This transcript has been automatically generated.

Josh Sheluk: Nvidia became the first company to hit a $5,000,000,000,000 market cap larger than the entire stock market of The United Kingdom, larger than the entire stock market of Canada, larger than every country’s GDP except for The US and China. So you can own every company in Canada or you can own Nvidia. Those are your two options. Which one do you pick? Next episode of Barenaked Money coming at you and it’s a special one today.

We’ve brought a couple of the Veracan team members along for the ride because we have a lot to talk about in the AI space. And as always, we’re looking to pull back the shower curtain and maybe explore topics a little bit deeper than much of the other commentary out there is doing. So Matt, Maria, Portfolio Managers with the Verecan team out of our Halifax office. Welcome. Thanks for being here.

Matthew Kempton: Thanks for having us.

Josh Sheluk: And I know you’ll do a very admirable job of putting Colin to shame, the two of you. He won’t be missed, let’s put it that way. So I wanted to talk about AI a bit with the two of you because we haven’t really done a lot of that, Colin and I, on the podcast over the year, even though it’s been probably the biggest topic of the year. So we’ve been a bit remiss to have not done that. But the two you I know are very research focused, very data focused, very investment focused.

So that’s what I want to focus the topic of the podcast on today, more of the AI from an investment focus or looking at the investment landscape for AI. Now I know we’ve seen AI kind of drive the bus with the market returns this year, but it’s also driving the bus for the market commentary on the tech side of things for what’s at the forefront of every one of our discussions with our friends, with our family, with the media. I want to start with you, Matt. Maybe you can explain how you kind of separate AI, the technology, from AI, the investment.

Matthew Kempton: Yeah. Yeah. Thanks, Josh. I mean, it’s a it’s a hard thing to do because the conversations sound like they’re so sort of interwoven here. You you you turn on Bloomberg or any network and what they’re talking about is AI.

You listen to a quarterly earnings call. They’re talking about AI. So it sounds like they they should be all one, but really, you do have to think about them separately because AI, the technology is exciting. It’s fast adopted. It’s one of the fastest adopted technologies, if not the fastest.

It is in everyone’s pocket right now, and it is being used in all sorts of exciting ways today. And then who knows even what ways tomorrow. But how do you make money on that? That’s all great, and that’s all fun, but the the question has to be, well, okay. It’s exciting, but how can you earn a return on that?

And that is that’s the very difficult question because to to even be at the stage we’re at right now, hundreds of billions of dollars have had to have been spent to get us here. And for it to get even a little better and certainly a lot better, hundreds and hundreds more billions of dollars will need to be spent. And so it’s almost necessary to spend this money, but what the hard math is, well, where’s the path to profitability for for those companies that are doing that spending? And then all of the players in there who might say, well, we’re gonna be the pure play AI version of this that you never thought you needed before or this company that you never thought you this would be an AI thing, but it is now. Will people pay for that?

Will the will a better one come out tomorrow? Will it just will it fold under just we couldn’t raise enough money to keep it going? Those are the really hard questions. I don’t I don’t know in the least that AI is well, it’s absolutely here today and that it’ll be here in even more tomorrow and certainly in five years. Who knows where we’ll be?

But will what companies will be the leaders tomorrow and in five years? That’s a harder question. And where will the stock market be as a whole? You know, will AI be the driver of the stock market continue to be for the next five years? That’s just as hard of a question.

So I I think that’s that’s how we try and, at least, how I try and think about these two things as related, but but ultimately separate in in, you know, the benefits of AI to to the economy and to to your everyday, but then is it can you continue to make money with AI being being the focus?

Josh Sheluk: What you said there is kind of the the counterintuitive part of all of this is a lot of people are using it. There’s literally hundreds of billions of dollars, maybe trillions of dollars being spent on it by companies that are pouring money into AI. So Maria, maybe you can flesh out a little bit more. If both of those things are true, if there were a billion people using this, probably multiple billions at this point, and companies are literally spending hundreds of billions of dollars on it. How could it not be a good investment?

