Podcast Ep. 18 Stanford MBA ’95 Brad Smith meets MBA ’25 Yoshimi Muneta

Today, I’m joined by Brad Smith from the Stanford MBA Class of 1995 and Yoshimi Muneta from the Class of 2025.

Brad spent over 30 years leading IT and operations for companies like Uline, McMaster-Carr, PayNet, EthnicGrocer.com, CellNet Systems, and Accenture. In early 2025, he transitioned full-time into nonprofit leadership, now serving as Co-Chair of Project Redwood, a GSB-founded initiative fighting global poverty, as well as a board member of THRIVEGulu and advisor to a family-run school in Northern India that educates 1,300 under-resourced students.

Yoshimi is a second-year MBA student at Stanford, passionate about building inclusive cultures, scaling innovation, and making ocean environments more accessible. Born and raised in Mexico with Japanese heritage, she specialized in retail and education consulting at EY-Parthenon before moving to Finland to spearhead Wolt (DoorDash)’s e-grocery expansion. Her launches in Cyprus and Malta became Wolt Market’s two most profitable markets — and now she’s exploring new frontiers at the intersection of education, HR tech, and ocean sustainability.

Together, Brad and Yoshimi reflect on navigating uncertainty, shifting from achievement to meaning, and how leadership, creativity, and human connection shape careers across generations.

Chapters: 

00:00 Introduction and Background

03:56 Career Paths and Job Search

07:14 Experiences in the Dot Com Boom

09:54 E-Groceries and International Launches

13:16 Navigating the Dot Com Crash

15:52 Entrepreneurial Aspirations and Social Impact

19:04 Shifts in Career Focus and Philanthropy

22:07 Education and Making an Impact

24:50 Generational Perspectives on Purpose

28:03 Life Transitions and Future Plans

32:28 Philanthropy and Giving Back

37:10 Navigating Career Paths and Partnerships

42:05 Ocean Conservation and Entrepreneurship

48:20 The Impact of Technology on Philanthropy

55:07 Advice for the Next Generation

Join the Podcast Series
Stanford MBA: From Baby Boomer to Gen Z | Class of ‘95 Meets Class of ‘25

Each of these episodes will feature a different pair of Stanford MBA people -- one from the class of 1995, and one from the class of 2025.

Remember to rate, review, and subscribe to stay connected with future episodes!

📺 Also available on YouTube:
Entire series playlist:
https://youtube.com/playlist?list=PLSaVisoF0D_GKxVmHmakNxdpAJCb5_VTP

More info: https://www.katharinemclennan.com/

Contact: kath@katharinemclennan.com

Linkedin: https://www.linkedin.com/in/katharinemclennan/

Chapters

• 0:00 Introduction and Background
• 3:56 Career Paths and Job Search
• 7:14 Experiences in the Dot Com Boom
• 9:54 E-Groceries and International Launches
• 13:16 Navigating the Dot Com Crash
• 15:52 Entrepreneurial Aspirations and Social Impact
• 19:04 Shifts in Career Focus and Philanthropy
• 22:07 Education and Making an Impact
• 24:50 Generational Perspectives on Purpose
• 28:03 Life Transitions and Future Plans
• 32:28 Philanthropy and Giving Back
• 37:10 Navigating Career Paths and Partnerships
• 42:05 Ocean Conservation and Entrepreneurship
• 48:20 The Impact of Technology on Philanthropy
• 55:07 Advice for the Next Generation

Transcript

Note: this transcript is generated by AI, so it won’t always be perfect, especially when it comes to: 

·        Incorrect breaks in a sentence (AI hears the pause and assumes a new sentence)

·        Exact word recognition – you may see that there are words that don’t make sense from time to time

Katharine McLennan (01:03)

Today I'm joined by Tony Ross from the Stanford MBA class of 1995, one of my classmates, and Mark RL Stark from the class of 2025.

Tony spent nearly 22 years at Apple, leading America's operations after key roles in worldwide planning and Mac product operations. Now based in Park City, Utah, he serves on the advisory board of CrowdStake, a platform using crypto rewards to fund new initiatives. And he's preparing for his second climb of Denali. Mark Arrell.

is a transformative sales leader, lending cutting edge AI technology with human connection to redefine how companies drive growth. A second year MBA student at Stanford, he's led global teams at MuleSoft Salesforce, shaped AI, go to market strategies for startups, and brings the same energy to his passions for photography, indie film, and team building, often with a mic in hand for karaoke.

Together, Tony and Marco Rales explored two awakenings, the internet in the 1990s and today's AI revolution and what it means to lead with purpose across generations.

Katharine McLennan (02:17)

And Mark, where do we find you today?

Marc-Aurèle Stark (02:19)

It's Wednesdays at the GSB, so we don't have class. But for some reason, I'm still back to back for the whole day today. So I think  kind of funny to be here and taking this podcast from here.

Katharine McLennan (02:26)

Yeah,

what?

What's the back-to-back activity that you got going?

