a16zWhy Top Founders Are Racing Into AI Infrastructure
EVERY SPOKEN WORD
50 min read · 10,331 words- 0:00 – 0:50
Intro
- BHBen Horowitz
We have a whole new technology that's the most important technology ever, and you need a whole new infrastructure.
- RRRaghu Raghuram
Normally, when we talk about the infrastructure world, we're talking about the servers and the storage and the network. Here, it goes all the way down to the mines, copper mines. [chuckles]
- BHBen Horowitz
Yeah.
- RRRaghu Raghuram
That's how widespread this thing is gonna be.
- SPSpeaker
It used to be when you built something, it was an engineering problem, and here it feels like it really is a resource limitation. So whether it's tokens or not, we're pouring a ton of money into systems, and then those systems are producing a result. And right now, we're bottlenecked on those systems' ability to actually match the resources we're pouring into them.
- RRRaghu Raghuram
The leading memory vendor said the demand they have today, it'll take them three years of capacity to supply.
- ETErik Torenberg
If this fund does what we think it will do, how do we see the world in five to 10 years?
- BHBen Horowitz
America wins in the infrastructure game, and that would be awesome.
- ETErik Torenberg
Ben,
- 0:50 – 2:00
Introducing the Machine Age Fund
- ETErik Torenberg
Martin, Raghu, welcome.
- SPSpeaker
Thank you.
- BHBen Horowitz
All right. Thank you.
- RRRaghu Raghuram
Thank you.
- ETErik Torenberg
I, uh, want to start with a Mark quote to introduce this new fund. "This is the biggest technological revolution of my lifetime. This is clearly bigger than the internet. The comps on this are the microprocessor, the steam engine, and electricity, or maybe the wheel." Guys, the Machine Age Fund, please introduce it. Ben, start, start us off.
- BHBen Horowitz
Well, um, basically what's, uh, happened is we have a whole new technology that's the most important technology ever, and what happens every time, um, there's a dramatic new way of using all of the things that we love, infrastructure, um, you need a whole new infrastructure. And never has it been more high impact as it is on this one. So not only do we need new chips, new system software, we need new ways of doing power, we need to replace copper. [laughing] I mean, like it's absolutely everything. So it, it's a very exciting time. So, you know, particularly for the kind of hardware aspects of, of this new
- 2:00 – 4:00
Why Founder Interest in Hardware Just 4x'd
- BHBen Horowitz
era, um, we needed a new approach.
- RRRaghu Raghuram
Yeah, I would agree. I mean, normally when we, at least in the computing, when we talk about the infrastructure world, we're talking about the servers and the storage and the network. Here, it goes all the way down to the mines, copper mines. [chuckles]
- BHBen Horowitz
Yeah.
- RRRaghu Raghuram
That's how widespread this thing is gonna be. Um, and that's number one. And number two, I think what we have seen over the last three years is the steady increase of the capabilities of the models, where the model is no longer the bottleneck. And in fact, using AI, these models are getting better faster and faster and faster. Now the bottleneck is all what I call south of the model, and so that's why we need to work on that.
- SPSpeaker
You know, the only thing I'd add very quickly is, like, we tend to follow founders, and we've been watching over the last couple of years as the number of very strong teams going after complex hardware problems has increased. I don't know the actual numbers, but I was trying to estimate it over the weekend. So I think we'd get, you know, maybe 5% of the deals from top founders would come in, would be hardware before. Now it's, say, north of 20% or 30% right now. So, like, the founder community, which tends to be much smarter than the VC community, has identified this as a very active area for innovation, and they're responding.
- BHBen Horowitz
I think 5% is probably generous.
- SPSpeaker
Yeah, it's very low. It's very low. Yeah, 3%. Yeah.
- ETErik Torenberg
And explain some of the macro conditions that have led to this, this transit, this change in terms of the surplus of founders pursuing these ideas. Like, what are they seeing that's en-- that's enabling?
- SPSpeaker
Well, I mean, the obvious is, like, you know, the, the demand for AI is basically infinite, and as a result of that, every part of the supply chain is under, under duress. I mean, everything, including, like, materials used to make things like, like memory. Um, it's also very interesting. There's something unique about AI, um, which because the demand is infinite and growth is infinite, um, uh, what you tend to worry about is the margin of companies, which is how efficient it is. Like, normally you worry about growth. Like, can I just, you know, can I just get people to buy this stuff? You don't have to worry about that here. The question is, is can you do this in a way that's profitable? And a lot of the,
- 4:00 – 7:00
How Do We Know Demand Isn't a Hype Cycle?
- SPSpeaker
um, efficiencies are actually strictly a physical limitation of hardware. And so even the business model of the AI wave is really putting a lot of stress on the existing systems 'cause they weren't built for AI, they weren't built for those workloads. And I think there's just this, you know, this global observation that we actually need to change the core components to get that efficiency to help drive the growth and to drive the value of the businesses.
- ETErik Torenberg
Yeah. And a-how do we know that demand is actually outpacing supply here rather than this being, you know, another hype cycle?
- SPSpeaker
[chuckles] Well, I mean...
- RRRaghu Raghuram
Yeah, there are any number of signals, right? Um, firstly, it is that some of the smartest judges of demand are cutting huge purchase orders. I mean, if you look at the hyperscalers, right?
- SPSpeaker
Yeah.
- RRRaghu Raghuram
Their CapEx spend has been exploding. Next year, supposedly it's gonna reach a trillion dollars collectively across the big hyperscalers. This year it's about $700 billion, right? And if you think about the hyperscalers' position in the industry, they see demand from everywhere, right? They see obviously the frontier labs, um, wanting their compute. They see the AI native companies, they see the enterprise, they see the US geography, the international geography. So if anybody has visibility, it is them, and they've been jacking up their CapEx like it's never been seen before, right? So that's a clear, clear sign. And secondly, if you look at the companies that we see on a day-to-day basis, they are all ripping. All the application companies, the growth is insane. The frontier labs, the growth is insane. It's been documented. So I would say on the demand side, the signals have never been clearer that, uh, this is not a hype. It's-- And to top it all, all of it is just-
- BHBen Horowitz
And prices are going up.
- SPSpeaker
[laughing]
- RRRaghu Raghuram
Prices are going up.
- BHBen Horowitz
Like, we've never seen prices go, like, up on chips. [chuckles]
- SPSpeaker
The GPU prices went down, then went up again.
- BHBen Horowitz
They always go down.
- SPSpeaker
Yeah, yeah.
- RRRaghu Raghuram
It always goes down.
