AI transcript
0:00:10 [MUSIC]
0:00:16 Hello, and welcome to the Nvidia AI podcast. I’m your host, Noah Kravitz.
0:00:21 We’re fortunate on the podcast to host guest after guest with amazing stories to tell about
0:00:26 using AI to achieve scientific breakthroughs and transform industries. But in a time of such
0:00:32 rapidly evolving technology, how do we all ensure that the next generation is equipped to work and
0:00:37 thrive in an AI-powered world? Workforce and economic development have a vital role to play
0:00:43 when it comes to all of society realizing the benefits of AI. Here to discuss why AI education
0:00:48 is so important and how artificial intelligence is impacting workforce training and economic
0:00:52 development is Lewis Stewart. Lewis is head of strategic initiatives for Nvidia’s global
0:00:58 developer ecosystem, a role to which he brings over two decades of experience and expertise in
0:01:03 innovation, entrepreneurship, and economic development. Prior to joining Nvidia, Lewis was
0:01:08 the first chief innovation officer for the city of Sacramento, California, a position that capped
0:01:14 off more than a decade of public service at both the state and city levels. Lewis, thank you so
0:01:19 much for making the time to join us and welcome. Yeah, thanks, Noah. It’s an honor to be here.
0:01:27 So should we start with setting the table, defining one or it might be two related terms.
0:01:33 What does it mean when we talk about workforce and economic development in the context of AI
0:01:40 and this AI era that we’re embarking into? Yeah, so great question. I think the challenge right
0:01:48 now is everything gets conflated. It gets conflated into what is, you hear governments talking about
0:01:56 gen AI, you hear governments talking about AI taking jobs, you hear a whole lot of generalizations,
0:02:07 if you will. And so for what does it mean truly? AI is fueling a lot of change in all ecosystems
0:02:12 right now. And so what that means is disrupting how traditional economic development is thought
0:02:20 of. So how states, countries plan what happens next, how they stay competitive globally with
0:02:28 each other. And workforce, AI and the speed at which it’s causing innovation or disrupting the
0:02:36 world. On the workforce side, it has the potential to create one of the widest disparities out there.
0:02:42 So training and getting folks to understand that it’s imperative for people to jump in
0:02:49 right now and be part of the conversation is huge. And so economic and workforce development is,
0:02:56 I think, at the crux of this next part of the conversation because the innovation and the
0:03:03 research and everything surrounding that is driving change so rapidly. So to back up a step
0:03:08 several years and then maybe we can work our way forward. When you were the Chief Innovation Officer
0:03:14 for City of Sacramento, were you thinking about the same kinds of things, you know,
0:03:18 sort of big picture that you’re thinking about now? Yeah, yeah. So I appreciate that question.
0:03:26 So the answer is yes. Was it truly focused on AI? Absolutely not. Right. But it wasn’t focused on
0:03:31 NVIDIA. No, I just knew NVIDIA was a player in the space, right? And so moving into that role in
0:03:37 the City of Sacramento, I was bringing with me a lot of the knowledge from 10 years at the state
0:03:43 working for two governors being the innovation guy for California and having conversations with
0:03:50 global leaders that were coming to California to talk about innovation. And so working in Sacramento,
0:03:56 what I understood is Sacramento was the capital. So all the legislators were here at least four
0:04:04 days out of the week. Sacramento was trying to move into a place to be an innovation leader
0:04:12 in the state and nationally. And I knew that I had a lot of knowledge behind that. So coming
0:04:20 into that role, the other part that I knew is I knew the city because I grew up here. Okay. And I
0:04:25 knew that there were areas of the city that would never see innovation unless it was brought to
0:04:33 them. Right. So it was important to me to look at how do you help the city shape economic and
0:04:39 workforce development policies, efforts, whatever, that included everybody. So that means if I was
0:04:45 bringing autonomous cars to Sacramento, it was for the legislators, it was for the CHP,
0:04:50 but it was also for the people so that people could understand what technology was coming,
0:04:56 how it would help them, how they needed to be trained differently, whether it be mechanics,
0:05:02 learning how to work on gas engine cars, now needed to understand the computers behind electric
0:05:08 vehicles and autonomous cars. Or just moms and dads needing to understand that they could put
0:05:13 their kids in an autonomous car going from home to school so they can stay at work and continue
0:05:19 to work. And so there were so many nuances in those conversations that working in that role,
0:05:25 I had great aspirations because I understood the innovation coming, but just not the speed at
0:05:30 which things were going to change. And so you left that post and came to NVIDIA. How long ago now?
0:05:36 It’s been four years, a little bit over four years. Okay. And so what’s kind of carried through and
0:05:41 then to sort of jump ahead? Well, you can walk ahead as opposed to jump, if you like, through
0:05:48 the barriers. But what is the role entailed day to day now? And I don’t know, how are you thinking
0:05:53 about these things in the context of, I mean, these have been quite the four years in the AI
0:06:01 world, right? Right, right. Well, so it’s really interesting, though, because coming here to NVIDIA
0:06:07 four years ago, I still spoke the language of government. So everything I started talking
0:06:12 about four years ago was workforce, workforce, workforce. But that at the time was not the
0:06:18 language of NVIDIA. NVIDIA was talking about training and didn’t see the two as synonymous.
0:06:25 Right. So I needed to learn how to figure out the way NVIDIA moved. But the North Star was still,
0:06:31 how do you get underrepresented communities involved in understanding what was coming next?
0:06:37 And so these last four years at NVIDIA has been incredible. We’re at the center of a lot of the
0:06:44 changes that’s happening, which is fantastic. But it’s actually increased my feeling that it was
0:06:52 100% necessary to really pivot hard into workforce development conversations throughout the country,
0:06:59 but really throughout the world. And falling back on my government background to help legislators,
0:07:08 to help state leaders, to help whoever needed to hear that this wave is coming. And working
0:07:14 from fear doesn’t really work. And you need to understand that if you really, truly care about
0:07:19 your citizens, it’s time to actually start working with companies like NVIDIA and others
0:07:25 to train a workforce to get your higher education systems in line and thinking about
0:07:31 what’s happening next so that as our students graduate, they’re employable. They understand
0:07:39 and have had touches in AI. And this isn’t just an engineering or a research challenge. This is
0:07:46 really a true workforce issue. We did an episode a little while back with Georgia Institute of
0:07:52 Technology who had opened a makerspace. And one of the key things about that is that it was open
0:07:57 to undergraduates, not just graduate students and CS. That’s an important step, right? But that still
0:08:03 feels like a big step away from bringing the autonomous cars to all parts of the city to
0:08:09 put it that way, right? So there was a federal call to build federal in the United States,
0:08:14 because we’re talking globally, to build a sustainable workforce. What does that mean and
0:08:19 how does that kind of drive some of the work you’re doing, some of the programs that either
0:08:27 you’re involved with or seeing in the United States? Yeah, so that call for the need for a
0:08:32 sustainable workforce really came out during the pandemic. And you saw all the shortages in the
0:08:41 supply chain. And I’m sitting here at NVIDIA watching change happen even faster because
0:08:47 of the technologies that we’re rolling out across industries. And you’re kind of observing the
0:08:53 landscape. You’re looking at the schools. You’re looking at even my kids, and I’m worried about
0:09:00 them. You’re looking at legislation. You’re looking at all of that because having an understanding
0:09:04 of what it actually takes and what programs actually go into building a workforce,
0:09:11 you see that there was a huge misalignment. So moving into this conversation with NVIDIA
0:09:21 entailed, okay, let’s try to become a trusted advisor and a responsible steward of the technology
0:09:28 when in the eyes of government, right? So help them understand that we’re a piece of the puzzle.
