E057 - AI or Not - Nithin Mohan and Pamela Isom

Welcome to "AI or Not," the podcast where we explore the intersection of digital transformation and real-world wisdom, hosted by the accomplished Pamela Isom. With over 25 years of experience guiding leaders in corporate, public, and private sectors, Pamela, the CEO and Founder of IsAdvice & Consulting LLC, is a veteran in successfully navigating the complex realms of artificial intelligence, innovation, cyber issues, governance, data management, and ethical decision-making.

AI is accelerating so fast that it’s starting to feel less like a normal tech wave and more like a societal gear shift, and that speed has consequences. I sit down with Nithin Mohan, an AI and supercomputing leader, to unpack what it really takes to build products for massive HPC systems, lead teams of deep technical experts, and stay grounded while generative AI transforms how work gets done.

We start with Nithin’s journey from joining an early-stage startup to helping scale enterprise innovation, then move into leadership tactics that actually work with highly skilled engineers and researchers: hiring for aptitude, empowering real autonomy, and shaping work so people can hit a true flow state. From there, we widen the lens to the inflection point where artificial intelligence, high-performance computing, and energy intersect. AI needs infrastructure, and infrastructure runs on energy, so energy efficiency and grid readiness become part of every serious AI strategy.

We also explore the upside: faster drug discovery, better climate modeling, and a future where AI plus supercomputing could compress research timelines in ways that change public health and the economy. Along the way, we call out two essentials that often get missed in the hype cycle: curated data and strong data governance, and a serious commitment to AI ethics and policy that keeps pace with technical progress.

If you care about AI leadership, supercomputing, responsible AI, and the future of work, this conversation is for you. 

Transcript

[00:00] Pamela Isom: This podcast is for informational purposes only.

[00:26] Personal views and opinions expressed by our podcast guests are their own and not legal advice,

[00:34] neither health, tax, nor professional nor official statements by their organizations.

[00:42] Guest views may not be those of the host.

[00:50] Hello and welcome to AI or not, the Podcast, where business leaders from around the globe share wisdom and insights that are needed right now, now to address issues and guide success in your artificial intelligence and your digital transformation journey.

[01:05] I am Pamela Isom and I am your podcast host.

[01:10] So we have a wonderful guest with us today, Nithin Mohan.

[01:14] He's an AI and supercomputing leader.

[01:18] We know each other from just many different ways and so it's a little too long to go into. So I would just say he is a wonderful person and I'm so honored to have him on the show.

[01:30] So, Nithin,

[01:31] welcome to AI Or Not.

[01:34] Nithin Mohan: Thank you, Pamela. Thanks for having me here. It's an honor. It's a privilege. I look forward to our conversation.

[01:42] Pamela Isom: Awesome. So let's have you start by telling me more about yourself. And as you're talking about yourself, tell me more about your career journey.

[01:52] Nithin Mohan: Certainly.

[01:53] So I came to the United States in 2010 for my graduate school.

[01:59] Soon after my graduate school, I started my career at a startup in Boulder.

[02:04] I joined pre revenue very early on as one of the early engineers and was part of the transformation journey.

[02:11] Take the startup from very low valuation to almost a billion dollars in valuation with a successful acquisition by NetApp over a span of four years.

[02:21] And over that time we grew from about when I joined about 30 people to find it people. So that was quite a enthralling ride, I would say, and something that taught me a lot.

[02:34] And it was great that it was a success. Right? And then I eventually transitioned into the enterprise side of things with NetApp. I stayed on with NetApp for a few years and then for the past three and a half years I've been working at HP,

[02:47] where again, I joined right at the inflection point of Genai and exascale supercomputing.

[02:53] It was my privilege to lead a team and build a team from the. From almost from scratch to build products that would go on to be deployed on some of the largest supercomputers in the world and make those supercomputers run efficiently.

[03:09] So that's been my journey in a nutshell. And always, each day is new, always learning, especially with how AI is evolving. It feels like drinking from a fire hose.