- SPSpeaker
Yeah.
- RRRaghu Raghuram
If you look at the c- price curve, it, it went like this, and then it went back like this.
- SPSpeaker
Yeah, yeah.
- RRRaghu Raghuram
And we know only, like, 5, 10% of the addressable market has started today.
- SPSpeaker
I mean, the, the, the supply, if you lo- if you look at the supply across the board, it's basically all booked out to 2028. I mean, it's so bad, we've actually seen multi-day auctions for a few thousand GPUs. Um, you know, the other side of that, of course, is demand. And as Raghu said, we've seen the fastest growing companies we've seen in the history of the industry.
- RRRaghu Raghuram
But also the unit of work that AI can do. The value of that unit of work keeps increasing, but underneath the covers, the number of tokens that are consumed is going by orders of magnitude, right?
- SPSpeaker
Yeah.
- RRRaghu Raghuram
If it's one token for, I mean, uh, 100 tokens for chat or an agent, it's thousands of tokens, right? So you got expansion on both sides of demand. One is the unit of work is becoming more and more consumptive-
- SPSpeaker
Yeah
- RRRaghu Raghuram
... of tokens, and then secondly, the number of people therefore that are gonna be benefited. It's
- 7:00 – 10:00
Sold Out to 2028: The Unprecedented Supply Crunch
- RRRaghu Raghuram
not just the developers, it's gonna be all knowledge workers, and then all of beyond that. So that's, that's what we see.
- BHBen Horowitz
You said the key components in, in supply are sold out to 2027, maybe in 2028.
- SPSpeaker
2028, yeah.
- BHBen Horowitz
What, what does it mean for, um, an entire industry to be, to be sold out that, that far, like?
- SPSpeaker
I don't know this has ever happened before. Do you guys recall? I mean, remember in the, um, in, in, in the internet days when we were doing massive build-out, the majority that was actually being put in the ground was speculative and was dark. Remember the dark fiber, and here, basically every GPU that's being created is already pre-sold. And so-
- BHBen Horowitz
Yeah. We weren't quite there. I mean, there was, there was a lack of bandwidth, like, in the '98, '99 timeframe, but th- there wasn't, there, there wasn't that much real demand for it because there just weren't that many people on the internet.
- SPSpeaker
Yeah.
- BHBen Horowitz
So, like, it was a two-sided thing, and the companies were all rushing there and needed more bandwidth theoretically, but there weren't the users on the other side to consume it necessarily. And then to really consume a lot of bandwidth, you have to do high bandwidth things like video, which weren't really viable for, uh, you know, a number of reasons that, that had nothing to do with how much bandwidth was in the data center. So it smelled similar, but it wasn't this. This is like we're flat out and people are reselling GPUs for four times what they bought them for, and this kind of thing. Like, it's just not... And then, you know, we're, we're also out of power and cooling. [chuckles] Uh, and then on top of that, it's really hard to build because there's these incredible political headwinds going into it. So it's, it's really unprecedented in my career, uh, that we've had anything, anything like this.
- SPSpeaker
No. I wanna give a, a quick anecdote. So this, I was talking to a CFO of a large company, large public company, who had historically been very resistant about going into the cloud, so they had a lot of servers. And they were doing an inventory, uh, check, and they realized that the memory in their servers had increased so much it could, uh, fund the entire migration to the cloud. [chuckles] So I just feel like we're in a very unusual situation now. [chuckles]
- BHBen Horowitz
Yeah.
- RRRaghu Raghuram
Yeah.
- BHBen Horowitz
Well, that's right. We're, we're out of many things.
- SPSpeaker
[chuckles]
- BHBen Horowitz
Power, cooling, memory, GPUs, like you name it, we're out of it.
- SPSpeaker
[chuckles]
- RRRaghu Raghuram
Yeah. So the flagship, uh, conference for the industry is the one called Hot Chips, is going on in Stanford. And the leading memory vendor said the demand they have today, it'll take them three years of capacity to supply. It's just today. It's not even future demand.
- BHBen Horowitz
[chuckles] So in terms of being about everything simultaneously, is it because people just underestimated how good the models would be, how, how useful they, they would be, uh, they just couldn't
- 10:00 – 14:00
What's Actually Bottlenecked Right Now
- BHBen Horowitz
have foreseen the demand?
- SPSpeaker
Well, I don't even think it's that. I mean, this stuff came out of nowhere, right? We've-- We're only four years into this. So even if we had a perfect oracle once it started working, I don't think we could've-
- RRRaghu Raghuram
Yeah, we couldn't have built the capacity fast enough
- SPSpeaker
... we couldn't have built the capacity. There's no way. And we're talking about, like, chip cycles, which tend to be three to four years. We're talking about breaking ground and building data centers, which is, you know, four to five years. We're talking-
- BHBen Horowitz
And, and connecting, breaking down and building them and having a power source. So, like, you either have to build your own power or, like, usually both. You've got to build your own power and have a power source, which is not easy.
- RRRaghu Raghuram
Yeah. You have a industry that's use-- If it's growing at 20, 30%, it's a great growth rate, right? And it's being connected to an AI software industry that's like triple of this as a base.
- SPSpeaker
Yeah.
- RRRaghu Raghuram
So you can see the disconnect, right? So it's, it's just widening.
- BHBen Horowitz
And so why didn't this fund exist, you know, fi- five years ago or seven years ago? Or why, why was it not a great category to, to invest in, in, in a, in the same way, Brad? Well, I would say we're probably-- I, I'd like to think we're just in time, but, you know, we probably would've been, uh, well-suited to have it at least a couple years ago.
- SPSpeaker
I mean, I will say you could actually point on, on, on basically every epoch to, uh, uh, an independent company that came up, right? Clearly, the move from the client, uh, from, uh, a mainframe to the client server, we saw a bunch of companies come up. Um, the move to the internet, that's why we got Cisco and Juniper. Uh, even in the mega data centers, which by the way, was largely driven by the incumbent cloud providers verticalizing. You saw, saw the, uh, uh, arising of Arista. So there has been the ability to invest in, you know, silicon and hardware, but it's been relatively minor 'cause the change has been relatively minor, like one chip company, one switch company. Where here, everything is. And so I, I agree with Ben. We're probably, you know, we probably could have started a little bit earlier, um, but the amount of change is so high now that it's just an obvious thing to do.
