if you're on a run rate where you're raising 5 billion bucks every two years, okay? So give or take that's, you know, $50 billion over a 10-year period of time, a 2% on 50 billion, it's a billion. Okay? A billion a year. Right. Let's just be clear. Right. So underscore that for everybody, Bill.

Great to have you here. Great to see you in Austin this weekend. Congrats on 25 years of marriage. Thank you very much. That was, it was a really fun time. And you know, I went by J Cal's, saw his new place. Yeah. Saw so many friends when I was there.

Austin's really, really bumping right now. I agree. Seriously, just an amazing number of people now calling at home. And I know that, you know, you recently took your dad who worked at NASA down to see the launch of Starship 5. Yeah. And I, look, I'm so grateful that SpaceX was able to make this happen for my dad's 88.

And we'd been talking about getting him down there to see a launch. And they put us in this VIP section, which made it easy for him to move around. And he was just in awe. You know, I'd maybe start this discussion by telling you, on the way home from the launch, I did a search for my dad's name and NASA.

And I found this document. It says, "A sketch prepared by John Gurley demonstrates the spacecraft's skip when entering the Earth's atmosphere." So this was hand drawn by my dad. Come on. And if you look here, "Memorandum John R. Gurley to Chief Flight Operations." That's Chris Kraft. So my dad wrote this to Chris Kraft, "A study of skips range sensitivities and allowable errors in exit conditions applicable to Apollo missions." How cool is that?

June 12th, 1963. And you just took him down to Boca Chica? He was 26 years old when he wrote that. What's the average age of the guys down at Boca Chica? 26. Oh, 29. Yeah. Yeah. Yeah. What was it like being down there with your pops? It was awesome.

It was awesome. So I grew up in a town called Dickinson, which was near Clear Lake. And my father worked for NASA. And he worked there from very early. When they commissioned NASA, they took 50 people from NACA, I think it was called, which was on the Langley Air Force Base.

And that's where he had started his career. And they moved him to Houston. So I'm a Texan, probably because of LBJ's pork barrel politics. But we grew up on a space street. Half the fathers on the street were NASA. And the Apollo launches, it's just like you see in the Apollo 13 movie, you go over to someone's house, if you didn't drive 16 hours to the launch.

Yeah. And yeah, it was just part of our lives. We had a wall in the house with all the Apollo launch things. And it was really like until he took early retirement in the late '80s, it was just part of our lives. And so to have him down there, and he's- So you went for Starship 5, the launch.

Yeah. And I'd been trying to do it for a while because he's 88. And all of his former colleagues that are still alive are kind of in awe of what Elon's doing and super appreciative. Because for them, the space mission was something that meant a lot to them. And they kind of felt like the government quit trying.

And so to see it rebirth just gets them super excited. And of course, we were there to witness. It was very lucky that this was the one I took him to because we witnessed the booster coming back, which was- How was that? Was it emotional for your dad? Yeah.

Oh, definitely. Definitely. Yeah. And you look at it today, the average age at SpaceX, probably about the same age as your dad was when he- Yeah, he talked about that. We went to an after party and all the SpaceX, not all of them, some of them were SpaceX employees were there.

And it was a very young crowd. Yeah. But that to me is part of the magic, right? That believing you can see how mission driven they are. And we have lots of friends who work there, work there. And it's great to see America cheering for it. I've even heard stories that people, just because you start looking around, I've heard stories, people leave SpaceX and go work somewhere else and just inevitably come back.

Elon has said that we need aspirations. We need dreams. We need to think about the stars in order to inspire us to invent. And that's part of the purpose of being human. And I certainly know with my kids and my family, we feel that way. So, super cool you're able to take your dad down there.

Yeah, it was great. It was great. Great. On Sunday morning, I went on a walk with our friend, Michael Dell. I always learn something from him. And the thing that dawned on me, he's not one to get hyperbolic about things. He's been at this a really long time. And he's like, we're in that grindy phase now where he's really starting to see the benefits of AI, right?

Inside Dell, inside his customers, other enterprises, finding ways to take, to find efficiencies in their business. I think we're entering that, what could be a really golden era where there's market leaders extend their lead, where their margins expand. I just saw a headline today that Visa is finding more efficiencies from AI, is letting 1400 contractors and workers go.

And I just think this is the beginning of a drumbeat that we're going to hear for a decade. He said, just at the very beginning of companies really starting to think about ways they can improve their business. And it's not the sexy chat GPT stuff. This is the real pedestrian stuff by using AI to basically translate documents into a hundred different countries.

One of my observations and a fun thing to come out of that walk. But there are a few topics I want to hit on today, including the latest on AI and GPU scaling. And I want to hit on the topic of how we're thinking about the markets heading into the election.

But I want to start with a topic that I know is near and dear to your heart, which is the state of venture capital. Yeah. Okay. So my partner, Jam and Ball, who we're going to bring in here in just a minute, wrote this week on his blog that VC funding sizes have ballooned, that the incentives for VCs have shifted perhaps a bit, maybe now focused a little bit more on this cadence of raising and deploying every couple of years, as much money as possible, which may create some incentive alignment problems with founders.

The key question he told founders they need to ask is, are you partnering with a 2% or a 20% venture firm, which I thought was clever. So you then retweeted his post and said, it's a must read for all LPs and money managers and called it the single most important issue in the VC landscape today.

So first welcome Jammin. You know, I thought maybe just start with you, summarize for us the blog post and kind of maybe why you wrote it. Yeah. Well, so I write this blog Clouded Judgment and it has many goals. One goal is to increase the transparency to founders of what goes on in the venture markets.

The venture markets have changed a lot over the last 10, 15 years. I think Bill, it was maybe you or someone else, many people have said this, right? The venture markets have transitioned from a high margin cottage industry to a institutionalized lower margin industry. And that has a lot of implications, implications for LPs, implications for GPs and implications for founders.