Maria Wagner: I think with the stock market especially, and you can look at it kind of in, I guess, two ways. Like, it’s gonna impact GDP growth in a positive way, which I think there’s more runway on because it’s there’s less frothy valuations and the expectation of it positively contributing to AI, especially in Canada when it’s a productivity problem. But in the stock market, valuations are very stretched right now, and there’s a lot of data out there that suggests that there’s a lot of frothiness, obviously, about the valuation that we’re seeing and for it to kind of continue at these valuations for the next three to five years that might not be actually realized in the stock market investments, but there will be a positive implication on GDP for the next few years, which is good for the economy. But even if, for example, I think there were a few articles that said AI has a positive impact on GDP, it improves productivity 3% annually for the next two to five years. That’s not enough to kind of justify the valuations that we’re seeing in the equity markets.

So there’s positivity that we can probably improve as an economy. But in the equity markets, there’s a lot of expectations that are going to be really hard to meet in the next few years.

Josh Sheluk: Right. I guess that’s kind of the punchline, right? Are the expectations already so high with the stock market, some of the stocks that are focused in the sector, that it makes it almost impossible for those expectations to be exceeded. And that’s really what investing is all about is trying to find something where expectations are one thing, but the actual results are better than those expectations. That’s how you really make money investing is finding those opportunities that are better than investing.

But so there again, there’s a couple of interesting things you mentioned. So there, this almost certainly is having a profound impact on GDP growth, especially in The US when you see some of the dollars that are being spent on it. But GDP growth does not necessarily equal profitable investments. That was one thing that’s I think really interesting. But you also mentioned valuations a couple of times.

And valuations are just an outcome of expectations. Expectations are super high, that means valuations are super high. So you’re paying a super high price to invest in these companies, these AI related companies. Some more than others, we could we could actually debate about how how high the valuations are. And and maybe I’ll I’ll put a pin on that.

I’ll come back to it in a second. But when the prices that you’re paying for an investment are so high, that’s really gonna drive your return on that investment to a significant extent. And as we said, expectations need to be exceeded to drive a satisfactory return. But but maybe I’ll just ask that question for you, Maria. Valuations are high, but are they too high?

Are they justifiably high? Let me put it that way.

Maria Wagner: If AI does play out as it is, the best case scenario essentially is that it will improve productivity by 3%, and that’s not enough to justify the valuations that we’re seeing in the stock market. So there’s discrepancy between like, it will be really good for GDP growth by improving productivity, but even the best case scenario is not justifying what we’re currently seeing valuation wise in the stock market. So you can even see with companies that have slight missteps that are affiliated with AI. They get slammed on a day just because there’s so much frothiness in the valuations and expectations that everyone kind of knows that these valuations are high, but no one wants to not be a part of this AI buzz and boom so they’re just hoping that everything remains status quo and they’d rather lose some of the downside when they spot the valuations than not participate at

Josh Sheluk: So lots of FOMO going on and that’s necessary but not sufficient for what the words that’s been thrown around a lot these days, bubble. So a lot of FOMO going on. Now Matt, you and I have had quite a few debates about bubble, not bubble, maybe it is, maybe it isn’t. We’ve been, I think, pretty reluctant amongst ourselves to use the term bubble or to suggest that it is, but maybe give me your 2¢. When you hear I I don’t want you to say whether it’s a bubble or not.

I don’t think we wanna go down that path. But when you hear some of the ideas that are thrown out there about it being a bubble, what do you think about that idea?

Matthew Kempton: I think it’s definitely possible that that’s what it has become or it’s on the path to becoming a bubble. Like we’re pumping here and, you know, you can still kind of pump with ease. You haven’t hit that, like really can’t push the pump down anymore because it’s gotten so big. So maybe we’re at an earlier stage of pumping things up because you’re seeing I think in a true bubble, there’s true mania. There’s true you know, there’s tests around you’re getting in a you get in a cab or you get in an Uber and you’re hearing the stock tip from from the person driving the car or your barber’s giving you the stock tip.

And these are the these are historically these times of maybe things have gone a little too far here. And and I think occasionally those conversations are happening, but it’s not

Josh Sheluk: My tow truck driver is perfect example. Right? That’s true. So That was a year ago. That was even that was before the main event started.

Matthew Kempton: So we’re starting to see, like, those type of anecdotal type signs that, okay. There’s there’s a lot going on here. And you’re seeing, you know, when you look at the performance of the market this year, we talk about valuations. Well, some of the best performing companies this year have no revenues. So I I don’t even know how you value them.