- BHBen Horowitz
And the other thing is the demand for intelligence is so vertical, um, with really no end in sight. I mean, 'cause every company that's adopted it ... is growing very fast in its usage, and then most companies haven't adopted it to a high degree. And then consumers are just getting started. And so it's gonna probably, the demand for tokens is probably gonna grow close to 1,000% a year, which you cannot grow supply that fast. Like, like we're not-
- ETErik Torenberg
There's no way
- BHBen Horowitz
... like the amount of just work we're gonna have to do across the board to get to the point where we can grow like infra at that kind of rate is, is pretty vast. So I think there's a lot of investing opportunity on the way. And by the way, the other thing is like all the architectures of the hardware systems were built for a whole different era of computing. And so more than just we need more capacity, we need capacity to build-- There, there's lots of opportunities to build different kinds of infrastructure.
- RRRaghu Raghuram
Yeah. They're, they're all reaching their, the physics limits for what they were designed, right? Like what Ben was talking about, copper and so on and so forth. And you could go across every one of these categories, and you could find, okay, this is the limit of this type of technology. So now you gotta get some technical breakthroughs to get to the next level.
- ETErik Torenberg
Yeah. I wanna dive deeper on the demand side for a second. A-as we've moved from chatbots to reasoning to agents to, to multi-agents, each step has multiplied the number of tokens a single task takes up by, you know, orders of, increasing order, orders of magnitude.
- BHBen Horowitz
[chuckles] Nobody likes to use AI more than AI.
- ETErik Torenberg
Right. [laughing] So, um, why does that keep happening
- 14:00 – 19:00
Tokens, Scaling & Why There's No Natural Regulator
- ETErik Torenberg
instead of a leveling off, and do you just see that happening, you know, in-indefinitely, just continuing to?
- SPSpeaker
Uh, well, so there's a couple aspects to that. The first one is, is for sure right now, if you look at like the, the way we're achieving scaling, the way we're doing it is through a lot of inference, so through a lot of token, right? If you think about what RL is, you know, so it's a lot of inference. If you think about chain of thought, it's a lot of inference. Uh, if you think about long-running agents, of course, it's a lot of inference. And so that's just basically been one of the approaches that we've been using to, um, uh, to scaling. Um, I think if you wanna step back and say kind of what is the macro trend here, it used to be when you built something, it was an engineering problem, and you throw a bunch of engineers at it, and that doesn't scale, and that would have a n-natural law of engineering physics, uh, which is what the Mythical Man-Month came from. And here it feels like it really is a resource limitation. So whether it's tokens or not, we're pouring a ton of money into systems, and then those systems are producing a result, and right now we're bottlenecked on those pos- those systems' ability to actually, uh, match the resources we're pouring into them. And so I think like tokens right now is probably where we are on the scaling curve, but we don't have a natural regulator like engineering like we did before. So I think we should expect this to continue, and we have to build the supply to support it.
- BHBen Horowitz
Yeah, like the simple way to think about it is any problem that you have can be solved with enough infrastructure. [laughs]
- SPSpeaker
Basically.
- BHBen Horowitz
GPU power-
- SPSpeaker
And money
- BHBen Horowitz
... and money. Uh, and so until we run out of problems, we're not going to run out of demand, and that's the, that's the, uh, challenge.
- RRRaghu Raghuram
I mean, AI's answer to getting better and better is to use more AI, right? Inference is one basic building block, but that it keeps using over and over and over again. And so that's why these tokens multiply each time.
- SPSpeaker
Yeah, even the autocatalytic effect. So even the idea of using AI to create more AI, like creating a GPU kernel, of course, is just using more AI, um, as part of the process. So again, one way that we, we think about it is in the past, money would come in, you have an engineering problem, we know that it takes two years, normally fails, you know, it's a national governor, and then you get the product on the other end. This, there's, there's, there's nothing between the money going in and then the hardware, you know, creating intelligence. And so now we're just limited by our ability to create supply. It's a very, very different dynamic.
- RRRaghu Raghuram
Yeah, it's giving more GPUs than our solid is called.
- SPSpeaker
Yeah, that's right.
- RRRaghu Raghuram
So that's the cycle.
- SPSpeaker
As long as you have the money, the GPUs, and the data, you know, r- for the foreseeable future, you'll be able to scale these things.
- ETErik Torenberg
And it's, it's fascinating because I've-- you know, over the last decade, it feels like there are so many, you know, people, and the pervasive sentiment was there's too much money going to startups. We're, we're overfunding these startups. There's too much money in, in, in, in, in venture capital. Say, say more, Ben, about what that means, 'cause there, there used to be this, um, sort of skepticism that the more money you put into, into the industry that, you know, that there would be bigger outcomes. And now, you know, we were saying at the offset that there's, to some degree, the, the market is as big as we, uh, collectively contribute to it.
- BHBen Horowitz
Yeah. So this is, this-- Look, the one thing we all knew w- in startup world is that if I have a two-year lead on you and you try and catch me by hiring 1,000 engineers, you're gonna wreck your company. Like, that never works. It's a Mythical Man-Month. Nine women can't have a baby in a month. That, like, that's it. Like, that never works. Okay, now that works. [laughs] Um, but it's not hiring 100,000 engineers. It's taking $3 billion and, like, lighting up a magnificent cluster, and then all of a sudden, you know, whatever, Grok can come out of nowhere and like, oh, all of a sudden it's real, or, or Kimi or, or, or what have you. It's just like these leads, um, you can throw money at the problem, and you can throw money at almost any problem, and that works. And so that is just completely different than anything we've ever lived through. So we're-- By the way, we're all psychologically adjusting to this.
- ETErik Torenberg
The ChatGPT app has a billion weekly actives. There's about 30 million, uh, developers, um, who are using, you know, relatively a big portion of compute demands. H-how do we think about commute
- SPSpeaker
compute demand needs now and in the future in light of what people are actually doing with AI.
- RRRaghu Raghuram
That's the progression, right? So ChatGPT was a casual app to coding for professionals, right? Now, using coding, you know, now built amazing tools for knowledge workers, so that's the next frontier. And now there are over a billion knowledge workers in the wild, right? And with that, it's a long ways to go for that demand. And by the way, the work that they do, all this work around automation and so on, and then you get to the back office, which is all the agents. So progressively, each of these things unlocks,
- 19:00 – 25:00
Agents as a New Kind of Employee: The GrokBot Moment
- RRRaghu Raghuram
uh, I would say an order of magnitude more demand, and we are just at the start of this.
