00:07:43 · Tom Lee
[00:07:43] S5: I've witnessed several bubbles, you know, because I've been covering markets since the early nineties. And the two that people would describe as bona fide bubbles are the Internet bubble and the housing bubble. I mean, those are genuine bubbles. And it's hard to compare the current cycle to either at this moment because, you know, the Internet bubble was apparent because the the type of innovation that was taking place was simply cost savings. The Internet in... Into 1999 was not a revenue story. It was a brick and mortar to etailer model. It was trying to basically say, this is a new way to do it, but you could save money. And the housing bubble, of course, brought leverage and capital into the hands of unqualified holders. So it was basically a bubble where money was... Debt was given to people, and then a lot of people borrowed a lot of money. This AI story so far is one of pretty remarkable innovation taking place, like otherworldly innovation. And so I think as long as that pace of innovation is happening, and then we're seeing it as productivity for businesses because revenue per worker is going up. There was no productivity metric in the Internet we could point to at all at any time into '99. I think AI becomes a bubble when we start making up use cases that don't actually have end markets yet. As far as circular financing goes, and I know people are making claims that that's the reason it's a bubble, I think it's a people do need to be students of history. There are many cases where circular financing is not called circular financing. It's really ecosystem development. Some examples are, of course, the energy industry is... Then would be notorious for circular financing, but that is the nature of resources. Another example is the early days of of radio. RCA made radios, Then they had to actually create radio stations across the country. Then they had to invest in programming across the country. And imagine if someone said radio was a bubble because RCA is investing in radio stations and in in radio programming, they were creating an industry. And that was not... It would have been a huge mistake because RCA was probably the biggest stock of its time until the nineteen twenty nine crash, which was not a a radio bubble. It was just basically a stock market bubble. So I think, you know, it was more than a 100 x move.
00:10:33 · Tom Lee
Cisco was a 100 x move. NVIDIA has been about a 10 x, you know, from its, the start of ChatGPT. So to me, it's, of course, has all the makings eventually to create a bubble, but I I think it's very early. I mean, I would just say during the Internet period, and I covered it from '93 to '99. Oh, well, I covered it all the way through the crash and recovery. No one even called it a bubble until after 2000.
00:11:03 · Ed Elson
[00:11:03] S4: In terms of the circular financing, I think one of the concerns, even if we would call it ecosystem development, is that it is implying that demand might be stronger than it than it than it would have been if the demand were organic. Like, if you didn't have these circular relationships, then you wouldn't see as large of a business, and therefore, the argument is that this is artificial growth that we're seeing. I think the same thing would be said about token maxing as an example. Businesses tell their employees, you have to use as many tokens as possible. And the reason that we wanna do that is because we wanna be part of this revolution and we we feel very strongly about this. Then suddenly they say, actually, this is too expensive. Let's pull back on the on the token spend. And as a result, it does seem at least that the growth of the token use is beginning to slow. Whether that's directly a result of token maxing, I'm not sure. But it does seem in those cases that there are these dynamics that point to an ecosystem where the signals that we're getting aren't maybe the purest signals of organic growth that are completely dependable. Do you disagree with that, or do you not worry about that?
00:12:23 · Tom Lee
[00:12:23] S5: I mean, I just wanna point out as a practical matter, exponential growth industries don't have the same rate of change, sequentially. Cisco, for instance, in 1997 had two quarters of 20% sequential growth, and it went down to five. And in 1997, Cisco stock fell 50%, and the the data networking analysts said this... The growth story is over. And, they said there's competition coming from Internet protocol switching. So Cisco fell from $9 to 5. A year later, was at 18. So growth, an exponential s curve industry doesn't grow at the same pace. I think token usage still has the Jevons paradox at work. You know? And it doesn't mean every day and every month and every quarter, it grows exponentially. I covered mobile. There might have been six, growth cycles in there and growth recessions because, hey. You roll out GSM, then growth slows. Or if you roll out a new Nokia phone, there's an upgrade cycle, and it slows. But everyone thought that was the end of the penetration cycle for mobile, and, of course, it continued for thirty years. I think that token maxing and people thinking rate of change for tokens is gonna explain the peak of the cycle, they they haven't covered prior growth cycles. And I... And, again, I'm just emphasizing I've covered many in my lifetime. I'd say the real key is is AI no longer providing remarkable innovation? And if it doesn't, that's really the end of the cycle.
00:14:02 · Ed Elson
[00:14:02] S4: When you look at Anthropic growth as an example, does that make you feel more bullish on the AI trade? I mean, it's grown dramatically over the past year. But one of the criticisms now that we have these q three numbers is that the growth has slowed quite significantly to around 47 to 50, I believe. And then next quarter, based on ramp data, it's expected that it'll be around 25%. And some people are saying this is not good. Do you think that that is indicative of a regular growth cycle? Is that the kind of growth that you would have expected from Anthropic?
00:14:41 · Tom Lee
[00:14:41] S5: Well, I think, you know, part of the confusion around Anthropic is really its its revenue policies and how they treat... You know, like, what you and I would consider, like, subscriber and organic and unit growth is not necessarily how they're reporting revenue. And so it affects the growth of sequential. And you know what? They'll probably learn that as a public company. And another thing to keep in mind is that, when it comes down to the fullness of time, when we look back at the Internet cycle and mobile cycle, the long term winners might actually be second wave companies, you know, downstream companies. So, like, in other words, OpenAI and Anthropic are the frontier companies. They're not that dissimilar to Netscape and, Cisco. But were those companies the ones that you made money on in the next ten years? It's... It'll be TBD because, actually, the history shows downstream did better. The post Internet downstream companies were companies like Netflix, you know, eBay, Expedia, Tower Stocks, Apple. Apple wasn't even in the first wave of Internet and mobile. You know, they didn't launch a product until 2007, which is thirteen years after the launch of Internet and after the bubble had burst. So I think, you know, we probably have to have some flexibility to say, is is my personal investment, how am I gonna make money in AI? It it may not be through Anthropic or OpenAI. It may be, though. So I'm not. But, you know, it end up being a company like SpaceX or Apple as the long term winner.