I don’t even know how they fall into that, into that, you know, calculation of the valuation. So there’s mania there, but those companies are while they might be driving some returns for the market, they aren’t the biggest companies. And the biggest companies and the companies that I think would have the most impact if this is a bubble and it were to burst are, for the most part, in I’m pretty they’re pretty sound in terms of they’re making big investments, but they’re largely funding it with cash flow that’s coming in. They might issue debt, but it’s, you know, very manageable when you look at their balance sheets, the level of debt they are assuming. So there is a big spend happening, and it is it’s absolutely one of the big parts of what’s driving the economy right now.

So it a lot is tied in right now to what’s going on in AI. And, you know, often you know, I think it’s important to always remember that the stock market is not the economy and that the economy can do very well, the stock market can do different than that. There are different drivers of each. Right now, there’s kind of the same driver of both. Mhmm.

And so that that brings about some concerns too that if if it slows or there’s a misstep on this side, it the stock market or the economy might get hit too, and and and who knows where that takes us. So that I still don’t think that means bubble, but it means caution. Right. It means this is it’s a very important, not just story and exciting thing to talk about, but it truly is to where the economy might be headed, the stock market might go as well. But I don’t know if there’s that level of mania that would result in, you know, 80% drawdowns in the Nasdaq like you saw in the in the tech bubble or 90 plus percent in, you know, the great depression from just the mania that we saw in those phases.

So caution to be warranted, but I I don’t I’m not quite sure it’s a it’s a bubble or if it’s maybe it’s the very early stages and and you can deflate it from there, it won’t pop. You know? I I don’t know exactly.

Josh Sheluk: That’s not a bubble. If it doesn’t pop, a bubble. Yeah.

Matthew Kempton: So just let the arrow slowly. I, you know, so yeah, I would say not, I don’t believe it’s a bubble at least at this stage, but it’s something, see where it becomes in twelve months if this mania continues.

Josh Sheluk: Yeah. So caution’s interesting word, Maria. Matt used it a couple times there. You do focus a lot on individual company, individual stock research amongst your team. How are you staying grounded and avoiding buying into the mania through the research that you’re doing?

Maria Wagner: Well, some of the stock movements that we’ve been seeing, like, and fundamentals can’t change that quickly. And sometimes you see a company come out with a headline and then it goes up 25% over a short time period. And that’s just based off of expectations for the future that don’t really have much ground versus fundamentals, but it’s how we invest. I mean, if I think it’s more of a warning sign if a company is increasing by 20% over a small period time, maybe even a week.

Matthew Kempton: Or 55000% in

Maria Wagner: twenty months. That’s pretty crazy. So, sticking to our discipline, I guess, is just how we continue to not get sucked into those type of investments.

Josh Sheluk: Right. Looking for some concrete examples of revenue growth and profitability from something before we start projecting that into the future.

Maria Wagner: Exactly. And not getting too excited by something that does move quite quickly and be more skeptical, I guess, than excited.

Josh Sheluk: We’re great at a dinner party much. Not excited, very skeptical. The 55000% you’re referencing, there’s an Indian company that’s rumored to have grown 55% over what do you say? Was twenty months, Maria?

Maria Wagner: Twenty months.

Josh Sheluk: So pretty good one. As from what I saw, negative revenues is reported most recently.

Matthew Kempton: Yes. Two employees.

Maria Wagner: They were once a real estate company and then just put the word semiconductor in their name and rebranded this themselves. And that was the byproduct.

Matthew Kempton: All you need to do. That’s what the

Josh Sheluk: Yeah. So the three of us, we should have a company worth how many billions? If this is a bubble, if we look back five years and say, Yeah, that was a bubble, I think this would be probably one of the quintessential stories that people look back on and say, Of course, of course it was. What questions were there when you saw stuff like that? But yeah, so that’s kind of an astronomical, outlandish number for one specific company and one specific country of the world.

But I wanted to throw out some pieces of information or data points to the two of you and kind of get your reactions, like your knee jerk reactions on these. And these are not gonna be data points that you haven’t seen before, but just give me your first whatever jumps to the mind opinion when I say these data points to you. So Matt, I’ll start with you on this one. US hyperscalers are expected to spend about $450,000,000,000 on AI related CapEx in 2026. Thoughts?