This post focused more on the founder GP leg of the stool. And I wanted to focus on that leg because I do think that the implications of this transition to an institutionalized asset class, it changes the game for founders that I don't think they're fully aware of what, of all the implications.

And I had a lot of, I've had a lot of conversation with founders over the last few months that really highlighted that to me. So before diving into how have the incentives changed and how are they diverging a bit more amongst founders and GPs, you know, first we'll just describe what the incentives are for the audience, just to make it quite clear.

So in venture funds, I'm sure folks have heard of the two and 20 model that is a 2% management fee and 20% carry. There's a guaranteed portion of funds comp, which is the management fee. It's a percent of the fund size that you'll collect every year. And then there's the carry, which is the funds share of profits.

So take a hundred million dollar fund that you 3X, you'll take 2 million a year in management fees. You generate 200 million of profits, which is 40 million of carry. 10, 15 years ago, the funds were smaller. And as a GP, as an investor, you'll make money on that guaranteed portion, but not necessarily, right, as I call it, get rich money.

Bill, what were you making when you started per year when you started in the business? No, but I would say on average, people are making a couple hundred thousand bucks a year working in the venture business. Nobody was getting rich on that management fee. Keep going, Jeremy. That's right.

So if you wanted to get rich, you had to maximize your carry. The way to maximize your carry was to maximize the value of the underlying investments that you made, which resulted in a path of getting rich for founders, which also resulted in getting rich for investors, right? The incentives are aligned.

Let's fast forward to today. Funds are much bigger. That $400 million fund is now 4 billion. That guaranteed portion of comp, the 2%, the management fee, you can now get rich on. And the reality is, is a path exists today- In that case, roughly 80 million a year. That's right.

For a $4 billion fund. That's right. And so they're now- And you could imagine the managing partner taking a quarter of that, a third of that. 10, 15 million bucks a year. Yeah. Right. And so now there's a path where investors, GPs get rich, where the outcome of the founders and their companies is irrelevant.

Not to say they are aligned in opposite directions, but they're no longer aligned. And now, as a rational actor, you could say, "Why not maximize the guaranteed portion of the comp, the 2% versus caring about the 20%?" And that leads to some pervasive incentives where funds incentives are more about deploying dollars quickly as opposed to maximizing the value of those deployed dollars.

There's a lot of downstream implications of that. It leads to companies, early companies that show early traction, get flooded with offers and investment dollars. And we can talk about why overcapitalizing and overvaluing your business actually can pose a risk. I think one of the reasons I wanted to write this post was I thought we would have learned a lot of lessons coming out of 2021 that it's very clear we haven't, or we just choose to ignore because the incentives are no longer there.

But for founders, I think understanding and appreciating, are you partnering? Are you marrying a firm that is more focused and caring about maximizing the value of your company together? Or are you partnering with a firm that just wants to deploy dollars as quickly as possible? And there's lots of things we can double click on, but that was kind of the broad rationale for the post or the quick summary of it.

- And by the way, I mean, rather than say they only care about the management fee, they may view the other one, there's a phrase in poker called a free roll. They may view it as a free roll. I'm getting rich no matter what. - It's a lottery ticket.

- Right. - It's a call option. - But this other, it's a call option. And if this company happens to be the next Google, the next Meta, we've seen how those compound over 20 years and it'll work out. - Right. - It'll work out in that case, or maybe it'll work out for one of the 10 that I'm putting 400 million in and then I'll be okay.

- Right. As investors, we get to make many bets. As founders, you have one. - Right, exactly. - And one of the things we were talking about just earlier today is for founders, there are implicit things you are signing up for by taking a round that is too much money at too high of a valuation.

I think the preference stack and preference in general is something that is sometimes understood by founders in the founding community, but not always understood. There are companies that can be sold for $100, $200 million that results in life-changing outcomes for founders and early employees. If you raised $100 million too early, that exit path is no longer on the table.

You can't sell the business for $100 million and make any money because that just returns the preference stack. As the call option investor, your call option didn't hit, but you get your money back. - Well, let's drill down. Let's split this into two sections because I think that this thing that's happening and the reason I retweeted it has implications for both founders and companies, but the asset class also.

- That's right. - So, we started down this path. Let's do it first. What does it mean for a company to have maybe too much money crammed into it at too high a price? - Yeah. There's many deep implications of this. One thing that I've learned that I hold, that I will argue with anyone on is every founder and every company and every board will tell you, "If we raise money, we're not going to spend it.

We're going to stay frugal." That never happens. - Yeah, never. - And instead of focusing on, you might ask a founder, "What are the three things that matter most this year that are critical for your success?" If you only focused on those three things, you might maximize your chance of success.

When you have lots of money, you're going to do six things at once, which means you are diluting the three things that matter. - Let's stay on this for a long time. So, many, many, many great people have said that constraints drive creativity. I've heard famous stories about Steve Jobs where he felt his job was just to say, "I want it this thin.

Go figure it out." And by saying that, he limited the space. "We're not going to build a phone." And then people can focus and be creative. You've constantly heard, "We're going to make a better decision because we're going to have constraints, and we're only going to be in two markets, not five." If you're in five, guess what happens when revenue starts to slow?

You've built some of your revenue in these places where you don't have a strong competitive advantage. Those churn out. And so, you've grown revenue faster, but it's less sustainable revenue, is another thing that can happen. - Well, when I look at this, if we look at the poster child or children for what went wrong during peak Zerp, okay?

So, if your incentive is to deploy so that you can raise again in two years, then you're going to want to get maximum dollars into the business. Well, there may be only so many primary dollars you can get into the business. And then we started to see this desire to buy secondary shares because I wanted to get more dollars into the business.

I wanted to deploy more in the company, even though you were buying common shares that were much riskier. And then, oftentimes, Bill, something I know you love, the founders or founding team were taking big dollars off the table, oftentimes before product market fit. And I think, you know, Jamin and I have discussed that we came out of this 20 to 22 period, and we would have thought that we would have seen less of that, right?