Marc-Aurèle Stark (02:32)

I mean, that's a good question. I don't even know where my time goes and I should maybe be way more intentional about it. ⁓ I just, I'm doing two part-time jobs on the site. So I think that's making me busy generally. And I'm also TAing this class. So essentially it's a lot of work on top of classes. So yeah, I think it ends up, yeah.

Katharine McLennan (02:37)

You

So

what's the clash that you're TAing?

Marc-Aurèle Stark (02:52)

AI Awakening, which is an across the street class.

Tony (02:55)

That's what we were discussing when you came in.

Katharine McLennan (02:55)

Yes it is!

Marc-Aurèle Stark (02:57)

way.

Katharine McLennan (02:58)

Yeah,

tell me about AI Awakening. How cool is that?

Marc-Aurèle Stark (03:03)

It's a really cool class, actually. I took it last year and it was one of the best classes I took at Stanford. And so then I wanted to be involved and be a TA for that just because of how amazing it was. essentially, it's more of a speaker series, which is interesting because we get a lot of... I think the issue of AI, I was actually at dinner yesterday with Eric Horvitz, who's the chief scientist of Microsoft for this class, which is funny. But he was saying that...

back in the days when he did his PhD on AI, a lot of people were doing a PhD on AI because to master AI, essentially, you had a few papers, In a sense, it was a relatively small field. And now it's such an insane field where there's something new every day and it's impossible to know all the literature in AI ⁓ anymore, right? And so I think this is a really good class because it's a speaker series and because you get all of these.

Katharine McLennan (03:49)

Yeah.

Marc-Aurèle Stark (03:57)

incredibly smart people who spend so much time on it. And so you get a lot of interesting perspectives, but yeah, cool people are Eric Horvitz, two scientists at Microsoft, Mira Murati, the former CTO of OpenAI, who now just started her own startup. think she raised a one billion seed, which is a record of some sort. she's coming in two weeks. So I'm excited to see her again and hear what she's doing.

Katharine McLennan (04:01)

⁓ my...

Okay, I'm coming back to this because Tony, I'm going to say where you were, but we did not have internet awakening. Why did we have internet awakening? I totally

Tony (04:28)

Yeah, yeah. We should have. mean, totally dating us the first time I ever used email was at Stanford.

Katharine McLennan (04:38)

and barely at that, right? So where do we find you, Tony?

Tony (04:42)

I'm in Park City, retired a couple of years ago after 22 years at Apple. And we'd had a place here and been coming regularly. And so we ended up retiring here. And it's been a surprisingly warm spring, but we have a storm coming in this afternoon and expecting six inches of snow.

Marc-Aurèle Stark (04:44)

Nice.

Katharine McLennan (04:45)

as

you

⁓ fantastic.

And so that retired word, Tony, you're the first of our class to actually use that word. Everybody else.

Tony (05:09)

I know. I met some mothers at our last meeting who, whether they said it or not, are retired. Anyway, what retired for

us doesn't mean what it meant for our parents, of course. It means I choose what I spend my time on. And it's a lot more variety. So yeah.

Katharine McLennan (05:17)

No, it doesn't.

Yeah, I love

that. I love that. But it's interesting. The internet was definitely coming alive, And in 1995, when we graduated, a company called Netscape went public. that was the first retail internet browser, I believe. And I think it became AOL eventually. But anyway.

Tony (05:44)

Thanks, I guess.

Katharine McLennan (05:50)

It was an interesting thing. So one of the fascinations I have with doing this podcast is with not only because there's 30 years apart and we're having our 30th reunion in October, but your two classes are emerging into these two different worlds. And the fact that this, you you're even talking about AI awakening is quite to the point. So.

What do you see?

Marc-Aurèle Stark (06:16)

so I came to the GSB where I explored a few things and I think my initial hypothesis was more on education. I wanted to make more of an impact around that. And it's a wonderful institution for that obviously. think it has a long stand in history of having a dual degree with the Graduate School of Education. And obviously a lot of amazing startups and EdTech came out of the GSB. But the closer I got to education and thinking about innovation within the space,

closer I got to AI actually, in a way, because I think it's pretty revolutionary within the field or it will impact the field in ways that we're not expecting yet. I think partly that class that I took last year and that I'm now TAing this year, I think I went to that dinner with Mira Moradi at the time. And for me, some of the discussions that we had around AGI potentially happening a lot sooner than we think.

Tony (06:47)

So, thank

Marc-Aurèle Stark (07:06)

It doesn't matter when it happens, right? And to me, it's not necessarily about whether it's 2032

or 2035 and so on, but it's just realizing that we're very much at such a interesting, pivotal moment for history and for humanity when it comes to how things are going to change.

whether on a societal level or economic level or political level as well, right? From just like how AI is going to impact all of these spheres. It's hard for me to not want to be closer to the technology to try to understand it better so then I can go back to education or something. I think my thesis is that the models at the moment, the foundational models are evolving so fast.

that it's better to be close and try to understand what's happening. And I think a lot of people are like, it's so hard to always be at the top of what's happening and in touch. And so I think 10 years down the line, we'll see a lot more value at the apps level, where people are sort of leveraging AI in a way that makes more sense for them. But right now, it makes more sense for me to be at the model level to just understand what's happening. yeah, essentially, that's a long-winded way of saying it.

