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Hello and welcome to another episode of the Outlass podcast.
I'm Joe Wisenthal and I'm Tracy Allaway.
Tracy our colleague here at Bloomberg at Harrison, had interesting newsletter today and it's actually something I've been thinking about a little bit lately, which is that for all the talk of the AI boom or the A bubble driving the stock market, there's no AI pure plays really that are publicly traded. Like in video is probably the closest, but three years ago people were excited because they were mining ethereum. Before that, it was like video games. You know,
this was only an AI company in people's mind. For since late twenty twenty two, Google still is you know, we know they're all investing in a ton. There's actually no like no AI company that people are excited about in the public markets.
I mean, I think it's true. Here you have this thing that a lot of people would say is revolutionary technology, right, but you kind of have to decide if you're going to invest in it, is it going to be like upstream or downstream? And there doesn't really seem to be that much pure play, as you say.
As our colleagues said, Verma might like to say, people are investing in the picks and the shovels, you know, this gold rush. I don't think he actually said that. It's just a million other people's but it is.
It shovels, it's fun, a completely reasonable commentary, That's what I say.
Is there? You know, it turns out instantly picks and shovels have been great. You know, you could have bought Caterpillar, or you could have bought some old school HVAC company that's providing cooling or heating or whatever and made a ton of money. So actually, it turns out, at least for the last few years, all those awful cliches have actually been big money makers and I should not make fun of them.
Well, here's the other thing I would say. It does feel like everyone kind of agrees at this moment in
time that there is froth in the market. Maybe it's on a massive bubble, right, but there's some froth, and everyone is kind of admitting or saying that you're going to have some companies that emerge as big winners, much like the dot com era, and then a bunch of companies that like actually end up being losers, and I think again, like that is consensus at this point, but it doesn't really necessarily translate into actual investment, because of
course the trick is actually picking the winners and losers in the market.
Yeah. I don't know.
It just seems like a weird point in time where people are like, oh, yeah, AI is great, but we all know that some of these companies are going to be massive losers, right.
I think now they're all kind of big treated as winners, which is the other thee Yeah, anyway, it's a very weird time. You got to do more episodes on this because it is sort of the central question for on whether we're just talking about the market or talk about the economy, et cetera. Someone I've wanted to talk to for a long time. Earlier this year he wrote a essay for Colossus called AI will Not Make You Rich. It came out in September. It seems like ages ago.
It's very disappointing because I think a lot of people really are hoping to get rich on AI, so this is a very unwelcome message.
It's also very much a sort of core odd Lots thesis because in the essay he compares and contrasts AI with containerization, which is another which facing.
So let's just get to the guest. Someone I've wanted to talk to for a very long time, someone who literally is the perfect guest longtime VC started a venture investing in nineteen ninety seven. Also a professor at Columbia Business School. We're going to be talking to investor Jerry Newman, also the co author of a recent book, Founder Verse Investor, The Honest Truth about Venture Capital from Startup to IPO. Maybe he'll tell us one we'll see.
You the bringer of excess Halloween candy. So he gets he gets brownie points for that.
Literally the perfect guest. Uh, Jerry, thank you so much for coming in. Thrilled to finally have you here.
Thanks, I'm glad to be here.
What does that mean? A I won't make you rich. AI has made people super rich, and it's making people rich every single day.
You know, as an old mentor used to say, money is not money till it's cash. Okay, So is anybody really rich yet? Oh? Come on?
I mean Jensen Wong bought an entire bar in Korea. He's like bought beer and fried chicken for everyone.
He's right, I think it's smart to cash out early. Okay, that's what he was doing. Okay, let's say you I really believed it, would you be selling at stock now?
I mean, see what you mean talk about this because you obviously have a lot of experience. Actually, that brings another line of question that I want to get into. But what does that mean it's smart to cash out early when in your experience? What does that actually mean?
So, look, I believe that AI is a revolutionary technology. Okay, I'm going to put that on the table.
Which is important to say because not everyone agrees with that.
So that's yeah, totally. You know, I'm on Blue Sky and nobody agrees with that, but I do. I think so. But there's a difference between value creation and value capture. So even if AI creates a lot of value for society, who's going to get that value? Is it going to be the early investors? Is it going to be the court, you know, the foundation model companies. Is it going to be YEA consumers? You know? They think that's the question people need to ask.
I actually broadly agree with this thesis when it comes to AI, but maybe just to clarify the idea here, compare and contrast this current AI cycle with maybe previous technological breakthroughs. And you know, I mentioned containers. I think a lot of people aren't used to thinking about boxes as this major advancement in technology, but at the time they really were.
Yeah, I mentioned containerization, and most of my peers think I'm talking about doctor. So I'm talking about shipping containers. Right, the big boxes they put on ships, and then they can move from the ships onto the rail cars and now to the back of trucks. And this was a revolutionary technology. I mean it changed everything about the way
we live. I don't remember. I'm probably a little older than you all, but when I was a kid, my grandmother used to send up oranges from Florida at Christmas time, right, because they were rare. You couldn't just go into a grocery store and buy them. Now you can buy oranges anywhere at any time. People don't really realize how much our lives have changed because of shipping containerization, because of these global logistics and the globalization of shipping. Now this
is utionary technology. Who got rich from it? I mean generally, if you look at the nineteen sixties, say how many people became wildly rich from technological innovation? Can you think of anyone? Because I've been asking this question for years. There are people who got rich in media and whatnot, but there wasn't a lot of technological innovation that made individuals.