Because we have, as you've discussed, 1,400 companies, right? 90% of which are going to have to do a down round, IPO or otherwise, in order to get through the system. But somehow the echoes of that period have not reverberated that loud, right? The incentives to deploy much bigger rounds into these companies continue to persist.

And so, you know, gets back to your point about scarcity. Not only are you putting so much money in the business that perhaps they're not being as focused as they would otherwise be, but you really question whether or not the incentives for the founder are there. If you're taking 10, 20, 50, 100 million dollars off the table before the company has achieved profitability, then do you really have the fire in the belly needed to get, you know, both parties?

And without picking on anybody, there are numerous examples from previous waves of even the founders like not being in the building or not showing up. So that can definitely happen. But there's so much more that can happen. I mean, one thing that happens is you create a prisoner's dilemma with your competitors where they feel forced to raise the same amount of money.

And now you have multiple overfunded companies in a single category. Right. Just taking shots. So it's not only too much money within the firm that's causing the firm to be less fit, less efficient, less, you know, inventive, but it's also creating this dynamic where you used to talk about, you know, capital is a weapon of economic destruction.

You have excess capital causing excess competition. So the natural market winner does not emerge as fast as they otherwise would. Well, maybe to level set the conversation. Can I mention one more thing? Sure, sure. That I think becomes a reality. And we've talked about this before, but I find far too often that founders think about raising money at a particular valuation as if they've earned an award.

They've won a prize. They've proven their company is worth this thing. And they can then show the world the trophy and say, we've achieved X. And I always try and remind them that valuations represent discounted future expectations. And so you may feel like you've won a prize, but you've really increased everyone's expectation for what this company can achieve.

And in order to raise that up round from here, it's way harder than it would have been otherwise. Right. And perhaps way more dilutive. I mean, the reality is even if you're getting what appears to be a high valuation, if you truly think you're one of those seminal businesses, you look at the ownership today that Zuckerberg has or Bezos had, because they raised so little capital in those businesses.

And they compounded over a much longer period of time in the public market. And let me drive home this point, I think, in a very, very stark way, which is we're borrowing a number from the Code 2 presentation, but they said there were, what, 1,400 unicorns that are still private from what I like to call the pre-LLM period.

What percentage of those could raise enough round right now? What is the number? I think it's less than 10%. It might be less than 5%. Today, yes. So that means there's over a thousand private unicorns that are somewhat stuck right now and could not raise enough round. So this risk I'm talking about, about putting too high a valuation on your company, we've just had this experience in this massive fact pattern.

But you're right, we're still doing it. AI came along, and it has so much potential and all the things you're excited about that brought the money in. And the money's back in. And I'm seeing activity that is at least no different than what we saw in the past, and maybe even more frothy.

Let's come back to that. But I do want to level set to the total amount of VC that's actually being raised and deployed. And this first slide we have here just shows that we peaked in Zurb in 2021 at over 700 billion deployed. We've come back down to about 300 billion deployed, which is still meaningfully above where we were in 2014, 2015, but we're back to about 2017, 2018 levels.

But it kind of hides a couple of things. Number one, the number of first-time funds raising a second-time fund has plummeted. The number of first-time funds have plummeted. And so really what's happening is you have the consolidation among a few big platforms. Just this week, we saw that General Catalyst has raised $8 billion in new capital.

Now, of course, I love my friends at General Catalyst, but just 24 months ago, they raised $4.5 billion. So that's $13 billion raised in that 24-month period. Similarly, Lightspeed recently announced that they raised $7 billion after raising about $6.5 billion, so another $13 or $14 billion over kind of that 28, 30-month period of time.

Clearly, LPs are raising their hands and saying, "We don't mind these larger funds. The capital is available for them." What do you think that they're concluding? If you believe that this is going to fundamentally reduce the returns of the entire asset class, then what must be going through the minds of those LPs to want to back those much larger businesses?

That raises so many different questions. One thing I would highlight is that when, you know, my whole career in the venture industry and prior, because I read about the history before I joined, the industry was inherently cyclical and there would be these boom-bust periods. And they're very long waves, partially because of the construct of the agreement between the GPs and LPs, which used to be a 10-year thing, and now it's like a 15-, 16-year thing.

And so, the window for which you would evaluate whether someone can accurately or successfully deploy a $4 billion fund might be 20 years. And we just started raising them that big. So, no one knows. Like, no one knows. They're raising money off of paper marks, you know, from this period.

And it's just, the cycle's forever. It's beyond the lifetime of most GPs' career left to be done, which gets back to the 2%, 20%. And I think it kind of depends. I think one way to, one argument or one lens to look through when trying to predict will it work is everyone will look at venture funds and there's kind of this view and belief that the bigger you get, the later stage you invest, you can more evenly distribute your returns in a fund to achieve a top quartile return.

That, I would say, I strongly disagree with. All of the numbers that we've seen suggest that to have a top quartile fund, you need to have outlier power law outcomes within the fund. You won't evenly distribute them. So, I think one way to look at this is to say, and this is the way we talk internally, what does it take to have a power law outcome at a certain stage?

At the seed stage, you might have this many companies that could get you a power law outcome and return your fund. Series A, Series B, Series C. And it's just, it's a downward funnel of the number of companies that could give you power law outcomes. I think one of the challenges is if you're investing just in growth stage, there's only so many companies you can invest in that can give you power law outcomes.

And so, you are almost inherently widening the aperture to do more than what could be a power law outcome, the larger and larger you get. I agree with that. So, I think that the burden of proof is on the picking of the large funds to say, we will pick and hit those power law outcomes, but then have a much higher hit rate on the rest.

And so, it won't be this big power law outcome. It will have the power law and then be more evenly distributed in the long tail, which it can happen. It's just really hard, especially when your incentives are just to deploy to raise the next fund. It's, are you giving up or saying, "Hey, I don't care.

