All right, everybody.
having a hard time getting a core and here on the podcast. But David Friedberg is here. David Friedberg is back our Sultan's science. How you doing, brother? Great to be with you. It's great to be with you. And everybody loves when Brad Gersner is here. He's your Bruce Wayne. If markets are your gay, he brings that namaste to your payday. His glasses at discount and touching one of those fancy trump accounts. All right. Welcome back to the program, Brad. I love it. I love it. You're bringing the
rhymes back. I bring a little intro back. We've been trying Chamop is on the road right now. Chamop is on the road. But we will get a field report from Chamop and I call Daniel some how sex is going to be here.
But you know how he is. He's always late because you know, you get a phone call from very important
people, but he will break in at some point. Oh, wait. I see in the text here. Oh, there he is. You made it. How do you like my beautiful summer of the late? It's incredible. It fits perfectly. I don't know how Chamop does this. Well, here's the report everybody. As everybody knows, Chamop is on the road. He, oh,
“here he is. He, this is a photo. He went. He went to check his data center progress. I think”
that's in Colorado in the water where he's building a data center. I think that's on June. Oh, it's on June. Yes, it is. Four. Oh, yes. There he is in my ring himself. Oh, look. Here's
that. You know, when a meme has reached its peak when your wife starts dunking on you. There it is.
And here we are. This was at the Christmas party. I think. Oh, you were on C.R.C. on the Sunday. Andrew, we're a scork. And no, I wasn't sure if it was my Twitter feed that was just selecting into it, but it's not everyone, right? This is it. This is it. Everything. All right, let's go. I've to get to an up with the shenanigans and small talk. Google had two major shakeups to its AI staff on Wednesday. Demis has saw this has moved to chair of deep mind and
chief scientists at Google reports described this as them is stepping down or being kicked up stairs. We'll get into that. But Google framed it as a promotion and says he was stepping up. Here's exeos is quote explaining the shakeup quote. Google's Gemini 3.5 Pro is months behind with some company sources telling exeos that it's in part due to low morale. Interesting. Several top researchers including Gemini's co-lead have left the firm for competing in labs.
Chef Dean plus three other AI super stars are leaving Google to start a company called Discovery Loop. Dean is a legend for your bird. And I think you worked with him at Google. One of the world's great AI engineers. He was employing number 30, joined in 1999 and has worked there for what I understand continuously for 27 years. Discovery loops going to be focused on deep scientific
breakthroughs in AI. Google shares down 4% on the news of Dean leaving. So 200 billion in
“lost market cap if you want to correlate those two things. Freeberg. This is your alma mater.”
What are your thoughts here? Is this creative destruction? Maybe these people weren't delivering and they wanted fresh blood or is this just the siren call of doing a startup in an age of unlimited capital for AI and unlimited opportunity. Just being too much for the OGs at Google cannot take advantage of. Maybe it's the third bucket which is if you're the board and the management, you're having a debate about how to best deploy capital. Google has made a commitment to deploy
200 billion dollars in cap X this year in AI infrastructure data center build out. Because of the cap X and accelerated depreciation, making an investment in AI compute in the US right now is hugely tax-advantaged and because of the extreme demand for compute, it's a pretty obvious kind of ROIC model return on invested capital. So if you make this sort of an investment, you have significant demand for that compute infrastructure. You're very good at running the compute infrastructure.
That capital can deliver massive profit returns for you with very high confidence in some forecasted period. Building the most advanced frontier lab driven model also takes tens of billions of
“dollars of capital and the question really is, can you deliver the profits from the model?”
And in a world where open source is becoming so good and open weights models are catching up so quickly and all the frontier labs are catching up to each other so quickly. Does it really make as much sense to deploy tens of billions of dollars against building a model? And I think that
The scientists that we're seeing transition out are the scientists that have ...
of model development of making this frontier models. And they were certainly first out the gate. You can look at some of the early interviews with Jeff Dean for a couple of years ago where they actually had a chat GPT equivalent internally a year before chat GPT came out from open AI. Google chose not to release it for fear of cannibalizing search and so on. That's when Sergey stepped in and there's this whole kind of revitalization. But it's time has gone on and
“it's everyone is competed on models as we've talked about many times on the show. I think it's”
pretty obvious that it is very hard to get the same sort of return on capital invested in model development as it is in capital invested on compute infrastructure and being model agnostic. What Google has is probably one of the greatest install enterprise bases in the world for compute. Save the most enterprise customers. They have the most consumers and in both cases,
they don't necessarily need to have the best model to make an incredible business.
They can be model agnostic. They can work with anthropic. They can work with open AI. They can work with SpaceX. They have a significant ownership stake in SpaceX and an anthropic. And they can work with all the open weights models. They can host them all. So now, if you're one of the great computer scientists, you're Dennis, you're Jeff Dean, you're this whole crew and you're inside a Google and they're allocating capital not to your
models, not to the things that you're most interested in, but they're allocating capital to infrastructure and data centers and supporting the broad ecosystem of models. You start to say, well, given the fact that I can go down the road and visit Brad Gorsner and a couple other people
and raise a couple of billion dollars at a multi-billion dollar pre money with a PowerPoint deck
because I'm the greatest in the world of doing this, that might be a better path for me. And I think that that's the moment. So the way I would frame it is capex is high alpha, low beta in data center infrastructure, that capital. And model development theoretically could be high alpha, but it's very high beta. It's a very risky way to deploy capital. So if I'm the board, I'm the management, I'm deploying more capital and computing infrastructure, less capital
“into model development. That's what I think's going on. Brad, what you're taking on this?”
I think David nails it. I mean, listen, the same thing's going on at Microsoft, right? Sacha is out this week saying, you know, Saudi Morgan Stanley's report and saying they're seeing over a 30% return on invested capital in tokens as a service, right? So in the infrastructure business. So I think David's exactly right. Those are such good businesses, right? You deploy capital, everybody's running it from you, but the scientists who want to be involved in super
intelligence, who want to cure cancer, who want to be on the frontier of these models, right? They're sitting there dealing with this channel conflict at Google because, you know, Google Cloud wants all of the compute in order to rent it out to Anthropics. And those, those building the frontier models internally want that compute in order to compete with Anthropics. So you have this inherent channel conflict between those wanting to build the models. I think David said it really
“well. And I think that's a big challenge for them. It looks like it's being resolved in favor”
of being more of an infrastructure company. So where does, you know, telescope out for a second, SpaceX also reported this week? They also have channel conflict. They're running out their compute to Anthropics at the same time. They're trying to build their own model with rock and cursor. You have that channel conflict at Google. You have that channel conflict at Microsoft, although I don't even really see them pushing the frontier anymore in terms of models.
Met us talking about getting into the infrastructure as a service game. And then at Anthropics and OpenAI, you don't have any of that channel conflict. They say we're not in the infrastructure business. We're only in the model business. So I think it's a, you know, a clarifying view as we look forward that we may in fact not have those companies on the frontier of model development if all these people leave. By the way, thanks to the law passed on CapEx depreciation. If you assume
a 26% corporate tax rate, every dollar you deploy in CapEx because you get to write it off in this year, you're basically getting 26% off. You know, that's money. You get right back. Yeah. Yeah. Hey, Sachs. Let me have you comment on this as well. Polymarket, which companies will have the number one AI model by the end of this year on December 31st. Now, of course, in the last time they did this andthropic ones. So they're not on the list. They're the winner.