0:09:37 We’re not the solution. But if you want a workforce that can thrive, help your economy,
0:09:43 help your innovation ecosystem, we have stuff that can help, whether that be our deep learning
0:09:51 Institute workshops or our startup ecosystem called inception or just the knowledge that we have
0:09:57 around chip design, right? And so on one side, we do the chip design that’s manufactured something
0:10:02 else. So that’s one part of the workforce that we need to worry about. But then when you go back
0:10:06 to the economic development conversation, there is the workforce that’s generated out of the higher
0:10:12 education system. Some of those higher education systems like HBCUs, you have first time students
0:10:17 that they’re not first time students, first time college students, you know, and their families.
0:10:24 And how are they being taught? How are they learning about all the changes in AI so that
0:10:29 they can be more hireable in the industries around those universities or back at home where
0:10:33 they’re from. That’s not just HBCUs, but that’s that’s been one of my focus areas over the past
0:10:39 four years is trying to reach into the minority serving institution community. And so you have
0:10:44 to look at the workforce that’s being trained. But then you have to look at the Ansley workforce,
0:10:51 which is say you have a large bab that’s being built in a particular state and the union,
0:10:56 and they tell you that there is not a workforce to do the job that they’re trying to do. But
0:11:04 that fab makes our chips. So we actually need to care about that workforce as well,
0:11:09 even though we don’t make the chips ourselves, right? So there’s the stuff that we can touch
0:11:13 directly through our workshops, through our subject matter experts being engaged with the
0:11:18 students and telling them what a day in the life of NVIDIA is like. There’s our industry partners
0:11:22 that can walk alongside us with their training and their subject matter experts. But then there’s
0:11:29 the fabs that we need to be watching as well to make sure that should we need to think about
0:11:33 our supply chain differently, we can make sure that there’s a workforce to support that here in
0:11:38 the States as well. Right, right, of course. I’m speaking with Lewis Stewart. Lewis is head of
0:11:43 strategic initiatives for NVIDIA’s global developer ecosystem. And we’re talking about
0:11:49 workforce and economic development. It’s been kind of a whirlwind couple of years, particularly
0:11:55 with generative AI and capturing the public’s imagination, let alone the resources being
0:12:02 invested. But it’s still early days in terms of kind of the long-term impact of AI on everything.
0:12:08 But in terms of the workforce, when you’re talking about college level, undergraduate level, or that
0:12:17 age of a student or learner, and you’re talking about AI education, is it first time using a chat
0:12:24 bot? Is it industry-specific training for somebody who knows that they want to go into
0:12:29 whatever field it might be? Is it kind of the whole gamut of things? What does that look like?
0:12:34 That’s phenomenal question. So it’s really the whole gamut, right? So our efforts in the U.S.
0:12:40 right now, state by state, we do an economic analysis of the landscape there to understand
0:12:44 what industries are the most prevalent. The top five, top 10 industries that are most prevalent
0:12:48 in that state. We look at the universities to make sure they’re teaching stuff that’s aligned
0:12:53 with our efforts. And then we try to do a statewide initiative. So every state is going to look and
0:12:57 feel a little bit different based on the industries that they have. Is that to jump in for a second?
0:13:04 Is that with all 50 U.S. states or? Well, we hope to get to all 50 states right now.
0:13:09 Yeah, right now we have an agreement with California and the community colleges in
0:13:15 California. So that’s 116 community colleges. We’re currently in active conversations with
0:13:21 five other states, and we figure that we’ll have more coming on over the next couple of years.
0:13:26 Again, just because of the speed at which stuff is happening. But to dive a little bit deeper into
0:13:33 that question, community colleges cannot be the lowest level that you start thinking about
0:13:38 AI training and curriculum and reskilling and upskilling. As we travel the state,
0:13:42 as we get into these conversations, states, and we get into these conversations,
0:13:49 everybody’s asking about K-12. And NVIDIA doesn’t have a K-12 practice per se. So we try to do
0:13:55 partnerships with dual enrollment opportunities where the community colleges reach back into
0:14:00 high schools. We try to work with colleges that have high school to college pipelines
0:14:05 in order to influence that. But for this conversation, if you really talk about workforce,
0:14:12 you have to literally start at kindergarten level, like the folks in Gwinnett County out in Georgia
0:14:20 have where they’ve done K-16 curriculum, getting kindergarteners thinking about AI and ethics and
0:14:24 stuff like that. They’ve opened up a couple high schools. I don’t know if you have the details,
0:14:29 but what are they having kindergarteners think about? So I don’t actually have the details
0:14:33 right now. And I know it’s evolved, but what they presented to us two years ago was phenomenal,
0:14:40 right? Just AI basics, like thinking about associations, thinking about what should AI do,
0:14:48 how do you think about AI? So really, if young kids are already playing with AI on their phones,
0:14:56 yeah, they should actually be thinking about it a little bit deeper. So they’re not just
0:15:00 users of the technology, but they can actually start thinking about and seeing themselves as
0:15:06 creators of the technology and being part of that evolution. So thinking about slightly older
0:15:13 learners, what are some of the things that NVIDIA is offering to students, developers? Obviously,
0:15:18 there’s the whole developer ecosystem. There’s the Deep Learning Institute. What are some of
0:15:21 the educational offerings that training development offerings NVIDIA has?