Picking is too hard. I don't need to do it." In which case, maybe you get the power law, maybe you don't, but you're just naturally going to capture more of the long tail, which I think ultimately will dilute a lot of those returns. And so, we'll see how it plays out.

That's the fun part of it. Or not, or not. I mean, this is kind of Bill's point. So, if you're on a run rate where you're raising 5 billion bucks every two years, okay? So, give or take, that's $50 billion over a 10 year period of time. A 2% on 50 billion, it's a billion.

Okay? So, now it just- A billion a year. Let's just be clear. Right, right, right. So, underscore that for everybody, Bill, right? Because these funds layer on top of one another. So, you're getting paid on multiple funds. Correct. And that's the guaranteed portion. Now, these firms are much larger firms, much more institutionalized.

To Jamin's point, they're going to have to spread their bets over a much, much wider field. So, the potential that you're going to have enough ownership in a power law business to earn venture-like returns is much lower. But I think you also made the point that maybe what you're doing is your mortality rate goes down.

And so, you're giving more confidence. But Bill's point is, we don't know. You remember that. The experiment's never really been run in venture at this scale. And we would have thought that coming out of the Vision Fund experiment, right? We had all these comments during Vision Fund that we wouldn't see, you know, kind of this cadence of these size of funds.

And then if you want to take some targeted big bets, say in an open AI or something like that, there may be only one or two of those that come around every couple of years. Every year, maybe every 10 years. And so, you place a lot of wood behind a couple big bets.

But then your traditional venture fund is smaller such that it can generate those historical venture-like returns. But I haven't seen any math that I find compelling how you can get to a 4 to 5X fund on, right, that $5 billion pool of capital. Well, in fact, yeah. I mean, in 2011, there was this famous report by the Kauffman Foundation that argued that billion-dollar-plus funds had never had good returns.

And of course, after that, everyone raised billion-dollar funds. But I have this story I want to share with you that relates to this in a funny way. I was at one point in time invited into the office of this PE firm. I didn't know PE very well. But they had backed DoubleClick and Google bought it for $3.1 billion.

And this particular firm made-- I forget, they had a lot of it. So they made like a billion or a billion two. And I said to him, I always say, "Congratulations, man. That's incredible." He goes, "Well, it's in a $4 billion fund." Wow, wow. You know? So you have an incredible outcome.

Right, right. But the denominator is so big that it's just hard to claw it back. It's hard to get back to that number. Which is why you can't get to the 4 or 5X because you have a power law outcome, and it returns 25% or a third of the fund.

Correct. Right? What we've witnessed is kind of this bill coming out of the '22 period, these two paths effectively, you know, that the firms have followed. We've seen some firms downsize. Founders Fund, Altimeter, a few others have downsized the fund size. But we've seen other funds that just said, you know, we're going to consolidate and we're going to get way bigger.

And so I do think that, you know, if we look at a little bit of returns math on this. So we have a few slides. But, you know, I love, you know, Fred Wilson's rule of thumb. You know, a third of companies fail, a third basically underperform, and then a third gets you your 5 to 10X returns.

And recent breaks it down even more, which, you know, says it all comes down to the 10% that produce, you know, kind of that 10X fund. And if you look at this stepstone data, you know, it actually shows that, you know, basically what differentiates those top tier funds. And by top tier, what I mean is that the top 5% of Decile funds, they're earning about a 4.5X, you know, cash on cash return in their funds.

You know, you go back and you can look across all of these vintages over the last 20 years. Now, I think there's a question whether or not any of these mega funds on these $4 or $5 billion funds are going to be able to, you know, generate those returns.

And maybe the reality is that these new LPs, pension funds, sovereign wealth funds, and others, look at these as strategically important. And they, you know, they're less concerned about venture-like returns, and they want to protect the downside more. And so maybe you can sell the fact that you're going to have less mortality, right?

And you're going to have less downside risk to the funds. But I mean, I think that that is really where the rubber meets the road. You know, when we look back at this, you know, this analysis, whether or not these funds are going to be able to generate returns that are equivalent to the top Decile of historical.

One of the things we don't know that it would be really hard to gather data and prove, but this zombie unicorn class, pre-LLM zombie unicorn class, you know, had it not been flooded with money. And, you know, there's a notion in science called the observer effect, you know, where if, you know, VCs are too big and like, do you actually impact the results of the game on the field?

And, you know, had that not happened, and these companies grew up on a normal way, you know, in a more organic, you know, growth path, would they have had more liquidity? Would they have had more investor returns? Would they have been more acquirable without these high marks on their head?

And so did you take out, you know, you're so, we're so focused on the outlier, you know, breakout Google meta types. Did you ruin- - The two, three, four X returns? - Yes. - Yeah. - Did those go away? - Yeah. I think you totally removed it as an outcome path, right?

Which is to say, when you are investing in these companies at high prices, the only thing as an investor you care about is, are you an outlier outcome? Are you a 10X plus? - Right. - As a founder, you might say, I don't need that. As employees, you might say, I don't need that.

And if I was sitting on a $600 million valuation, not 6 billion, it's going to be much different to go and sell the business for 2 billion when the prep stack isn't one and a half, right? So I think we've just, we removed a thick middle of an outcomes that would be relevant to everyone outside of the investors, where now the only outcome that's relevant to anyone is, are you a 10X or are you a zero?

And you made it a binary outcome- - I agree. - For all constituents. - And you force everyone into that game. - Right. - Obviously, all three of us are in an industry. We believe it's the engine, you know, that provides the fuel for, you know, incredible founders to go innovate the future.

And it's really just a question of whether or not we're overcapitalizing the business, whether funds are getting too big, but what recommendations, Bill, might you have or Jamin, for founders or funders, right? Jamin, what I hear you saying is founders just be aware, right? Ask the questions. - Then know what you're signing up for.

- Think through the people you're putting in your capital structure and like what their incentives are. Are they sitting on 20 different boards? Are they clearly in the deployment mode rather than the investment mode? And if they're in the deployment mode, just know that. - And know what you're implicitly signing up for.