But who will have it going forward? Opening AI 32% Google 20% only Bob of 14. And then you got moonshot XAI meta by dense all that about 10%. So Sachs, your thoughts here on what's the better business is the better business being in the language model frontier model or is that getting quickly commoditized and really you want to be in the token sale business or is that also
going to be a commodity and you just need to be on the application layer? Here's what I think is going
on in terms of the market structure is when I saw this Google news, my reaction was and then there
Were two because like Brad was saying, we used to have five major companies i...
leading frontier lab, the leading frontier model just a year ago. Now, we're really down to just anthropic and open AI. So the market for frontier intelligence has become a duopoly. Now, Elon is still in the hunt. I'm sure Google would say they're still on the hunt. But like Brad is saying they may have contradictory incentives there because they can actually do quite well just with their
“compute. So I think that the market for frontier intelligence has become a duopoly. I think it's a”
very powerful duopoly. I don't think it's being commoditized. I think that we're evolving to as a two-tier market structure where there's a market for frontier intelligence and there's a market for let's call it kind of commodity or lagging intelligence, whatever you want to call it. That's
six to 12 months behind. There is a market for those tokens, those models. But the reality is you
can't charge anything for the weights. You can charge for the compute. You can charge for the inference that you're providing. You can charge for essentially consulting services to help put the whole thing together. But if you're not at the frontier, you can't charge for the model layer itself. If you are at the frontier, you can charge a premium. And that's where anthropic and open AI are. And I think the proof for this is just you look at the growth rates of these companies,
the latest we heard is anthropic is now over 80 billion of ARR. Start of the year at 10. It had forecast a hundred billion as exit ARR for the year. And most people said that that would be impossible to achieve. Now it looks like they're going to do it with a couple of months to spare. So their estimates are going up. I mean, 110, 120 or higher for end of your ARR. Open AI seeing acceleration. So I think what you're seeing now is a very clear bifurcation in the market.
You've got a frontier model doopily that can charge a premium. I think of it like Apple. Apple is competing against Android. It's open source. Android actually has more users in the world. But all the monetization goes to Apple because people are willing to pay for the premium experience. I think in a similar way, people are willing to pay a premium for true frontier intelligence. If it's really at the leading edge. But if you're not the leading edge, there's a huge market for that too.
But it's highly commoditized. People are just willing to pay you for the compute.
“So I mean, that's what I see happening right now.”
Yeah, what do you think? Jason, what do you think? Well, if you look at Google Cloud,
they posted 82% year over year revenue growth, which is at something we've never seen in the history of
these cloud providers Elon Musk and XAI just had the SpaceX earnings were going to get into that. But they also had massive uptick in their Elon web services as I've dubbed it. And if you look at Google, I still think Google will be the number one AI company because they have so many people using AI inside of their products already. They have five products now with over three billion monthly users each. Android search, Gmail, Chrome, YouTube, all have
over three billion. If you've used any of these products recently, they are becoming AI first products. YouTube especially, but obviously Chrome and Gmail, you're seeing tools pop up there for AI.
And then, freeberg, you kind of alluded to this. They have 13 products total with over a billion.
And that now includes Gemini. In Q2, Gemini had over 950 monthly active users tripling year over year. They will be the number one AI company in terms of consumer usage,
“by far, I think, fish year. That doesn't mean that the frontier models are not great businesses.”
They obviously are. But I have been using exclusively non frontier models. And for 95% of the jobs I'm doing, SACS, it's good enough. And I just posted about this, you know, and Elon and I got into it a little bit here. And I think you referenced this in our group chat. I tweeted just the other day, the difference between the open source models I'm using in frontier is negligible or ready. I believe that to be a true statement for the work I'm doing. And he said, you know, I'm responding
back to me. It's actually a world of difference. You know, if you're doing something other than making a copy of a video game, or you have incredible speed needs, the frontier models are not necessary anymore. They're just not necessary. The people using the frontier models are doing it because their company set it up. And it's too hard to implement open source right now. But it's going to get easier in using to implement it. So I'm still going with open source in Gemini.
Being the leaders. It's true for your use cases. Yeah. Let's say the cheaper commodity intelligence that middle of the market is good enough. Look, an Android phone would be good enough for me. I could get by on a cheap Android phone. You know what? I still pay a premium for this because
I use it so much.
highly competitive industry, you don't want to take the chance that you're not getting the best
intelligence to power your models. You know, and there's a lot of industries like that where the competitive dynamics will drive you to pay for the best intelligence. There's also situations that goes back to the blog post that Decagon posted, which is if you're looking for use cases, you also want to use the true frontier because again, when you're dealing with immature use cases, you don't know where the value is going to be and you're searching for opportunity to use AI.
You just want to use the best because again, the return on finding those use cases is going to be so much greater than the small premium you're paying at the token level. So I think there's a lot of examples like that when, you know, the use cases immature where you're in a competitive industry, where you're just deploying AI. You want the convenience of the full stock. So not go frontier models. Yeah, I can, you know, unless you're employees are doing something stupid like you
create a leaderboard and they're token maxing, I don't think the cost is that great. And again, the benefit that you're getting is huge. So a lot of people just like give me the best. I'm willing to pay a premium for the best. I'll take a slightly different take. I think that it's not necessarily do you take the best model or the open source model. I think that there's a blend that's happening.
“At least that's what I see. For example, we'll use open source open weights for a vast majority”
of simple workflow applications. But when it comes to specialized applications where we really need to have high quality model proficiency, for example, in life sciences and genomics modeling, I'm going to go for the premium model. If I'm working at a media company and I'm trying to do AI rendering of video, I'm going to use Gemini's model that does video. It is the best model or Sora or whatever the best model is for that particular application. So I think the idea that
there's kind of a model that you pick for everything, I think is the false assumption. On the consumer side, it is likely the case of the consumers are not going to be using some open weight model because they can pay 20, 40 bucks a month and get chat GPT or Gemini or Claude and be very happy paying 40 bucks a month and they'll basically be able to minimize their cost to run that for consumers. For enterprise, I think the enterprise is going to be very active in selecting a blend of
models that are going to make the most sense. Very cheap open weight model for simple workflow applications, individual employees, spinning up an app, whatever, and then more complex models for those really key workflow tasks and then specialized models. And I will say it is way too early to
count Gemini out on building incredible specialized models. They have the best video data. They
have the best life sciences data. They've been working on this for far longer than an anthropic or open AI in the life sciences side. They're very well ahead on that front. I mean, demos is still going to be running isomorphic labs. So when it comes to be specialized models,
“verticalized specialized models like video life sciences, protein folding, I think these are the”
things where you're really going to see Gemini shine and then every enterprise is going to have a mixture. But hey, you can be the cloud service provider with that mixture of models, which is what Google, GCP can now be. I'm going to sign up for working with GCP versus working just with anthropic. One of the things this has created is down with pressure on the pricing. We start opening AI and Claude to mass surprise cuts for token. So they are reacting and not taking a sitting down
in the orchestration between these models is being built into a lot of harnesses side of enterprises. So what's your take on the downward pressure on token pricing? Or is it just great for consumers and enterprises? Listen, we've got massive competition. That's the thing. America is winning. This is exactly what you want. We have massively competitive market. We have Chinese open source domestic open source frontier national labs that are doing what they're doing. We have downward
pressure on pricing. You know, David referenced the doopily. You know, I think it's hard to call it a doopily when you're, you know, only a few years into this and you have giants like Amazon, Microsoft and Google. I do think he's right. I do think they've emerged, you know, as the pure plays, their revenues would suggest that they're, you know, they're gaining share of wallet.