0:15:27 Yeah. So within NVIDIA, you mentioned that we have the Deep Learning Institute and a lot of the
0:15:35 material in there, it’s self-paced learning. So folks can actually come in and take specific
0:15:41 workshops, either two to eight hour workshops, where they’re actually manipulating GPUs, right? So
0:15:47 while our trainings aren’t promising you a job or training you for a specific job,
0:15:57 they are absolutely teaching you how to effectively and efficiently use the resource that is the GPU.
0:16:01 So if you’re a researcher, you’re learning how to manipulate the GPU to help accelerate your
0:16:08 research. If you’re an enterprise or an industry, it’s helping you figure out how to create solutions
0:16:13 for your enterprise or your business. So you have the self-paced stuff. We have teacher or
0:16:19 instructor-led courses, which are a little bit more in-depth. We have teaching kits that are
0:16:24 available to instructors at universities. So you have to actually be an instructor and the
0:16:32 teaching kits can be taken on their semester-long courses of study that can be taken as they are
0:16:37 or you can download them and use them a la carte so you can incorporate them into your curriculum.
0:16:42 And then we also have the ability for professors to become ambassadors. So then they’re actually
0:16:49 certified by our master instructors to teach workshops, NVIDIA workshops. So those are all
0:16:55 some of the tools and resources that I lean on when I walk into a conversation at a state or
0:17:01 university and say, again, this is a piece of the puzzle because everybody’s not ready to walk
0:17:06 into master’s PhD level learning like our deep learning institute. You have to be technically
0:17:12 super technically proficient. And so we look for opportunities, especially at the university level
0:17:16 where they’re already teaching Python, they’re already teaching Algebra 3, they’re teaching some
0:17:23 of the basics so that you can discover there’s the aptitude already and you can get intro to AI
0:17:27 courses so that people can scale up into what we do. But then we also on the other side are looking
0:17:32 at the researchers, looking at the engineering talent to make sure that they have what they
0:17:38 need so that when they graduate out, they have augmented AI skills to be better employable
0:17:45 than the market. Fantastic. Outside of the tech industry, we talked a little bit about this, but
0:17:52 on the show across the country, look around in the world and AI is transforming all kinds of
0:18:00 industries and things that people do and create. And so if you’re thinking about less technical
0:18:06 industries or somebody who, as you alluded to, isn’t going to go to that master’s PhD level
0:18:17 of education, how do you think about, how do you work with partners thinking about AI education
0:18:24 and workforce development for workers who were doing jobs that aren’t highly technical?
0:18:31 Yeah, absolutely. So more of it, please understand that when we try to walk into these partnerships,
0:18:37 one of the things that we put on the table is having our subject matter experts or other
0:18:42 individuals with the company be accessible in these partnerships. So when you think about
0:18:49 the non-technical side of the house, we try to reach into our marketing team and get some of
0:18:55 our marketing experts to talk to business schools. We try to get our sales team to talk to business
0:19:01 schools and whoever else. Just so, one, you can see that it’s not all super tech focused,
0:19:07 and other job opportunities exist. But that also helps when you start talking about reskilling
0:19:13 and upskilling. So if somebody is making a transition and it could just be a change in
0:19:19 language, right? You may have the transferable skills, but not know how to speak the language
0:19:24 of a tech company, kind of like when I first came in from government, right?
0:19:28 Now you speak both languages, so you got the advantage.
0:19:34 So yeah, and so it’s getting people into those, even just those conversations. And so for us,
0:19:39 sure, we rely heavily, and we lean heavily on the research and engineering side, and that’s
0:19:45 what drives our company. But as part of trying to do good, we need to make sure that people
0:19:52 understand that there’s a spot for everybody in this space, right? And whether you’re going to
0:19:58 start an AI startup, whether you’re trying to change jobs, whatever it is, and let’s figure out
0:20:06 how we can help with that. What’s the feeling out there about how AI is impacting the workforce?
0:20:13 I mean, that’s broad, and I’m not asking you to speak on behalf of anybody, right? But in the
0:20:19 work you’re doing with folks and around the subject, I mean, it’s been, well, I don’t have
0:20:24 to tell you that it’s always a hot subject, but particularly, again, in the past couple of years
0:20:29 with generative AI and everything, it’s been, AI is going to take the jobs. No, AI is going to make
0:20:35 us all actually more productive. No, wait, we’ve invested in AI, but it’s a long haul, so we’re
0:20:40 not sure yet. What’s the feeling of the folks who you’re working with day in, day out?
0:20:44 Yeah, it’s another phenomenal question. You’re just full of phenomenal questions today.
0:20:50 The subject matter. Someone who knows what they’re talking about.
0:20:57 So it’s interesting, because internally and externally, I have that part of the conversation
0:21:01 a lot, because what we hear when we’re on the road is a lot of fear and trepidation, right?
0:21:08 From legislators, there’s a lot of fear about the impact on workforce, but then they’re also
0:21:14 trying to be responsive to this new technology, unlike other technologies that they feel that they
0:21:21 let run loose and didn’t have control of, right? So there is a lot of trying to get folks comfortable,
0:21:28 just even understanding what a GPU is and what’s possible. That’s oftentimes the starting point,
0:21:36 even with high-ranking officials and really level-setting. With the community being honest,
0:21:42 like, yes, there will be displacement, but most of this placement is going to come from people
0:21:49 that actually are using AI versus AI itself as a thinking being that can go just take a job.
0:21:56 And so trying to get folks to understand that all the innate things that are human, creativity,
0:22:02 critical thinking, teamwork, all that stuff is really critical right now when you think about
0:22:10 workforce and AI and what’s next in these next two to five years. And really helping students,
0:22:17 as well as adults and companies, think about this productivity thing. Let’s go back to,
0:22:24 hey, look, right now, human in the loop is the best thing. And how does this augment your skills?
0:22:29 How does this augment productivity? How does this augment versus how does it replace?
0:22:34 And once you can get people listening to what it is that you’re saying, again,
0:22:38 kind of speaking the language that they speak, you can get past some of that.
0:22:46 But understand everybody reads the headlines. So there’s a speed at which technology is changing
0:22:54 things right now. The headlines are intended for a certain purpose. And you have to fight hard to
0:22:58 counter that narrative that’s out there. And part of that is just by telling the truth.
0:23:02 If you can look at the World Economic Forum, you can look at all the reports that come out.
0:23:06 Yeah, there’s going to be displacement. There’s displacement with any big shift in innovation.
0:23:12 But what industry does, what government does to help close those gaps is crucial.
0:23:17 So we were talking about the states and how Alabama wants to be the data center of the South,
0:23:22 and perhaps Mississippi has different ambitions. Is there kind of a wide variety of approaches
0:23:26 states are taking when it comes to these things? Workforce development and thinking about
0:23:35 economic development around data centers and chip fabs and all the other business things,
0:23:40 avenues of business that AI and Accelerate Computing and all this stuff opens up.