- BHBen Horowitz
Well, and now you have GrokBot, which is kind of, uh, you know, what, uh, happened with coding is kind of happening with all use of computer via GrokBot. And so we're in a whole nother wave of demand, and most certainly [chuckles] there's gonna be more to come. Uh, so it, it does seem quite unlimited at the moment, and we haven't even gotten into embodied AI or robots, uh-
- RRRaghu Raghuram
Yeah
- BHBen Horowitz
... which are gonna be another source of demand.
- RRRaghu Raghuram
Mar- Marty's the expert, but, uh, my understanding is that GrokBot uses computer use, which is just like human beings sitting inside the computer typing away.
- SPSpeaker
Mm-hmm.
- BHBen Horowitz
I, I literally used it over the weekend, uh, to update my credit card with a bunch of services that I've been, like, lazy to do and cancel a bunch of subscriptions. I mean, this is not coding or whatever. This is true computer use.
- RRRaghu Raghuram
All of a sudden you create, like, half a billion knowledge workers, except they're all sitting inside of the computer-
- BHBen Horowitz
[laughs]
- RRRaghu Raghuram
... doing work.
- SPSpeaker
I, I do, I do think that, that, that Mar- Marc Andreessen is right. It's like the right analog here is, like, the steam engine or electricity in the following way. Like, we've, we've introduced this new thing that you can turn to work, and there are some very obvious applications now, but there's probably 30, 40 years of throwing compute at problems, I think with a clear reward signal, and we- we're just starting. Like, we've got language and code. That's it, and just starting computer use. But, like, what else are we looking at? We're looking at, uh, in terms of science, materials, biology. I mean, of course creativity is a massive use. And so listen, we're at the very, very early part of a very long journey, and we've re- removed this key bottleneck, which is, you know, traditional software engineering. Now, of course, you know, bottlenecks will move, and there'll be kind of more complexity elsewhere, but I think we're at a very early in a very long run of throwing compute at problems. So let's expect, you know, this compute need to persist for decades. By the way, because we mentioned it, um, Marty, ta- talk about GrokBot, um, because we, um, we were talking at the offsite about how, you know, what, what struck you about it. Obviously we're involved in every possible way you could, you could be-
- BHBen Horowitz
Yeah
- SPSpeaker
... could be involved. But what, um, yeah, what, what did you find so interesting about it? So I think we've, like, I think we've, as an industry, gone through kind of multiple realizations for how AI enters our lives, right? And, and, uh, very early on we're like, okay, well, you add AI to a product, and it's like a, whatever, it's like a search bar, and then you kind of, you know, you, you do chat with it, and it chats back, 'cause that's kind of the traditional way to do it. Um, uh, and then OpenCloud kind of sh- showed up, and that was earlier in the year. And with OpenCloud, I say, okay, well, maybe, like, it just being like Google, but better, maybe that's not the full embodiment of it. How about we'll have it be a standalone thing, but it'll be an extension of you, and it'll share your keys, and it'll know your passwords, and it'll just kind of do stuff that you would do, right? So it's kind of an extension of you, but it's more like a human e- an extension of you. And then when I think Grok- GrokBot got really right is, you know, how about it is actually an employee? So now you have this thing that's an entity, and it doesn't have, like, special access to your keys or whatever. It has its own computer, and it has its own browser, and because these are the smartest models in the world, it can do whatever an employee can do. And it's kind of interesting because now, actually, if I, if I want something done, my first thing I, I think is like, "Well, can GrokBot do it for me?" And, and often the answer is yes, even if it's something you wouldn't, uh, you know, expect it. So the obvious ones are, like, whatever. It'll, like, manage my calendar. It'll, like, book a meeting. But there's also n- uh, non-obvious ones as well. Like, so for example, I'll have it, um, uh, read through my email and do triage. And, and I didn't-- I don't tell it how to do that, but it will know to check with me before actually doing the triage. So, like, these things are sophisticated enough that you can give it relatively high-level tasks, and it'll do kind of, you know, like, sophisticated things as a result. Ben, I know you're thinking a lot, a lot about this and how, how this w- you know, works in the organization. You think a lot about culture, of course. What, what are your thoughts here?
- BHBen Horowitz
Well, I mean, I think i- if you just look at us, um, y- you know, it's like having a new kind of employee, and there's gonna be a lot of them. And we have to, just like, you know, with our... We spent many, many, many years figuring out how to work with our kind of regular human employees, and now we've got these other kinds of employees. And, you know, there is a learning curve with them. So, um, they can burn a lot of tokens and spend a lot of money and get nothing productive done. Um, they can forget stuff. They can make stuff up. Um, you know, they can have good behavior. They can have bad behavior. They can-
- SPSpeaker
Like humans
- BHBen Horowitz
... they can create security problems. [laughs]
- SPSpeaker
[laughs]
- BHBen Horowitz
So, like, there, there, there's all those aspects to it, but, like, they can also be, like, super-duper productive. And so I think figuring out how to integrate them in, have them work nicely with the people that they're working with, um, the actual humans, uh, is all something that we're learning how to do. I mean, I, I don't wanna sit up here and say I've cracked the code. We've got this marvelous loop, and, um, [laughs] the whole firm is just completely automated now, and I'm gonna slowly get rid of all the humans 'cause I can. Like, that's not at all where we are. We're much more going like, okay, how do we make all our humans superhuman, um, without, like, wrecking the place, um, because the bots get out of control?
- RRRaghu Raghuram
Yeah, and it's interesting because we've done-- we've tried a couple of different ways as to how best to get agents into the system, if you will. And eventually, uh, it was Martin's insight, just treat them as people and get it done, and that's what we're doing. That's turned out to be the most durable way of getting this thing going inside of an organization.
- ETErik Torenberg
I wanna go back to the supply side and go deeper into the, the bottlenecks. You know, we, we were talking about how, you know, in terms of the data centers, the chip architecture, system software, facilities themselves, that none of them were designed with, with AI in mind.
- 25:00 – 28:00
What "AI-Designed" Infrastructure Actually Looks Like
- ETErik Torenberg
What would it look like for them to be designed with AI in mind? Like, what, what is sort of the mental model for thinking about what that could mean?
