What the Steam Tractor Can Teach You About the AI Boom

Every era has its breakthrough. The steam engine. Electricity. The internet. Today, it's AI. History doesn't repeat itself—but it does rhyme. 

#AI #ArtificialIntelligence #Technology #PursuitWealthGroup 

Transcript

SPEAKER_01 0:00

Hi, welcome to Pursuing Knowledge, brought to you by Pursuit Wealth Group. My name is Brittany Drish, and joining me here today is Tyler Speezio. And today we're going to be talking about something that's in the headlines a lot, whether it's exciting or people are scared of it. But artificial intelligence. So, Tyler, if you kind of want to kick us off with that.

SPEAKER_00 0:19

Yeah, uh artificial intelligence is everywhere. A lot of people know a lot, a lot of people know nothing. I think at Pursuit Wealth Group, we try to stay on top of it all. But in this talk today, we're not going to talk about the technicals too much. We are not an AI firm. We are an investment firm. So we'll talk about the investment side of AI. So if you want to learn more about ReLUs or other technical things like that, this is not the talk for that. But if you want to learn about kind of the high-level 10,000-foot view and how we're thinking about it in terms of our investments, this is the spot.

SPEAKER_01 0:53

Perfect. So let's start out with the basics. What is AI?

SPEAKER_00 0:56

What is AI? So AI is artificial intelligence. That's that's an easy one right off the bat. So how to get that leadoff hit there. But what AI is, in its simplest terms, is the simulation of the human mind using math. So what does that mean? I think the easiest way to equate that is to look at the industrial revolution. That's the easiest way to think about what does a simulation mean? So in the industrial revolution, we can think about that. That was a simulation of the human body using steam. So say, for example, you had a farmer, you had 10 farmers, it took 10 farmers to plow that one field. Now you have a tractor, it takes one tractor and one farmer to plow that field. So that tractor simulated the equivalent of 10 human bodies. Okay. AI is a simulation of the human mind. Say it used to take 10 coders to code an app. Now it might take one coder, for example. So that's how we think about AI.

SPEAKER_01 1:54

What would be a real life example of AI that people use every day that they maybe don't think is actually AI?

SPEAKER_00 2:04

Yeah, that's a great, that's a great question. So let's keep this super simple. In terms of how AI is structured, in my mind, and a lot of the business leaders we used to work with, the way they think about it is there's really three pillars of AI. Okay. So the first one is data. That's just all the information that's going into the AI system. The second one is you can say the algorithm, kind of the fancy stuff going inside from an investment or a business perspective, we don't really need to know what algorithm or what hyperparameters or parameters we need we need, but just know that's kind of where the money is. I like to think of it as the biggest if-then statement you've ever seen. Right. And then finally, we have the prediction. Okay. So one thing about AI that is a little confusing is that AI is not an actual person talking to you. We all know that. What AI really is, it's it's a prediction machine. So using an example, yeah, it's the easiest way to show this. So say you take out your phone and you want to unlock it. All you have to do is turn it to your face and your phone unlocks. How does it do that? It uses a simplified AI system. So let's go back to the three pillars. We have the data, we have the middle piece, that big if-then statement, the algorithm, and then we have the prediction. So focusing on the data of unlocking your phone. The data going into your phone is just a picture of your face.

SPEAKER_01 3:20

Right.

SPEAKER_00 3:20

I don't know exactly if it's infrared or whatever your phone is using, but essentially it's capturing all those complexities, those details of your face that make your face your face. My face, not Brittany's face. So that's the data going into it. That's the first part of the AI system. The middle piece, this big algorithm, this big if-then statement is where the magic is happening.

SPEAKER_01 3:40

Right.

SPEAKER_00 3:40

So that data is going in into the second piece here, and it hits the first little if-then statement, that first little dot. That first dot is saying, hey, is this Tyler? Does he have brown hair? I do. So then it'd go to the next one and say, Does he have a big nose? I've been told I do. It'd go to the next one and then it'd say, Does he have blue eyes? I don't have blue eyes. That would stop, and then the prediction would say, we predict that it's not Tyler.

SPEAKER_01 4:05

Okay.

SPEAKER_00 4:05

But if it was, does he have hazel eyes? And then it'd go through and it would predict that 98% chance this is Tyler, 1% chance this is, I've been told I look like Mac Miller, and then 1% chance this is not Tyler. So 98% chance that it's probably is Tyler, it would go through, and then the prediction would be this is Tyler, the phone on the block.

SPEAKER_01 4:24

Okay. And the more you use it, is it kind of teaching itself or learning based off of that data?