It just start, like twenty years ago, did they have technology.
Bout the right? I mean, it's I think this is the thing. Right, So we talk about computer technology, the information and computer technology revolution as technology, but obviously this has always been technology. But only at certain times in this technological cycle do people seem to make money as investors and as inventors.
Explain more, though, because I mean I could argue that Marisk or someone like that got pretty rich off of containerization. Like maybe it took a while, but even though the shipping industry is highly cyclical, when they are in the boom period, they make a lot of money.
Sure, I mean, the existing shipping companies got very large and made a lot of money. They got larger and made more money. Is mayor you know who made money.
Completely new entrants?
Yeah? So just to me as background, I'm a venture capitalist, right or have been a venture capitalist for a long time, recently retired, And I think about people investing in making money new companies, inventors or entrepreneurs making money, not the existing incumbents making money. And I think that people will make money on AI. Might be Microsoft making a ton
of money on AI. It could be AI. You know, when containerization shipping containerization came around, Sealand was the instigator of this, and the founder of Sealand made money primarily because he sold early, right, he sold Sealand to r J Nibisco or sorry, it was just r Jr. At the time, and they thought they were diversifying, which is the big thing. Then paid them a lot of money and then they drove it into the ground.
So what did Sealand do? What was did they? I actually don't I'm not familiar with this company at all, which I think kind of speaks to your point. But what it was Seland?
Yes, So so it was a truck. It was started out as a trucking company. And the founder of Sealand was a trucking entrepreneur. And he said, it's silly you you go into a port, your truck sits around all day. Well, you know, the long charman put a cargo net into a container ship, load everything into it, pull it out, unload it and then reload it back into your truck.
This is not efficient. And this obviously it's an obvious idea, right, just put it all in a box and you can then put that box on a truck.
The best ideas are always the obvious rights in retrospect.
But the problem with it was it was a systems problem, right. The long charman didn't want it, the ports didn't want it, the port authorities didn't want it, the politicians didn't want it. Nobody wanted this to happen because this sort of enormous change would put a lot of people out of jobs. It would up set the existing order, and it did. I live in Hoboken, and in Hoboken there's a lot of peers that nobody uses except to go running on now, because back in the sixties it was a long sharmantown.
And when I moved there in the early nineties, it was empty. It started to gentrify, but because all of those people had lost their jobs and moved out.
And I suppose, like even in the case of marisk And I'm sure you know, they obviously have made a lot of money because the explosion of global trading volumes and containerization is part of it. Like, it wasn't overnight wealth, right, it wasn't.
It was not.
It was not people got richer, but it was not like some bubble get rich quick thing where they suddenly cashed in on a new thing.
Yeah. I mean, I suppose whoever owns mask may have gotten richer. Yeah, but it's not like you're going to look at the forest four hundred and see all these shipping magnates who became suddenly, you know, enormously wealthy. There are a few.
Wait, okay, so if I think about a box, you know part part of that.
We just keep this whole conversation on boxes.
Actually, well one more question then we will be able to discuss ai. But I think about a box, and as you say, it's sort of an organizational structural problem, Like the box itself is not the huge technological advancement necessarily. So what exactly was it about containerization that prevented it from being disseminated I guess to new upstarts or new companies that could actually use that technology.
Well it was, so I'm not sure I understand the question, because uanization became widespread very quickly, right, But.
What I mean is like, why was that value seemingly captured by incumbents versus startups?
Right? I think because it disseminated so quickly, Right, it was an obvious idea. Everybody who saw it said, Okay, we need to do this. Right. Everybody who's already in the business said, if this is going to happen, we have to do it. We can't be left behind. We will be left behind if we don't do it, which you know, I think was also obvious. So the reason nobody else did it first was it was hard to do. It was hard to make happen. And technology has always
come in these technological systems if they're worthwhile technologies. Right. So the personal computer didn't change the world on its own, right. It changed the world alongside the Internet, you know, alongside a bunch of technologies that formed the system. So the hard part here was building the system, not the individual technologies. And this is true I think of computers as well. The first microprocessors weren't considered revolutionary. Intel didn't consider the
four thousand and four revolutionary. They considered it evolutionary. The engineers have said this, And it wasn't revolutionary until people put it to use in ways that they didn't anticipate.
Actually, can we go. I didn't know that, like, I hadn't really thought about that with Intel that at the time it didn't feel to them that it wasn't a revolutionary technology. That's sort of mind blowing.
It is, right. This is I think from Michael Malone's The Intel Trinity of the book. You know, he interviewed a bunch of Intel engineers and he said, you know, like they thought they were building a better chip set to build pocket calculators or desk calculators. I just say so, they had a client, Busycom, who wanted to build a better desktop calculator with calculators were big back then in nineteen seventy ish, and one of the engineers said, well, why do we keep building custom chip sets for each
different calculator. Why don't we just build a chipset that we can customize the software and change what it does. And Intel is kind of like eh, and Busycom was like, okay, we'll pay for that. And then Busycom actually tried to back out and they gave the rights back to Intel. So Intel owned the rights to this four thousand and four, and then they started selling it and it wasn't Intel.