[03:21] Pamela Isom: So before I get to my next question, just kind of piggybacking off of that. So is startup being a part of a startup startup, has that, has that helped you?

[03:31] Nithin Mohan: Certainly, absolutely. I,

[03:34] I would say I was fortunate. I did have an opportunity to join a bigger company and coming out of college, right, I thought I'm young, why not just take a,

[03:46] take a swing at it?

[03:47] And I think my risk appetite was high. So joined an almost an unknown startup, right? And I would say yes,

[03:54] because in a startup one gets wear many hats, right? There are many challenges. The rate of challenges is much more than what would be typically encountered in a bigger company.

[04:05] So I got to learn a lot and I got to develop a lot of my leadership muscles at the startup,

[04:12] develop resilience through challenging circumstances, through chaos. Right.

[04:18] And also got to build a deep network which I can still count on and the network continues to do well. So they say then your network is your net worth.

[04:30] So I can certainly say it's true.

[04:32] So yeah, it's been quite transformative to start with a successful startup venture.

[04:37] Pamela Isom: I am a small business owner, so I feel like a startup every day.

[04:43] You do, you wear many hats and there's always new challenges and so I'm never bored, so I get it. And then you have to work on that risk appetite. You have to figure out like what risks are you willing to undertake and quantify those risks and how do you want to go about mitigating risks.

[05:00] So I, I can relate to what you're saying.

[05:03] So you've worked in some incredible, you've worked in some complex environments. You've worked with skilled engineers, researchers in AI and HPC as well, working with the supercomputers and the like.

[05:19] So that's not something as a leader that everyone can do well.

[05:23] So I want to ask you about your leadership characteristics. You started to kind of touch on it. But tell me, when you're leading teams made up of deep technical experts, what have you learned about the kind of leadership style and practices that work in that environment?

[05:42] Nithin Mohan: Certainly that's a great question, Pamela,

[05:45] especially very important when working with high top talent.

[05:51] So I would say I'm very by default, I'm very inclined towards service leadership style and empowering people with agency.

[06:00] And I have built those muscles by watching leaders who have grown under at the startup I was telling you about.

[06:09] So I think that really helped frame my mental model to a first hire the right people because I try to place a lot of rigor during the hiring process to make sure we hire for the right aptitude.

[06:23] And once aptitude is there, the skills, you know, usually follow because people with aptitude like to gravitate towards tough situations, tough problems, and that's how they pick up the skills.

[06:38] Starting with aptitude as a foundation is primarily important. And then once I do that, I try to give those people a lot of autonomy, agency and,

[06:48] and set them up for success by giving them problems. That gets them into a flow state. So it's important that the problems are not too daunting for their skill level.

[07:00] Right. Relative to experience of the people I'm managing.

[07:05] So I try to create a situation,

[07:08] they're vibing, they're flowing. Right.

[07:11] That is usually the right recipe and formula. It seems to have worked well so far.

[07:16] Pamela Isom: That's awesome.

[07:18] It's not easy managing and governing those that are super smart and those that have brilliance. Right. It's not easy. It is easy, but it's not.

[07:29] So you have to balance that. So I like how you said impart people with agency and autonomy hire for the right aptitude.

[07:40] I like that you clarified that. It is a exciting time and we should embrace this opportunity as leaders.

[07:52] But I know that it is also an opportunity for us to cultivate our own leadership skills.

[08:00] So thank you for that feedback and insight and then speaking on those lines. So you and I have talked about this inflection point between AI, supercomputing and energy,

[08:15] and I'd like you to elaborate more on your perspectives of that inflection point and where you see that taking us.

[08:24] Nithin Mohan: Exactly.

[08:25] I would put it as just very fortunate time to be alive because of the enormous upside. Yes, there are risks,

[08:33] but the upside is enormous.

[08:36] And what's interesting about this inflection point is this is not decadal. This is possibly millennial or, you know, once in a century event along the lines of the Industrial Revolution.