SPEAKER_00 4:30

It totally depends on the AI system you're using with the phone. I'm not quite sure. Okay. But for the people that created the phone, the more you use it, the more you can train the algorithm and the better data you can get for it, the better it's gonna be.

SPEAKER_01 4:42

Okay.

SPEAKER_00 4:42

And if we think about AI today, the AI today is the worst AI we're ever gonna see again. That's that's something one of my old mentors used to say the AI today is the worst AI we're ever gonna see again. And that is because the models are constantly uh trained, right? And then the data we use is constantly being refined and better used.

SPEAKER_01 5:02

So, where is all of the money that's going in to build these trillion dollar systems?

SPEAKER_00 5:08

Yes. So this is where we get into what is the AI conversation, more to how are we thinking about this app pursuit, how are we thinking about this in the Wall Street Journal, so on and so forth. Yeah. So now we know how AI works, we have a better idea of what it is. Why is why are people talking about it on Squawk Box? No one really talks about coders on Squawk Box besides Steve Ballmer every once in a while, but why are they all talking about AI? And and that is because of the trillion dollars you're talking about getting invested. The stock market the last few years is has has skyrocketed. There's there's no denying that. And a big reason for that is because the tech companies, a lot of them like Micron or Nvidia, those big tech companies are making a ton of money. And that's just because if some places put this number in different spots, but we can say pretty confidently that about five trillion dollars, and that's what the T, five trillion dollars have been spent on AI.

SPEAKER_01 6:00

Wow.

SPEAKER_00 6:02

That is more than the interstate system and the Apollo program combined. So this is just a ridiculous amount of money being spent in AI. And if you're an investor, say in Nvidia or Micron or another one of these companies, you're like, holy cow, five trillion dollars being spent on my product or associated products. That's really, really exciting.

SPEAKER_01 6:20

Yeah.

SPEAKER_00 6:21

All right, now we're gonna flip that coin and look at the other side. About only a trillion dollars have been returned on that five trillion dollar investment. Wow. So say I'm an investor, say you come to Pursuit and say I have this great investment for you. You put $5 into it, you're gonna get a dollar back. I don't know if you would stay around for the next meeting. How patient are you, all right? Right? Exactly. That's the question. How patient are we? So some of these companies, if you think of Google, if you think of uh not Apple, if you think of Microsoft, if you think of Meta, these artificially scarce companies. These companies that sold products that weren't physical, but were were code our source. So for example, if you have a Netflix account, I buy, I buy an account from Netflix, it costs Netflix a dollar, Brittany buys an account from Netflix, it still costs Netflix a dollar. Their costs never rise based on how much they sell. So these companies had huge free free cash flows. They used to spend 5% of it. Now they're spending up to 90, 95, even over 100% of their free cash flow on these on AI, on things like data centers.

SPEAKER_01 7:32

Okay.

SPEAKER_00 7:32

So these companies that used to be incredibly profitable are no longer profitable. Is that a problem? It depends on the patience and the confidence you have in AI, right? Yeah. So today, it's not making much money. And the car didn't make much money when Mercedes first invented the car. Right. Going back to the industrial revolution. But in the future, are the investments these companies are making, will those investments pay off? That's what that's what we're concerned about, and that's what we're thinking about every day.

SPEAKER_01 8:00

I think something that when people hear AI, they're fearful that it may take their jobs in the future. Where um, or has there been an example in the past of this similar situation? Maybe not AI, but how you know that developed.

SPEAKER_00 8:18

Oh my gosh, yeah. So that is one of the things that is the scariest about AI is how it's displacing jobs, especially in the software and coding space. I think it was Meta or Microsoft, or it might have been both of them. I know Amazon, you can throw this in there as well. They laid off about 20 to 30,000 employees each, more on the software coding side, because they thought AI could replace it. So we're seeing that displacement today, and it is real, and for folks in those fields, it is scary. Right. And for folks in more, especially white-collar jobs, it is scary to think about how can I be replaced. And there is a threat. There is a threat there, and it is scary. But going back to the industrial revolution, I think we can learn a lot from history here.

SPEAKER_01 9:01

Right.

SPEAKER_00 9:01

So take ourselves back to that field. So in that field, you are a farmer, say you're you're a farmer, a serf in Russia, and you just lost your job because a tractor came into town. And you said, and we ask you, hey, what do you think about the industrial revolution? That farmer would say, I hate the industrial revolution, I lost my job, and fairly so. And if we even go to more specific example, there were some uh textile, textile workers in England called the Ludites, and they got so upset that their way of life being about their way of life being displayed that they actually went in one night and destroyed all the factory factory mills.