Katharine McLennan (08:10)

Well, no, but it's, love

the way that you talk about it because I'm not sure, Tony, we could have talked about it in that philosophical way because, you you said, it's going to take me a while and us to understand it, but I reckon it's, understands us. I mean, I'm on chat, TPT literally all day when I'm writing. you know, it's, it's, it's amazing. Tony, so you're,

Tony (08:20)

Mm-hmm.

Katharine McLennan (08:33)

long career at Apple, you would have seen a huge evolution. So tell us a little bit about when you came into Apple and when you retired and, you know, in five sentences or less, but

maybe the thing you loved about it. Let's start there.

Tony (08:49)

I always felt like I was part of something bigger that was making a real, when we succeeded, we helped make the world a better place. And I, I loved and one of the things I miss the most is the amazing people I got to work with. Super smart, motivated people who are working together for a common cause.

Katharine McLennan (08:55)

Sure did.

Tony (09:05)

In all my years there, I never saw a case where somebody tried to get ahead by making someone else look bad. And there's politics as there is in every company, but it was all because people had different ways of trying to get to the right result, not because we were trying to step over each other to get to some career goal.

Katharine McLennan (09:11)

God, Tony.

So did you join right after business school?

Tony (09:26)

Now I went to another company called 3Com in between. was there for six years. ⁓ it was competing. Some people think, sticky paper. No, that's 3M. ⁓ 3Com was competing in the late 90s with Cisco in networking hardware. so I would say, well, have you heard of 3Com? No. Have you heard of Cisco? Yes. Guess who won?

Katharine McLennan (09:29)

yeah, that little company. It wasn't.

No. Another.

Marc-Aurèle Stark (09:37)

No.

Katharine McLennan (09:47)

what's interesting, Tony, about that is I had in organizational behavior, we had to go to pick a company to go and do a project with. so we...

picked this tiny little company that was, I think at the time it was 300 people to go and see its thoughts and philosophies. And it was fascinating and it was Cisco. So there you go.

Tony (10:10)

Yeah

Well, I sat over there for six years and I had thought, you're talking about lessons learned from Stanford. One of the things I learned is that you don't have to know it all coming out of school. And that was from a class where the speaker was John Margridge from Cisco, after his, you know, so basically he was the protagonist of this case. at the afterward,

Katharine McLennan (10:21)

That's good.

Tony (10:31)

you know, the whole case discussion that he listened to, said, well, you guys were right. You guys had a good idea, but here's what we really did. But then he said, one of the things he said, I always remembered is I needed every ounce of wisdom I gained from 20 years at HP to have any idea how to get Cisco off the ground and how to make decisions day to day. And I was like, Oh, I don't have to know at all. Cause this is, you know, the nineties and everyone's like, I have to go to a startup. And I was like, okay, so it's okay to go get some knowledge afterwards. And,

learn from a world-class company and then go to a startup. So that was my plan and 3Com was world-class in operations. But they lost and in the end downsized their way to oblivion. And I got laid off as part of a dot-com bust. So I joined Apple as a safety job to see me through the dot-com bust. And 22 years later, there I was.

Katharine McLennan (11:21)

Wow. Wow. So

hold on. So, so in 1995 was what I remember if Apple was even around, I don't remember it being. Yeah. And what I mean is the popular thing to do for our class. Yeah.

Tony (11:31)

Yeah. look, mean, Apple was founded in 1976, I think. Yeah. Yeah. So Steve Jobs didn't

come back to Apple until 1997. So Apple was failing, floundering on its deathbed in 1995. And so yeah, in 2001, when I joined Apple, Steve Jobs, Steve had come back, had reintroduced the iMac, had simplified the product lines and

Katharine McLennan (11:43)

Got it, okay, okay.

Okay, got it, okay. ⁓

Tony (11:59)

Apple had rebounded substantially.

Katharine McLennan (12:01)

What was your first job at Apple? How's that?

Tony (12:07)

came into a role that leveraged my engineering and business background. So it was working within operations to help get new products off the ground. And that was partnering with the design engineering teams to help influence the designs of future projects and say, hey, if we qualify these suppliers, if we change this design, we can build the next generation at higher quality, higher volume, lower cost. In the meantime, they're making in

Katharine McLennan (12:11)

Bye

Tony (12:32)

making it more complex, it was a never ending battle. And then the other half is working with teams of operations engineers to design the factory layout, to design the step-by-step, how do you assemble it? How do you measure the quality? How do you repair it? And then to actually make it happen, to bring it all to life.

Katharine McLennan (12:49)

I'm going back to the AI world, Mark, so you mentioned education. Now, so when you leave Stanford, is that education still a theme that you're going to take as you go forward in whatever you're going to do?

Marc-Aurèle Stark (13:03)

So no, I think I want to be very much close to the models. Anthropic, obviously on the Google side Gemini, Mistral, so it's an interesting one, but I think that would be interesting. yeah, I mean, we were talking a little bit about this before you joined with Tony, but it's interesting because I think the intersection of AI and education is promising, I think, in the future. For example, for this class.

