Lenny's Podcast: Product | Career | Growth
00:28:30 · Benedict Evans
So there's a lot of creative redefinition here. Superintelligence, I'm not sure, is superintelligence more than AGI or less than AGI? Because last year I thought superintelligence was like really good, but not as good, not actual AGI. And now it's like, "Oh no, no, we've already got AGI, but superintelligence, that's really hard." It's funny, I was having an argument on Hacker News this morning, you remember the argument, which is never a good use of time, but you remember the argument of like people would argue about whether crypto is blockchain, or whether blockchain is crypto. There isn't a right answer to that. Let's just be sure. It's important to understand what you mean when you say that, but there isn't like a correct answer to this. Are we going to get to something that has human level intelligence? We don't know. I don't think we have any way of answering that question. Maybe, maybe not. You can make arguments either way. Meantime, in the meanwhile, we've got this thing that's clearly kind of a completely transformative technology. And maybe the serious point here is like you don't have to believe, even if the model stopped it getting better tomorrow. If this is it and we hit a brick wall tomorrow, this is an incredibly useful technology that's going to change your world and get rolled out over the next 10 years. So you don't have to believe in any of that stuff to believe that this is a giant deal.
00:29:46 · Lenny Rachitsky
[00:29:46] S1: Something that's definitely changed, I had your former boss, Mark Andreessen on the podcast, and we didn't actually talk about this during the conversation, and he brought it up before we started recording and I never got to it, is he had this insight that the opportunity set for companies now is so much larger. We used to have no trillion-dollar companies, now we're going to have dozens of trillion-dollar companies. Just like the size companies can grow to are going up so much, and valuations also go up along with that. And his point is just people haven't really grokked just how large companies can get now. Everyone's hitting a hundred million AR in five months, six months. Just thoughts on that.
00:30:23 · Benedict Evans
[00:30:23] S0: Yeah. I mean, this was his whole software's eating the world thesis from 15 years ago, whenever it was. Yeah. The TAM, it gets progressively bigger, because you can address larger and larger parts of the economy. And so if you think about the classic platform ship framing that mainframes are, I think peak mainframe install base was something like 70, 80,000 units. I mean, slightly fuzzy term, what exactly is a mainframe, and at what point does it become two mainframes as one. But something like that, that order of magnitude. And then when the internet kicks off, there are, as I said, 50 to 100 million PCs on earth, maybe. Today there are something over a billion, one to one and a half billion, but obviously a lot of those are corporate. Like seven, 800 million consumer PCs in the world. There's about five and a half, six billion smartphones in the world, which is why you can have 900 million weekly active users on ChatGPT. And so there was this narrative five years ago of like, "Well, we've run out of people. So the next thing can't be in order of magnitude bigger." Which was true up to a point, but that was the wrong model, because clearly what's happening now as you're moving in another direction, is you're just branching out and automating big news weights of the economy. Now, back to your job point, you could argue, well, we're just going to replace all the people with AI and all the money will go to Sam Altman. And Mark can buy himself another Gulfstream, add to the fleet. I think the other answer, it's back to the lump of labor fallacy, and the last 200 years, that each of these technologies removes a bunch of jobs, creates a bunch of new jobs, creates a bunch of new value, unlocks prosperity for all of us, and that's painful as you go through it, but it always creates more value. And so here you could certainly make an analog to... The useful analog to the electricity industry is just saying how that electricity became part of absolutely everything. And software has been kind of slowly working its way out. Another would be electricity in factories, and then electricity sort of slowly spreads out. And so that would be the point again, that it slowly spreads out to do more and more things. And so more and more value and a bigger and bigger contribution to the economy. Also, of course, disappears inside things.
00:32:38 · Benedict Evans
And the other side, the point of my capital section in the presentation is there's this quote from Sam Altman where he said, "We're going to be selling AI intelligence on a meter like water or electricity." And you look at this and think, "My dear sweet child, you need me to explain the margin structure of the utility industry to you." Because guess what? When you watch television, the TV company isn't paying a percentage of your monthly bill to the electricity company. When you wash your clothes, Bosch isn't paying a percentage of the price of the washing machine. And clearly, this is like the much more specific tactical question at the moment, is, do we even end up with three giant models or does it become hundreds of models and open models and local models and so on? And even if we do end up with, say, pick a number, three to six to 10 giant foundation models that cost hundreds of billions of dollars a year, fine, do they get all the value from that? Now, I started my career as a telecom analyst, and so still pay attention to it a bit. Global mobile industry has revenue of about a trillion dollars a year, maybe a bit more now. And it spends about $200 billion a year on CapEx every year. Total telecoms is about 300. Mobile is about 200. It's about 15, 20% of revenue every year. And if you look at a chart of mobile data consumption, it's an exponential curve, like perfect curve going spread up. And the number now, I think it's about 1,500 to 2,000 times what it was in 2010 globally. And the stocks have gone nowhere in 25 years, because it's an X gross low margin commodity utility, where they're selling this objectively amazing piece of global technology infrastructure that has enormous complexity and enormous sophistication, but all the cool stuff is made by you. It's made by the people listening to this podcast. It's made by somebody else. This was that kind of pivotal moment where the telcos thought that they would do all the stuff that you did on your iPhone. And not only do they not do it, but Apple doesn't do it either. It's all further up stack. And so this is the elemental question right now around foundation models is, does the model do the whole thing? Do you just go to the chatbot and get the chatbot to do the whole thing?
00:34:49 · Benedict Evans
Can the model companies keep building these like Claude for X, Claude for Y things, which to me look very much like what you see if you hit file new in Excel. It's like the tablets, but all of those are actually billion-dollar companies as well. And if not, no, does it all have to be "apps"? Whatever app means. And if it all has to be apps who builds those, well, they can't all get built by the model labs, just as they didn't all get built by Microsoft. And so if they're all built by other companies, does their notion models have leverage up the stack the way Windows did? Or is this more like AWS where, if you're, I don't know, an engineering company or a law firm buying a piece of software, you don't care which cloud it runs on? And you don't have to standardize on AWS because that's where all the software is. And the developers all standardize on AWS because all the customers use AWS. That's not how it works. That's how Windows or iOS works, but that's not how AWS works. And so it does sort of seem to me that if the chatbot isn't the UX, and it needs to be apps, and the model companies aren't going to build that, and the models themselves are basically commodities, at least as you can see them as users, then why would the model companies have pricing power? And wouldn't all the value be further up the stack? Aren't you basically, have you got like three to six companies selling a commodity at marginal cost? Now, obviously the semi-analyst guys are like, "No, no, no, no, no. There's going to be infinite pricing power forever." I'm sorry, I'm exaggerating. But I think you have to really important to draw a distinction between where are we now, where you have radical price disequilibrium, and you've got these, what's the guy, the OpenClaw guy spent one and a half million dollars on token this last month. But that's somebody getting like a 50 grand mobile data built in 2010. That's temporary. What is the steady state equilibrium point where all of these lines on the chart kind of get lined up, and we don't have this kind of weird, crazy stuff going on? And then will you have pricing power, or have you got like three or four or five companies kind of all selling the same thing? And so then you should have a pricing price. You should have lower pricing and lower margins, and the value you've got stack.
00:37:04 · Lenny Rachitsky
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