SPEAKER_01 9:39

Wow.

SPEAKER_00 9:40

Outrage, you know, well, well deserved. They lost their jobs because of the technology.

SPEAKER_01 9:47

Right.

SPEAKER_00 9:47

But if you were to go to one of those Ludites or you were to go to one of those farmers and ask them, what do you think of the airline industry?

SPEAKER_01 9:53

They'd have no idea.

SPEAKER_00 9:54

They'd have no idea, right? And that's and that's that's the positive side of AI. Yeah. So say today we are in this AI revolution. In the short term, it it does hurt. People are losing their jobs, and that is not something to beat around the bush about. Right. But if you want to have a positive lens of it, you can say, well, there was an airline industry because of the uh industrial revolution.

SPEAKER_01 10:16

Right.

SPEAKER_00 10:17

Could there possibly be an airline industry or an industry that we don't know about for the AI revolution as well that we can't see? And the hope is that there is. A lot of industries are starting, starting to get there. I know in the pharmaceutical industry, there's a lot of new research going into it. Obviously, with software, there's a lot of new research going into it and ways that we can see AI helping us. But those aren't brand new industries.

SPEAKER_01 10:41

Right.

SPEAKER_00 10:42

Is there a brand new industry out there? I'm an optimist. I hope there is, and I think there is. We just don't know what it is yet. And by nature, when you're in the middle of a tech breakthrough or something like that, you don't know you're in the middle of it until it's over.

SPEAKER_01 10:54

Right. Lots of scary thoughts with AI coming in. But you know, if you choose to stay on the positive outlook and mindset of things, there could be a whole another plethora of jobs or opportunities that AI does open up for people.

SPEAKER_00 11:08

So for sure. Yeah. And we can start seeing that a little bit today. And maybe this is more of an aside, but going back to those companies like Nvidia and Micron, those companies that are profiting so much off of AI, on the tech side, there's a lot of gain there, but there's also a lot of loss from the layoffs. That's one thing we're talking about. But the AI revolution isn't just helping or helping or hurting the white collar industry.

SPEAKER_01 11:33

Right.

SPEAKER_00 11:34

If you want to look at some of the biggest winners of this, this AI spend, just go look at Caterpillar. Go look at John Deere.

SPEAKER_01 11:40

Yeah.

SPEAKER_00 11:41

Those comp those companies that are traditional, you know, they make they make the products, the products moves the earth, and that's kind of the end of it, or the product makes the energy, and that's the end of it. These data centers take up so much space, so much water, so much energy that more say more traditional non-tech companies are now winning just as much as Nvidia and Micron. So another side of the coin there as well.

SPEAKER_01 12:05

Yeah. Anything else you want to leave the listeners with any of your insight on AI?

SPEAKER_00 12:12

You know, I think my one insight would be I'd actually, I'd say there's two insights. One, we we've been here before. Or another way to say is his history doesn't repeat itself but it rhymes. So going back to the industrial revolution, we've had technological breakthroughs that have displaced the workforce before. There are ugly parts and there are beautiful parts about that. Being an optimist, we can hope that as the industrial revolution helped us get to where we are today. We can hope the AI revolution helps us where we need to get tomorrow. I say that that's one takeaway. We've been here before. It is scary, but there is light at the end of the tunnel too. It can be a great thing. The other one I would say is I iterated this before, but just want to re-harp on it. Is the AI we have today is the worst AI we'll ever have again. Right. You go in, you can ask AI to help you make a new pasta recipe. I do that, I do that quite often. I'm not a great cook, so I go to AI for that, and it's super helpful. But if you ask AI a more nuanced question, it's not quite there yet. Right. You have to check it, it hallucinates, so on and so forth. There are shortcomings for AI. But tomorrow the model will be better.

SPEAKER_01 13:20

Right.

SPEAKER_00 13:20

And the month after that, the model will be better. And a year from now, the AI we are using then is going to be totally different than the AI we use today. Right. The pace of progress is astounding. So it'll only get better from here and more impressive. So I would say don't give up on AI. If you can use it, use it. Yeah. And as investors at Pursuit, we're constantly thinking about what it can do and what are the companies that are investing it and using it doing. So it's an exciting time, it's a scary time, but we're here for the ride.

SPEAKER_01 13:48

We're here for a whole bit. Awesome. Thank you so much for your insight today, Tyler. And um, if you are watching this video, this video does not constitute any legal tax or investment advice. If you have any questions, please reach out to your advisor. Um, but we will see you next time on Pursuing Knowledge.