“But there are two points I want to make here because I think they're non-consensus views”
that we're spoken this week. One was Elon's response to you, Jason. Right. Over the last two weeks, everybody's been saying that the Chinese have caught up, that open source tokens have caught up in intelligence that they're much cheaper, et cetera. And Elon comes out and says not so fast. We're entering the singularity and the frontier models are way further ahead than people think. I believe that to be true. I think for your use case, they're very similar. But I don't think that's the most
sophisticated use case that people are trying to train on and try and to experience. And then Jensen came out this week and said close models are actually cheaper. You know, if you don't have to build it for yourself, if you don't have to, you know, the training costs and a lot of expertise
to fine tune and maintain and guard rail and keep it safe. So he's basically making the argument
that not only are the frontier models further ahead, but that the cost differential between
The two is not what everybody's making it out to see, to be, which I think ex...
continue to run away with it on the revenue side of the equation. But I think we have healthy competition. You're right, J. Cal, you know, for the vast majority of use cases, I think token consumption is going up for the open source guys, while share of economics is going up for the
“frontier labs. I think that's what we want to see. Yeah, and it's just Android versus iPhone all over again.”
One platform makes the profit. One gets the majority of users at least globally and usage. All right, let's suck SpaceX here. They had their first earnings report as a public company. Share shop 13% I think because people were a little concerned about the surging AI capex. It's down 30% since going public in June, but it's now trading and it seems to have settled in at a 1.4 trillion dollar valuation when public obviously above two trillion.
Q2 results were spectacular. It's the only way to put it 7.8 billion in revenue up 90 to
percent year over year. Let that sink in and 67% quarter over quarter AI revenue. You want web services. More than tripled quarter over quarter to 2.6 billion dollars. That's not cursor. That hasn't closed yet. That's going to be one of the great purchases in history. This is from you on web services, renting out compute specifically to anthropic and Google from the Colossus collection of servers. But capex was up 18.4 billion in the quarter. That's 6x year over year. Obviously you can do the
math there for a run rate of about 75 billion dollars. I'll stop there and get your reaction Brad to the SpaceX IPO. I know you've been tracking this and commented on it. I mean, listen, I think that one first, let's start off. $1.4 trillion a value creation for this company is extraordinary. So the fact that from peak to trough it's down 40 or 50% from the IPO, we had that chart out
“a few weeks ago. Remember that within six months of the IPO, almost all these tech stocks are”
down 50% peak to trough. We see it again here with SpaceX. I thought it was a really solid quarter. I thought as guides were pretty extraordinary. 100 billion in ARR by the end of the year. And he pulled forward the one trillion dollar target in ARR by a year from 2031 to 2030. Now, to just put that in perspective, Morgan Stanley's 2030 revenue estimates 325 billion, which is also extraordinary. Remember, this company did 18 billion in revenue last year.
So whether you're taking Morgan Stanley's numbers or Elon's numbers, clearly the market is not pricey that in. At 2 trillion, we were pricey that had a couple of years. I think now the value reflects kind of where we are. The market has questions about a few
things. Here's what they are. Number one, on the rental business, the rental of compute business,
be rented out of huge block of compute to anthropic. It's the question that we've been talking about here. Are you going to use the compute to build your own frontier model or are you going to rent it out? And if you rent it out, are you going to be able to find those people who have the capital to offtake that compute? He's talking enormous numbers, 10 to 20 gigs and people are wondering how they're going to be able to finance that. And remember, those businesses, the GPU rental
businesses tend to trade at very low multiples. Look at core, we, etc. On the frontier model business, I think this is the sleeper. I think he said on the call that rock tripled tokens in the month of July, that doesn't include cursor. cursor was already on a path to go from 3 billion to 10 billion
by the end of the year. cursor plus rock could be at 10 to 20 billion by the end of the year.
That would be an extraordinarily valuable asset going to trade at a much higher multiple than the data center business. And then, of course, we haven't even talked about Starlink and what he's going to do, you know, I think going to run the table on mobile. So, this is the normal consolidation. We have funds like across Silicon Valley that are distributing their shares, the stock is traded down a bit, nothing surprising to me here. Now it's all about execution.
“I think the most important thing to watch the two most important things to watch are number one,”
how do the rock and cursor revenues end the year? And number two, you know, the traction they get on, you know, continuing to replace traditional mobile carriers with Starlink. The distribution started, I think today, or yesterday, I got my first distribution from the fund. I mean, I'm in a couple of funds that are in SpaceX, seems like everybody's in that. And that will obviously create downpressure if you are amongst the people who want to cash out and have been in it for
a long time, but I'm holding these for my grandkids. Sacks your take on these spectacular, yeah, I guess, is the only way to describe them results coming from a vertical that was in part of SpaceX's business, but nine months ago. Yeah, look, I thought it was a very bullish earnings call. I was a little bit surprised that the stock went down after the earnings call because not only was it a beaten raise, but also, I think, Elon spoke to a lot of their plans.
The only thing I would add to what Brad said was around Starship, Elon basica...
it, right, that the Starship test flight was successful. The Starship floating in the ocean,
“the heat shield worked. That's going to enable more flights of Starship now at a more accelerated”
rate. That paved the way for the V3 satellite, which enables much more bandwidth for the Starlink network, which then powers the whole direct to cell play. So you had that piece of it, I mean, just the whole telecom aspect seemed very on track and they're very bullish about that, and then you've got the whole AI data center play. Now, on the data centers, I think what they said is that they expected to go from 1.4 gigawatts to compute to about 2 by the end of the year.
And Elon said that the spot price for compute is in the 30 to 50 dollars per watt range. So,
you know, you do the math that gigawatts is a billion watts. So 30 to 50 dollars per watt means
30 to 50 billion per gigawatts. And I think they're at the high end of that range right now. So when Elon says, look, we're going to end the year at 100 billion of ARR, all you have to believe is that they're at 2 gigawatts of compute, running for 50 dollars a watt to hit that. That doesn't include Starlink or the launch business or the Grok cursor piece or any of these things.
“So I think that's why they're supposed to pull ways to win is what you're saying,”
there's multiple ways to win with the stock. I think Starlink's just an unbelievable juggernaut cash machine. If you look at the financials, there's segment reports space connectivity in AI. And on the connectivity side, the Starlink side, they generated $2.6 billion in adjusted EBITDA. You can kind of approximate that to be kind of operating cash flow. Space was kind of, you know,
negative 200 million to call it break even. And AI was plus 1.1 billion. But AI to Brad's point,
it's unclear whether the pricing they're getting on compute rental today is temporary at a premium because of the lack of compute available in the market today and people that need computer paying you want to premium for that coupon queue. So I think there's a question mark where that goes. But the connectivity piece on Starlink, 4.3 billion in the quarter and 2.6 billion in adjusted EBITDA. He's got $12 million subscribers. That's doubled year over year. $66 R.Poo per month. What people
are paying per month. And he grew 20% quarter of a quarter. So if you extrapolate this out, he's pretty close to being at a 24 million subscriber run rate on this multiple and assuming this enterprise stuff, which is like airlines and other things scale, which they seem to be scaling
with the consumer business, Starlink alone could be generating on the order of $40 billion of revenue
top line with a huge amount of that flowing to free cash. That could be a $30 billion free cash flow within the year. That alone provides the cash flow to fund much of what Elon's doing. And if you just put a 30x multiple on that, which I think you can because these subscription businesses are very high renewal rate, very low-capped. I think you could probably get a 30x just on the Starlink business. The Starlink business alone could be a trillion dollar market cap within two years, within 18 months.