You know, Intel believed at the time it was going to be maybe used for dedicated hardware, you know, can you hardware controllers that kind of thing, not by consumers. So it wasn't until people on the outside said, hey, you know, I love these IBM mainframes or these deck MANI computers. I'd like to have my own, but obviously nobody can afford that. Why don't I just try to
build my own? Right, So there's these kind of outside inventors, this permissionless invention, and then it really the real revolution didn't happen until this. You know, everybody's like, oh Intel. It was the six five oh two where the price came down so dramatically that, you know, Steve Wozniak could walk into a computer fair you get some for free and go home and build up a personal computer.
It's crazy. I wonder who made the chips for the Commodore sixty four computer that I had.
They were six five o twos. Those were Intel, that's you know, they weren't until there were Moss technologies. Oh got it, got it, those are the cheap ones.
Then yeah, wait, what year was that when you had well, I had I think I like learned some basic and did some coding on it. I would have said maybe nineteen eighty eight, nineteen eighty seven somewhere around there, made a few I missed those days. It's crazy that I didn't be. Can I just say I sometimes when I think about my life path, like how did I not end up like a tech guy? Because I was like very into math. I was like one of those people who had a computer when I was six or seven.
In nineteen eighty seven, you were coding you were seven years old.
Yeah, I got that. My dad got me this magazine that just it was very crazy. There was literally just sent you pages of code and then you just typed it in and you could like make a video game. I was doing that at seven. I could be like one of those like who's per s gave of a computer when he was seven? It anyway, and it's not too late.
It's not too late.
Yeah, it isn't too late. Well, maybe it is too late because now we have AI doing all the coding, right, Okay, just so I understand when it comes to I guess the advantages of the incumbents to actually monetizing new technology or benefiting from new technology is the moat around their business the network and their sort of role in the network, or is it the vast amounts of cash they have and the ability to sort of roll out massive investment to capture that value.
I think it's the latter, right, So anybody can build a foundation model, right if you have the money. I mean, the technology is not mysterious. It doesn't feel like the technology is really changing very quickly anymore. And of course I don't have insight into what's happening inside of open ai, but looking at it over the past couple of years, it's the same thing, but slightly better. It's evolutionary now, right.
The first part was revolutionary and now it's evolutionary. So if you wanted to build one, you could build one. And I have friends who are running them on their laptops very slowly, but it's possible. So now the question is do you have enough cash to build the data centers, to buy all the chips, to build something that is large enough that when you train it, it does something useful, And it's just a question of having that the authority in the market to be able to raise that money.
By the way, speaking of ideas that were sort of really obvious that took a while. I'm always blown away that, like how long it took them to put wheels on luggage. I don't think anyone like made got super rich on that. But when I was a kid, I remember like we had these big suitcases, and that's the most obvious thing. It took a while. Anyway, I don't think anyone goes.
Technology is still not perfected, as you know, because you've been in airports with me and the wheels on my luggage are broken.
But I don't think anyone got like super rich off of wheels. That just seems like an that was just sitting there.
You know.
I want to jump ahead actually in the conversation a little bit because I know to forget this point. But this is something I've become a little obsessed with, which is I've been meaning to ask a VC about this, which is that there seems to be this blurring of private and public markets in various ways, retail participation in
private markets, et cetera. For the VC, in my mind, I feel like the exit was the IPO or the acquisition, right, so you buy do vcs these days have to think a little bit more about market timing and selling early. So someone who was an early investor in open ai or whatever you know, in the past, they might have just held or then sell at the IPO or the acquisition. It is probably going to happen in an open AI's case,
they're too big to be acquired. But to vcs and in your experience these days, have to think a little bit more about this idea of selling early, timing the exit.
Well, I think vcs always had to think about timing. You know, I've done pretty well in VC, and I attributed it entirely to being lucky at starting investing at the right time. So the first time around, I was starting in ninety seven, which any you could make money in. The second time around, I started in two thousand and seven, which again it was just two thousand and eight. It was just an easy time to buy in.
But I mean, the timing of the sale is that something that where in the past it might have been automatic exit, now now is not the case.
Yeah. I wrote this thing about VC in the nineteen eighties a long time ago on the blog. You can find it. And the thing because nobody talks about the nineteen eighties, right, there's plenty of VC in the eighties, but nobody talks about it. People talk about the sixties and in the nineties. So I was like, all right,
what happened. Then. One of the interesting things about it is there were the IPO windows then where you know, nineteen eighty three the IPO window opened a bunch of companies on public and then it closed again, and you can see it in the numbers when people in public. So people always had to think about timing. The IPO is obviously the best exit because you want to sell to the greatest fool, and nobody's greater fool than the public, right, So you look for the IPO window to open. When
you can't, you have to sell to somebody else. You know. Vcs have this problem of their limited fund life. So I look at my portfolio. I'm an really early investor or have been a really early investor, so I'll look at companies and say, oh, I invested ten years ago. They're going to have to sell, you know, it's the So people look for the IPO window, but if they can't find it, they have to sell somewhere else.