Katharine McLennan (13:06)

You're going to be closer to the AI.

Tony (13:25)

you

Katharine McLennan (13:17)

Yeah. Yeah.

Marc-Aurèle Stark (13:27)

AI Awakening, one thing that we've been testing is working with a company called Real Avatar. And essentially what they do is they have, they are leveraging sort of the voice aspect, sort of from the multimodal like LLMs, where we fed a lot of the writings and a lot of the papers and a lot of the conferences that the professor did. And so essentially what this does is that a lot of students are able to interact directly with the avatar.

discuss some of the readings, discuss some complex questions, essentially have a bit of a leveraging the Socratic method, right? Because I think one thing that we've noticed about education is that the impact of Gen AI is that a lot of students essentially are just feeding whatever homework they have into chat GPT, right? Or cloud, and then they're getting that output and using that as their homework. And the issue is that this maybe the output is okay, but it doesn't mean that they've actually put in some critical thought into it.

And so here we're trying to make sure that they're actually engaging with the content. But this is still a very early application of AI. So I think my point here is that I want to be as close as possible to the models. think, mean, ChachiPT came out in November 2022. I think what we are using today, personally, I talk to ChachiPT, right? Like I use the voice command a lot more now. And that was impossible three years ago. So it's really hard to know what it's going to look like in five years.

And so I think my rational is that I want to see, I think we're still in that part of history where AI is evolving so fast and it's more about being close to the technology and seeing what's happening and then looking at the applications when we're getting to some sort of plateau. Not that we will be there, but yeah, I think it looks like scaling laws are showing that big as they were.

Katharine McLennan (15:12)

The scaling

laws, what is it, Moore's law, Tony? The capacity would, well, I don't even remember the number, but double every 18 months. It probably doubles every hour now, right? So I mean, capacity is not even a constraint, I would say, anymore. Well, the planet will constrain us in terms of the data set, the power usage, yeah.

Tony (15:19)

Double every 18 months.

Yeah, feels like it, but AI.

Well.

Yeah, it's the data center and the power usage and yeah, in

the end is physical in capacity.

Katharine McLennan (15:39)

Yeah,

But when we were at Stanford, I don't recall too much interest in the environment. We certainly had a few people doing the double degree in education. We certainly had double degrees in law and maybe a few engineers.

Tony (15:40)

You know, back in my day.

Katharine McLennan (15:56)

It's changed, hasn't it? How did Apple, I remember one incredible commercial that you guys did on the environment, but how did you see it infiltrate,

Tony (16:05)

You know, when after Steve Jobs' death, Tim Cook took over, Tim kept all the things that made Apple great.

that Steve had done, the fanatic attention to detail and focus on making the technology simple and hide all the complexity, all that stuff. also use the power of Apple as one of the world's largest and most influential companies to do good. And he did it because it's the right thing to do. And it wasn't necessarily because it was going to bring Apple business. But wait.

I mean, many, many things like he won, Apple won the Stop Slavery Award from Thomson Reuters for doing the most of any organization in the world to stop modern slavery, for example. But also in the environment, you know, going beyond, yeah, we're going to have our own facilities to be carbon neutral. To go from that to having all of our production be carbon neutral by 2030 is way beyond

what anyone else is doing. And I still hope it's possible, but it's definitely has received a setback here in the last few months. But some of the things you need is all the airlines to change the kind of jet fuel they use. And there's not even enough of the new kinds of jet fuel available in the world. So you have to like influence the world to make that kind of stuff happen. But you know, Tim is taking this stuff on is like,

because it's the right thing to do and because we have the unique situation of Apple's influence on the world, we can do it.

Katharine McLennan (17:34)

So the terrible question that you answered so beautifully that I hated at this time at Stanford was, so what are you going to do?

Marc-Aurèle Stark (17:45)

It feels a little bit weird, if I'm honest. I mean, it's been two years. It's definitely a simulation here. It's a very interesting bubble. And it doesn't feel like the real world. But yeah, AI, I want to be as close as possible to the technology and to models. And I was telling Tony this a little bit before, but I worked for this seven years before.

Katharine McLennan (17:50)

In a bubble, nice little bubble.

Tony (17:50)

Yeah.

Marc-Aurèle Stark (18:07)

the GSB in sales and it's interesting because I actually just want to go back to sales. I've tried a few other functions and I've just realized that this is what energizes me the most. I want to be as close as possible to customers and I feel like when I'm selling a solution that makes sense and then is transforming their business, I'm actually making an impact. So yeah.

Katharine McLennan (18:26)

God, I'm hiring you. Geez Louise.

Tony (18:27)

All

right.

Katharine McLennan (18:29)

Tony? Did we have anybody that said I'm going into sales when they finished? I don't remember. I mean,

Tony (18:34)

No, mean

everyone, the popular thing was consulting or iBanking and yeah, so the lemmings all flocked there.

Katharine McLennan (18:38)

Yeah. Yeah.