Let's say. That I think funds all of the rest of this is kind of science projects and upside. So I'm kind of making a bullcase. It's crazy to me how well the Starlink business performs. And you can see it in AT&T and Verizon, Huesnet, VSAT. I mean, these companies have been decimated. I used to have a Huesnet satellite dish on my Sonoma County ranch. In order to get
“internet, that's what we had to use. It was like, you know, 200 bucks a month or two. Because those”
are most service. And they take forever to terrible service. And that market got decimated by Starlink. And if you launch the handset thing, that subscriber growth is going to go right now. He's adding 2 million subscribers on the consumer side a quarter. You could see that going to four to five million a quarter. You could actually see an acceleration in a consumer subscription, four hundred million mobile subs just in the United States. You can make, you can make the bullcase on Starlink
alone. And then the rest of it is like, hey, is Elon going to do well with investing the excess capital that's fitting off of Starlink? How's Elon going to do with that money? Well, I don't know who else I'd give it to. You know, do what he's doing with Starship and with AI compute and the Terra Faber. Oh my god. This is the science fiction. I mean, like, if you want to talk about bounty, you know, how the US gets off of this dependency with Taiwan and China from semiconductors.
If Elon takes this on his shoulders and he delivers what he's showing as a vision here today, this is going to be the greatest semiconductor fabrication site on planet Earth. Well, you know, I would say something, you know, David to your point. You know, how many CEOs or founders would just take that Starlink business, which is such an exceptional business, trillion dollar business going to two trillion, and they would not take any of these other
Risks.
trying to build their own model that's highly risky, but highly important investments that are being made. I mean, it is heroic and important that we have this level of, I just think, I'm bridled enthusiasm for innovation on the frontier that Elon's doing. And I wish we saw more CEOs, more public companies willing to take this level of risk. We just got done talking about, you know, some CEOs, maybe that we're taking less risk because the safe bet was was easier to make.
Elon refuses just to take the safe bet. He's taking all the dollars from this thing where he has an extraordinary business and plowing them back into these things that are critically important to the United States. And by the way, Brian, such a good point because if you look at other CEOs and other management teams, they're getting in on this, they're starting to realize that buying back your shares, giving dividends is not as important as betting on the future,
Door Dash got taken to the wood shed because they're investing too much in Cap X. Obviously Google got smacked with their Cap X spend. So that keeps happening over and over again. And just on the
“headwinds that SpaceX is going to face, the arguments that I think will turn out to be wrong,”
but they're valid to talk about here are, hey, is this demand for tokens and compute going to keep up or does on-prem and desktops and open source models getting smaller, better? Does that actually mute at some point demand? I don't think it does. I don't know there's an upper,
I don't know there's an upper bound for on-demand intelligence. The second one, obviously,
is Starlink is for people who are in a rural neighborhood. If you've got Verizon, fiber to your building or spectrum, you're not putting nor can you put a starlink on your building. So the piece there that's going to be explained probably in the next year or two is every single Tesla sold's going to have Starlink in it when they get that merger done. What that means is, you're going to have Wi-Fi networks connecting any phone to any Tesla, say, while those robot
taxis out there, you'll be able to connect also directly with the next generation of Starlink. So your phone will be able to direct if it's got clear line of site, it's going to be able to connect to any Tesla on the road, which there are many that all future ones will have a Starlink built into them. So those are super promising and then finally, you know, there's been a lot of speculation
“about the valuation. Brad, you brought it up. I think at liquidity when people were asking you”
and I heard you talk about it. Hey, private companies venture capital. We are a voting mechanism and then when it goes public it becomes a weighing mechanism and sometimes you'll have this moment in time where there's hand ringing about those valuations and the hand ringing peaked in the last quarter. You had 160 times price to sales ratio for Tesla when it first came out. 160 times, right? You take this two or three trillion dollar market cap and you put it against a smaller revenue
number. Well, if you look at the revenue number increasing, now we're down to a 45 times price to sales ratio. So some kind of balance is occurring here. Yeah, Brad, between these private and public markets as well as the increase in revenue. Yeah, I mean, honestly, I think this is all super healthy. I think the SpaceX IPO is extraordinary. I think the consolidation here is perfectly predictable. And now you have a company at 1.4 trillion that I think if you take a three or four year view,
you can see yourself tripling your money in this business at a very reasonable valuation
on the Morgan Stanley numbers or on the Elon numbers or whatever. But that's always been the
“bet. Do you believe that Elon is the greatest innovator and great allocator of capital?”
But the price of entry matters, right? When you get carried away on day one of an IPO and you buy this thing over two trillion, you got to know that this is going to happen. I was on CMBC the day of the IPO and I said, I would want to own this company, but I'm not sure today's the day I would buy the company, right? And so entry price matters and entry price not fundamental. But let me give you another one. You know, like we've talked about the anthropic IPO or a lot of people have talked about it later this year.
I hear a lot of people saying 1.5 or 2 trillion dollars. David just talked earlier that it's going to be run rating over a hundred billion maybe by the end of the year. That's like 10 to 15 times revenue. That is not that much for a company that just grew 10x and is rumored to be profitable in Q2. And so I look at the market, the consolidation we saw in the month of July, you know, we put in the Leopold bottom, hopefully in July, you know, a lot of semi-stars are down. It's hard. You know,
30, 40 million. Hey, listen, the guy's doing great. He's apparently still up 80% for the year,
just made another big private investment. I think he's done extraordinarily good job building in a firm to short period of time. But the market did panic around that. Yeah. As he had to cover. I think all of that is really good. So as I look ahead, marching to these IPOs later in the year on the
Back of the SpaceX IPO, I think we're in really good shape, you know, particu...
continue a pace. You know what Elon is really good at? It's just building stuff. It's just physical, physical, physical sites. That is such a core advantage in this world where everyone's competing for data centers and fabs, the software layer needs hardware in the physical world in order to deliver their software services. And there is no one better than Elon, and actually doing that. Look at how giga factories have been stood up around the world. This is
his core competency. So Brad, like when you put Elon up against Adario and a Sam, and even an alphabet, which has 27 years of doing this, I mean, man, Elon's got a core advantage of this is what this world comes down to. He says something like that on the call, where he said, look, putting up data centers is nothing compared to the difficulty of putting up a rocket, right? It's like, you know, creating data centers is not rocket science. So they take some of those hardware
“expertise that they have from SpaceX, and they put them into data centers, and that's why they've”
been able to stand up, you know, more data centers or bigger data centers faster than all the competitors. A couple of points there. Is it clear why Starship is so important to
startling? Okay, let me just explain this quickly. So basically SpaceX has developed a new V3
satellite that has 10X the bandwidth of its V2 satellite. So currently, the Starlink network is powered by V2 satellites. They deploy them on the Falcon 9 rocket, and they launch about 27 satellites per launch, and that adds about 2.6 terabits per second of total network capacity. Starship deploys 60 of these V3 satellites per launch, that would add 60 terabits per second of total network capacity per launch. So over 20 times more capacity per launch, that's the power of it.