0:23:45 What’s it like sort of working with all these different states that must have different points
0:23:51 of view? Yeah, like working from an NVIDIA perspective with these different states
0:23:55 is actually refreshing compared to when I actually used to work for the state.
0:24:04 All the states are uber competitive with each other. Some are more loud about what it is that
0:24:10 they’re doing and what they’re known for versus others. They let everybody else think what they
0:24:17 want to think, but they’re working on stuff that nobody knows about. So what’s been super refreshing
0:24:23 about coming at it from an NVIDIA perspective is yes, every state is different. Every state has
0:24:30 their idea about what they want to do when it comes to AI. At the end of the day, when we walk in,
0:24:36 we’re talking about empowering the workforce, creating job opportunities, collaborative innovation,
0:24:43 inclusive growth. When we speak those words, walking into a government, they tend to open up
0:24:48 and let us know what it is they’re actually working on. So there’s some states, southern states,
0:24:52 that we’ve actually been pleasantly surprised at how far along they are with their AI strategies.
0:24:58 And then there’s other states where we walk in and we’re like, whoa, you guys, whoa.
0:25:09 We need to think differently about how we even talk to you and what you’re actually ready for.
0:25:17 When we successfully signed an MOU with California back in August, and it opened up a bunch of
0:25:22 conversations throughout the other states, which is great. But understanding that signing the MOU
0:25:28 is just the beginning of the conversation. In California, we’ve committed to working alongside
0:25:34 them to try to train 100,000 people over the next three years. That’s going to take all the community
0:25:40 colleges, 116 of those, that’s going to take the Cal State system, that’s going to take the UC system
0:25:47 to get that done. That we have to work with the Cal HR system to help them understand how
0:25:53 these AI skills are incorporated into job roles within the state for their state IT folks.
0:25:58 So there’s a lot that there’s a lot of stuff that has happened in California. But then you go to a
0:26:05 state like Mississippi and they have a platform where literally you actually just go to the
0:26:11 platform and say, here’s what I’m doing. And it already tells you what you qualify for when it
0:26:18 comes to a state workforce. Did we know that walking into Mississippi? Absolutely not. Did we
0:26:23 know that the legislature was 100% bought into the AI strategy? No. So there’s, Mississippi is
0:26:28 one of those states where you’re pleasantly surprised. Yeah, yeah, that’s amazing. But I know
0:26:31 nothing about Mississippi to be clear. They just, I was trying to think of something. No, no, no,
0:26:38 yeah. Near Alabama? Is it, they’re going to take that out. No, no, it’s fine. It’s fine. But what I
0:26:44 told my team was it’s actually not surprising because when I was working for the state of
0:26:50 California, a lot of the federal initiatives, we actually lost to Mississippi. So we lost the drone
0:26:56 competitive opportunity. We lost the cyber competitive opportunity. And there were two
0:27:02 schools in Mississippi. But what we’ve, what I found out is because everybody in the state has
0:27:06 bought in. So as opposed to in California, we have Northern California versus Southern California.
0:27:11 And you got to try to get the two together. And there’s just a lot of work there. Right. Mississippi,
0:27:15 they’re like, yeah, we’re just all one team. Yeah, we’re doing. And yeah, let’s go get it.
0:27:23 It helps. And so now discovering how they work versus what I understood
0:27:31 when I was in the space, it’s actually awesome because it allows us to have a much deeper
0:27:37 conversation where we’re not starting from what is a GPU. We’re like, oh, okay, how do we tap into
0:27:44 what you guys are doing? How’d you guys build that platform? Pretty cool. Yeah. And how do we help
0:27:51 your research get further? How do we, so every state is different. What we like to do is engage
0:27:58 the governor’s office because that kind of gives cover for us. It also gives cover for the higher
0:28:04 education systems to partner with us. And but then, you know, we absolutely look at, you know,
0:28:10 where the opportunities are for alignment with NVIDIA to support sustainable development,
0:28:14 to have real-world impact, and to help develop a future-ready workforce.
0:28:20 Lou’s last question before we wrap up here. For a listener, maybe it’s a student, maybe it’s an
0:28:27 educator or somebody working kind of in the education or local system who hears the message
0:28:32 and wants to get on board, but doesn’t have the resources in front of them, kind of doesn’t know.
0:28:37 The autonomous car hasn’t come to them just yet, but they’re listening, right? So they have you.
0:28:44 What’s your advice to someone in those shoes? Is it just start using the tools? Is it research?
0:28:51 I should stop trying to put answers in your mouth. No, no, no. Like, I am very clear what folks,
0:28:56 when I’m on panels, when I’m doing keynotes, whatever, when I’m talking to my friends,
0:29:02 this is not the time to be shy. And this is the time to jump in. Start understanding when I talk
0:29:08 to small businesses. Start using tools like ChatGPT and see how it actually can transform your
0:29:14 business. If you don’t know how to use it, then partner with the high school and bring in some
0:29:18 high school interns and have them develop it. So then you’re building a workforce that way.
0:29:25 But staying on the sidelines right now is not the best idea. So this is one of those where you say,
0:29:31 come on in, the water’s fine. It’s just really deep, right? Because, you know, so, but it’s time to
0:29:37 explore and get involved in the conversation. Absolutely. Lewis, for listeners who would
0:29:42 like to learn more about some of the work that you’re doing, perhaps, you know, other places in
0:29:46 NVIDIA related to workforce development and economic development and everything else we’re
0:29:53 touching upon, where’s a good place for them to start? Yeah. So I work with the internal team. So
0:29:57 every once in a while, there’s a blog post on the NVIDIA website, but really everybody can find me
0:30:02 on LinkedIn. I try to stay pretty active on there. And if you don’t know the spell my name,
0:30:08 just look up Meet Mr. Stewart and you’ll find me. Fantastic. Lewis, thank you again for making the
0:30:13 time and best of luck on the work you’re doing. It’s kind of, I don’t know, it’s one of the core
0:30:17 reasons I think that we’re all doing all this is to make a better world for everybody. Yeah,
0:30:35 thank you. It’s been a pleasure and hopefully we get to chat again.
0:30:44 So,
0:31:09 , you.
0:31:12 (upbeat music)
0:31:20 [BLANK_AUDIO]
0:00:16 Hello, and welcome to the Nvidia AI podcast. I’m your host, Noah Kravitz.