I tell you, truly artful sales, and back in the day, I'd said, you need to go out door to door and sell encyclopedias or vacuum cleaners, for example, to really fundamentally understand how it works. And we would make,

our employees, whether it was in a grocery store or an Apple store or something like that, to really fundamentally understand that. how does this?

Tony (19:08)

Do we need to go back and define encyclopedia for Mark?

Katharine McLennan (19:11)

As a sales guy though, What do you love so much about it? Where's the passion? your face lights up.

Marc-Aurèle Stark (19:18)

A few things. I think one is just, it's awesome to be in contact with people, right? Like obviously the B2B sells and like it's more sort of abstract in that way, but you mentioned, you know, going door to door. I mean, one thing that I did in college was canvassing quite a bit, right? And it's similar to that. just, liked the human contact. I like being able to go right there and just discuss something and figure that out. I think I enjoyed the challenge of it.

Tony (19:18)

So.

Okay.

Marc-Aurèle Stark (19:44)

I tend to be a little bit competitive. like having a quota. like, I like feeling like I can

tangibly have a tangible impact. can quantitatively say how much I've done essentially. And I think that's kind of cool, right? It's like in a sales job, can say, Hey, I brought in 6 million to the company this year. And that feels like a very specific impact. And it's awesome. And you feel like you can.

overperform and you can be better than yourself and there is a competitive element that I enjoy. And then I think it's a good school because you have to learn to deal with rejection and failure and that's something that you have to face for your entire life whether it's at work or in know life or relationships or whatever it is right. So I think it's a good school of life.

Tony (20:29)

The best salespeople build long-term win-win relationships and make a real difference for their customers or partners. We thought of them, maybe selling to Verizon or Best Buy or AT &T.

Katharine McLennan (20:29)

I look like total

Marc-Aurèle Stark (20:35)

Yeah.

Tony (20:46)

There are also huge companies and there are partners and together we're doing tens of billions of dollars of business.

Katharine McLennan (20:52)

Apple must be the most phenomenal case study in making something we didn't know we wanted

Tony (21:00)

Yeah, I mean, the really interesting thing at Apple is I think different than probably any other company, any other company, if you're in, if you're a sales leader, you have tremendous say as to what the next product will look like and how it will function. If you're a sales leader at Apple, you have no idea what the next product will be until it's launched. You have zero input at all. you know, unless you're the most senior executive, then you might get it unveiled to you say, here's a sneak peek of what it will look like.

you know, in great secrecy, but you still don't have input to it. So it's a real difference. So in Apple, you're like, okay, here's the product. I, okay, it's a surprise to me too. I'm going to go sell it.

Katharine McLennan (21:32)

Wow.

That is amazing.

And going back to Mark, even the fact that you're describing an AI as something that you're only just beginning to understand, how can we possibly know what we'll be selling?

Marc-Aurèle Stark (21:52)

I can tell you essentially some examples, but I think ultimately just to take it a bit, like take a step back, I think ultimately this is what brings me back to education. think ultimately what's exciting is that this is ever changing. And so it's about constantly learning. And that's something I like, right? It's the idea that I can never rest on my laurels. I can never sort of just always have the same sort of playbook that I'm using, but I have to very much adapt to how things are changing to.

Tony (22:14)

So,

Marc-Aurèle Stark (22:20)

this product to the impact it's making. And it's sort of a loop where the more you talk to customers into how they're using the product, into how this is impacting them, the more you understand and you think about new use cases and you're developing this with them. So I think in that sense, it feels very rewarding. And that's why I'm excited about it, because I get to learn a lot. I get to shape a lot. And so that's what is

Tony (22:25)

thank

Marc-Aurèle Stark (22:41)

exciting about it.

Katharine McLennan (22:42)

Okay, so okay, just

does a salesperson do in OpenAI?

Marc-Aurèle Stark (22:46)

So I mean, on the B2B side, lot like all of these startups, all of these companies are building on top of these models. So if you look at a Zoom, for example, I know that they're leveraging Anthropic, for example, to now develop new features where you're on Zoom and you get all of your meeting notes immediately summarized by AI at the end, right? And you get that, right? So a lot of these companies are building on top of the current models to be able to develop new features, which I think is really interesting.

Katharine McLennan (22:53)

Okay.

Marc-Aurèle Stark (23:14)

Notion is something that people use a lot for notes, obviously that's leveraging AI.

Tony (23:20)

The core of what we do is a payment processor leveraging proprietary blockchain technology. But why people would come use us is because of the ways we've leveraged AI. And two examples, one is to bring

Marc-Aurèle Stark (23:30)

Hmm.

Tony (23:33)

people to donate to their favorite charitable causes using our platform. One of the things we did is use AI to scrape the government database for all 501 C3s. And there's like 1.2 million of them. And any that have enough information out there to do this, it automatically created a summary page for each one of these nonprofits saying, here's what we do and here's why you should donate to us, basically.