So if they get Starship working, by the way, the last test, not only did it prove that the heat shield worked, my understanding is they actually launched, or rather they deployed 20 V3 satellites as a test, and they were able to make connection with those satellites and prove that it worked. So like the camera's on it. The reason we were able to see the Starship was because they're
“like yellow. Let's put some cameras on them. Right. Now, I think those satellites, basically,”
it was just a test and they they burned up. So I think the next big milestone here will be when they launch Starship with let's say 60 of these V3 satellites, put them in the correct orbit, make connection with them, add the bandwidth to the network. That's going to be a big milestone. But you play this out to his logical conclusion, and the bandwidth available to the Starlink network goes up 10x or eventually 100x times. And that's when they can do all the interesting
things like direct cellular. There were some interesting hints that Gwynshaw will talk about with ground stations, about what they could potentially do there. And I think they might buy T-Mobile or something like that. So it's easily within their range of purchases. And I think Elon mentioned something about potentially the Starlink network could eventually handle roughly half of internet
traffic. So I mean, this thing could get so much bigger than just 12 million subscribers to your
point freeberg. But look, I want to actually talk about the data center for a second product. I do have a couple of questions about this. So Elon mentioned that, okay, we're going to be at two gigawatts by the end of the year. He said that we will be at 5 to 10 next year closer to 10 than 5. So let's just say 8. Okay. So I'm just making that up, but it's on their range. So let's just say that's an ad of 6 gigawatts. So they go from 2 to 8. Okay. To me, there's two questions.
One is, how do you know that the spot price is going to stay where it is? You know, can it stay at $50 per watt? How do we know? How do we track that? How much risk is there around that? I got the sense on the call that Elon thinks that number is going up because the market is memory constrained right now.
“I think he mentioned that we might see a 20% increase in memory production next year,”
but the demand is going up 200%. Plus. So the market is constrained by whatever the ball neck is at that time right now. The ball neck is memory. So where do you see the spot price going? How do we know how much risk is around that? And then the other question I would have is if you go from 2 to 8 gigawatts that you have net of 6, we know that a gigawatt power data center is, you know,
50 billion of capex. So six incremental gigawatts of compute would be 30 billion of capex next
year. It's something they built that right? I mean, they have optionality around that. I'm sure. So how do you finance that? You know, what's the most non-delutive way? They said their payback is a year or less. I'm sure that's tied to the spot price. So you only have to finance it for a year.
The question, do you think Nvidia gives them that financing?
I guess is my question. It's a great framing David. First, it's $50 billion per gigawatts to build
minimum. So you're $300 billion dollars. So in order to finance that, it seems to me, you either have
“to go into the market and borrow the money or you have to do a dilute of equity raise, neither of”
which they want to do. Or you get Nvidia to backstop it, which they've indicated that they're going to do more up. But the problem there is Nvidia shareholders don't want them backstopping unlimited because the fear in the world is that that sprite spot price at some point may go against you. And when it does, the payback period changes. Now, nobody thinks that the payback period is going to be one year. Even though the spot price is suggesting that it is that today. Just a few years ago,
people thought you would get paid or not few years ago, a few months ago. People thought you'd get
payback over four years. So you basically spend 50, you then earn 10 to 15 per year. You get payback
over four to five years. And then hopefully you get the six year, which really takes you up well above 20 per cent in terms of your returns. Right now, the shortage is so acute. And the willingness to pay from the front, from tier labs is so high because they all recognize they're on the verge of some massive breakthroughs that they're willing to pay three, four, five X market pricing
“in order to get at scale compute. And that's what happened with the anthropic deal with SpaceX.”
I think anthropic would buy a lot more of that today if they could. Same with open AI. You're saying that they would be willing to overpay by a factor of up to five X. Well, that's the fifty, you know, that's the fifty dollars per watt. The David was referencing. They would be willing to pay this thirty to fifty if they could get at scale compute that would give them a competitive advantage over the other people in the market. And remember,
there aren't a lot of people who have the off-take revenue that can afford to buy compute at the scale. Right? It wasn't the Chinese open source companies that were buying, you know, SpaceX's excess computer, building the 10 giga watt, you know, plant in Ohio. That's open AI in Anthropics. So the vast majority of the off-take commitments are coming from anthropic, open AI, and in video. Right? When you hear about the hyper scalars, building all of this,
you know, this computer, they're building it out to sell to the people that we, you know, that we just mentioned. So David, net net, if he built six gigawatts next year and by the way, probably only Elon, you know, can actually stand up that much in that time frame like, Jensen said to me on the pod, it's like, nobody comes close, Microsoft doesn't come close, you know, Google doesn't come close in terms of standing it up in that time frame.
“I think that he's going to have a challenge, you know, getting all of the componentry, right?”
I know he can stand it up, but can he get the memory, can he get the chips, can he get that land powered shell all in time? I think the off-take is there, right? But to put it perspective, this year Anthropic and Open AI combined, they're starting total compute. It was like five gigawatts. So he's talking about incrementally adding more than they had as combined companies. Right. That's not that much of an increase when Anthropic is growing 10x
year of a year and Open AI is maybe at what Forex or maybe higher now. So you may exist in the world. The demand exists in the world today. I think it will exist in the world for, well, you know, the next 12 to 24 months, but there is a wall of worry in the market. The reason we saw the pullback in July is Kimmy scared people into thinking, oh my gosh, they're going to undercut the frontiers revenues and if they undercut the frontier labs revenues, who the hell is going to
pay for all this compute? That's why you saw a 40% trade down in the core weaves of the world and you know, all of the semi-conductors stocks and semi-conductal related AI. In some ways, the fact that there's a discussion going on that this next 10 gigawatts is going to
cost, you know, sacks $500 billion in U.S. The question, where does that come from? The secondary
offering does Nvidia put it on their books? Do they create SPVs off their books? Like some people are doing, you know, the fact that we're having this conversation, everybody's aware of it, the market has been educated on it means I think people will be able to change in real time if it doesn't come to pass or if it slows down, which I suspect this cannot keep up at this pace, you know, more than another two years or so. As our good friend Bill Gurley likes to remind us, he's like,
I can't believe that we're all just taking and stride this level of seller financing, right? He would call it circular revenues, right? But the market has gotten comfortable with this, and remember, like we saw in July, if there is a scare about demand, the whole sector trades down. Yeah, everything will trade down, you know, together because that's just the leverage that
You're pumping into the system.