Well, how much of the money flowing into AI startups now is just the expectation that a bunch of these little companies are eventually going to get bought by larger incumbents, and basically you're going to have consolidation and you will get that exit.
I don't think anybody can predict when the IPO opens. I mean, I wish I could, but I don't think I've never seen anybody even say they could predict when the IPO window opens. So I think a smart VC invests in a company that can become self sustaining to some degree, and then you wait for the timing to come. You don't invest and say I'm gonna flip this in three years now. Yeah. The other problem is vcs don't invest in all these IA companies saying a bunch of
them are going to become valuable. They invest saying one of these is going to be come right.
The lottery ticket theory, yeah, the power law.
Speaking of the IPO window, I'm never totally satisfied by a lot of the explanations for the drop off in IPOs generally. Do I know there was that law passed in two thousand and one.
Or what was it, sins ox Yes.
Surbins ox Ley, and I get that law.
That law law that everyone hated for a really long time.
I don't know, it doesn't. But then you see, like you know, twenty twenty one there's like a billion garbage companies went public via SPACs et cetera. How much is
it about? Okay, there are some disadvantages to being public versus there's just so much more private capital out there such that the imperative to perhaps ever go public and it's liquid and the rounds and like, what do you attribute There are these big companies that are a private stripe but open AI and onanthropic that choose to stay private. What do you think the main reason for that is?
Well, it's because they can, right, I mean, being a public company is no, it's no party, right, I mean it kind of sucks being a public company.
What is it about it?
What sucks? Well, you have to tell everybody what you're doing every three months. Yeah, that's you know, and then they come back and complain about it. So sorry, I'm being a little facetious, but it is. It's hard to be a public company. Everybody, you know, anybody who runs a public company will tell you they spend a lot of time being a public company if they're running the company. So that's taking away from actually running the company. I think the flip side is your liquid and that's yeah.
You know, So if you can stay private, why wouldn't you stay private? Or if you can go public and retain control of the company, you know, like Henry Ford or Mark Zuckerberg, then why wouldn't you do that? But I think it's because there is so much late stage money. This isn't necessarily a good thing. It's because there's so much money out there that's not being invested in more
revolutionary technologies earlier. With all this money being invested in AI, you may wonder if people are still going to want to invest late stage stripe or the analogous stripe might be making money now, I'm not sure.
I know you brought up previous historic analogies like VC in the nineteen eighties, but just to focus on the one that everyone else seems to be focused on at the moment, which is the dot com bubble in the early two thousands. What are the key differences you're seeing in terms of the VC and financing environment now versus twenty or twenty five years ago.
I think the key difference is that most of the money is coming from people who aren't looking for much risk, right, So I mean open ai is primarily funded by bigger companies. Right, most of their money is coming from large companies. What happens if open ai gets hit by a bus? Right, So Microsoft's at a bunch of money. A whole bunch of big companies are at a bunch of money. I don't think much happens to the economy. I think, which is different than in the bubble, where a lot of
consumers were in it. A lot of consumers were in it leveraged right, the buying and margin or whatever. A lot of people had options, right, people employees, and they were spending the money from their options before they were licking. You know, it was there was a much I think it was a different dynamic.
But the wealth effect, I don't know.
I think this is a contrarian take on your part, because you hear a lot about I mean, in two dimensions. You hear a lot about the direct wealth effect from people's exposure to the stock market, which AI is a big part of the story. And then you also hear about, of course, the sort of real economy effects through all of the spending, which we will get into on the data centers and the caterpillar, the turbines for the gas generation,
et cetera. I think many people would say there is a lot right now riding on the health and the sustainability of this particular sector.
So I think we can separate the companies like Microsoft and Video. Are they over valued because of this? Maybe doesn't make a huge difference to the economy. Probably not, I don't think so. And the companies who are spending money on infrastructure like building data centers, building power generation plants, those things I think are probably overbuilt or not so
much overbuilt as they are built. And I think in ten years you're gonna have a lot of extra compute, a lot of extra power generation, and people will be able to use that for other things. It'll also drive down the price of just using AI.
Probably, yeah, Jevin's paradox bro is gonna be out back and forth. All right, So AI, where are we? You talk about cycles? And I think you use word that I hadn't ereruption? What was the word you use? So well, I'll tell us how you see cycles in what cycle we're in?
Right? Right? So A lot of this is based on KARLOA. Perez's work, which is pretty familiar to the ventro capitalists and your audience. I'm sure. She wrote a book called Technological Revolutions and Financial Capital where she explains the dynamics behind the Kondrati of waves that the Chumpeter talks about.