- RRRaghu Raghuram
Yeah. So, um, I mean, if you start with the statement that you just said, "Hey, original model, um, of infrastructure underneath these models has to change," you can go seg- category by category and see where it breaks, right? And then you start, uh, unlocking the bottlenecks in each one of these things. So eventually, you have to get to a system where if you look at what an inference engine does, right, it takes up a lot of memory, it generates new tokens along with the compute. And so you can just think about how do I optimize all of this? What does the memory need to be? What does the compute need to be? How do they need to talk to each other? How much power does each of them need? And if they need all of this power, how do you cool each of these, right? And then how do you put the collections of these things together? That is the exercise that's underway in the industry right now with a lot of the founders. So they're breaking down the problem into its fundamental components and saying, "What is the exact nature of the compute that's getting done? Okay, it's gonna be matrix multiplications. How do I optimize my compute around that kind of a scenario?" And then they all need memory progressively to generate these tokens. What is the best way of hierarchically arranging this memory, right? And then how does the power consume-- I mean, then you've got to connect it together. What are the ways of connecting it on the same chip, but across chips and across data centers? How much power does each of these data transmission take? So you have to progressively break it all down and rebuild it from these fundamental building blocks. And that's what we see underway, and that's where we see the opportunity.
- SPSpeaker
Let me give you an interesting mental model to think about on, like, how the landscape's changed. So, um, uh, so today to build a frontier model costs, let's say three to five billion dollars, right? So, and let's, you know, and, and that's to train it. And so the inference has to pay back at least that, of course, right? You know, in order for any of this stuff to be viable, let's say two times that. So let's say that now inference has to, to make $10 billion. So if you can save 20% of efficiency on that, that's $2 billion.
- ETErik Torenberg
Mm.
- SPSpeaker
And you can easily build an ASIC for $2 billion, right? So it's, so we've actually gotten to this interesting point in the industry where it actually makes sense to build an ASIC per model just because the mont- amount of capital investment in that model. And then unlike traditional software, traditional software has a lot of state and a lot of, you know, it, it's very dynamic. These models are fixed. The model weights are fixed. And so we don't know if the world goes to per model ASICs, but it gives you a great mental model of how you would evolve the architecture to be far more bespoke for these massive capital investments we're doing. Like, I don't think in the history of the industry we've ever created a digital artifact with something like $5 billion
- 28:00 – 34:00
Rack Power, Liquid Cooling & the Data Center Redesign
- SPSpeaker
that went directly into that artifact. And so, you know, like this I think is gonna put the greatest demands on hardware that we've ever seen.
- ETErik Torenberg
Well, to, to that end, rack power requirements are moving from roughly five to 10 kilowatts to 100 to 250 kilowatts. Compute density is climbing something like 70x.
- SPSpeaker
Mm-hmm.
- ETErik Torenberg
Cooling is moving from air to liquid as a requirement. What are the investment opportunities as, as a result of this?
- BHBen Horowitz
Well, first of all, when you get to that level of power per rack, AC power doesn't work anymore. [chuckles] And so, like, that's a pretty wild thing. Um, so now, now you're into DC power, which by the way, also requires its own cooling, um, and is like, uh, by the way, super fucking dangerous. Uh, which is kind of ironic 'cause this was, um, Edison promoted DC power by claiming how dangerous AC power was and demonstrating it by, like, electrocuting animals and things.
- SPSpeaker
The horse, yeah.
- BHBen Horowitz
Um-
- SPSpeaker
The horse, yeah.
- BHBen Horowitz
Yeah. So, but he was right, but around his own kind of power, which is extremely powerful, is the good news. Um, so, you know, just starting with power, uh, y- yeah, that's gonna be like very, very different. I think with cooling, so the, and this gets into, so yes, we're going air cooling to liquid cooling. I think we're already at liquid cooling for any state-of-the-art data center. Like that's already kind of a done thing. But it gets into, okay, you know, given the political environment and so forth, you, like, liquid cooling isn't enough. It's got to be eco-friendly liquid cooling, um, and, you know, kind of DC power is not enough. It's got to be, um, power that contributes, uh, to the power of society, not takes away from it. And so you have data centers who have been behaving badly, um, small percentage actually, probably 10%, wasting a lot of water. Um, you know, not as much as pistachios or almonds and so forth as people demonstrate on the internet, but, like, they could be a lot more efficient with that. Uh, and then there are ones that, you know, kind of are, uh, parasites of power and don't contribute power back. I think all that's gonna end. It's gonna have to end just because like, like that, we, we've kind of gone through a one-way door on that. Uh, so that requires like a level of engineering, um, that, you know, many haven't invested in yet, so that's coming. Uh, and then, you know, like- If racks are that dense, [chuckles] um, there are other things that, like the way the floors are designed have to support that kind of weight. Uh, y- you know, that kind of thing is, is actually for real. Um, and then, you know, I, I think that there's, you know, you just need a lot of everything, and so there's gonna be, you know, kind of also by the things are really loud, so you have to build the data center with thicker walls or you're gonna disturb the peace in the neighborhood, which is not gonna be acceptable. Like, I don't think any state's gonna allow that.
- SPSpeaker
Yeah.
- BHBen Horowitz
And so a lot of the ways people have architected and designed the buildings themselves are already completely obsolete. Like, once we get to Fineman, um, a much smaller s- percentage of the data centers that we have today work.
- SPSpeaker
In fact, I mean, everybody talks about memory prices, but one of the fastest areas where price is increasing is reinforced concrete for the-
- BHBen Horowitz
Yeah. [chuckles]
- SPSpeaker
... for their centers. The other thing that happens when these data centers are, uh, sending 800 volts to the rack is it's become so dangerous, number one. But secondly, we don't have enough electrical contractors that have the expertise to deal with the 800 volts inside the data center because this is high voltage.
- BHBen Horowitz
Only 2% of electrical engineer- or, uh, electricians in the US have been certified on DC power. [chuckles] So, like, that gives you an idea. Now, Meta's got a whole program to train people up and so forth, which is great. It's like a new Job Corps where they train people for free to do this job. But, you know, it, it's funny, AI is taking all the jobs. AI is gonna create a lot of new electricians. [chuckles]
- SPSpeaker
Yeah. I think we're, we're just doing something in space too. Yeah. And the big guys that own the big cloud data s- uh, big data centers, they all are furiously experimenting with, uh, robots, right, to do the work of assembling or putting servers into the data center, et cetera. And so you will see that increasing as a res- result of the evolution in AI. By the way, to be c- to be clear on the, um, on the actual fund that we're raising, our focus is on computer science infrastructure. So anything a model runs on, that's computer science, right? So think, you know, chips, network, interconnect, storage, all the way down probably to the electricity. Yeah. And, and say more about the robotics a- at Arm in terms of what we'll be doing versus maybe American Dynamism or how, how to think about that. Yeah, for sure. So, um, you know, again, we, we think that any platform that, that AI will run on, like one of the c- the, the, the great breakthroughs that AI, uh, does is it allows computers to interact with the physical world, right? It, it can see, it can hear, it can talk, right? And this means new platforms, right? And the simplest way people say edge device, but that doesn't really mean anything, right? I mean, it could be a mobile device, it could be a CDN, it could be a laptop, but it also could be a, an embodied d- you know, device that goes around. And so again, we, we, um, as, you know, as infrastructure-focused investors don't do heavy regulated industries, um, or more verticalized industries. But any sort of computer science platform that's
- 34:00 – 38:00
44 Gigawatts by 2028: Why Building Faster Is So Hard
- SPSpeaker
gonna push AI further out, we're quite interested in. Yeah. Go, going back to the data centers. By 2028, new data centers are gonna need something like 44 gigawatts of additional power against maybe 25 gigawatts of expected grid additions. The gap-
- BHBen Horowitz
Hold on, hold on. We, we use that word gigawatt.