Matthew Kempton: I mean, that’s a lot of money. Right? This is it’s absurd in some ways to hear numbers like that. And but it’s these businesses are so big. And I as much as we think that’s a big number, and it absolutely is, their management teams are sitting there and saying, this is going to be worth it.

We’re gonna spend this much. Or they might be sitting there saying, we have to do it, or we just don’t wanna fall behind. So there there is there is that risk to it. But I guess my first thought on that is it’s just an incredible amount of money. I hope they’re right.

Josh Sheluk: Yeah. It’s interesting because you’re right, these companies, they can pretty well finance this. They can finance a lot of it out of the cash that they have on their balance sheets and then for the rest of it, because they’re so low debt for the most part, they can easily finance it through issuing debt or issuing stock if they really wanted to. The biggest and most interesting whole part of this discussion for me is, and for these companies in particular is they’ve been capital light business models. They’ve had very little CapEx required for basically the entirety of their existence.

When you look at like Meta, for example, or Microsoft, where the incremental cost of building or delivering an extra version of Windows or Excel or something like that is basically zero. So you have a very capital light business model and they’re transitioning to a very capital heavy business model. And I think that’s the biggest question for me and what we might look back on and say, yeah, of course, we should have known that something was a little bit crazy at that time. It’s gonna be interesting to watch them transition, try to sort of move these hulking businesses from something that was very light on capital expenditures to something that’s maybe and and maybe consistently gonna require a lot of capital expenditures just to kinda replenish these data centers over and over again as the chips get obsolete. But time will tell.

Matthew Kempton: Yeah. That that’s really interesting because to the other companies who were in that space, capital light software, software as a service, those were, you know, the places to be for so long. They haven’t necessarily made that spend, but they’ve been hit so hard because of AI because, oh, can AI just do what you’d once did that I paid a subscription for? Why pay you however many thousands of dollars a month to do that when I could write my own program that could be just about as good. So while the capital light businesses that have maintained have been hit because of AI.

So AI is just it really is everywhere.

Maria Wagner: But have they like, has, I guess, monetization of AI been like, if you could draw parallels, I guess, to the .com bubble, these mega companies like the Meg7 have kind of come or were able to monetize their product much quicker kind of after that .com bubble. And how long will it take for them or to become profitable with their story with with the different landscape of needing more maybe debt to finance these infrastructure projects? And how long will that take, I guess, for the these companies to be profitable in a different landscape? Yeah.

Josh Sheluk: Yeah. In some ways, some of the companies were really born out of the dot com bubble. But yeah, and I think that is like literally the trillion dollar question is, are they gonna be able to monetize and generate a paw, not only a profitable, but also a sufficient for current valuations return on investment. I think that is the biggest question at this point for them. And I think because these companies make up such a large part of the index and the global benchmarks now, that’s what’s also gonna drive stock markets as a whole.

Maria Wagner: Did that also skew, I guess, like how investors look at these projects to be like, well, now we can justify all this spend because it’s required and it is not the same as this .com bubble. They don’t need debt to be unprofitable. Companies have lots of revenue. They just is this skewing, I guess, people’s investment thesis by being justifying large CapEx spend because they think that it’s required to get to that monetization stage? Yeah.

Josh Sheluk: And think that’s certainly as we talk about bubbles and comparisons versus historical periods, which has been rehashed many, many times out there over the last several months, especially, that would be a really big meaningful difference is during the dotcom bubble, the companies were a lot less profitable and a lot less dominant in their traditional business models than they are today. So we will see. But I wanna change directions a little bit and ask you this one, Ria, throw this data point at you. OpenAI’s valuation, reportedly somewhere between $500 and $750,000,000,000 depending on where you look.

Maria Wagner: I mean, I think it’s easy to throw those numbers around too, especially if it’s a private company. They can hide a lot of things on their balance sheet and you won’t know until there’s an IPO, really. But there is a lot of also public companies that are realizing a lot of intangible assets that are essentially affiliated with AI spend and saying, this is going to be a realized value in the future. We don’t know what it is, but it’s going to be put the word AI in front of it, then it makes a lot of sense. And then it really improves your balance sheet.

So I don’t know how much of the value of OpenAI is just an intangible asset and how that will skew things.