So we ended up with 300,000 summary pages of nonprofits and created a search function to be able to target exactly what you want in the locality that you want. And you can make a bundle of nonprofits then that say you care about dog welfare in Tuscaloosa, Alabama, you can find and create that right now. But to hire humans, to scrape the government database of 2.1 or 2.2 million.

non-profits and create 300,000 summaries that would never happen. ⁓ Another use is for crowdfunding. So a lot of people want to do crowdfunding, but they have no idea how. so most crowdfunding campaigns fail. Well, we're leveraging AI to teach people to crowdfund. if you want to, so you can actually have a conversation with our AI to say, well, here's what I want to do. Here's my project.

Katharine McLennan (24:25)

Oh, go ahead and add time.

Wow.

Tony (24:47)

And they don't come back and say, based on what you're doing, we suggest that you target this amount and you look for this kind of people and you advertise in this way.

you have to have the whole conversation of what you're trying to do. to tell it what you want and then it can give you ideas of how to do it the best way. And then,

Katharine McLennan (25:02)

So Mark, you threw in something earlier on, an acronym, which everybody knows in the lingo. But a lot of people don't, which is, say it again, it's the when the AI reaches a point, AGI.

Marc-Aurèle Stark (25:16)

AGI, artificial general intelligence, yeah.

Artificial general intelligence, which is...

Katharine McLennan (25:21)

Okay, tell us about

what that is

Marc-Aurèle Stark (25:24)

think there, I think that's the issue. think there's no clear definition of it because ultimately, I mean, for a long time, the whole definition of artificial intelligence was around the Turing test, right? And like being able to pass the Turing test. So this idea that you wouldn't be able to know whether you're talking to a machine or a human, I think to a certain extent, a lot of current models have been able to pass the Turing test depending on who's testing it and how we define that.

So artificial general intelligence is this idea that it's almost omission ubiquitous and able to do all these things. But I think if we take a bit of a philosophical standpoint here as well, like what is intelligence in the first place? As humans, there are things that we can do, but mean, bats can have like sonars and like see distances in ways that we can't, right? Like animals have forms of intelligence that we don't have in terms of abilities and things that they can do in the world. Whereas obviously maybe we have more of like

Tony (25:59)

Okay.

Marc-Aurèle Stark (26:16)

of thinking and things that we think animals don't have, right, or reasoning. But ultimately, it's hard to determine what are all these sort of facets of intelligence and when do we

access that essentially and what do we define as this ultimate artificial general intelligence. But essentially, think the idea is like, if you think about some altman's vision, I think it's more about having a model that is able to do all of these things that humans are currently doing and to render work obsolete to a certain extent.

Which is that a society that we want to work in, right? Like what is the purpose that people are going to have for a post-work reality? So that's a whole complex question. But I do think there is a world where a lot of the things that we're currently doing are going to be done by machines.

Katharine McLennan (27:00)

How is Apple, Tony, how have you seen, you talked a little bit about how Apple's responding,

Tony (27:06)

I think that was actually Apple's big push into AI last year is to say that Apple has this unique position of controlling the hardware, the apps and the software and being able to integrate it all and can make AI actually useful for every human rather than just people doing research or people doing specialized cases.

by it knowing what you do every day and how you do it and being able to help you do it more efficiently. And that's the idea of Apple AI and it's taking time to roll out. But yeah, that was kind of Apple's unique ability to contribute in this space.

Katharine McLennan (27:32)

Yeah.

It's extraordinary. you also used a word that's important to me. Marcus, the Socratic method and our ability to ask questions. And you're suggesting your your generation

may not have that as much. That's the art, right? How do you ask questions? Talk a little bit about how that's manifested in the business school

Marc-Aurèle Stark (28:00)

Yeah, I think we're fortunate in business school so far because obviously we're being very disrupted in terms of pedagogy when it comes to AI. But ultimately, because we're still leveraging the case method for a lot of classes, we're still mostly discussion-based and debate-based.

think

it's hard to be able to just output something through a model, through a language model, right? At the moment, but I'm more worried about education that's meant for you to learn very specific things and have reasoning and then output a problem set, right? Because that's being disrupted so much, currently, by the models where people are just able to leverage that without doing the work.

I've talked to lot of undergrads here as well because they think it's interesting.

And also this across the street class that I'm seeing has half business school, like 20 % PhDs and then the rest are undergrads. And the undergrads here are very, exactly. And they're very intentional about trying to not use AI for their problem sets because they're worried that then it becomes too easy and they're not training in that way. And I think we need to rethink the pedagogy. And obviously this is why.

Katharine McLennan (28:49)

Good mix, good mix.

Tony (28:51)

Yeah.

Thank you.

Marc-Aurèle Stark (29:04)

I had to get a little bit away from education in the moment because they think we're at a juncture where it's really important to think about all of this and that's why I want to be on the model side. But I think one thing that is just interesting philosophically is that, you know, this analogy that, you know, the calculator came out, but we still need mathematicians, obviously, right? Because it's all more abstract than that. models are allowing us to simplify language or to not necessarily have to write as much. And that's already a big change for humanity.

Tony (29:12)

So,

Marc-Aurèle Stark (29:33)

But I think the biggest change for me that I'm worried about is what happens when we delegate reasoning, right? We're moving from language models to reasoning models.