ahead of their revenue. So it becomes much more violent. If you ever see demand slippage, you know, famous last words, I don't see it today over the course of the next 12 to 18 months, but you know, you have these unknown unknown moments that certainly causes people to be fearful. Yeah, spreads are blowing, you know, have continued to to stay wide on these deals. So there is fear in the market about them. All right, everybody, the fifth annual, if it's September,
you know, it's time for the oil and summit, the fifth annual is happening. Yes, that's right. David Freeberg's been at work, and we have an all star, all star list of people joining us. Chets and long, founder and CEO of Nvidia, if you care about where AI is headed, you won't want to miss this conversation. The best, the Oracle Satya Nadella, CEO of Microsoft
fan of the pod will be coming on for the second time, Jarrod Isaacman from NASA, the one the only
Brad Gerser and Bill Garli BG2 coming back, SpaceX is going shot. Well, my guy, Jake Paul, Nick Shirley, a lot of incredible people coming, Martin Schrelli, maybe he's even coming. He's that's going to be fun. Go to the all insummit.com to apply today all in.com or the all insummit.com. Any of those will get you there. And we're taking over universal studios again. We'll have our own private playground day, freedberg, great job on the summit casino night, too. Aren't going to be
a bit casino night. Biggest yet. And the concert to be announced, who will be performing at the concert, but it is going to be incredible. So I'll just say one of the things about the summit, we've had people come to the summit from over 60 countries. It's really incredible to meet all these people, entrepreneurs, investors, people that are just really interested in the topics
that we talk about. We try and have the world's most important conversations, but it's really
“this amazing community experience. That's what brings folks back. So we try and invest more and”
more over your in making it an amazing experience, not just cool content on a stage, which I think is one of these other shows really deliver. But it's like, how do you actually come and have a have an experience for a couple of days? It's going to be awesome. So it's really as those three things that we focus on. One, you don't learn something, right? You got these great people on stage, you don't learn something from them. You're going to meet new people. You're going to network
and then you're going to have these great experiences. It's the trifecta, folks. You're excited, Brad. You're excited to be back. What are the dates? What are the dates? It's like, look at your calendar, you're speaking. September 13th through 15th in LA. This couldn't be better dates for the summit. I mean, we're going to be within 60 days of an election, internal election. We're going to be within 30 days of an IPO, you know, potentially of improv. I mean, it's going to be heated. The SAS
apocalypse, not the SAS apocalypse. This is the SAS apocalypse. I guess winding it's way out. The indigestion might be clearing. AirTable just got acquired for less than it raised.
It's a profitable SAS company, a great product. $480 million, half a billion dollars in annual revenue.
Growing 20% a year, respectable if it was a public company, with almost a billion dollars in cash has been sold. It's been sold for $1.28 billion. About 10% of its peak valuation, which was 11.7 billion in 2021. Now, they did have a bunch of cash. I mean, the cash position sell was $2.25 billion. They were acquired by a firm called Bending Spoons. This is an Italian company, Milan-based company. They buy, challenged, but, you know, interesting businesses, AOLs,
Legacy Business, Evernote, Eventbride, Vimeo, meetup.com. And they just went public last month, shares, that is Bending Spoons went public last month, shares up 15% on the AirTable News Sacks. When we look at this, this was a company that had done a lot of things right, had a massive amount of cash in their war chest. But rumors were maybe the founders were a little exhausted.
“Maybe some of the investors were exhausted, who bought it in a high level. What can we take away?”
From this transaction in Bending Spoons, are they the buyer of last resort? Well, I think they're creating a great business for themselves, because I think this will end up being a fairly profitable acquisition for them. Let me just add a piece to this, which is AirTable spun out its AI agent business, which is known as Hyper Agent into a separate independent company, prior to this acquisition. So I think what's going on here is that the founders and
town of the company, they said, look, we don't want to have to make this legacy product work. That's basically a private equity play. I'll explain what that means in a second. We want to focus on the new thing, the AI company, that's where the big value creation is going to be in the future or the potential for it. So essentially, the town is going to focus on the venture play. And then they're selling the private equity play to Bending Spoons. Now, why do I think this
“could be a good acquisition for Bending Spoons? I think there was a really interesting data point”
that I saw in the commentary on this, which is only 30% of AirTable sales team was making
Quota.
what it told me is, and I'm reading between the lines here, but this was a company that had a successful PLG motion. In other words, organic growth, product leg growth, and they were growing about 20% a year. But that was not good enough for its board. You know, these are investors,
some of whom invested in $11 billion peak valuation. So they're looking for a venture type outcome.
So what happens? The board pressures the founders to do something that frankly is unnatural for them, which is they say, look, you should bolt on a traditional sales lead motion here to get the growth up faster. Does that work? No, they probably get a little bit of growth out of it, but they only get 30% attainment. So they've got hundreds and hundreds of sales reps here trying to push on a string, and it's not making a growth faster. So now, what's the opportunity for the acquire here?
Bending Spoons can go in here and do what Elon did at Twitter, eliminate 85, 90% of the cost structure. Don't do this sales lead motion. Just go back to your product lead growth roots. You'll probably keep most of that 20% growth. And it'll be a very profitable company. You'll be able to
be-- A percent profitable probably, right? Probably. I mean, you'll punch it into the bottom line,
pace for the power station in the whole years. You're saying they're only going to generate
“30% EBITDA margin. I think like you're saying it could be 80, 90%. I don't think you need to”
keep most of this business. Or most of the cost structure associated with this business. Air table is a company that has its fans. I think they will probably stick with it. And you'll be generating, I don't know, you could probably generate 300 million of EBITDA year or 400 million while growing 10 to 20%. So that's a play for Bending Spoons. Bending Spoons are investors here, Sax. They're happy to get their money back and move on to the
next thing. It's a bit of a push for them in terms of at the Blackjack table. Rather than, they've got to go 10x just to catch up. And then they would have to go 10x again to make their LPs happy. It's not going to happen. I think the question is, if Bending Spoons can basically take
this business, that's not making money and probably generate 400 million of your EBITDA on
pay for the acquisition in just three years. Amazing. Why isn't that something that the company
“could do on its own? And I think that's the structural problem is I think it's very hard for both”
VCs who are on the board and the founders to shift into private equity mode. Why? Because they're going to have to demolition what they've built, right? They've got all this loyalty to the team. They don't want to think about how do I eliminate 80-90% of the cost structure. It's just not what they do. I mean, what the founders want to do and the outcome that the board members are going for is a venture backed outcome. And I think they could have done this. They could do a Bending Spoons
does. They're not built for it. They're not built for it. They're not built for it. And they're over the structure of the cap tables all wrong because they're sitting behind this giant liquidation preference. All these investors have to get paid back. We invested at this 11 billion dollar valuation and all the way up. The incentives are broken, Brad. And you, yourself, that you're a firm altimeter, you are pretty frisky in this period. You made a lot of bets.
So I don't know if air table was one of them, but you made some satsets there. Some of them were at high valuations. How are you looking back at that time period? Any lessons that you take going forward? Multiple of revenue can compress very quickly. It works great when the company's growing greater than 50%. But remember, it's just a heuristic. It's just a very rough estimate used almost exclusively in Silicon Valley. You know, so people are saying, oh my god, this thing to sold for
two times revenue. But when you actually look at it on a look through basis, probably sold for maybe 30 times free cash flow, I don't think it's easy to get it to 400 million in EBITDA. I think if it was the board would have done that, I'm, you know, we're involved in some of these companies. Once they slow down, the company morale goes to hell. Turn over among your customers, you know, begins to spike. It starts to feed on itself. So I think it's still to go to work every day.
“Brad, what do you need to keep? What do you need to keep? Because it's very tricky.”
I don't know the core product and what's happening in terms of turnover in the core product, David. But my hunch is that the core product is started to really fizzle as the advances in the core product is slowed down. You're seeing a bunch of churn out of it on the product side. And now people are saying, listen, it's almost impossible for a software company today to keep any decent sales people to keep any different decent product development people because they all want to go
work on AI. Agreed. So you don't need them for this product. I mean, the market is being efficient. I mean, look, this is where I think bending spoons has an advantage that the company's board and founders wouldn't have, which is they already have an infrastructure, right? They have a
Core team at bending spoons that's managing now, I don't know, dozens of thes...
they can plug this in. I think AI in a way makes their job easier because in the past, the reason
why you couldn't eliminate like all of the talent the infrastructure is because you need the institutional memory. You need a people who knew the code base. Now AI can learn the code base instantly. That's interesting inside. And so yeah, so the change is easier with AI.