Josh Sheluk: Yeah. Depending on how tangible you think ChatGPT is, vast majority of the value of that business is somewhat intangible at the moment because the value of the business relative to the revenue and the profits, which are non existent at this point is quite massive. But let me throw a different one at you, a different company, public company this time. So Nvidia became the first company to hit a $5,000,000,000,000 market cap, Maria. And just for some comparison, how large that is, larger than the entire stock market of The United Kingdom, larger than the entire stock market of Canada, larger than every country’s GDP, except for The US and China, would be a $5,000,000,000,000 mark.

So you can own every company in Canada, literally every company that’s publicly traded in Canada, or you can own Nvidia. Those are your two options. Which one do you pick?

Maria Wagner: I mean, as a portfolio manager, I cannot just say Nvidia because of diversification. Again, there’s a lot of expectations for where this company can go and there’s been a lot of historical comparisons that the leaders of today aren’t necessarily or even having a first or third advantage isn’t necessarily a good thing long term. So to be 100% invested in any AI company right now would be a big concern for anyone. And hopefully, that’s not the case of any one person. But, yeah, I think the story can flip quickly.

Mean, we’ve seen kind of examples with the Oracle company being a front runner and now back to where it was before this AI boom. Being fully invested in any one company is definitely mistake.

Josh Sheluk: Yeah. Well, and that’s a couple points there that you made. Just wanna emphasize. So being first mover doesn’t always give you an advantage when things actually play out. We saw that in the tech bubble and .com bubble, for example.

And really what probably happens is a lot of these companies disappear at some point, there becomes some type of more concentrated power. And I was reading about the automotive boom in, I guess it was like the 20s in The US and the story that I heard about that, it was there was 2,000 companies at that time and basically three ended up making it. Your GM, Ford and Chrysler, the ones that made it through. So it’s not to say that that’s necessarily gonna happen today, but definitely something to be cautious about, as you said. But I’m glad you brought up Oracle because I had another data point on that.

I’ll throw this one to you,

Maria Wagner: Matt. It’s

Josh Sheluk: such a great story. So it saw its market cap increase by about $400,000,000,000 over the span of a couple months. And then it dropped by about $480,000,000,000 This all happened within a six month time span. So two months basically rocketed right up and then two months came crashing right back down to earth. So a 65% increase and a 50% decrease if you owned it for the last six months, you’re down 14% on the stock.

Crazy.

Maria Wagner: And it’s wild, yeah. Then that just kind of shows you that there’s a lot of expectations out there that are even very fragile. I read somewhere that since OpenAI, I don’t necessarily feel affiliated with Oracle, but just the AI story, I guess since OpenAI was launched in November 2022, there’s been $24,000,000,000,000 added in market cap to the stock market. And only 12 to 15% or 12 to 15,000,000,000,000 of that has actually been affiliated with earnings growth, and the rest is just expectations. So Oracle’s a good example of, oh, this is gonna be this is a new winner, obviously, based off nothing but just some headlines.

Then it just goes down because there’s actually been no infrastructure investment and what people expected was way too frothy for its valuation. Right.

Josh Sheluk: Yeah. So that kind of brings up like that amount of market appreciation due to earnings worth is actually quite substantial. I think if you ask most people, they’d say, well, it’s all expectations. No, it’s not actually all expectations. And this comes back to sort of countering the bubble argument.

But Matt, you and I have been going back and forth a little bit on the way that AI is really driving the market. You sent something to me last week, but what I have also seen is headline from b BBC that 80% of US stock market gains in 2025 came from AI companies.

Matthew Kempton: Yeah. I mean, AI, it it’s been the real driver. Well, it continued this year. And the and the Oracle one I mean, I guess I don’t know when that headline came out because Oracle might have been part of that those returns depending when that was dated, and it would not have been if it was dated a little bit later. I think the Oracle one is just, like, one of the in the list of crazy examples, it is it’s definitely up there just given the size of the business.

It’s a hundreds of billions of dollar business, and it depends what day, I guess, how many of those hundreds of billions it’s it’s truly worth. But, you know, Josh, was sharing this with you a bit just how what it sort of struck me as is that no one, I don’t think, ever quite has understood what Oracle does. Like, it’s been around for decades. Larry Ellison, one of the richest people in the world, or it’s always just kinda hung around. It’s been this tech company that’s been, you know, no one’s ever top pick, but it always just kinda sticks it out.

