, both in terms of background and current work with Chetan Gupta today, who is chief AI officer at Rackspace. Well, welcome Chetan. How are you doing?

**Chetan Gupta** (1:15)
Hey, I'm doing good. Thanks, Daniel and Chris, for having me. Quite excited about the conversation.
Yeah.

**Daniel Whitenack** (1:22)
Well, like I say, we had bonded even yesterday when we are chatting about our backgrounds in physics and mathematics. I know you started out in mathematics and spent a bunch of time at Hitachi. Do you want to give us just an idea of a little bit of your background and what you've been involved with over the years?

**Chetan Gupta** (1:43)
Sure. Sure, Daniel. So my background is actually quite diverse. It's atypical of people in my role. I started off with a PhD in mathematics, then I joined Hewlett Packard Labs as a research scientist, working on data mining, machine learning. Then I joined Hitachi as a principal researcher, if I remember correctly. Then through the management ladder, when I left Hitachi in 2026, I was leading all of AI research at Hitachi globally. It was a very strong team, and that's what I did. We were focused a lot.
We started with focus on industrial AI, as we defined it at that time.
As the industry matured, we started looking at a broader spectrum of things, and that's what I was doing. Then I joined Rackspace, and I've been here four months, so it's been a very fascinating journey. In some sense, prior to this podcast, I was thinking about my career. I quickly don't think about these things. I realized that I have a few... In some sense, I have followed the trajectory of the whole community at a broad level.
If you remember, guys, we were all doing machine learning, making small models, solving specific problems, and there was a community in Bay Area that was focused primarily on set accommodation systems. As Chris, you would know in companies like Lockheed Martin or Hitachi, the focus is on industrial problems. That's what I was doing for the first half of my career, and then more than the half. Then obviously, deep learning became important. We started looking at vision models, language models that had been blossomed into large language models. In some sense, a lot of the traditional machine learning problems today are much more solvable with automated tools, with wipe coding and so on and so forth. The new challenge now is, yes, you can do all this in machine learning, in AI, but how do you make it accessible to more people? How do you make it actionable? How do you make it much more safe? That's where Rackspace comes in. In some sense, if you look at the trajectory of problems, that's how I have traveled in some sense, like looking for trouble, so to speak.

**Daniel Whitenack** (4:01)
I love that.

**Chris Benson** (4:04)
I want to go back for a second. I'm going to drag you back as you went through your timeline for a second because as you were talking about coming up through the ranks, the managerial ranks at Hitachi, and you look at with the AI world exploding in terms of volume and importance and budgets and all that stuff. So many times organizations will go to an outside expert and bring them in to fill a particular key position and stuff, and yet you came through the ranks at Hitachi. And I'm wondering if you have any thoughts about like what, what, you know, because there are other people out there that are watching this and listening to this right now, that are in their careers and they are aspiring to move up through the ranks themselves. And what were some of the things that you brought to bear that made you able to kind of move up through that and take on the leadership role at Hitachi before you were able to come over to Rackspace?