So she has this theory about why these happen. And you look at the Industrial revolution, the Second industry Revolution, you can see these waves of technology technological systems happening through the economy where they kind of start out, they grow really rapidly, and then there's usually some sort of adjustment, some sort of bubble bursting, and then things kind of level out and then start to plateau, and then a new one starts. And this is people have noticed this
since at least Kentdrati nineteen twenty six. She has a mechanism for explaining it, and her mechanism has these four phases. The first phase is eruption, which she spells with an I, which I think is actually in the dictionary as a word. I don't know what the difference is between that and the eruption, but it is the part where smart right, So yeah, keep saying that it is the start. It's when people have invented something and it is starting to catch on, but it hasn't caught on yet. There's a
lot of people saying, is this the future? Is it not? You look at personal computers in the nineteen late nineteen seventies, early nineteen eighties, and maybe even before IBM got involved, and people didn't think personal computers were Some people thought they were their future. And then you look back at computer history. Everybody talks about the people who did think that. They don't talk about the other ninety nine point nine
percent of smart people who said they weren't. This is the eruption phase where there's a lot of uncertainty about where this technology will go. It's starting to build connections to other technologies, starting to attract money, attract smart people because it's interesting and it might actually change things. So this is the beginning. And I think the connection here to AI is people wonder if we're in the eruption phase of AI or not. Is this the start of
a new technological revolution phase? I think we're not. I think we're in. I think this is the end of the information computer technology wave, the end of the computer wave. Right, I think it is. This is the culmination of the computer wave. Right, Why did we build computers. We build computers to help us think better. Right, this is what they're for, their knowledge machines. So now we've kind of reached the natural end stage what they do. They're smart,
machines are smarter. So I think this is not a new technological revolution. I think it's the end of the old one. And this is why I compare it to container is thea because the previous wave was automobiles mass production, and starting in nineteen fifteen or so up until nineteen seventy was the previous wave, and containerization was squarely at the end of that wave, and it was really kind of pulling together the technologies of that wave into something that increased productivity, right.
Like the final step of the global trade and I guess mobility revolution.
Yeah exactly.
Okay, so how do you react as an angel investor? Are you at the stage where you're looking for I guess the downstream winners, like the companies that are going to be able to apply or use AI most effectively, or how are you actually deploying all these thoughts in terms of your own investment strategy. I retired, Okay, you know, I standing it out and I.
Said, look, how am I going to invest in foundation modes, right, I don't have a billion dollar fund. I don't think that. You know, if you look at the big winners from the early big winners from globalization, the IKEA is right. I mean it was a Scandinavian company until containerization, and then they became a global powerhouse, a hugely successful company.
But they didn't need outside money. You know. Comprade, I think he borrowed like a couple thousand dollars to start that company or to get that company to buy some inventory. He never took outside You look at Walmart, which had been around already. It was an incumbent and used this kind of globalization to bring a lot more variety of products to the stores. They didn't need outside money to do that. Yeah.
I guess if you're at Kia and suddenly you're flat packing everything and shipping it in containers, and that's your big innovation. It's a money saving technology, right, So you don't actually have to raise new capital in order to flat pack everything.
Yeah, exactly, Okay, they were already flat packing.
Yeah. Your mention of the Walmarts and targets of the world, it was like in your essay it was like a sort of very light bulb thing. It's like, yeah, I don't know. I guess we'd take them for granted. But they're clear like massive containerization winners. The skill that they succeeded is impossible to fathom in some prior era.
Of Walmart is a logistics company and changed my mind.
Literally and many of you literally literally literally that. But it doesn't feel like with AI that the equivalent has emerged yet. Right, We're still at the age where people are building the container deployed. But the company that exists and is massive that couldn't exist prior to a like does not feel does it We haven't seen that yet.
Well, you gotta be a little patient.
No, no, but like seriously.
Iikia so contained. The first container ship sailed in I think nineteen fifty six. Okay, so when did Akia become a global powerhouse? It really wasn't until the nineteen seventies that they started to expand that this is really important.
They really take a while. Where would you expect it to show up? Like what industries would you expect because obviously retail existed for a long time, furniture existed for a long time. Then you get these Bahamas. Are there industries that you think are right to produce very torture analogy the Ikea of the AI way.
Well, I think they have to be knowledge intensive industries, right right, I mean this is what AI is doing, what it is making more efficient. I mean I think there's people been asking me like, well, then what should I invest in? And yeah, tell us, well, you know, I think, well, so give us. I've been thinking that myself. But the answer is really that as an investor, I don't decide what to invest in. I evaluate opportunities that come to me. And so I have built a box
in which you can evaluate opportunities. Right, they have to look like this. They have to look like an Ikea. And if I Kia came to you and said I needed money at that time, you should have said, okay, I can see how shipping containerization is going to make you a much larger company. Where nobody else seemed to see that, right, Certainly the furniture makers in North Carolina didn't see it. So I think this is the box
that you evaluate things in. And as a long time investor, I'm used to evaluating and I trying not to come up with ideas, you know, that said it has to be a knowledge intensive industry. And I think something that I said in the essay, which I wish I had said more about, was the companies that tried to use shipping containerization to cut costs so that they can increase margins did poorly. Oh this is key, Whereas the companies that use the efficiencies and passed the efficiencies onto the
consumers so that they could become larger became larger. Right. I mean this is you look at these people saying, oh, we have AI, We're going to fire people. I mean, that's I think is the exact wrong move. And I think it's probably just every you know, every new thing comes along, people like, oh it's we're going to fire people. You know, it's just an excuse. But but if you're firing people because of AI, you're doing it wrong. Right. You should be using AI to say I can use
my people to do more. I can grow my company, I can vary my products, I can take more market share.