0:00:21 We’re fortunate on the podcast to host guest after guest with amazing stories to tell about
0:00:26 using AI to achieve scientific breakthroughs and transform industries. But in a time of such
0:00:32 rapidly evolving technology, how do we all ensure that the next generation is equipped to work and
0:00:37 thrive in an AI-powered world? Workforce and economic development have a vital role to play
0:00:43 when it comes to all of society realizing the benefits of AI. Here to discuss why AI education
0:00:48 is so important and how artificial intelligence is impacting workforce training and economic
0:00:52 development is Lewis Stewart. Lewis is head of strategic initiatives for Nvidia’s global
0:00:58 developer ecosystem, a role to which he brings over two decades of experience and expertise in
0:01:03 innovation, entrepreneurship, and economic development. Prior to joining Nvidia, Lewis was
0:01:08 the first chief innovation officer for the city of Sacramento, California, a position that capped
0:01:14 off more than a decade of public service at both the state and city levels. Lewis, thank you so
0:01:19 much for making the time to join us and welcome. Yeah, thanks, Noah. It’s an honor to be here.
0:01:27 So should we start with setting the table, defining one or it might be two related terms.
0:01:33 What does it mean when we talk about workforce and economic development in the context of AI
0:01:40 and this AI era that we’re embarking into? Yeah, so great question. I think the challenge right
0:01:48 now is everything gets conflated. It gets conflated into what is, you hear governments talking about
0:01:56 gen AI, you hear governments talking about AI taking jobs, you hear a whole lot of generalizations,
0:02:07 if you will. And so for what does it mean truly? AI is fueling a lot of change in all ecosystems
0:02:12 right now. And so what that means is disrupting how traditional economic development is thought
0:02:20 of. So how states, countries plan what happens next, how they stay competitive globally with
0:02:28 each other. And workforce, AI and the speed at which it’s causing innovation or disrupting the
0:02:36 world. On the workforce side, it has the potential to create one of the widest disparities out there.
0:02:42 So training and getting folks to understand that it’s imperative for people to jump in
0:02:49 right now and be part of the conversation is huge. And so economic and workforce development is,
0:02:56 I think, at the crux of this next part of the conversation because the innovation and the
0:03:03 research and everything surrounding that is driving change so rapidly. So to back up a step
0:03:08 several years and then maybe we can work our way forward. When you were the Chief Innovation Officer
0:03:14 for City of Sacramento, were you thinking about the same kinds of things, you know,
0:03:18 sort of big picture that you’re thinking about now? Yeah, yeah. So I appreciate that question.
0:03:26 So the answer is yes. Was it truly focused on AI? Absolutely not. Right. But it wasn’t focused on
0:03:31 NVIDIA. No, I just knew NVIDIA was a player in the space, right? And so moving into that role in
0:03:37 the City of Sacramento, I was bringing with me a lot of the knowledge from 10 years at the state
0:03:43 working for two governors being the innovation guy for California and having conversations with
0:03:50 global leaders that were coming to California to talk about innovation. And so working in Sacramento,
0:03:56 what I understood is Sacramento was the capital. So all the legislators were here at least four
0:04:04 days out of the week. Sacramento was trying to move into a place to be an innovation leader
0:04:12 in the state and nationally. And I knew that I had a lot of knowledge behind that. So coming
0:04:20 into that role, the other part that I knew is I knew the city because I grew up here. Okay. And I
0:04:25 knew that there were areas of the city that would never see innovation unless it was brought to
0:04:33 them. Right. So it was important to me to look at how do you help the city shape economic and
0:04:39 workforce development policies, efforts, whatever, that included everybody. So that means if I was
0:04:45 bringing autonomous cars to Sacramento, it was for the legislators, it was for the CHP,
0:04:50 but it was also for the people so that people could understand what technology was coming,
0:04:56 how it would help them, how they needed to be trained differently, whether it be mechanics,
0:05:02 learning how to work on gas engine cars, now needed to understand the computers behind electric
0:05:08 vehicles and autonomous cars. Or just moms and dads needing to understand that they could put
0:05:13 their kids in an autonomous car going from home to school so they can stay at work and continue
0:05:19 to work. And so there were so many nuances in those conversations that working in that role,
0:05:25 I had great aspirations because I understood the innovation coming, but just not the speed at
0:05:30 which things were going to change. And so you left that post and came to NVIDIA. How long ago now?
0:05:36 It’s been four years, a little bit over four years. Okay. And so what’s kind of carried through and
0:05:41 then to sort of jump ahead? Well, you can walk ahead as opposed to jump, if you like, through
0:05:48 the barriers. But what is the role entailed day to day now? And I don’t know, how are you thinking
0:05:53 about these things in the context of, I mean, these have been quite the four years in the AI
0:06:01 world, right? Right, right. Well, so it’s really interesting, though, because coming here to NVIDIA
0:06:07 four years ago, I still spoke the language of government. So everything I started talking
0:06:12 about four years ago was workforce, workforce, workforce. But that at the time was not the
0:06:18 language of NVIDIA. NVIDIA was talking about training and didn’t see the two as synonymous.
0:06:25 Right. So I needed to learn how to figure out the way NVIDIA moved. But the North Star was still,
0:06:31 how do you get underrepresented communities involved in understanding what was coming next?
0:06:37 And so these last four years at NVIDIA has been incredible. We’re at the center of a lot of the
0:06:44 changes that’s happening, which is fantastic. But it’s actually increased my feeling that it was
0:06:52 100% necessary to really pivot hard into workforce development conversations throughout the country,
0:06:59 but really throughout the world. And falling back on my government background to help legislators,
0:07:08 to help state leaders, to help whoever needed to hear that this wave is coming. And working
0:07:14 from fear doesn’t really work. And you need to understand that if you really, truly care about
0:07:19 your citizens, it’s time to actually start working with companies like NVIDIA and others
0:07:25 to train a workforce to get your higher education systems in line and thinking about
0:07:31 what’s happening next so that as our students graduate, they’re employable. They understand
0:07:39 and have had touches in AI. And this isn’t just an engineering or a research challenge. This is
0:07:46 really a true workforce issue. We did an episode a little while back with Georgia Institute of
0:07:52 Technology who had opened a makerspace. And one of the key things about that is that it was open
0:07:57 to undergraduates, not just graduate students and CS. That’s an important step, right? But that still
0:08:03 feels like a big step away from bringing the autonomous cars to all parts of the city to
0:08:09 put it that way, right? So there was a federal call to build federal in the United States,
0:08:14 because we’re talking globally, to build a sustainable workforce. What does that mean and
0:08:19 how does that kind of drive some of the work you’re doing, some of the programs that either
0:08:27 you’re involved with or seeing in the United States? Yeah, so that call for the need for a
0:08:32 sustainable workforce really came out during the pandemic. And you saw all the shortages in the
0:08:41 supply chain. And I’m sitting here at NVIDIA watching change happen even faster because
0:08:47 of the technologies that we’re rolling out across industries. And you’re kind of observing the
0:08:53 landscape. You’re looking at the schools. You’re looking at even my kids, and I’m worried about
0:09:00 them. You’re looking at legislation. You’re looking at all of that because having an understanding
0:09:04 of what it actually takes and what programs actually go into building a workforce,
0:09:11 you see that there was a huge misalignment. So moving into this conversation with NVIDIA
0:09:21 entailed, okay, let’s try to become a trusted advisor and a responsible steward of the technology
0:09:28 when in the eyes of government, right? So help them understand that we’re a piece of the puzzle.