And then after their second quarter earnings, everyone seemed to find out that they were actually a cloud business, and the business went up and it went up 30% in a day, but everyone found that out. And since then, it’s people have been less comfortable with that part of the business or just the commitments they thought they had, and it’s worth less than it was, you know, at that announcement. And it struck me it really reminded me of a scene from a movie. And, Josh, I was telling you about this. The movie Hardball.

It’s it’s a great movie. And in the movie, Keanu Reeves, he coaches and, you know, some some kids from that, from lower income neighborhoods. He becomes their baseball coach. And at the end of the movie, he gives them a speech, John, how proud he is of them of showing up. He says, blown away by their ability to show up.

And it feels like that’s what Oracle has done just forever. They just kinda show up. They’re just kinda there, and you don’t really know what they’re doing. And then eventually, the market really rewarded them for being there, taking some of that back. So I guess it’s not it’s not all about just showing up, but that is you can do pretty well just by showing up.

And Larry Ellison’s still off on his on his private yachts. I think he’s still pretty happy.

Josh Sheluk: Yeah. I mean, give give somebody $300,000,000,000 or whatever he has now, I think. I mean, I guess it’s less now. He what? Yeah.

Was he was he briefly the richest person in the world recently or was was Elon was that still Elon’s title to hold?

Matthew Kempton: I’m not sure if he passed it for that day or not, I think. Yeah.

Josh Sheluk: Well, yeah, anyway, he had a pretty big ride with his net worth over the course of the last couple months as well. So Maria, this is a recent MIT report. MIT reports suggest that 95% of AI pilot projects don’t yield ROI, positive ROI, return on investment. 95%. What do you think about that?

Maria Wagner: I think that’s true. Again, I think I’ve mentioned this earlier in the podcast about just drawing parallels between expectation AI will improve in productivity. And even the best case scenario in a lot of those studies being that 3% annually isn’t sufficient enough to kind of justify these valuations that we’re seeing in the stock market. So I think AI is definitely like, the expectation is that it’s going to improve productivity, but that doesn’t necessarily mean it’s gonna be a good investment. Mhmm.

And I think that’s an important distinction that investors have to keep in mind is just because this technology isn’t gonna go anywhere, like, that’s, I think, an undisputed fact, Does it mean that these companies that are investing so heavily in CapEx are going to become profitable in the next three to five years, which I think is embedded in all of the prices we’re seeing today, but might not necessarily be a material result that we end up seeing.

Josh Sheluk: I think it’s been said, humanity often overestimates the impact of technology in the short term and underestimates it in the long term. So this might be an example of we’re not quite getting the results that we wanna see short term, but maybe five years from now, we do see 95% positive ROI on projects. So it’s hard to I think the the key point that we’re saying, we keep coming back to is it’s really hard to know.

Matthew Kempton: I could just offer something on the pessimistic side just like just to what was being said there. The to just to show an example of how hard it is. Earlier in the year, there were a lot of articles out about how JPMorgan had spent $2,000,000,000 on AI investments, and they had finally seen $2,000,000,000 in in productivity results. So they made zero on their investment, but that was being heralded as look at this. JPMorgan, one of the biggest companies in the world, they have actually seen some results, but not even past their spend.

But that was still a big deal. So we’re definitely early days, and the ROI is, I think, mostly to come. Hopefully, it is sort of it is in projections. It is just in the spreadsheet really for the time being, but, hopefully, it will come. But it’s it’s still early days in a hard investment.

And another area where I’m a little pessimistic on AI is that it’s hurting I think every time we say it in this in this fashion, we’re hurting the legacy of the original AI, and that’s Allen Iverson. And as an Allen Iverson fan, I just want to make sure we don’t forget about him. And we don’t have AI only mean this new term, the original AI is Allen Iverson. Just wanna make sure we don’t forget about him.

Josh Sheluk: Okay. Yes. One of the most exciting guards to watch of the early two thousand. That’s for sure.

Matthew Kempton: That’s right.