So the value goes to the consumer. And I guess you capture the value by selling more right, more knowledge?
Yeah, I mean I think Walmart never tried to maximize margins.
They it was it was volume.
Yeah, Okay, from a consumer standpoint, why do I care if your workflow internally at your company is become more efficient things AI, either the product is better or new or something.
You know.
I was thinking about this. I don't mean to like pick on anyone, but situating like open door meme Stock they have new CEO. He sent out this memo. He's like everyone has to do start using A or it's clearly a press release in the form of an internal memo because it got it I think waving.
A flag going us.
It's like, yeah, but like, does the economics of buying homes via whatever get better? Like does it actually make the business better? This strikes me as very interesting, this idea that like, it's not gonna it's just not that exciting, especially any sort of customer oriented company, which I guess is all companies. The fact that AI has become part of their workflow. It's the electric knife effect, right, So I don't know that effect we might.
Just call that, but I mean electric knives are one of the fastest growing consumer products in the late nineteen sixties because people are like, oh, we are electrifying things, like let's electrify the knife and within like three years they were in some massive percentage of households, like eighty percent of American households had an electric knife and things like you know, the blender didn't get adopted that quickly.
But who has an electric knife now? Right? It's I think people take whatever it is the technology is and say this is everything. I mean, back in you know, the early two thousands, late nineteen nineties, every company was an Internet company. Right. Do people walk around saying that's an Internet company? Now are you an Internet company? I mean everybody's an Internet company. Everybody uses it. It's the baseline. That's I think the what a revolutionary technology does is
it becomes part of everything. So, yeah, you're right. Consumers don't care that your you know, your lawyer's using AI. They want to make sure that they have good legal advice. Yeah.
Our producer just messaged Dash saying that he had an electric knife. Oh does he have Probably not in the nineteen sixties.
There do you have one?
Now?
My mom might have one case that didn't get picked.
Up on the audio.
Well, his mom might still have one. Dash, will you bring it in for us and we can we can use it as a.
Prop I'm just imagining like going to a restaurant at the time it's like, oh, we slice your bread with electric knives. That are like how unexciting that would be From a consumer stand I don't care, you know.
Yeah, I guess that's true, but okay, but things are different from a shareholder standpoint, right. And one of the reasons we see when companies say that they are using AI the share price goes up, it's because shareholders expect all these easy cost cutting gains. Do we have any indication that investors are actually going to be patient and wait for I guess the value to spread to the consumer or are they just going to demand basically these fast cuts.
Will And I mean, I'm not a stock market investor. Yeah I know, I know you're stock marketing, you know. I think they have a very short attention span. There's a great quote in that article that you see in the eighties where the Wall Streetjournal said, you know, there was the beginning of the eighties, there was a craze and anything that ended with an onyx rightes right, it was people were right funny, but it was a short
lived one because it didn't really deliver. And then people were like, all right, let's move on and do something else or invest in something else.
So funny, if I were writing a fiction about the eighties, I would immediately I would say, like applied fouxtronics or something that. Yeah, right, yeah, I hadn't thought about that. That's amazing.
So I think they want results. But I think it's two people are impatient. I mean, I was kidding, but I'm not kidding. People are impatient. They want to see results today. I don't think AI is going to show you the real revolutionary results for a decade. Taking AI and just retrofitting it on to the way you do things now is only going to add a little bit
to your efficiency. You have to actually re engineer everything around this, change your processes, hire different people, or get you know, train people, and then you're going to see big efficiencies.
You got to have prompt training in schools, right in high schools or something. Well, we were talking about this with Tyler Cowen earlier and he had, you know, a similar point.
Are big companies setting aside? Okay, like, yeah, it's not very exciting that a big company is able to marginally reduce their workforce. I think a lot of those are fake. I have a feeling a lot of these companies are going to have to end up having to hire people back when these things don't work, or they had nothing to do with AI and they just wanted to do layoffs.
Can legacy institutions like there's some like inherent roadblock to the degree to which legacy institutions can incorporate on AI Or is this the type of thing where it's just going to be entities that didn't exist before becoming really big household names.
No, I think it will be legacy. I mean I think you know, Walmart was legacy, Ikia was legacy. It may not be the names you expect, right, Sears and Woolworths didn't really benefit from shipping containerization. They ended up going out of business. I think you have to have the right attitude of how you're going to utilize the efficiencies it brings within your business again, to grow your business,
not to grow your CEO's salary. Right, you have to be spreading this to the consumers for your company to be successful, all Right.
In the intro, Joe made fun of Sid saying something completely rational. It Yeah, I know, I know, but this is your joke, right, Okay, So I'm gonna ask the cliched question in that theme, are we in a bubble?
Can you define bubble? No? I should.
I think the question should be asked liberally.
It's like, are things overvalued?
Are things overvalued?