“I think maintenance mode becomes a way easier with AI because you don't need the historical”
knowledge anymore. The AI can go in and sort of reconstitute that that historical knowledge. Let me get you in here, Friedberg. If I may, when we look at the lessons from peak syrup and sass, and then we look at, you know, this moment in time, the surging AI market, any parallels that we might find here or lessons between the two between Zirp and AI. The Zirp sass era, we had a lot of very high valuations, a lot of enthusiasm, a lot of suspending disbelief.
We're here in the AI era. We've just talked about the price of compute and all these companies being out of 100x. It's a kind of a software question for you. No, this is a very different paradigm. The AI capex build out and model training, which is where the predominance of the capital is flowing, is not about some high multiple on revenue, which is where capital was flowing into sass. It's like, oh, you get a 20x multiple, turn a dollar into 20. That's great. Let's
do it all day long. This is a very different structure and strategy and capital allocation process. So, I don't think that I would look at them as being linked. It was a horrible question to me on as I was letting you hit it out of the park. Look, I mean, obviously sass companies were overvalued during the Zirp era for two reasons. One is that we had artificially low interest rates. So, we had a kind of a speculative asset super bubble. But the other is that people were treating
these things like guaranteed annuities and actually growing annuities. They'd look at it and see, oh, 120% net dollar attention. So, this thing will just grow 20% year over year forever as a base case, right? And they were then price that way. But what we've seen with AI is obviously there's disruption. And you can't, to Brad said, I'm sure they're seeing elevated turn right now and it's not an annuity. Things can change. So, obviously now these things are trading at a much
greater discount. All of that being said, let me just say, I don't think you can extrapolate
“to the entire sass space based on this one company air table. I think there's some things”
about air table that make it very different than, I don't know, let's say a sales force or a
workday is, you know, air table is always a little bit of a quirky product. I remember at the peak
hype for this company. People were saying like, oh, this is like a new Excel or a new Google cheese cheats. It's really soft. Often. Yeah. Yeah. It was basically a spreadsheet for words. That's how people were we're viewing it. Is this like this new kind of spreadsheet for words as opposed to numbers? And it never achieved that kind of promise. It never achieved that kind of ubiquity. People understand how to use spreadsheets. Everyone uses them. Air table never got to that point.
Most people still don't know what air table is. Again, it had its dedicated fans, but it was a hard product to explain to people when do you use it? It had a cult volume. It's not a good volume, but it never, it never achieved that sort of level of acceptance. It was never self-explanatory.
“In terms of why you should use it, what the use cases are, they never were able to”
kind of get the market right because of that. And to be honest, if you look at cloud co-work,
complexity computer agents, those things are now doing what air table did. So it never carved out
I think in niche where it was super clear when you were always supposed to use air table. And really it was part of this hodgepodge of this grab bag, you could say of no code tools. This is the category was put in. And no code has to be the most impacted, the most disrupted area of SaaS right now because I mean, what is cloud code really good at? I mean, that's the ultimate. It's no cloud load, lovable cloud code. Yeah. I mean, that's what it's worth. Yeah, the thing with air table or
retool things like this is it's true. You didn't need to be a coder to use it, but you had to learn how to use air table. You had to learn how to use retool all these. It was kind of these alternative programming languages in a way. And you just don't need to learn any of that anymore. I mean, you use cloud and you just tell it what you wanted to create. And so, you know, if you do want to create some sort of new dashboard, some sort of, I don't know, like a verbal spreadsheet or whatever,
you just tell cloud what you want. You don't have this learning curve. Look, all this has been impacted right now. But this has got to be the most impacted area. So I don't know that you can totally extrapolate based on what's happening to air table. I don't necessarily think that you want to replace your CRM, your ERP, your HR system with something that's been vibed coded. You want
The certainty, you know, for anything that involves compliance.
Sachs, made, I don't, do you use like a portfolio off the shelf, SaaS tool for managing crafts, like, uh, portfolios and everything? Well, we, we've I've coded something actually. So yeah, we just did the same too. Yeah. So my team just belt something that is so mind-blowing
that to buy with off the shelf software would have been a quarter million dollars in software
and like a million dollars in integration over two or three years. And we built it in a month. And now we have complete insight into the whole portfolio, the competitive set, the founders, everything going on. Keep in mind that one of the reasons why Leah pulled got blown out. Okay. I mean, it is because he bet on the SaaS apocalypse. Remember, it wasn't just that he was super long these chips stocks that had a correction. Oh, is that right? He was short. He was short.
Adobe and a whole bunch of other SaaS companies. And those trades also move the wrong way on him. So again, I just think that it's painting with two broader brush to say that all of SaaS is going to get obliterated here. Yeah. And there was a really good post about this. Let me just quote from this where they said, nobody buys Microsoft because Microsoft writes the best code. They buy Microsoft because Microsoft is the rail that everything else runs on. Active directories where your employee
identities live, Excel is where your board decks numbers come from, teams is where the compliance recorded conversation happens. Azure holds a Fed ramp high authorization and Department of Defense impact level five clearance, which means the defense contractor cannot casually swap it out for something cheaper and so on down the line. So there's a lot of really good compliance reasons. Why if you're a large enterprise, you're not going to want to spend tens of millions of dollars ripping
out something that costs you a million dollars a year. That just doesn't make sense. And I noticed
that many off just tweeted five minutes ago that 15 out of 15 cabinet agencies run on sales force. Look, the government is not going to rip and replace it. So look, it not all SaaS is equal in this dimension. I just want some figment. I just think at some of these SaaS companies with great
“founders who are in and for the long term and they have like passionate user bases, I think they”
will make the jump to AI first products and I put figment in that bucket. Just to wrap this, this actually lists, IGVs up 20 percent in the last six months, sub 20 percent in the last five years explained IGV. So the high growth software stock index, snowflakes 88 percent in the last six months. That's an IGVs at an ETF of IGV as an ETF of gross software companies. So to to David's point, there was a panic about software companies, there was a big tradeout. You know, honestly they
performed pretty well and as he mentioned in the month of July, they were up when a lot of the semi-conductor AI stocks were down and some of these companies, data breaks, snowflake, clickhouse, et cetera are doing extraordinarily well as I just mentioned snowflakes up 90 percent in the last six months, which puts it in the same category as the semi-conductor AI stock. So to David's point, you can't throw him on the same bucket, but I do think that for these no code,
a lot of these applications software companies, they're realizing like, you know, the game is up, sell the company, get what you can get, you know, importantly here in the air table story, all the late stage investors, right? We passed on this in the last three funding rounds,
“right, which I think were at $2 billion, $5 billion in $11 billion, but all those late stage”
investors, which were the most venerable of growth firms, they all got their money back. And the early stage investors ended up making a lot. So if this is a failure, this is a pretty good failure for so if you're happy. This is one of the points that was made at that time, which is, hey, this is a strong enough company and team and revenue base that if we just get our money back with the optionality, hey, maybe this would be a good investment, you could say the same thing
about some AI bet. Well, this is one of those cases where the liquidation preference actually mattered, you know, absolutely, it doesn't matter, but they don't have a strict money here. My understanding is this wasn't like they had like a 7% interest rate, or they didn't have like a participating preferred, where you get two times your money back. And then they do the trade, does anybody know because I looked deeply into the market, and I think that net of cash, they may have come in
a little bit last, the total cash raised, but it seemed like everybody got made whole. Yeah. But if they had the, I guess, ax, we live through moments in time where companies had to guarantee a 1x, right? You know, another 1x liquidation preference is standard. It just means you get your money back for other people start to profit, which is appropriate.