- SPSpeaker
[chuckles] No. Yeah.
- BHBen Horowitz
It's like, it's like, "Oh, we'll have 100 gigawatt." Martin, what's a gigawatt?
- SPSpeaker
I mean, I mean, how big is it? It's multiple football fields. I mean, it's massive. It's 50,000-
- BHBen Horowitz
And what is the power?
- SPSpeaker
... 50,000 people. Uh, what do you mean what is the power?
- BHBen Horowitz
Like, like-
- SPSpeaker
The equivalent? It's like 50,000 houses
- BHBen Horowitz
... a town, a city, uh, yeah.
- SPSpeaker
50,000, 50,000 homes. 50,000 homes. It's like-
- BHBen Horowitz
50,000 homes. How does it compare to power?
- SPSpeaker
I, I, I grew up, I grew up in Flagstaff, Arizona, [chuckles] which is a town of 40 to 60,000 people, depending on the universities. We have less than a gigawatt of power consumption. I mean, this is a tremendous amount.
- BHBen Horowitz
So you could basically light up and air condition your entire town for a gigawatt.
- SPSpeaker
Yeah. Yeah. I mean, this is enormous.
- BHBen Horowitz
He's just throwing them around. [chuckles]
- SPSpeaker
It's... No, but e- by the way, everybody talks about the gigawatt. There's very few gigawatt data centers that are actually up. I mean, we've got a long way to go.
- BHBen Horowitz
Right. Yeah.
- SPSpeaker
To, but then why can't utilities and hyperscalers just build faster?
- BHBen Horowitz
Oh, there's so many things there. Well, there's, first of all, right now you need humans to build them, so there, there's just like the regular construction. But much more than that, you need permits, um, you need access to power, uh, that you can plug in. So you're either, you're doing a combination of you've gotta get access to power, which is a massive kind of regulatory bidding struggle. There's very limited kind of amounts and things you can tap into in terms of nat- natural gas, power grids, what have you. Um, but then you also have to build your own power, and guess what? We've got shortages of transformers and turbines [chuckles] and everything that goes into that. So it's just, y- you know, like you've gotta get all that stuff. It's not, this is not a software problem. It's not just like a bunch of engineers, "Can't you, like, work weekends?" and that type of stuff. Like this is, not that that works anyway, but, uh, it, there are real bottlenecks in this, and these, these lead times are not that easy to compress. And look, we have the best minds in the world trying to figure out how to compress them, uh, but, uh, it's not easy.
- SPSpeaker
It's hard.
- BHBen Horowitz
It's not easy. And the demand is not slowing down. So we're already behind. The demand is growing, you know, 10X a year right now, and, you know, the supply just can't grow that fast.
- SPSpeaker
By the way, it is so bad that right now, if we have new companies going for GPUs, it's often in Mexico or Australia or another country just because it is so difficult in the United States now.
- BHBen Horowitz
Yeah, we're creating huge job, both job and long-term economic opportunity in other countries by, uh, banning data centers here. I think, look, the, the right answer would be to set a standard where a data center contributes back to the community.
- ETErik Torenberg
Yeah.
- BHBen Horowitz
Like that power gets better, there's no noise, there's no water issue, um, and it's adding jobs. Like, that ought to be the standard.
- SPSpeaker
Yeah.
- BHBen Horowitz
And then everybody ought to be just held to that standard. And by the way, like, there are, there are data centers that do that now. Like, that's not a, you know, like a, a futuristic dream or something. Rates, energy rates have gone down, like, every year they're there, and the reason is they provide their own power. They give power to, to the state during the day, and then at night they borrow power from the state when the state doesn't need it, 'cause you're always-- the, the way power plants work is you're always generating peak, uh, capacity. And since a data center has steady capacity during day and night, and a city goes way up in the day and
- 38:00 – 40:00
Why "Machine Age" Is the Right Name
- BHBen Horowitz
way down at night, um, that's a symbiotic relationship.
- ETErik Torenberg
Zooming out, uh, why do we think the-- You know, we, we were batting ar-around the name for, for a little bit. Uh, why do we think machine age is a, is a compelling term for, for what we're doing here?
- SPSpeaker
Well, listen. Let, let me, let me, let me take a crack. So the first one is I think Ben's absolutely right, artificial intelligence was the wrong word.
- ETErik Torenberg
Yeah.
- SPSpeaker
Like, we shouldn't have called it art. It's machine intelligence. Um, it-
- ETErik Torenberg
Say more about that. Why is that?
- SPSpeaker
Uh, because it's not how humans think necessarily, right? I mean, it is a cache of how humans thought, is a collection of humans' thoughts. But, like, to date, we don't know how to take a, um, uh, an AI with no knowledge and put it in, uh, out in the world and have it reconstruct language, right? Like, that's not what we've done, right? We've, we've built a, something that can learn off of everything we've already learned and then use that in a productive way. And listen, A-A-AI is a general term that goes back 70 years in computer science formally that applies to many different things, and of course, it's got a lot of baggage, either from science fiction or from, you know, Nick Bostrom who wrote about it or whatever. And so, so the first one is just an acknowledgement, like, this really is machine intelligence. And then you want to emphasize the machine part of it. I mean, there's kind of this deep irony, and this is from the, you know, the, uh, the software's eating the world people that, you know, you've really come to a place where you pour money into something and then you're limited by the actual machines below it. And so I think it is a kind of a nod to, like, the hardware component is so significant in this wave and, and we want to acknowledge that.
- ETErik Torenberg
Yeah.
- SPSpeaker
I think that's what's gonna create the next breakthroughs in technologies is the quality of the machines underneath. Um, so that's, that's basically the reason for the name.