What bets are you making, not just on your behalf, but on your entire employee base's behalf, where do they want the binary bet? Binary bets are okay for investors. I don't think early employees or founders necessarily want that. But I'd say that, you know, know what implicit bets you're making.

Buy the rounds that you're raising. - Yeah, I mean, to that point, like this is super simple math, but if you raise 400 million or let's just say 100 million, even if you're being conservative, what are you going to spend that over? 36 months, you know, something like that.

You're still signing up for a three, four million a month burn rate. And there's no way that doesn't represent risk in some way. And the bigger you take that number, I used to always think about venture capital as, you know, you invest in a company and you grow that burn up until a point.

And then the job is to converge back against it and go to profitability. And with all this money, I mean, we're taking that point up to 10 million a month, 20 million a month. And this gets into who can grow out of that. - Right. - And it ties into did you destroy that middle?

Because some of them just can't ever get there. - And you then rely on the beneficence of the capital markets to keep feeding that machine. And sometimes it runs out and then you're in a massive course correction. - But my general response is unfortunately more sanguine, which is I think these systems are emergent.

I don't think any one person made a willful decision to force this reality. - Correct. - I think it emerged out of a combination of what was happening with interest rates and Zerp and then the rise of AI and maybe the globalization of fundraising that brought sovereign wealth in.

And it all kind of combined and created this mix that we're living with. And for the most part, I think we're all actors stuck in the game. - Right, right. - You know, I'm not sure you can escape it. - You know, a couple of observations. - Is that the positive take on it?

- No, I know he wanted one. I apologize. - Well, I mean, I'll give you my spin on that. Number one is, you know, I do think that pensions and sovereign wealth funds have, you know, stepped in to replace some of the money that came out of the endowment ecosystem, right?

Because endowments, you know, I think about the legends of that business who were allocating those dollars, you know, the Phil Rotners of the world or the Swensons of the world, right? Like they would phone up everybody on Sand Hill Road and they would say, "You're getting over your skis.

You need to back it off a little bit," right? That industry is long gone. But I would also say, I just, you know, I saw news this morning, you know, at FII, which is doing, you know, like I think an incredible convening of investors and leaders from around the world.

I think they're doing incredible stuff, you know, in the GCC and Saudi in particular. But they said, "We're going to deploy more of PIFS dollars on investments inside of Saudi Arabia than outside of Saudi Arabia," right? So I think there was like, and I've heard this as well from, you know, the UAE.

They're going to consolidate the number of GPs. And so I think there is increasing focus coming out of sovereigns as well. I hear the same. I was just down in Texas talking to the Texas pensions, the same thing happening there. But when they consolidate, that probably means more dollars into fewer, right, platforms.

So maybe it's starting to crack, but I don't know. And so I don't know, you know, we've seen from that slide that I showed, the total amount of funding has definitely come down by about 30 or 40% over the course of the last couple of years. So that's one half of it.

The other half is there is no doubt that the outcomes that we're now talking about are much bigger than the outcomes we were talking about 10 or 20 years ago. So it would make sense to me, if you looked at a trend line for the industry, the industry and the number of dollars deployed and the size of funds should be much bigger today because companies are scaling much faster today and the outcomes are much faster.

OpenAI got to, you know, $4.5 billion of revenue in a fraction of the time it took Google and Meta. And, you know, and so like that to me supports more dollars, larger funds. But I do think the law of economic gravity prevails. There's a certain fund size I think it can deploy if you're aiming for traditional venture like returns, then I don't think there are 100 growth companies, right, that you can go put in a fund of $5 or $10 billion, equally weight them and get a 4 to 5x over any reasonable period of time.

And we can, I mean, let's move into that. I mean, I think the enthusiasm around AI is part of what led to that reality. And if it didn't feel spectacular, it wouldn't have happened, right? Right. So it's tautological that those two things contribute to one another. Well, it's a, you know, so one of the topics we've been talking about all year is, you know, is AI and GPU scaling.

Will these AI models continue to scale? Will GPUs continue to scale? There was a lot of question whether or not NVIDIA would grow in 2025. But just this week, we saw a few announcements. First, we saw out of XAI, the Colossus cluster in Memphis, which I discussed at length with Jensen.

They announced this week that they're scaling. Elon said, we're now going to go from 100,000 GPUs to 200,000 GPUs in that facility. Did you see the video that Supermicro put out on this? No, you told me about it though. Right. So it's- Describe it. Or you put a link in.

It's incredible to watch what they built. Yeah. And if I think about for the last decade, data center engineering and construction has been in the background, right? Like, you know, Meta had breakthroughs. Google had breakthroughs. Like we'd talk about it, but it wasn't something that people were posting videos on.

I think there's some Equinox shareholders that might disagree with you. But I would say we generally took it for granted. But now it's clearly becoming a much more important source of competitive advantage. And I would just say, you know, it's super impressive what they pulled off in Memphis. It all gets to this question of, you know, you were asking at the beginning of the year, will we need or will we get to clusters of 200,000?

Now those questions are clearly off the table. And so we have all these mega caps reporting this week. It's expected that CapEx will continue to, you know, continue on at this $250 billion run rate. Google came in tonight at $13 billion, just above the $12.7 billion that was expected.

So they revised that higher a bit. Bill, what do you just make out of, you know, as we sit here toward the end of 2024, do you expect that this is going to, you know, continue at this pace? Is this a sort of, you know, I've heard people describe it as a Pascal's bet sort of situation?

You know, how are you thinking about, you know, where this all leads? I'd love to drill down on that, but let's come to it in a bit. Look, it's something we've never seen before. You know, if I think back to, and you and I were discussing this, but if I think back to the breakout companies of the previous generation of VC backed companies, none of them had massive CapEx.

The biggest one was Amazon, actually, with their distribution facilities. And it caused a lot of skepticism. And they raised a lot of debt, and they did things other people hadn't done before. And, you know, I've discussed it. I don't think we've ever seen kind of a CapEx race before.