[08:47] Right. And what's interesting is relative to the previous industrial scale transformations,

[08:55] this one gives us very little time to adapt our skills.

[09:01] So I think that's the most interesting challenge. Humanity has gone through such waves before.

[09:06] Interesting angle here is it's happening so fast. ChatGPT came onto the scene a little over three years back and within three years we have seen the disruption in white collar workforce.

[09:18] So the rate of change makes it a unique challenge that we have not faced before.

[09:24] So it's going to be interesting. I think it will definitely create a lot of opportunities,

[09:29] a possibility.

[09:31] Many small business owners can be empowered to solve challenges because of what AI enables. Yeah. So looking at just the advanced possibility of advancement in medicine,

[09:45] in manufacturing technology and climate change modeling,

[09:49] I think we can solve many problems within the span of the next decade to two decades. Think cancer, think possibly through material science,

[09:59] slowing climate change.

[10:00] Yeah, the possibilities are truly endless.

[10:03] AI needs energy. AI needs infrastructure which runs on energy.

[10:08] So I think technologically,

[10:10] because I am a techie, right, Technologically,

[10:15] just the possibilities of the work available for the next few years seem very interesting and appealing at the same time for humanity at large.

[10:25] It's a very transformative, yet disruptive inflection point that makes me deeply reflect on how we can adapt to take the upside while dealing with the disruption.

[10:37] Pamela Isom: I spent some time reflecting on this as well.

[10:43] But I mean,

[10:45] if you think about energy and AI is actually everything is dependent on energy, right? So everything that we do is dependent on energy.

[10:58] And so we've got to figure out ways to use AI to not just consume energy,

[11:03] but to help to generate more.

[11:06] And so when I think about it from an inflection, when I reflect back in it just from an inflection point,

[11:13] I think more people should have an opportunity to use supercomputers, for instance. And I know you've mentioned that to me before,

[11:20] there should be more opportunities, there should be more of them.

[11:24] There should be supercomputers that are paving the way to accelerate energy generation and energy, energy distribution.

[11:36] That's an area that we need more help.

[11:41] And then there's also the risk because today the AI is quite the consumer of energy,

[11:49] but we ought to be able to take that capability and use it to generate energy.

[11:55] Right? And so that's kind of what I think about. And so when I think about inflection points, for me that's where I'm coming from. But I think that your perspectives, and I know you agree with me because we've talked about it, but I think that the other perspectives that you mentioned,

[12:10] like, be it's a disruptive time,

[12:13] but in a good way. Right, that's what I heard you say.

[12:16] And I heard you mention the fast pace. Because when you think of AI, supercomputers,

[12:22] hpc,

[12:24] when you think about today, that's what you think, you think speed, just everything is fast paced. So we gotta be able to adapt and be prepared to make changes quickly and accept changes quickly and move on like quickly.

[12:38] Right? So we humans have this, like this mindset that we now have to cultivate because we've got to embrace the change. We can't just sit back and say, well, this is not something I'm going to leverage because that's not an option.

[12:52] And then, so you mentioned disruption in the, in the workforce and then the fast pace. But you also said that the work is interesting,

[13:03] so that that's good. Right. So that is, that's a wonderful set of characteristics that we. That is an inflection point. Right.

[13:11] So it is interesting work and there's no way that we should be bored with our work today.

[13:17] And I think those are really good points. So then if I look ahead, let's say five to ten years from now,

[13:24] what types of problems do you think AI combined with HPC will finally make traction in?

[13:33] Right. Maybe areas that were too complex to solve, but now we've got this advanced capability or do we not have it? Right. So tell me your perspectives there.

[13:44] Nithin Mohan: Sure.

[13:45] So I did a quick backtest using Claude recently to ask it a question on if we had the AI and supercomputing capabilities we have today at the time of COVID which is almost six years back now,

[14:01] how soon could we have found a vaccine here and rolled it out?