- ETErik Torenberg
It's also a cool name. [laughs] Machine Age.
- BHBen Horowitz
It sounds good.
- ETErik Torenberg
[laughs]
- BHBen Horowitz
Futuristic.
- ETErik Torenberg
Yeah. The, um, given how much has been spent on AI infrastructure to date, to date, and how CapEx intensive these businesses can be, are we past the point where new companies can bre-break in at, at, at sort of material levels? Uh, you, you know, inc- why not incumbents
- 40:00 – 48:00
Won't Incumbents Like Nvidia Take Everything?
- ETErik Torenberg
like Nvidia, CoreWeave, et cetera, just take the lion's share of these markets?
- SPSpeaker
They all do. Well, there's no question about it, right? But to our discussion earlier, when you get-- You're gonna need fundamentally new innovations to keep the growth continuing or the pace of improvement continuing, whether it's tokens per second, per dollar, uh, uh, tokens per watt, uh, tokens per rack, right? Um, or power. You take any metric, if you want to have a 10X on those metrics, you gotta have new innovation. And new innovation traditionally comes from brilliant founders thinking about solving the problem from first principles in a different way, right? And that's what's needed here for the next jump in innovation. I mean, this is the law of markets, right? I mean, let's assume that the, the existing silicon incumbents are multi-trillion dollars in market cap, which is absolutely the case. Even 5% of that is a massive private company. Massive private company, right? We're talking-
- ETErik Torenberg
Yeah
- SPSpeaker
... you know, annual. Um, and you could say, "Well, but Nvidia could do that." They could, but why would they [chuckles] if they're focused on things that are in the 90%, which is also driving the same amount of growth? And you always ask these questions. We asked these questions during the cloud days, right? Like, "Well, why wouldn't Amazon did this?" You asked these questions during the Microsoft days, "Why wouldn't Microsoft do this?" There's a very natural law of markets is once you get to a certain scale, there's tremendous opportunity for innovation, um, at, at the margins.
- BHBen Horowitz
Yeah. There's a funny, uh, quote from our partner, Alex Rampell. He had this startup called TrialPay, and he was trying to sell it to... or sell the, its, his services to, to Meta and, uh, then Facebook. And Dan Rose, who was the head of corp dev at the time, said, "Alex, that's great. You're, it sounds like you can collect a lot of silver bricks, but I'm like, I have so many gold bricks, I can't even pick them all up."
- SPSpeaker
Yeah. [laughs]
- BHBen Horowitz
"And so the last thing I'm doing is looking at a silver brick."
- ETErik Torenberg
Yeah.
- BHBen Horowitz
And I think Nvidia's in that position today.
- ETErik Torenberg
100%.
- SPSpeaker
Yeah.
- ETErik Torenberg
We were talking about, as it relates to the model providers, that if you're, you know, in the sweet spot of, of what OpenAI or Anthropic can, can do, you know, one of their main sort of interest areas, that might be a tough place to be. But anything outside of those maybe, you know, three to five areas might, uh, you know...
- SPSpeaker
As mark- as, as markets expand, they fragment, right? And it happens all the time. And remember, in the early days of Ford, there was the 1913, there was the Rouge River plant. Literally this, you know, this was like, made cars. Like, in went like water, coal, and rubber trees, and out came cars.
- BHBen Horowitz
By the way, he bought a whole rubber tree-
- SPSpeaker
Rubber plantation [chuckles]
- BHBen Horowitz
... plantation in the Amazon jungle.
- ETErik Torenberg
Right.
- BHBen Horowitz
And, and there's a great book called Fordlandia. [chuckles]
- SPSpeaker
Yeah.
- BHBen Horowitz
Where, so 'cause he wanted to, like, own, like, the complete vertical thing, where he created this city called Fordlandia- In the Amazon jungle, um, which had like-- it was all Americanized, bandstands and ice cream and all this kind of stuff. And it actually worked for a while until, uh, he made people, like, show up to things on time, and then they were like, "Screw this. Get the fuck out of here."
- SPSpeaker
[laughing] So, so now if you look at the car industry, of course, there's multiple levels of supplier and there's a bunch of companies, and this always happens. So, you know, as markets expand, they fragment. There's a lot of... And then, and then once that growth slows down, they tend to consolidate. The consolidation can either be acquisition or it can be, like, new challengers rise up, and that, that is the, you know, everlasting cycle of private markets.
- BHBen Horowitz
Yeah, 'cause the use cases are, are multiplying, and there's no way-- L-like, if you're the biggest company, you can get to the biggest use cases, but there's so many use cases, and all, as, as Martin was saying, very valuable use cases that it's just very hard to get to in a great way.
- RRRaghu Raghuram
Yeah, even inference used to be one simple architecture, right? And it no longer is. It's like it's so complex now. So it's inevitable that you can optimize things in a different way.
- SPSpeaker
By the way, here's a very interesting thing. Like, th-th- people don't, um, uh, o-often don't understand that, like, margins kind of fell out of the standard way of doing the technology with software, right? Like, it wasn't really a technology problem. Like, once you got the business working, you tended to have pretty good margins 'cause that's just kind of how software works, certainly when you shipped it, but even as a service. Uh, and that's not necessarily the case with AI. So we may actually be entering an era where the optimization in the hardware is absolutely meaningful to the upside of the business in a way that we haven't seen in the past. So there's a lot of opportunity here.
- ETErik Torenberg
Let's get deeper in talking about the types of companies we'll be investing in. Um, maybe we could start by either illustrating the, the, the sub-sectors or, if we can, talk about a few, um, or a couple investments that we've made. I know there's some that haven't been announced yet, but Raghu, do you want to take us down?
- RRRaghu Raghuram
Yeah. I mean, the sub-sectors, as we've been talking all along, is every one of these categories, right? The obvious ones are, um, uh, compute chips. But these days, it's not enough to build a chip. You need to build a full system, right? And then therefore, what goes into the system. There's potentially memory innovation. There is potentially networking innovation. There is potentially power chips, and so on and so forth. So each one of these categories are categories where you can see public company-style companies emerging, and those are all things that we are looking into. Um, and then once you put it all together, there's a layer of software around it to automate all of these things, to manage these fleets, and so on and so forth. So that is another important area. So these things keep building on each other, but every one of these categories is important.
- ETErik Torenberg
Talk about what's different about these kinds of companies fr-from the usual company. I mean, one thing you could tell from the companies we announced is their first rounds have been massive, you know, hundreds of millions. Is it a different kind of founder, or w-what else is different as we think about just the practice of, you know, building and investing in these kinds of businesses relative to our traditional software?