You look at O3, that's more of a reasoning model. And isn't that what makes us different from animals? Not that we're, you know, I'm not trying to create a hierarchy or anything here, but I think when we're trying to find the definition of humans, that tends to be something that we bring in, right? Reasoning and the ability to think in a different way, to dream all of these things that you apparently, you dogs can dream.

But then if we're delegating that completely to machines, what are we? And I think that there is sort of an existential sort of question here.

Katharine McLennan (30:14)

Tony, What does one do when one says R word, retired,

Tony (30:20)

Well, certain things that you just can't do, passions that you can't pursue while only having two to three weeks off a year. And for me, I grew up mountain climbing in the Cascades, grew up in Tacoma, Washington. And I always had this long lifetime goal of climbing Denali. But, you know, it's a month trip and not to mention the training, which takes multiple hours per day.

And it's just not possible. I trained for it last year and spent three weeks on the mountain. got to 19,000 feet, four hours from the summit and had to turn back there. And I thought I'm going to give this one more shot. I'm in the end stages of training again and leaving in two months for another shot at that. And I just came back from a month in Nepal.

I always wanted to go to Himalayas and do some trekking there and I did some climbing as well. So I got another thing you just can't do when you don't have enough time. And then beyond that, that's kind of taking up my mornings, just training for mountain climbing. But in the afternoons, like I said, I'm invested in a startup that I'm heavily involved with getting off the ground. I'm actually just invested in a brewery that I'm gonna work with.

And I'm on the board of my HOA. I've been working with a nonprofit, like stuff that keeps me active and busy. It's fun. I like to do and challenges and teaches me new things. So yeah, it's all good. I love retirement. I highly recommend it.

Katharine McLennan (31:41)

Yeah, that is a life.

Yeah, that is life. And that's actually back to the question of what work is, right? So what is work?

Tony (31:51)

You just transition to different things, it's a, know, pursuing passions and projects that are, passions that you love and projects that are interesting.

Katharine McLennan (32:00)

Well, it's in that place. if you zoom forward, Mark, and literally 30 years, we asking ourselves, what does the day look like in the AI awakened?

Tony (32:08)

Hmm.

Marc-Aurèle Stark (32:11)

Mm-hmm.

it's interesting, obviously, everyone has a different scenario in mind and it's really hard to anticipate and predict, but my hope is that indeed machines are able and we coexist really well, right? There's no issue here, right? There's also a doom scenario, a sci-fi scenario where there's a machine uprising, I think we've seen a lot of that.

Katharine McLennan (32:30)

Yeah. Yeah.

Tony (32:31)

Yeah.

Marc-Aurèle Stark (32:34)

I think it's a world where hopefully technology has given access to a lot of people to think. So I'm hoping that on the education side now, you know, people in countries where they don't have access to as much resource, as many resources are able to have a personalized tutor. And there's more in the day to day is more about finding your own purpose, finding the meaning of life, enjoying leisure in a way. A lot of work has become.

obsolete on the human side and it's machines producing a lot. And then hopefully we're in a society where people are just able to enjoy the small things and go back to a simpler life where it's about, you know, hopefully a beautiful retirement for everyone, like exploring the world, hiking, mountain climbing, gardening, taking care of your family, creating art, doing things that we enjoy in a way that feels fulfilling.

Tony (33:07)

Okay.

Katharine McLennan (33:24)

it's Wednesday, What would a absolutely perfect Wednesday look for you?

Marc-Aurèle Stark (33:31)

I mean, I personally love working, which is why I have two part-time jobs and I'm also TA-ing while I'm business school. So, know, clearly I have an issue ⁓ there. Yeah, I think a perfect day is like waking up early, going to the gym, having a bit of a mindfulness time around there. And for me, that's a good me time. And then going to work, having a very social time at work. And I think that's why I enjoy sales.

Tony (33:38)

Bar to you.

Marc-Aurèle Stark (33:57)

just talking to people, being with colleagues as well, and then hopefully having a hobby in the afternoon. And so for now it's photography, but who knows where we'll be after. Yeah.

Katharine McLennan (34:10)

photography itself must be changing radically.

Marc-Aurèle Stark (34:14)

It's interesting. If you think about the creative aspect, I mean, I'm working with one company, it's called Raspberry, right? And what they're doing is Gen.ai for the fashion industry specifically. And it's helping designers sketch a lot faster. Essentially, you're able to prompt very clearly what kind of clothes you want. And then you can give very specific feedback on, for example, the sleeve and so on. So you could say, okay, well, this is changing radically how we design, but I think it's not about automation. It's more about

Katharine McLennan (34:23)

Mm-hmm.