0:09:37 We’re not the solution. But if you want a workforce that can thrive, help your economy,
0:09:43 help your innovation ecosystem, we have stuff that can help, whether that be our deep learning
0:09:51 Institute workshops or our startup ecosystem called inception or just the knowledge that we have
0:09:57 around chip design, right? And so on one side, we do the chip design that’s manufactured something
0:10:02 else. So that’s one part of the workforce that we need to worry about. But then when you go back
0:10:06 to the economic development conversation, there is the workforce that’s generated out of the higher
0:10:12 education system. Some of those higher education systems like HBCUs, you have first time students
0:10:17 that they’re not first time students, first time college students, you know, and their families.
0:10:24 And how are they being taught? How are they learning about all the changes in AI so that
0:10:29 they can be more hireable in the industries around those universities or back at home where
0:10:33 they’re from. That’s not just HBCUs, but that’s that’s been one of my focus areas over the past
0:10:39 four years is trying to reach into the minority serving institution community. And so you have
0:10:44 to look at the workforce that’s being trained. But then you have to look at the Ansley workforce,
0:10:51 which is say you have a large bab that’s being built in a particular state and the union,
0:10:56 and they tell you that there is not a workforce to do the job that they’re trying to do. But
0:11:04 that fab makes our chips. So we actually need to care about that workforce as well,
0:11:09 even though we don’t make the chips ourselves, right? So there’s the stuff that we can touch
0:11:13 directly through our workshops, through our subject matter experts being engaged with the
0:11:18 students and telling them what a day in the life of NVIDIA is like. There’s our industry partners
0:11:22 that can walk alongside us with their training and their subject matter experts. But then there’s
0:11:29 the fabs that we need to be watching as well to make sure that should we need to think about
0:11:33 our supply chain differently, we can make sure that there’s a workforce to support that here in
0:11:38 the States as well. Right, right, of course. I’m speaking with Lewis Stewart. Lewis is head of
0:11:43 strategic initiatives for NVIDIA’s global developer ecosystem. And we’re talking about
0:11:49 workforce and economic development. It’s been kind of a whirlwind couple of years, particularly
0:11:55 with generative AI and capturing the public’s imagination, let alone the resources being
0:12:02 invested. But it’s still early days in terms of kind of the long-term impact of AI on everything.
0:12:08 But in terms of the workforce, when you’re talking about college level, undergraduate level, or that
0:12:17 age of a student or learner, and you’re talking about AI education, is it first time using a chat
0:12:24 bot? Is it industry-specific training for somebody who knows that they want to go into
0:12:29 whatever field it might be? Is it kind of the whole gamut of things? What does that look like?
0:12:34 That’s phenomenal question. So it’s really the whole gamut, right? So our efforts in the U.S.
0:12:40 right now, state by state, we do an economic analysis of the landscape there to understand
0:12:44 what industries are the most prevalent. The top five, top 10 industries that are most prevalent
0:12:48 in that state. We look at the universities to make sure they’re teaching stuff that’s aligned
0:12:53 with our efforts. And then we try to do a statewide initiative. So every state is going to look and
0:12:57 feel a little bit different based on the industries that they have. Is that to jump in for a second?
0:13:04 Is that with all 50 U.S. states or? Well, we hope to get to all 50 states right now.
0:13:09 Yeah, right now we have an agreement with California and the community colleges in
0:13:15 California. So that’s 116 community colleges. We’re currently in active conversations with
0:13:21 five other states, and we figure that we’ll have more coming on over the next couple of years.
0:13:26 Again, just because of the speed at which stuff is happening. But to dive a little bit deeper into
0:13:33 that question, community colleges cannot be the lowest level that you start thinking about
0:13:38 AI training and curriculum and reskilling and upskilling. As we travel the state,
0:13:42 as we get into these conversations, states, and we get into these conversations,
0:13:49 everybody’s asking about K-12. And NVIDIA doesn’t have a K-12 practice per se. So we try to do
0:13:55 partnerships with dual enrollment opportunities where the community colleges reach back into
0:14:00 high schools. We try to work with colleges that have high school to college pipelines
0:14:05 in order to influence that. But for this conversation, if you really talk about workforce,
0:14:12 you have to literally start at kindergarten level, like the folks in Gwinnett County out in Georgia
0:14:20 have where they’ve done K-16 curriculum, getting kindergarteners thinking about AI and ethics and
0:14:24 stuff like that. They’ve opened up a couple high schools. I don’t know if you have the details,
0:14:29 but what are they having kindergarteners think about? So I don’t actually have the details
0:14:33 right now. And I know it’s evolved, but what they presented to us two years ago was phenomenal,
0:14:40 right? Just AI basics, like thinking about associations, thinking about what should AI do,
0:14:48 how do you think about AI? So really, if young kids are already playing with AI on their phones,
0:14:56 yeah, they should actually be thinking about it a little bit deeper. So they’re not just
0:15:00 users of the technology, but they can actually start thinking about and seeing themselves as
0:15:06 creators of the technology and being part of that evolution. So thinking about slightly older
0:15:13 learners, what are some of the things that NVIDIA is offering to students, developers? Obviously,
0:15:18 there’s the whole developer ecosystem. There’s the Deep Learning Institute. What are some of
0:15:21 the educational offerings that training development offerings NVIDIA has?
0:15:27 Yeah. So within NVIDIA, you mentioned that we have the Deep Learning Institute and a lot of the
0:15:35 material in there, it’s self-paced learning. So folks can actually come in and take specific
0:15:41 workshops, either two to eight hour workshops, where they’re actually manipulating GPUs, right? So
0:15:47 while our trainings aren’t promising you a job or training you for a specific job,
0:15:57 they are absolutely teaching you how to effectively and efficiently use the resource that is the GPU.