[14:06] So it took 11 months from genome sequencing to rolling it out six years back with today's technological capabilities,

[14:15] perhaps taken four months was the answer from Claude. Right. And I tried to make sure it's not hallucinating, so went back and forth and it was still in the four to five month ballpark,

[14:26] which is already significant. Right. Because it means the economic disruption during COVID was severe. Right.

[14:34] So what that implies is, I'm just using that as a hindsight experiment to reflect on. Wow.

[14:42] Already we have leaped so far in terms of AI and compute capabilities and at the rate of where we're going now, if we were to extrapolate that five years, 10 years out,

[14:58] I think what this inflection point enables is much rapid drug discovery which was just unimaginable a few years back. So just unlocking parallel streams of discovery which previously was limited by the human factor.

[15:15] Now if we can think of AI to which many experts are predicting will have AI capability in perhaps two to three years,

[15:25] developing research and pushing the frontiers of discovery at the level of top PhD research scientists,

[15:33] that means we, we have unlocked the, what, human limiting factor.

[15:38] Right. So,

[15:40] and that means possibly definitely a cure to cancer, definitely a cure to many diseases we cannot cure right now.

[15:52] Climate modeling is an area which, with capabilities that we can imagine in three, five, ten years,

[16:00] I'm optimistic that we can start first mitigating some of the climate damage and then reversing it perhaps,

[16:08] which again,

[16:10] that needs energy. Right. And I think with energy, small modular reactors unlocking energy efficiency in 10 years,

[16:18] very reasonable prediction is that the cost of energy will drop significantly because of the Proliferation of nuclear fusion. And nuclear fusion is safe because of small modular reactors.

[16:30] So if that thesis plays off,

[16:33] then converting saltwater to ocean water to fresh water becomes very economically feasible.

[16:42] Producing materials economically in a sustainable way becomes feasible. It creates abundance. I think it should create, generally uplift the standard of living in the developing nations as well.

[16:54] So I see perhaps a Goldilocks scenario in 10 years where there is abundance,

[17:01] and this because of that, the standard of living goes up. So I think scarcity for fresh water, scarcity for housing,

[17:09] scarcity for food.

[17:11] I think,

[17:13] well, humanity as a whole, not just in the developed countries, as a whole, across the globe, would have raised up the Maslow's hierarchy of needs.

[17:22] And that will unlock more art, perhaps, right? The great renaissance is how I put it, because it unlocks. It frees humans to be more humans.

[17:31] And I think the humanities will become important again as skills will trade.

[17:36] Who can write a great poem, who can tell a great story?

[17:41] I feel,

[17:42] you know, because technically, AI will be much more advanced and capable than any one of us could be.

[17:48] So I see a return to humanities, maybe more Michelangelo's, you know, sculpting great marvels. Imagine 8 billion people free to creatively think.

[17:59] I think creates endless possibilities. So, yeah, that's my perspective. I'm purely looking at it as an optimist.

[18:06] Pamela Isom: So the future from your perspective is very bright.

[18:10] And it was interesting that you are saying that humanity is at the forefront because the worry from many is that AI will take over.

[18:19] But that's not what you said.

[18:21] You said humanity would be at the forefront and humanity would maintain agency and even more agency. Did I hear that correct?

[18:30] Nithin Mohan: Absolutely.

[18:31] Pamela Isom: That's interesting to hear you say that because that's totally different than what some, some folks are saying.

[18:37] Let's go 10 years back to your younger self. What would you tell your younger self?

[18:43] Nithin Mohan: I would say don't wait for opportunities and keep going for it. I did go for it, but if I were to go back and dial back the time, I would say just keep taking more risks.

[18:56] Because when you shoot for the moon, right, the possibilities are the. The downside is still an upside.

[19:05] Pamela Isom: Do you think that your younger self would have embraced AI or been afraid of it?

[19:13] Nithin Mohan: I think my younger self would have definitely embraced AI because I've always had a creative bent and almost dreamt of a day like we live in today, where a lot of grunt work goes away, right?