“But both of these interest rates were taken out, right, of these deals. I think during”
months of the standard terms, you know, what's known as clean terms is this is a simple 1x liquidation preference. Right. The preferred just gets their money back before the common starts to participate in a successful sale of the company. That just makes sense, right? Yeah,
but we're not anticipating preferred is the double debt, right? Yeah, and look, we've never done
That, you know, we believe in clean terms.
it doesn't make sense for some people in the cap table to be making money while other people are losing money. Yeah. It just doesn't make sense, right? That's just a transfer of value from some people in the cap table to other people in the cap table. So the standard thing you do is you make sure that the investors get paid back and then everybody is participating in the upside. Okay, fourth story here, China is training on U.S. data from U.S. providers, Forbes,
published an investigation called these American startups are making China's AI smarter,
“and I think this relates to a lot of your work in the early part of the administration's facts.”
They claim U.S. data labeling startups are selling valuable training data to Chinese labs, which in turn is helping them catch up with the U.S. frontier ones to start up surge AI in
America or are both valued at over 20 billion dollars. They sell training data sets to people
like opening AI inthropic federal agencies. They all sell the same data sets to top Chinese AI companies according to this report like Tencent by Tencent. I'll be about the moonshot, etc. Top six AI labs in China according to this report are spending $500 million a year buying what Forbes calls secret sauce, PhD written content, reinforcement learning, knowledge pipelines, all that kind of great stuff. I have investments in a couple of these companies including
micro one, the founder of micro one, didn't participate in selling to China. He made that decision sex. What do you think here about this new wrinkle in terms of really the secret sauce behind a lot of these models is the data. We've run out of open data on the web, obviously. We talked last week about the books being having the spines taken off of them and scanned in. I mean, people are looking for data, micro one, all these companies are providing it. Should they be providing
the same data and selling it to Chinese open source companies or not? Well, look, I think we got to decide what our objective is here. Are we trying to just get in like a full-blown economic war with China? Are we just trying to prevent all of our companies from doing business over there? If that's our objective, then you can take that position. Historically, the rules have been that you want to be careful about technology transfer of technology that has a dual use, right?
That it has a military application. My sense of data is that it's largely commodity. I mean,
data labeling certainly is. If you basically tell them that they can't use data labeling,
I guarantee you there's no shortage of labor in China that they can use to do the data labeling. In fact, they probably are. What I'm saying is there's a lot of ways to get this data. So, look, if we basically ban these companies from selling to China, we should expect reciprocal actions taken by China to ban companies over there selling to us, maybe rare earths. These two countries are not completely independent of each other. By the way, I want us to be as independent and
sovereign as possible. I don't want to have any dependence. No dependencies. But we still,
“at this moment in time, do you have some dependencies? So, I think you have to ask the question”
is this data really proprietary? Does it? Does it have a military application? Yeah. I don't think it has military. It's definitely not data labeling. This is like hiring PhDs, hiring super professionals to, you know, create unique data set. So it's trying to can do that too. And I guarantee you they are. I don't think this is going to give us a decisive advantage in the AI race. It's going to annoy. It's going to create annoyance. It's going to create
friction. And how bad you want our relationship with them to be. Do you want to risk starting another trade war? Look, I'm not against restrictions when I think they're going to hack a punch.
For example, I'm really glad that the first term administration limited the export of UV
lithography machines to China. You know, that was all way back. I think in 2019. So that was a
“really important decision. And so look, I think targeted strategic controls make sense. I would just”
make sure that this one actually meets that bar. Brad, any thoughts here on this open source catch up the data being sold to China in our adversaries? Are you concerned about these open source models and then us providing data to them? First, you know, I'm an absolute agreement with David that we want maximum competition. As we sit here today, the U.S. is winning. We talked about it at the start of frontier labs are winning. Our open source is winning. And we have fairly limited
regulations, right? She's coming here in September in a bilateral meeting to meet with the president. We're advancing relations on a variety of fronts. So I think everything looks good and you want to continue down that path. With that said, I will tell you that this will irritate people in Washington who feel that this along with distillation and other things could be the exported
Chips all of which at a certain level makes sense caused people to wonder whe...
it too easy on the Chinese labs to catch up with American labs, you know, in the race to frontier
“intelligence. So, you know, it's a type of story, Jason, that I think will continue to muddy the”
waters that will continue to be monitored. The reason I don't think it will cause us to change our stance with respect to China is because we're winning. But if the president asks his advisors, you know, one of these days, six months down the line, are we winning against China? And all of the sudden he gets a response, no, we're no longer winning, they caught up, they passed us, etc. Then these things will get a lot more scrutiny than they're getting today. I think the
only reason they pass a monster today is because we're still leading the race. I got to say using Kimmy and Quinn and, you know, GLM-52 for the last 60 days, my Lord, these things are good. And I don't think it's very patriotic to be giving them an advantage. I wouldn't do it. I'm glad the company. Sorry, what's the advantage? What's the data set that you you're worried about? That's so proprietary. Any of these data sets are created by experts here in America who are given
like the queries that have errors in them. So when you give them, you know, a thumbs down to a query. That's highly technical. It could be code. It could be biology and science. These are, you know, PhDs going in there and putting in the latest and greatest content and then verifying it,
“double verifying it. And that's why we're getting better and better results out of the LLMs.”
So essentially, you're just helping them catch up. And this could be a big advantage for America. If we were in sending it there, I think a big reason these models are getting better is because data is being leaked to them. But what makes you think that China can't do this? They have tons of PhDs over there. They would have to hire. No, no. If they were to do it at this scale,
they would need to hire the best and brightest scientists and experts in the West. So basically,
all the knowledge of the West is being, you know, put into packages for our LLMs to get better. They're sending those same packages and reselling them to Chinese companies, which means they catch up just as quick. I think it's a big part of why they're catching up. In line with distillation, you know, it's really very similar process. Look, if there's something truly proprietary here, I don't want us to sell our secret sauce to China. So, you know,
I'd have to look into that and see, like, is there some real secret sauce here? But this idea that it would seriously disadvantage China. You know, they're graduating more math and science graduates every year than the rest of the world combined. I mean, they don't have a shortage of smart people's specialties. Yeah, and we're graduating some checking them out of the country as the other problem we've got to get that fixed. Well, it's like
this is a lot of different issues here. I don't know. I mean, you want to conflate. But this idea that they can't, but this idea that they can't recreate those data sets. I mean, look, if there's something truly proprietary here, if it has a dual use, if it's military-related, but I don't know
“that that's what this is. Well, they're all proprietary. It might design, but I don't know about the”
dual use because I don't have the data sets here. All right, folks. That's another amazing episode
of you're all in podcast. Thank you so much, Brad, for joining us, Chema. Good luck on your world tour. I hope you're enjoying a little rest and good luck trying to buy a white turtle neck disease and they're sold out every week. So go to the all-in.com store all-in.com/store. We have 1,000 signature Chema autographed. White sweaters coming. You can sign up and advance for them. All proceeds go to charity in my charity. A munchbox. Yeah, fun. All right, we'll see you
next week everybody, bye-bye. [Music] We should all just get a room and just have one big huge or two because they're all just a little stuff. It's like the sexual tension that we just need to release out. [Music]