0:16:01 So if you’re a researcher, you’re learning how to manipulate the GPU to help accelerate your
0:16:08 research. If you’re an enterprise or an industry, it’s helping you figure out how to create solutions
0:16:13 for your enterprise or your business. So you have the self-paced stuff. We have teacher or
0:16:19 instructor-led courses, which are a little bit more in-depth. We have teaching kits that are
0:16:24 available to instructors at universities. So you have to actually be an instructor and the
0:16:32 teaching kits can be taken on their semester-long courses of study that can be taken as they are
0:16:37 or you can download them and use them a la carte so you can incorporate them into your curriculum.
0:16:42 And then we also have the ability for professors to become ambassadors. So then they’re actually
0:16:49 certified by our master instructors to teach workshops, NVIDIA workshops. So those are all
0:16:55 some of the tools and resources that I lean on when I walk into a conversation at a state or
0:17:01 university and say, again, this is a piece of the puzzle because everybody’s not ready to walk
0:17:06 into master’s PhD level learning like our deep learning institute. You have to be technically
0:17:12 super technically proficient. And so we look for opportunities, especially at the university level
0:17:16 where they’re already teaching Python, they’re already teaching Algebra 3, they’re teaching some
0:17:23 of the basics so that you can discover there’s the aptitude already and you can get intro to AI
0:17:27 courses so that people can scale up into what we do. But then we also on the other side are looking
0:17:32 at the researchers, looking at the engineering talent to make sure that they have what they
0:17:38 need so that when they graduate out, they have augmented AI skills to be better employable
0:17:45 than the market. Fantastic. Outside of the tech industry, we talked a little bit about this, but
0:17:52 on the show across the country, look around in the world and AI is transforming all kinds of
0:18:00 industries and things that people do and create. And so if you’re thinking about less technical
0:18:06 industries or somebody who, as you alluded to, isn’t going to go to that master’s PhD level
0:18:17 of education, how do you think about, how do you work with partners thinking about AI education
0:18:24 and workforce development for workers who were doing jobs that aren’t highly technical?
0:18:31 Yeah, absolutely. So more of it, please understand that when we try to walk into these partnerships,
0:18:37 one of the things that we put on the table is having our subject matter experts or other
0:18:42 individuals with the company be accessible in these partnerships. So when you think about
0:18:49 the non-technical side of the house, we try to reach into our marketing team and get some of
0:18:55 our marketing experts to talk to business schools. We try to get our sales team to talk to business
0:19:01 schools and whoever else. Just so, one, you can see that it’s not all super tech focused,
0:19:07 and other job opportunities exist. But that also helps when you start talking about reskilling
0:19:13 and upskilling. So if somebody is making a transition and it could just be a change in
0:19:19 language, right? You may have the transferable skills, but not know how to speak the language
0:19:24 of a tech company, kind of like when I first came in from government, right?
0:19:28 Now you speak both languages, so you got the advantage.
0:19:34 So yeah, and so it’s getting people into those, even just those conversations. And so for us,
0:19:39 sure, we rely heavily, and we lean heavily on the research and engineering side, and that’s
0:19:45 what drives our company. But as part of trying to do good, we need to make sure that people
0:19:52 understand that there’s a spot for everybody in this space, right? And whether you’re going to
0:19:58 start an AI startup, whether you’re trying to change jobs, whatever it is, and let’s figure out
0:20:06 how we can help with that. What’s the feeling out there about how AI is impacting the workforce?
0:20:13 I mean, that’s broad, and I’m not asking you to speak on behalf of anybody, right? But in the
0:20:19 work you’re doing with folks and around the subject, I mean, it’s been, well, I don’t have
0:20:24 to tell you that it’s always a hot subject, but particularly, again, in the past couple of years
0:20:29 with generative AI and everything, it’s been, AI is going to take the jobs. No, AI is going to make
0:20:35 us all actually more productive. No, wait, we’ve invested in AI, but it’s a long haul, so we’re
0:20:40 not sure yet. What’s the feeling of the folks who you’re working with day in, day out?
0:20:44 Yeah, it’s another phenomenal question. You’re just full of phenomenal questions today.
0:20:50 The subject matter. Someone who knows what they’re talking about.
0:20:57 So it’s interesting, because internally and externally, I have that part of the conversation
0:21:01 a lot, because what we hear when we’re on the road is a lot of fear and trepidation, right?
0:21:08 From legislators, there’s a lot of fear about the impact on workforce, but then they’re also
0:21:14 trying to be responsive to this new technology, unlike other technologies that they feel that they
0:21:21 let run loose and didn’t have control of, right? So there is a lot of trying to get folks comfortable,
0:21:28 just even understanding what a GPU is and what’s possible. That’s oftentimes the starting point,
0:21:36 even with high-ranking officials and really level-setting. With the community being honest,
0:21:42 like, yes, there will be displacement, but most of this placement is going to come from people
0:21:49 that actually are using AI versus AI itself as a thinking being that can go just take a job.
0:21:56 And so trying to get folks to understand that all the innate things that are human, creativity,
0:22:02 critical thinking, teamwork, all that stuff is really critical right now when you think about
0:22:10 workforce and AI and what’s next in these next two to five years. And really helping students,
0:22:17 as well as adults and companies, think about this productivity thing. Let’s go back to,
0:22:24 hey, look, right now, human in the loop is the best thing. And how does this augment your skills?
0:22:29 How does this augment productivity? How does this augment versus how does it replace?
0:22:34 And once you can get people listening to what it is that you’re saying, again,
0:22:38 kind of speaking the language that they speak, you can get past some of that.
0:22:46 But understand everybody reads the headlines. So there’s a speed at which technology is changing
0:22:54 things right now. The headlines are intended for a certain purpose. And you have to fight hard to
0:22:58 counter that narrative that’s out there. And part of that is just by telling the truth.
0:23:02 If you can look at the World Economic Forum, you can look at all the reports that come out.
0:23:06 Yeah, there’s going to be displacement. There’s displacement with any big shift in innovation.
0:23:12 But what industry does, what government does to help close those gaps is crucial.
0:23:17 So we were talking about the states and how Alabama wants to be the data center of the South,
0:23:22 and perhaps Mississippi has different ambitions. Is there kind of a wide variety of approaches
0:23:26 states are taking when it comes to these things? Workforce development and thinking about
0:23:35 economic development around data centers and chip fabs and all the other business things,
0:23:40 avenues of business that AI and Accelerate Computing and all this stuff opens up.