And it's pretty mind boggling that these are being built at this scale. It's interesting, you know, to try and count how many people are going to want to do it. Like, you know, the hyperscares obviously are reselling this. So, they're like an arms merchant to everyone else. You know, in Tesla's case, and extended AI's case, and Meta's case, they're consuming this, you know, for their own good.

And, you know, I'd throw this back at you. Do you think there'll eventually be 50 of those that are Tesla-like, that will want to build these out for themselves? No, I think there are going to be a handful of companies, you know, like take Mag7. Because the scale is too high.

Yeah, think about it this way. You know, if you look at Google, in the quarter, GCP has accelerated its revenues by up to plus 35% year on year, okay? So, just to put that in perspective, they added about two and a half billion of new ARR in the quarter.

That's like adding a Databricks in the quarter, right? So, it's only companies of that scale that can afford to spend $50 billion a year. And, you know, I do think there are increasing advantages to scale, both when it comes to data and compute. And so, you know, I found this Pascal's bet to be a good framing of this, which is, if I were running any one of those companies, it would now be sufficiently clear to me.

Explain, explain this, Pascal. You know, so Pascal's this French philosopher. He says, I don't know whether God exists or not, but if he does exist and I don't believe, then it's going to be a really bad outcome for me. And if he does exist, I do believe I have eternal life.

So, if you believe that the upside of AI, right, is infinite, is eternal, right, is some really big outcome and all your competitors are doing it, what else are you going to invest your money in? We said here several weeks ago, you can buy back your shares, you can issue a dividend, or you can buy GPUs, right?

Do you think any one of these founders or any of these companies- You can do licensed deals with companies you want to acquire. You know, so I think, but I think most of these people are in this game for this moment, but I think it raises a really interesting alternative question, which is, it's pretty clear to me now that there are very few new entrants that are going to be able to play in that game, right?

You may be able to build an application that rides on those rails, but the idea that you're going to be able to build that level of compute or build a frontier model that's going to require that level of compute on an annual basis and compete with those companies, I think it's very, very difficult.

Yeah, and another thing that I think the law of large numbers just starts to catch up as well. I think there's some CapEx spend from even a Mag7. I'd mentioned that maybe the CFO's voice goes up a little bit, but the investors will start asking as well. And there was another data point this week that may seem trivial, but there was something that just came out yesterday that OpenAI is talking to TSMC about building a chip and has put their foundry ambitions on hold.

Right. I always thought the foundry ambitions were a little too ambitious, but in some ways, that's an odd recognition that, oh, well, that may have been too much money. And with the burn rate that's rumored that they have, like, oh, okay, maybe, you know. And so, there is some...

One thing I would say about the Pascal thing is if that's truly what's on everyone's mind, that's exactly how you would go over the top. Right, for sure. The exact formula. First, I mean, listen, there is some non-zero probability. Just as Elon says, there's a non-zero probability that AI is going to end up being bad for humanity.

There is a non-zero probability here that at least for some of the players, they don't see a return on that investment. Or that you get a supply-demand imbalance in the middle. Or you get a diluted return, right, that you all overspend. And had you just waited and spent slower, the cost of the technology would come down.

It would cost you less over time. I mean, look, there are people that will argue that the, you know, we're going to get in here and the first pass is we're going to place a bunch of programmers. But then we're going to replace a bunch of paralegals. And then we're going to replace, you know, a bunch of, you know, imaging analysts.

And then, you know, and the longer that list gets, and if you are successfully fine-tuning models specifically for those particular tasks, and that gets longer and longer and longer, that's big, I mean. So it leads me perfectly into this comment out of Masa Sun today, you know, that we couldn't not talk about.

But at any rate, Masa at FII today said, "9 trillion of cumulative CapEx on 200 million GPUs is very reasonable." He said, "In fact, I think it may be too small." And he went on to say, you know, that if you took the most critical estimate, so of the value of AI.

So he said the lowest estimate that he's seen on the value of AI is that it could do the, you know, what he calls artificial super intelligence, which is what he thinks we'll have if we spend $9 trillion, is that it would replace 5% of the global workforce. And it just so happens, if you do the math on that, 5% of the global workforce costs about $9 trillion a year.

So he said, "Imagine you were a single entity, single enterprise, the global workforce was your workforce, and you could spend 9 trillion cumulatively over the next seven years, that you would then recoup in a single year through the efficiencies gained in that workforce, it would obviously be an NPV positive investment." Bill, is Masa's 9 trillion the top?

Is it where all this, you know? I think the key math for that number is that it was bigger than any number anyone else has said. There you go, there you go. I do think though there's, I mean, many have made this argument, right? You look at IT budgets as a whole, about half of that generally goes to headcount and people, a smaller percentage of that goes to software, and even smaller percentage of that goes to new spend in the year.

Most of the software spend is just renewal. You spent it last year, you're gonna spend it this year. A lot of people have written about this, but it's the great services to software rotation. Services markets are usually 10x bigger than software markets. If we look at how can spend attack IT budgets as a whole, it's not just let's replace this software spend with this software spend, it's let's replace these call center agents.

Let's replace these insurance people filling out forms in the back office. It's let's replace a lot of this headcount spend. I mean, most of these firms replace, you know, employ hundreds and hundreds of thousands of people, and we're seeing those numbers. That's where, you know, I started, you know, the conversation about my walk with Michael.

And, you know, again, this is looking over a 30 to 40 year period of time, never has he seen, or have I seen, the ability for companies to take out 10,000 people and actually see customer satisfaction scores increase, right? There's always a cost to letting people go. But in this case, you know, you hear Zuckerberg talk about take out 20,000 people.

Flatter is faster, leaner is better. We're getting more done with less, right? When you look at span of control in companies, right? There are some companies, you know, that still have, and that's the number of employees per manager, right? So you can imagine that will widen, you know, because AI will allow you to, you know, have more people, you know, who you can effectively manage.