Josh Sheluk: All right. So optimistic quarter data point here. So this is actually a quote from Sam Alvin, Matt. We are now confident we know how to build AGI as we have traditionally understood it. And to continue with this quote, we are beginning to turn our aim beyond that to superintelligence in the true sense of the word.

We love our current products, but we are here for the glorious future. With superintelligence, we can do anything else. Superintelligence tools could massively accelerate scientific discovery and innovation well beyond what we are capable of doing on our own and in turn massively increase abundance and prosperity. So you can’t really get much more optimistic than that. Sam Altman, the CEO of OpenAI, But when you hear somebody say that, what’s your first reaction to it?

Matthew Kempton: I mean, my first reaction is he has to say that. If he’s going to attract the the level of investment, if his company is going to be worth 700,000,000,000, he’s he better have that mindset. But I I think it’s I think it’s true. And I think it’s that’s the, you know, the power that, you know, you can use AI to make you a meal plan, and that’s a great use for it. And it’s it’s helpful in just these very mundane simple tasks.

But the the you know, where I think it’s going to take us and and likely where already it’s helping, you know, in scientific research and and the progress that we can see because of this just this AGI that is, you know, and all of these different companies fighting to be the best at it. I mean, we’re as consumers, as members of the economy, we’re probably in the best spot we could be in and okay. You fight it out. You, with all of this capital, build the best possible thing you can build. It doesn’t mean it won’t be without bad impacts and possibly job losses, and and there will be it won’t all be great.

But if if that’s the race they’re all in and the race is happening in China as well, it’s not just happening in this part of the world. And, you know, you you get news all the time. You hear about something called deep seek. And, oh, by the way, they’re way better over here at AI than than they they’re doing all these things that you were told were not possible. And so it’s moving so fast that, you know, the just the the applications of it in, you know, today and and in a few years, I think we’re gonna be living in potentially a very different world.

So I I think there’s very good reason to be optimistic. Some reason to be scared, probably, but optimistic definitely. You know, Sam Altman, he’s one of the leaders of it, so he better be optimistic. And in some ways, you wish him the best, and, you know, we’ll see we’ll see where he goes.

Maria Wagner: I think it’s also easy to be optimistic because we are see like, there are use cases for it right now. Even if they’re small, there are like, a lot of companies have integrated AI in some capacity in their day to day work that has improved their operational efficiencies. So it’s easy to Including get us. The mindset of

Josh Sheluk: So I think we see firsthand some of the benefits that can come out of it for sure.

Maria Wagner: And even on the research side, it saves you a ton of time with reading through 100 page documents. So it’s easy to get caught up in the narrative of, if this is where it is today, where will it be in five or ten years? It’s hard to, again, of make that a separate thought of, are these companies profitable? Will these companies be profitable in three to five years versus will this be a revolutionary technology? What do think it will be?

Josh Sheluk: Well, it’s crazy to think that almost literally three years ago, we didn’t have any of the AI as it exists today. Like the LLM, chat GPT type AI didn’t exist. It was just over three years ago that it kind of came out. So if it’s advanced to where it is today from literally nothing three and a half years ago, then you can kinda get caught up pretty easily extrapolating what that means for three and a half years from now.

Maria Wagner: Right?

Matthew Kempton: Yeah. What’s pretty incredible is if you probably seen charts that have done this, I know I’ve I’ve seen these charts, but the the 2022 poor year for the stock market. If you plot the launch of chat GPT, which I think was November 2022.

Maria Wagner: November. Yeah.

Matthew Kempton: Open And you see what the market has done since then. Like, it’s like a it didn’t exactly call the bottom. It didn’t but it didn’t maybe create the turn in the market. But since the launch of ChatGPT, you know, one or whatever the first version was called, The market has, for the most part

Maria Wagner: Well, it’s a 24,000,000,000,000 that it’s added Right. Market cap Right. Yep. Since the launch of traffic abuse.

Josh Sheluk: Yeah. And correlation or causation

Maria Wagner: High material.

Josh Sheluk: Correlation or causation, we could probably argue both sides of that. There’s probably some elements of both. But if you were sitting there very pessimistic late twenty twenty two, like a lot of people were, all of a sudden, maybe the most revolutionary technology comes out in our lifetime. That’s another reason why we should be a little bit suspicious of anybody that thinks they know what’s going to happen next. We’ll kind of come to the end here and wrap this up, but I want to give you each the opportunity, positive, negative, neutral.