Marc-Aurèle Stark (34:41)

And the way I think about photography is that obviously we've seen a lot of improvements throughout the history of photography,

Tony (34:46)

So,

Marc-Aurèle Stark (34:48)

right? Like, I mean, the first few, like you had to expose something for like an hour before you're able to get a photo, right? Back in the like 40s or whatever that was. And I think it's just technology has helped photography, but ultimately it's more about what kind of art you're trying to do. So yeah, so I think, yeah. I mean, I took a...

across the street class for photography here. And it was interesting because it was more about being proactive rather than reactive. I always saw photography as me capturing beautiful moments around me. But that class was more about creating art. It was more about, okay, kinship is the theme. What am I trying to do around kinship? And coming up with a concept. And I actually leveraged child GPT a lot for that because I would prompt ideas that I had because I wanted to see what they could look like. And so that gave me ideas as well.

Tony (35:16)

Yes.

Marc-Aurèle Stark (35:38)

and I just had this whole conversation and then would end up like doing a photo shoot, having someone model for me and do a whole thing. But so

I still think that even with technology advancing, we have a lot of agency around how we conceptualize art.

Tony (35:46)

Thank

Katharine McLennan (35:52)

That's a great example. I love how you've just described it. And when you're working with ChetTPT, is it actually drawing or describing it in words for you?

Marc-Aurèle Stark (36:01)

So I describe it in words and then I get an image. I'm saying, so kinship, I'm thinking this, I want this kind of tone. I'm thinking these colors. I'm thinking this kind of sort of facial expression, just trying to think my concept, but sometimes visualizing it in a way that's quite literal rather just in your mind helps. And then I'm like, okay, that doesn't work. So I need to do something else instead.

Katharine McLennan (36:04)

Did you get image? Yeah.

go back to your passion, Tony, The incredible outdoors. And here I'm picturing you on Denali, You're gonna do it again.

how does technology help you?

Tony (36:39)

Yeah, I mean, the gear is better. Lighter was the big factor. Anything you can do to reduce ounces on there, because you currently, and then there's one amount where you cannot.

Katharine McLennan (36:41)

Yeah!

Tony (36:51)

hire anybody to help you carry anything. So it's all you with your, and you tow a sled along with your heavy backpack. So yeah, lighter, better gear is great, but also navigation is a way, big way that technology has changed mountaineering a lot. I mean, grew up with like, you'd have to bring a paper map and a compass and like be citing things and, now it's all GPS and there's lots of apps that make that far.

Katharine McLennan (36:53)

Yeah, there you go.

Tony (37:15)

better. Of course, have to carry a solar panel to keep your phone charged if that's what you're relying on for navigation. anyway, it's a simple place where you are cut off from the rest of the world, other than brief satellite, just a few character text conversations you're going to have maybe once a day. But also then you're relying on technology for your navigation, for your life and safety.

Katharine McLennan (37:37)

Yeah, it's amazing.

Tony (37:39)

we got to 19,000 feet elevation. We were four hours from the summit at point, after three weeks on the mountain.

Katharine McLennan (37:43)

hours, thank you, thank you.

Tony (37:45)

the odds are no better next year. And the thought process I had to go through and I had to decide really quickly because it was like, it was a rush to the last spots were available when we came down for next year or for this year. But the thought process I went through is if I knew for sure that I would not make it to the summit this time, the second time.

Would I still choose to do that in order to spend three to four weeks on that mountain in that unique place in the world one more time? And I said, yeah, I'd do that.

Katharine McLennan (38:16)

That's a life, that is a life metaphor. All right, well, as we bring it to a close, what do we have to say to Mark, Tony?

Tony (38:25)

I came up with two thoughts on this. One, can I hint at this before, but it's okay to not know everything. And it's okay to not be the person, to not be the smartest person in the room or the person with the great ideas.

But the key is being able to recognize great ideas when you hear them and to be able to bring people together to act on them and to bring them to fruition. I always, you know, that was kind of what I think of what special sauce that I bring in my career was like, that's a good idea. How are we going to do this? I, but I was rarely the guy who had that, you know, the bright idea. So, so that's one thing. And I think I to feel great. just ever thinking, they have to be the smartest person in the room?

You just don't. And then the other thing is the importance of culture and purpose to an organization and to business success. There was a Ted talk by a guy named Simon Sinek a while back. And the crux of it, he said, if they believe what you believe, people will work for you with blood, sweat, and tears. Otherwise, they'll just work for a paycheck.

Marc-Aurèle Stark (39:18)

No,

Katharine McLennan (39:31)

There you go.

Tony (39:32)

If you can create a sense of purpose and of working for something bigger than ourselves, then you can create that sort of experience for the people that work with you. But otherwise, yeah, just working for a paycheck and they can go anywhere else and get that too.

Katharine McLennan (39:48)

And you had it, Tony. I mean, just as you described the apple, you know, it was just wonderful to see your face, you know, described such an amazing place to work. And just as important, Mark, we need all the help we can. what do you need from us and what would you tell us to get our act together

Marc-Aurèle Stark (40:08)

 I think where I think we need every single generation to work on is climate. I think ultimately, I'm hoping that AI will solve this for us and we'll be able come up with solutions, scientifically at least, or help with scientific research. But I would love for all generations to be able to work in climate because I think ultimately...

That's what is most pressing and that's what we need to be able to do joint efforts for.

Katharine McLennan (40:31)

thanks, you guys. really can't agree more.

Tony (40:32)

Couldn't agree more.