- It'll be interesting, I do think that some of the fine tuning of the math is still to come. And I'll use the coding example. You know, when we started, you know, oh, we're gonna replace engineers. But if you talk to someone, a CIO type, and say, what kind of lift do you get from a co-pilot product?

They're kind of generally in the 15 to 30% range, which isn't, you know, if you're replacing somebody, it's 100% or infinite percent. And so whether or not, and maybe customer service is different than coding in this case, where you can, you know, replace 100% or 90% of the people.

But it'd be interesting to see as the analysis come out of these things, what those different numbers look like for each of these different verticals, so that you can get a better sense of that. But if you really can, you know, if Sierra, Brett Taylor's company is right, and you can replace 100% of your customer service agents with this technology and get a more satisfied customer, and if there are multiple verticals like that, then you're right, this could go on for a long, long time.

- I'd say, you know, there's no doubt in my mind that there's some sloppy spending going on, right? Like, you can't add this magnitude of spending without there being a little bit of waste, okay? But it's also clear to me that the reward on the other side, there is nobody taking their foot off the accelerator.

- Yeah. - Right? When I talk to CoreWeave, when I talk to Azure, when I talk to OpenAI, when I talk to Amazon, Google, et cetera, not one of them is talking about anything other than how do we find the facilities that can support a gigawatt or two gigawatts or three gigawatts of power to power up the clusters that they wanna invest in.

And remember, these are three, four, five-year-long investments. - Another thing that came out this morning that I was kind of waiting on as a proof point, 'cause it didn't make sense to me that it hadn't happened yet, TSMC said they're gonna do across the board 20% price increase. And that's, I was like, this should be happening.

- Right. - And so seeing that is also indicative of this, right? - Indeed, indeed. And maybe we could close out here by talking about the markets a little bit. We always talk about the markets at the close. But one of the questions I keep getting asked, Bill, is whether or not this election is priced in.

I mean, in a lot of our text threads we have with our friends, everybody's trying to figure this out, all eyes on the election, which is here in seven or eight days. And the question is like, a lot of people looking at the prediction markets saying increased probability that Trump wins the election.

So they're wondering, is there still time for me to adjust my portfolio, right, ahead of this? And so you heard Druckenmiller talk about this this week. Paul Tudor Jones talked about it. I think Ray Dalio all said the market is fully banking on a Trump victory at this point in time.

I probably wouldn't put the market is at 100%, but, you know, there's 70 to 80% baked into the cake. You can see that a lot of stocks have moved a lot. And I peeled this back a little bit. - This is unbelievable. I'd love to see what's in this democratic spread trade bucket.

It's down 20%, 30 days. - Well, I'll tell you, you know, I looked at it, you know, some companies in the solar complex, like Enphase, et cetera, down 25%. Companies- - In 30 days. - In 30 days. You know, companies like in the healthcare trade, Humana and others down significantly because obviously they provide Medicare Advantage and other products that will get hurt, that are expected to get hurt under a Trump presidency.

And so if you look at the policy consequences of these two candidates, they're very stark, right? And I would argue that most- - He's also talked about an MFN clause for drug prices inside versus outside of US. - So at this point, would I sit here and I try to fine tune my portfolio for the election?

Probably not. You know, I think that markets have been quite efficient on this over the last 30 days. And my own sense is that the bigger surprise, right? If you thought that it wasn't 60 or 70% likelihood that Trump was going to win, let's say you thought it was actually even odds and you believe the polls that are out there, right?

That whole trade there will unwind if Harris wins. So there would be a massive move in the other direction, right, if Harris were to win. I put both of them in the too hard bucket, but I thought I'd put them out there because we get certainly a lot of chatter about it.

- All right, we're in the earning season, Brad. So, and we had a couple, like right before we just started today, I guess Google and AMD, what's your quick interpretation of what you're seeing and what do you expect? - Well, I think we came into this week, we and lots of others, like if you look over the course of the past several weeks, the Mag 5 has underperformed software and other categories.

And I think people are pretty concerned about the CapEx guides. There's been a lot of talk about that. I came into this week and said to my team, I think it's largely priced in at this point in time. I said, I thought the whole Mag 5 would probably trade up three to 5% this week, including Google.

Google came out tonight, they grew their search revenues by 12%. They grew YouTube revenues by 12%. The stock's up, I think, four or 5% after hours. That all smells right to me. It had traded off a lot going into this period. I think the more interesting thing, Bill, is if you look at kind of-- - Hey, can I ask you just a quick follow-up.

When you said they were worried about the CapEx guide, which way were they worried? - They were worried that it was gonna be even higher. - Yeah. - Okay, so-- - But from your analysis earlier, it's a good thing if they wanna spend more. - Well, no, I think that there is, I mean, remember, these CapEx expenses have gone fairly parabolic in the last couple of years.

- Yeah. - But operating income, so margin expansion and top-line growth have outpaced the increase in CapEx. So people have tolerated it. What won't work well, right? Let's say we had a recession next year, and then earnings came in a lot lower than people expected, or top-line growth came in lower, but you were unhinged on CapEx.

I don't think that would be a particularly good equation for the stock. So some people were quite worried about this. But I think, let's talk about Google in particular, right? I think there's a lot of concern and chatter in the world. I've been out there talking about it. Chat GPT has consumed an extraordinary percentage of the time and energy that I used to spend in search.

So it's kind of hard to believe that it's not really having an impact on search revenues, but it's not. And so if you look at this chart that shows the search revenue growth over the course of the last eight quarters, I mean, they've accelerated search revenue growth from end of '22 and early '23, from 2%, 5%, all the way up to 14%, still at 12% today.

So part of the question is, how long can search revenue growth stay at this level? And one of the key questions there was whether or not the AI-enhanced search results were going to monetize at the same level as non-AI-enhanced search results. So they call these SGE. And it turns out that they said on the call tonight that they're monetizing at the same level.