What is the one thing surrounding all of this AI stuff that is most interesting to you? So Maria, let’s start with you. What is the most interesting to you out of this whole narrative, this whole story that we’ve built over the last few years?

Maria Wagner: Right now, it seems that we only care about the hyperscalers of AI as an investment right now, but I think a lot of the beneficiaries will be the people who are much lower on the supply chain, the companies that aren’t necessarily in the, in the spotlight nor have AI mentioned in their earnings call on every other word or have it in their business description, but are actually using AI to optimize their business via supply chain optimization or other things like that, that will actually improve their bottom line and don’t need to invest billions of dollars in infrastructure to implement these AI strategies.

Josh Sheluk: Just an anecdote on that. So I’m gonna get the numbers wrong, I can’t remember the researcher that published this, so forgive me. But somebody was surmising that like, just take Walmart as an example. So Walmart runs something like 3% margins on its business because it’s so it’s such a massive scale business, but extremely tight margin business. So they’re suggesting that if, not saying that this is likely or even possible, but let’s say AI helps Walmart expand its margins from 3% to four percent.

That’s monumental for that business. And I think that’s what you’re talking about, Maria. We don’t know what those spillover effects necessarily gonna be for every industry that is maybe not at the forefront of AI, but could see a profound impact from it. Matt, what about you? What’s most interesting about this whole story, this whole narrative for you?

Matthew Kempton: It’s similar to that. Mean, it’s really just, it’s the application. Like you, this stuff is incredible. I I don’t I think I think we should just yeah. It’s been a few it’s only been a few years.

It’s been in our lives, but it’s just how amazing this technology is. The even the mundane ways that I would use it, I’m still just, wow. It’s it’s such it’s such an advantage versus, you know, 2021, Matt, 2025, Matt now has this. And I could just you know, it’s such a great assistant, and and who knows what it will form into. And then I, you know, I think we might be sitting here in one of these big phases of the economy.

Like, you know, you look back the industrial revolution, you know, the, well, the the railroad expansions, the the telecom build out. I I think we’re in one we’re in one of these big phases right now. And, you know, one of the big worries of for some time, I think, in the economy have been no one’s building anything anymore. No one’s spending. Capital expenditures have declined.

That’s not happening anymore. So I suppose whether it goes well or not, we’re seeing there will be benefits if not today, then hopefully and if someone will benefit from what’s happening right now, maybe it’s the current players. We’re in one of those sort of times that you’ll you’ll see you know, people will study, and it will change the world in in many different ways. I think that’s really exciting to to to be seeing it on the ground, and, you know, we’ll find out sort of where it goes. The story will be written.

It it hasn’t been yet, but it’s, I think it’s just a very exciting thing to be a part of. And some will make money, many will lose money, but, I think the world will improve as as part of it.

Josh Sheluk: And that’s, I think, a very optimistic way to end the podcast. So thanks a lot for joining me, guys. Is any final departing thoughts that you wanna share?

Maria Wagner: It’ll be a 100 invested in NVIDIA.

Josh Sheluk: Is sage advice, Maria. But you

Matthew Kempton: Yeah. The the theme, and I guess we’re just coming up on Christmas here. You know, if you run it out of if you have no ideas, run it through run it through AI, and that’ll save you here come the holidays.

Josh Sheluk: That’s a good plan. The amount of input that you put into your GPT is gonna gonna benefit the the type of output that you get out. So give a little bit of description of the person that you’re looking to buy for. Otherwise, you might not put

Maria Wagner: But no no social insurance numbers. Keep those up. Yeah.

Josh Sheluk: You you don’t wanna end up with a new set of pots for your newborn. That probably won’t go over too well. Well,

Matthew Kempton: it they’ll still you know, you’ll get they’ll they’ll play the drums. You might have a drummer in your life. So you never know.

Josh Sheluk: That’s right. They’ll they’ll make a a Toyota or anything. So Yeah. Well, that’s great, guys. Thanks so much for joining us.

I think it really helped provide a balanced view of everything that that we’re seeing on the AI space, especially as it comes to investing and as it relates to investing, and I I think that’s always a huge focus of this podcast. So appreciate you guys being here.

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