0:23:45 What’s it like sort of working with all these different states that must have different points
0:23:51 of view? Yeah, like working from an NVIDIA perspective with these different states
0:23:55 is actually refreshing compared to when I actually used to work for the state.
0:24:04 All the states are uber competitive with each other. Some are more loud about what it is that
0:24:10 they’re doing and what they’re known for versus others. They let everybody else think what they
0:24:17 want to think, but they’re working on stuff that nobody knows about. So what’s been super refreshing
0:24:23 about coming at it from an NVIDIA perspective is yes, every state is different. Every state has
0:24:30 their idea about what they want to do when it comes to AI. At the end of the day, when we walk in,
0:24:36 we’re talking about empowering the workforce, creating job opportunities, collaborative innovation,
0:24:43 inclusive growth. When we speak those words, walking into a government, they tend to open up
0:24:48 and let us know what it is they’re actually working on. So there’s some states, southern states,
0:24:52 that we’ve actually been pleasantly surprised at how far along they are with their AI strategies.
0:24:58 And then there’s other states where we walk in and we’re like, whoa, you guys, whoa.
0:25:09 We need to think differently about how we even talk to you and what you’re actually ready for.
0:25:17 When we successfully signed an MOU with California back in August, and it opened up a bunch of
0:25:22 conversations throughout the other states, which is great. But understanding that signing the MOU
0:25:28 is just the beginning of the conversation. In California, we’ve committed to working alongside
0:25:34 them to try to train 100,000 people over the next three years. That’s going to take all the community
0:25:40 colleges, 116 of those, that’s going to take the Cal State system, that’s going to take the UC system
0:25:47 to get that done. That we have to work with the Cal HR system to help them understand how
0:25:53 these AI skills are incorporated into job roles within the state for their state IT folks.
0:25:58 So there’s a lot that there’s a lot of stuff that has happened in California. But then you go to a
0:26:05 state like Mississippi and they have a platform where literally you actually just go to the
0:26:11 platform and say, here’s what I’m doing. And it already tells you what you qualify for when it
0:26:18 comes to a state workforce. Did we know that walking into Mississippi? Absolutely not. Did we
0:26:23 know that the legislature was 100% bought into the AI strategy? No. So there’s, Mississippi is
0:26:28 one of those states where you’re pleasantly surprised. Yeah, yeah, that’s amazing. But I know
0:26:31 nothing about Mississippi to be clear. They just, I was trying to think of something. No, no, no,
0:26:38 yeah. Near Alabama? Is it, they’re going to take that out. No, no, it’s fine. It’s fine. But what I
0:26:44 told my team was it’s actually not surprising because when I was working for the state of
0:26:50 California, a lot of the federal initiatives, we actually lost to Mississippi. So we lost the drone
0:26:56 competitive opportunity. We lost the cyber competitive opportunity. And there were two
0:27:02 schools in Mississippi. But what we’ve, what I found out is because everybody in the state has
0:27:06 bought in. So as opposed to in California, we have Northern California versus Southern California.
0:27:11 And you got to try to get the two together. And there’s just a lot of work there. Right. Mississippi,
0:27:15 they’re like, yeah, we’re just all one team. Yeah, we’re doing. And yeah, let’s go get it.
0:27:23 It helps. And so now discovering how they work versus what I understood
0:27:31 when I was in the space, it’s actually awesome because it allows us to have a much deeper
0:27:37 conversation where we’re not starting from what is a GPU. We’re like, oh, okay, how do we tap into
0:27:44 what you guys are doing? How’d you guys build that platform? Pretty cool. Yeah. And how do we help
0:27:51 your research get further? How do we, so every state is different. What we like to do is engage
0:27:58 the governor’s office because that kind of gives cover for us. It also gives cover for the higher
0:28:04 education systems to partner with us. And but then, you know, we absolutely look at, you know,
0:28:10 where the opportunities are for alignment with NVIDIA to support sustainable development,
0:28:14 to have real-world impact, and to help develop a future-ready workforce.
0:28:20 Lou’s last question before we wrap up here. For a listener, maybe it’s a student, maybe it’s an
0:28:27 educator or somebody working kind of in the education or local system who hears the message
0:28:32 and wants to get on board, but doesn’t have the resources in front of them, kind of doesn’t know.
0:28:37 The autonomous car hasn’t come to them just yet, but they’re listening, right? So they have you.
0:28:44 What’s your advice to someone in those shoes? Is it just start using the tools? Is it research?
0:28:51 I should stop trying to put answers in your mouth. No, no, no. Like, I am very clear what folks,
0:28:56 when I’m on panels, when I’m doing keynotes, whatever, when I’m talking to my friends,
0:29:02 this is not the time to be shy. And this is the time to jump in. Start understanding when I talk
0:29:08 to small businesses. Start using tools like ChatGPT and see how it actually can transform your
0:29:14 business. If you don’t know how to use it, then partner with the high school and bring in some
0:29:18 high school interns and have them develop it. So then you’re building a workforce that way.
0:29:25 But staying on the sidelines right now is not the best idea. So this is one of those where you say,
0:29:31 come on in, the water’s fine. It’s just really deep, right? Because, you know, so, but it’s time to
0:29:37 explore and get involved in the conversation. Absolutely. Lewis, for listeners who would
0:29:42 like to learn more about some of the work that you’re doing, perhaps, you know, other places in
0:29:46 NVIDIA related to workforce development and economic development and everything else we’re
0:29:53 touching upon, where’s a good place for them to start? Yeah. So I work with the internal team. So
0:29:57 every once in a while, there’s a blog post on the NVIDIA website, but really everybody can find me
0:30:02 on LinkedIn. I try to stay pretty active on there. And if you don’t know the spell my name,
0:30:08 just look up Meet Mr. Stewart and you’ll find me. Fantastic. Lewis, thank you again for making the
0:30:13 time and best of luck on the work you’re doing. It’s kind of, I don’t know, it’s one of the core
0:30:17 reasons I think that we’re all doing all this is to make a better world for everybody. Yeah,
0:30:35 thank you. It’s been a pleasure and hopefully we get to chat again.
0:30:44 So,
0:31:09 , you.
0:31:12 (upbeat music)
0:31:20 [BLANK_AUDIO]
In this episode of the NVIDIA’s AI Podcast, Louis Stewart, head of strategic initiatives for NVIDIA’s global developer ecosystem, discusses why workforce development is crucial for maximizing AI benefits. He emphasizes the importance of AI education, inclusivity, and public-private partnerships in preparing the global workforce for the future. Engaging with AI tools and understanding their impact on the workforce landscape is vital for ensuring these changes benefit everyone.
https://blogs.nvidia.com/blog/workforce-development-ai/