- BHBen Horowitz
Well, I, I think the big thing is, uh, you hit on one of the big things, which is a lot of money goes in, um, before they get to a product. Um, and that's just kind of the nature of it. Now, that's true on big models too, but I, I, I would say that's a little more of a known path, uh, whereas this has got a little more risk and a little more money than, uh-
- RRRaghu Raghuram
Yeah
- BHBen Horowitz
... than some of the other things that we've done. But, um, and, you know, look, a lot of, a lot of the chip founders, um, are here from the past. [chuckles]
- 48:00 – 53:43
The Founder Profile: Why Hardware Needs Experience
- SPSpeaker
I think there's general consensus that, that, you know, it is the time that to reshape this stuff. And so follow-on rounds, there's a lot of capital available, which, you know, of course, you want to be investing into areas where there's capital available. And so the atmospherics are also just different.
- ETErik Torenberg
Patrick Collison, you know, remarked a few years ago, he said, "Hey, it feels like there's less younger founders today" in, in the way that, you know, Zuck, you know, in college building the next Facebook or, or, or Gates, um, you know, in, in the same way with Microsoft. And of course, you know, the Michael Truells of the world. There, there's still, you know, some young founders building iconic companies, but it does seem, you know, y- to your point, that there's more older founders b-building these, these, these companies or, or less tw- 20-year-olds. I'm, I'm curious if you-- if it resonates and why.
- BHBen Horowitz
Well, I think it's Raghu's point that if, if you're building something that has, like, a very complicated supply chain, has to manufacture things, um, and is technically complicated- That, you know, some experience helps. Uh, and, you know, if you look at Elon or Travis Kalanick, their companies when they were young were software companies. It wasn't till they got, like, a lot-- Even those guys, the best guys, um, needed some experience in building a companies, building technology and so forth to kind of graduate to the much more kind of complicated or, uh, I would say elaborate domains. You, you know, there's just much more, there are many more moving parts in these things. And so, look, when you're learning how to build a company, it's hard enough if you completely understand the product. If you don't completely understand the product and have to learn it while you build the company, um, that's just such a steep learning curve for a brand new entrepreneur. So I think that what we're seeing is you see Michael on the one hand, um, who is a very young guy, brilliant, but what he built was kind of a pure software AI thing.
- SPSpeaker
Yeah.
- BHBen Horowitz
And then on the other end, you have like an Elon or a Travis who can, who's got enough experience. I think Michael could probably do that, you know, 10 years from now, but y- today that would have been hard.
- SPSpeaker
And it's, it's important to remember, like it's been defocused by the entire industry and academia for the last 20 years, right? It's just, there just hasn't been the s-same opportunity. Like it's been there, but like it's never been a growth area. The growth areas have been, you know, software, um, networking, things like that. And so I also think we just have a paucity of people coming out of the universities or having experience at large companies that have, have done this. I mean, there's just not that many.
- BHBen Horowitz
Yeah.
- SPSpeaker
Like you don't go intern and like build a chip. Um, so... But a lot of that's changing now. Like, listen, we're gonna create a whole generation of, of, you know, founders that come from these new companies that will know how to do this and, you know, they'll be hired in much more junior. And like, I would say actually one of the greatest legacies of Elon towards this is, is of course he's created these great companies, but the amount of entrepreneurs that have come out of SpaceX that, that have, are changing the entire industrial complex may be even greater, um, legacy than, than the companies themselves. And I think we're gonna see the same thing, uh, for-
- BHBen Horowitz
Yeah
- SPSpeaker
... for computer science and hardware.
- BHBen Horowitz
Yeah. Yeah. As a matter of fact, one of our investments, Edge, was started by, uh, two founders in their 20s, but if you go walk through their offices, you see the experienced people as well. So it's the ideal combination here.
- SPSpeaker
Yeah.
- BHBen Horowitz
Yeah. Yeah. It doesn't necessarily have to be the founder with experience, but that founder better be able to tap into that experience in a real way.
- SPSpeaker
Get the, get the people with it, yeah.
- BHBen Horowitz
Yeah, yeah. Well, and then be able to work with them and, and, and they have to be good and, and all these kinds of things. It's complicated.
- SPSpeaker
Speaking of experience, this is a, a big new fund we're, we're, we're launching and there's no new GPs. Um-
- BHBen Horowitz
Yeah
- SPSpeaker
... we're sort of collecting. It's because you guys have a lot of experience-
- BHBen Horowitz
Yeah, yeah
- SPSpeaker
... and the rest of the group, you know, in, in this field that has been kind of latent-
- BHBen Horowitz
Yeah
- SPSpeaker
... and, uh, dormant.
- BHBen Horowitz
Yeah. Well, it's kind of funny. I think we almost had to be warned against it almost just because like our backgrounds are from, it's hard. And I think the reason that we needed a reminder is because all of this has been so much in our careers, systems and hardware, we're kind of drawn to that. And so listen, we've been clearly invested, um, in hardware over the years, right? We're in SpaceX, we're in Android, these are very early checks. We're in Astras, we're in Waymo. You know, so we even, even early on, we did a number of those investments. Um, but like, you know, uh, uh, this is because it's so much in our DNA, and so I don't think this is necessarily need to increase the team or competency. It's just focus.
- SPSpeaker
If this fund does what we think it will do, how do we see the world changing or look, looking like in, in five to 10 years?
- BHBen Horowitz
Well, you know, hopefully, uh, America wins in the infrastructure game, um, and we have lots of like super eco-friendly, efficient data centers out there and lots and lots, an abundance of chips, an abundance of memory, an abundance of power. Uh, and you know, that would be awesome. Uh, and I think we-- look, we, we, you know, it goes back to like, we really think, uh, America is a special place and, um, we're important not only to everybody here, but anybody in the world who wants to kind of make a contribution and do something bigger than themselves. That it's kind of the best place to come with nothing and do something profound. So we'd like to keep that going, and I, I think that doesn't continue to go if we lose our lead in technology. I think, I think we'll be in another era and there'll be another country, and maybe they have a different set of values around that.
- SPSpeaker
Thanks, everybody. That's a wrap.
- BHBen Horowitz
Great.
- SPSpeaker
For Machine Age Fund, Martin, Ben, Raghu, thank you.
- BHBen Horowitz
Thank you.
- SPSpeaker
Thank you.
Episode duration: 53:58
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Transcript of episode Zx1Ec8LWFeM