Yes, but there's a difference between things being overvalued in the bubble, right, and I think things are overvalued, and I think there may be an infrastructure bubble. In the article I wrote for classes as a chart of container ships being built, of shipping ships being built, and you can see this huge rise right after containerization started for a bunch of years, and then it dropped back off because now people had their ships, but everybody had to
get into the same time. Everybody had to go order ships. A ton of ships were being built, and then the Capex, you know, and then they were like, okay, now we have ships. It's a little different with chips because chips aren't gonna last you know, yeah, or a long a container ship last thirty fifty years. But I do think that you're not going to need as many chips in the future as you are buying today. Really well, you know, you're gonna have more use of AI. Probably there's gonna
be more use. But I also would think they would become more efficient in compute. That's just the history of compute.
Does your definition of a bubble, does that have to include a buildup of leverage of some sort.
Well, I lived through the dot com bubble, so yeah, I would say so, right, because you're not seeing that right? Well, because I think a bubble popping has to hurt. And if Microsoft loses a billion dollars, that doesn't hurt. Doesn't hurt any I mean, sure it hurts whoever's invested that money at Microsoft, but it.
Doesn't who has which is everyone who is a four one K?
Well, I guess, but I mean, really, Microsoft loses a billion dollars, how much does that affect their stock price? And even if the stock win down ten percent, that's not a It's not like the dot com bubble. Right When that popped, people were laid off, the economy went to a recession. I mean it was pretty deep recession. Took a while to kind of pull ourselves back out of that.
Talk to us more about the dot com bubble. I tried to bring it up in every conversation because that's when I got interested in markets, did a little day trading in those days when I was in college, et cetera, and I just remember that period very fondly because I was young. What do people get wrong in their memories of the dot com bubble?
So here's the thing I remember most about the bubble. I was a corporate VC. I worked for a big company here in New York for to my front of company. And one of the companies I had invested in was a public company and they were raising more money. This was in January, right for the bubble popped right.
Was the peak was in market in March two thousand.
Then it was January two thousand, so the company was selling stock. They said, hey, you know, if you want to buy some more stock in our company, we'll sell to you without the underwrited discount or before the underwted discounts. We'd get it a seven percent below the market price. And I went to CFO of this giant company and I said, hey, we can get a good deal on this stock. We can get seven percent off, right, who doesn't love a bargain? And he said, well, do you
think the company is worth that price? I said, no, nowhere near. He's like, so why are you buying it? I'm like, oh, I guess that's a good point. He's like, so why would we still own it? And it's like, that's also a good point, right, which why aren't we selling this if it's overvalued? I mean the thing that people forget is everybody knew it was overvalued. They were all just waiting for it to go up more before they sold. And he said this, and I'm like, yeah,
I guess better to sell early than late. And we ended up selling that entire position, which luckily paid for the whole portfolio before the bubble popped.
This is a I mean, I think this is there's sort of the difference between John Authors had a really good newsletter I think about a year ago, which is.
There, you're just awsletters I'm doing.
I'm doing my job to Bloomberg. I like, but it was basically like, you know, you get these situations like dot Com where everyone said this is massively overvalued. We all know, we all It's then you have bubbles that are more like the housing bubble, in which I don't think on any sort of traditional metrics the banks were overvalued.
I think probably the pees are probably normal. It's just that the earning extreme was entirely unsustainable and I guess that's the question with AI, Like I don't know, videos prebaby expensive, but like I don't think people think it's like crazy stretched on pees. It's more the question of, like is this chip demand at this pace sustainable? Like are the earnings estimates realistic?
Right? Well, but I mean the economist said the housing housing was overpriced in two thousand and.
Five, right, the homes were, yeah, the banks, you know, but the banks got obliterated. And it was not because the ratios of the banks were completely out of way, because just the profits could not be sustained by any stretch at that point. Anyway, I think it's an interesting distinction.
Well, I think there's still an open question with AI about the network of relationships that are sort of driving a lot of this business. Like that's where I would see some of the maybe two thousand and seven two thousand and eight analogy actually being true. This idea that like you have this whole system of funding with banks that's keeping the whole machine going, but when the collateral that's underpinning that system suddenly loses value, the whole thing
falls apart. You could maybe make a sort of similar argument for AI, where you have this network of companies that are sort of investing and selling to each other. If the value of the underlying asset, which I guess would be compute in this case, starts to fall really precipitously, the whole thing kind of collapses. But I'm stretching that.
It's amazing to me how much of the lessons we learned in the nineties people just don't know or remember. I mean, the whole blank check company thing. We did that in nineteen ninety nine, right, and it'll fill all the SPACs, right, and it's totally failed, and then people did it again. It was crazy to me. And it's kind of circular. Yeah, I know, right, Yeah, I mean it's still a bad idea. And I think the circular revenue was also happened in the nineties and that was
all also a bad idea. You'd think that people could see that and factor that out.
Gotta have so many questions. Why are specs a bad idea? On paper? It seems like a totally fine way to go public. In practice, it only seems like total garbage companies take that route.
It feels self selecting.
Yeah, well, of course, because the way they're structured to get people to invest in a company you don't even know what it is yet, it means that it's not great for the companies, right, you get a ton of yeah, oh right, that's just leakage.
Well, just explained the mechanism again.