So that's a really good data point for Google, if true, which is they can layer in the answer at the top, push the blue links down the page without losing a lot of revenue. Although, I mean, this has been argued both as a positive and negative, but the searches that were, I guess, stolen most quickly by a chat engine are more of these kind of encyclopedic-type searches where you're looking for information, whereas the big money searches for Google are travel and new car and a home and those kind of things, big purchases.

And so those may not, in fact, be the ones where they're inserting much of this. So you may be talking about the long tail of their searches anyway that aren't that relevant to the big dollars. You know what I'm saying? I don't know, for sure. I mean, a lot of people think of these as the knowledge graph searches.

You know, I've been using, you know, all last night I was using ChatGPT to help Lincoln study for his AP History exam. There's not a lot of monetization of that in Google anyway. So that page could be the same. Right, so that monetization is about the same. Now, we've also, as you know, we saw this week that Anthropic released computer use, to take control of my browser, to, you know, what we've been discussing, book that hotel or book that airline ticket.

It's kludgy, you know, a lot of people, you know, but it's a step in the direction. A lot of people thought that Google was going to release Jarvis this week, which is their version of this. Someone just funded a new browser company, Kleiner did, I think. OpenAI will certainly do this.

For the agentic browser. So, you know, the fact of the matter is, Google is already discounting this. It's trading at the lowest multiple, you know, in the mag five. So I think people are saying at some point, it's going to have some effect. We don't know exactly when, but I would just say for this quarter, you know, super solid quarter out of the company.

And then you asked about AMD. AMD's down about 10% after hours, despite, you know, continuing to have blistering growth. And I think what's going on there is, there was some talk at the beginning of the year, that AMD could capture maybe 10% of the data center market. And the fact of the matter is, when they gave some forward guidance tonight, that suggests they're going to stay at about 3% of the GPU kind of data center market, relative to NVIDIA at about 90%.

The company's done extraordinarily well. Lisa is an amazing, you know, CEO. And I think there are a lot of good things in the works, but, you know, they're not closing the gap in terms of share of market. The tide is rising for both parties, but the opportunity clearly for them.

- And it's off big now. - Right, is to try to pierce a larger share of that market, but we didn't see any move forward. - You know, back on the Google thing real quick, I just have a really hard time, like in my brain, separating kind of my own user experience shift and how fewer Google searches I do, to accepting the idea that, oh, well, they're going to add it in too.

Like, I don't go back there and say, oh, this is better, like with it added in and the ads and stuff. I prefer the-- - Perplexity or-- - Perplexity or chat GPT, I really do. So I don't feel-- - Right, and so that to me is the leading edge, right?

Like at the end of the day, could Google give you that same clean experience that chat GPT gives you? Of course they could, right? But they cannibalize, that's what innovator's dilemma means. They cannibalize their core business. And so they either have to, you know, have a product that looks different, that still has the blue links, that still has the sponsored ads, right?

And you risk losing user affinity, right? Or, you know, so to me it's-- - Well, they have this other challenge that I think is hard for people to understand, but I've explained it a couple of times, which is their revenue per visit is going to fall if they complete the transaction.

Because someone is spending marketing dollars to take that customer to their website and run the transaction with the hopes that they'll come directly back to that website. So they'll spend 50 to 100% of first transaction. There's no one that's gonna, if Google or chat GPT or whoever convinces Kayak or whoever to be a white label rails in the background, the amount of money they're gonna give you for that, it's gonna be like 5% of the transaction.

- Bill, you brought something interesting. So like this new browser, right? It's company called Browserbase. And I think this is a really interesting concept to think about kind of transitionary states versus end states, right? The transitionary state today is we're gonna have agents that essentially can scrape websites and view it as if I'm doing it.

They're gonna recognize the button and click the button. They're gonna go here. What if we reinvented the browser and built it in a way where it's not a button for a human eye, but everything is some composable API that an agent can recognize and an agent can go interact with.

And so you're not scraping the website where you would lose the eyeballs. You're building a new browser for agents versus humans. Is that the end state? There's lots, I don't know the answer, but it's an interesting question. - You have to rebuild all the rails too. I mean, everything has to start to look like Stripe.

There has to be a travel Stripe. There has to be, like you need a transactional network and that's not what we have today. Like we have this browser-based world that sits between the consumer and all these businesses. But it could happen. And boy, we've talked about voice. Like if you just start talking to your computer, it's a very different world.

That's not a browser or it's not the browser we know. We'll be a different entity. - Yeah. - Well, I think the way you go over the top and why I'm so excited about the equivalent of computer use across the board is in the same reason perhaps that Elon says you use a humanoid versus a non-humanoid robotic form because a humanoid works in a world that was designed for humans, right?

And the thing about computer use, you don't have to build all these new rails and everything, which takes a really long time to negotiate all of that stuff. Instead, you just give it ubiquitous use of the world that already exists straight out of the gate. - I think this is something I really wanted to make a point on.

I think it's gonna be super interesting to watch which categories and which verticals fall into place first and why. There was an article out this week that was looking at, I think, open AI as a scribe. And they highlighted that it failed a lot. And this is also an issue with self-driving.

If the cost of a 5% error or a 10% error is super high, it's gonna take AI a long time to get there. I would argue programming's that way. You can't have 5% or 10%-- - Self-driving cars. - Wrong. Self-driving cars. - The error rate is death. - It may turn out that customer service, that's just fine because the best in class today already has that error rate just because of human failure.

And so it will take AI a while to get to where it has the kind of nines you need to solve certain problems. And that's why I'm so intrigued by which verticals are gonna line up first and get knocked over. - Well, another good conversation, Jamin. Great blog. - Thanks for joining us.

- Thanks for having me. - Great blog and I imagine we're gonna get a lot of feedback on this one from LPs and founders. So we'll make sure to put it in the notes. Great to see you both. Thanks for being here. - Good to see you. Take care.

(upbeat music) - As a reminder to everybody, just our opinions, not investment advice.