[19:27] Typing emails and all those things. I mean,

[19:31] AI unlock makes everyone a CEO, right? I tell the story to my team.

[19:35] They sometimes get hesitant about over relying on your AI.

[19:40] And I tell this to them.

[19:42] So that's why I tell them to lead with their curiosity and creativity and still use AI to make the voice their own and not just delegate everything to AI. So I think that that has resonated concept has resonated with many people who have been hesitant to use AI, which is think of it like force multiplier capability,

[20:03] which is the equivalent of aviation for the mind.

[20:07] It just lets it fly.

[20:09] Pamela Isom: And your younger self, when you were talking about how you coach your teams today,

[20:15] is that what you say to them? Is that something you would say to your younger self?

[20:20] Nithin Mohan: Absolutely.

[20:22] And to think of it, Pamela, Right. I would have loved to have this ability back for my younger self.

[20:30] I think I would have been able to go places more faster with Glacier. Yeah.

[20:37] Pamela Isom: Awesome.

[20:38] All right, so this has been a wonderful conversation. First of all, before I ask you for your call to action,

[20:44] you can share words of wisdom,

[20:46] a call to action,

[20:48] or just insights that you want us to know about.

[20:52] So think about that. But before you go there, is there anything else you would like to communicate on this call? And while you're thinking about that, the thing that comes to my mind is when we talk about AI supercomputers, we've had a really good conversation.

[21:06] HPCs and energy, mixing energy in the mix. But we didn't get to data today. We may have to do that another time. But I will say that it is still important to make sure that our data is curated properly.

[21:21] And as a part of that leadership that we're doing, even though we focus on the people leadership,

[21:28] part of people leadership is ensuring that our data is curated properly and managed and governed properly.

[21:36] So I wanted to say that because I have decided to always remember, as I am sharing and listening to my guests,

[21:45] to always remind us too, for the listeners that data is so important and data is the details behind the AI. So I'm just going to reiterate that while I give you an opportunity to think about,

[21:59] is there anything that you wanted to share today before you share your last point?

[22:05] Nithin Mohan: So, first of all, I would say this was very reflective. So thanks for inviting me, Pamela, and I'll go back to the inflection point. Right.

[22:14] Every inflection point in the past has created opportunities through disruption. I think this one will be no different.

[22:22] So to anyone watching the podcast, right, I would say,

[22:27] look it, it behooves us to look at the opportunities, look at the upside,

[22:31] and that would be my $0.02, my sharing of some wisdom to our audience.

[22:38] And yeah, I would say I would just put it at that.

[22:41] Pamela Isom: Now is the time for you to share either words of wisdom and any more words of wisdom or a call to action or anything else that you want to share at this point in time as we wrap up this episode.

[22:52] Nithin Mohan: So, as a call to action, I would say it's important for all of us to have the right dialogue around the ethical and policy implications of AI this time. I don't think the risks are just so enormous.

[23:10] We cannot let policy and dialogue and ethical implication trail the technological advancement. So I think that would be my call to action of everyone at the forefront of developing this technology and using this technology to think for our future generations,

[23:28] and not just the short, short term.

[23:31] So that. That would be my call to action.

[23:34] Pamela Isom: That is awesome. Well, I appreciate that. I appreciate the lean in to the ethical considerations which can get overshadowed when we get so caught up in the excitement about the possibilities of innovation until.

[23:49] But that excitement is only as good as the ethical and the ethical policies and the ethical groundwork that goes into it. Right? It's only as good as the ethics.

[24:01] So that is what you are saying, and I hear you loud and clear, and I'm glad you conveyed that message.

[24:08] All right. So I want to say thank you for being here. This has been a wonderful episode.

[24:13] You are so calm.

[24:16] You're so calm and methodical and I love that. So I'm so, so glad you were able to be here today and just share that leadership trait, which is what we need today.

[24:29] Right. That's why I invited you to be here, because that came across and that leadership trait and style is very needed as well. So thank you for being here. Thank you for your humbleness and I really do appreciate, appreciate it.