So people, you know, if you put money into a spack, when they decide they're going to do a deal, you're allowed to take your money back out of the spack. I can't remember all the details, all right, Right, So if you're like, well it's a good deal, I'll leave my money in. But if you're the company being acquired, you don't know if you're going to be acquired or not, because people could take their money out. So just why wouldn't if you could go public on your own, you
would prefer to do that. So by definition, the spacks are buying companies that couldn't go public on their own, right, right?
Is VC investing fun again? I got the impression like two years ago everyone was pretty depressed, and I'm quite sure we did a few episodes on it at the time. But are people having fun again?
Well again, I retired, so no, nobody's having fun. I wasn't having fun. I think if you have a billion dollars. It's probably fun if you're doing the big deals. I think if you're in AI, it's fun. If you're doing anything else, it should be fun if you're doing something besides AI. Right, because now everybody's distracted by the shiny new thing, you can go find companies that are interesting to you and invest. The problem is you have to worry about what happens a year from now when they
need the next round. Is anybody going to be paying attention? I think it's probably pretty hard to be an early stage investor unless you're investing in AI. And if you're investing in AI, you're probably not writing small checks, low valuations, and you can't control the outcome at the end. You can only control what you do at the beginning, so you probably won't be making money.
I have this theory that actually nobody likes bubbles or booms even but let's say bubbles in part like, if I missed it, I'm upset because someone else is getting rich. If I'm in it, I'm like really anxious. Am I gonna like I'm anxious about two things. I'm anxious. Am I going to sell it at the right time? I'm also kicking myself for not investing more. No matter how much I invested, I'm upset with myself for not having invested more.
Is that right?
This is just my impression when I read history, which is that everyone, even in the boom times, there's like this like din of like stress underneath. Is that true? Or am I just fantasy projecting how my own neuroses from birth onto.
Everyone thinks they're gonna time it.
Right, But it's fun. The bubbles are fun, especially if you're young and stupid. Right, there's the New Yorker cartoon. I want my bubble back. Yeah. Yeah. The flip side is it is stressful. I remember, well, its stressfull both after obviously I still have my Razor of His stock certificates. I had a certificated because I couldn't sell it for anything, you know, for any real money, and that at one point had been worth quite a bit of a month more than.
Again, I remember, what did that company do? It is like an ad network or something.
No, No, they built websites. Oh yeah, yeah, I remember. They were great. I mean they were a great company when nobody else knew how to build websites.
Friends who worked for Razor fish even as like recently. It is like twenty ten.
They sort of hung on.
For a little while. Jerry Newman, thank you so much for coming on odd lot. It's been wanting to chat with you for a long time, and I really appreciate your joining us. Yeah, thank you both, Tracy. I love that conversation. There's a lot there. I mean, obviously, I'd like anytime we can talk about the nineties bubble, but I had never really thought about or any come anywhere
close to thinking about the AI analogy with containerization. It's a little embarrassing because that's such a core topic for us. We've talked about boxes so many times, but it's sort of re orient my thinking of AI and thes term very helpful.
Yeah. Well, I mean this just kind of proves the point that no one thinks of containerization. I mean, I said before, it is a technology story. And one of the reasons I do think of it that way is because I read that book The Box, Yeah, which is really good, but no one thinks about it as an investment story. No, because of the reasons that Jerry just laid out.
Yeah, No, that's really interesting, and you know, again like it does feel at some point that non tech businesses non AI businesses. Eventually someone hopefully for the industry, like makes a lot of money actually using these tools because
we've been in the picture shovels phase or whatever. But at some point maybe it's an existing healthcare company or etc. Or maybe it's a new kind of law firm or an incumbent law firm where it's like, Okay, we have found a way to use this technology in a manner that is very profitable, productive, and market expanses.
So to me, that's the key thing. So the key thing is it's not that we're going to use this technology necessarily to cut costs and boost profit margins. It's that we will actually expand our customer base and make it up in volume by selling more knowledge.
You know, it's interesting thing that Jerry said, and you put into words something that I hadn't really thought about before, but this idea about being at the end of this sort of computer revolution, and there is something about AI specifically where people it's like and it can't really literally be this where it's like, well, this is the last technology, right because.
Because we're gonna get robots, yeah, right.
And I don't know if like other booms or technological revolutions had this feeling where it's like, this is the last one. Theoretically, if you get Agi or whatever robots, you don't need any further technological innovation, et cetera. It creates, I think, a very weird, uncomfortable dynamic. But the idea of AI is the end of what we do with computers rather than the start of like something genuinely new like that actually like snaps into place a lot of thoughts for me.
Once we invent God, we're done.
We're done.
Everything else takes care of it.
So yeah, all right, shall we leave it there?
Let's leave it there?
All right?
This has been another episode of the oud Lots podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.
And I'm joll Wisenthal. You can follow me at the Stalwart. Follow our guest Jerry Newman, He's at g A Newman. Follow our producers Carmen Rodriguez at Carman armand dash Ol Bennett at Dashbod and Keil Brooks at Kilbrooks. More odd Lots content go to Bloomberg dot com slash odd Lots. We've been daily newsletter and all of our episodes and you can chat about all of these topics with fellow listeners in our discord Discord dot gg slash od Lots and.
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