Why AI Demand Is Outrunning Compute Supply Transcript, AI Summary & Key Points

when the history of the 21st century is written, you know, there was like the Victorian age. I think this will be like the age of Elon and Jensen because they are fundamentally altering the fabric of human society and civilization. >> What happens if there's like a massive supply shortage? >> Every time you've had a real profound new technology, you get a bubble because the markets get really excited and they get ahead of themselves.

Things get overvalued. That overvaluation leads to an overbuild. One of the things that I think has been correct but ineffective is this idea that we need to stay ahead of China. >> You're opposed to data centers. Well, you know what? It's probably the best thing that has ever happened to workingass Americans. We are re-industrializing America and it's awesome.

>> Assume that you're right. There's not a physics reason why this can't work. >> An increasing fraction of the world's compute is going to be in orbit. This sounds crazy, but asteroid mining is going to be a very real thing. It has more gold, silver, platinum, every precious metal in it that exists in the earth's crust. >> Every LP conversation that we have starts with like, how's this all going to go wrong?

>> Gavin, uh, you've been out here hanging out on the West Coast over the summer and you've been talking about the fact that you're like trying to find someone to make you to give you like a a bearish case, like to make your sentiment more negative. Um, have you found anybody? >> No. And I ask everyone, my standard question is, can you tell me one quantitative data point in your business that's getting worse?

Just one. That's my standard question. And it's at least in July and August, I haven't been able to find a single person. Now, if we're being honest, you know, Anthropic is um, you know, in a quiet period, so maybe they've slowed down a little bit, but I do think the rest of the world has accelerated. You know, OpenAI is clearly accelerated. Open source, I think, has accelerated more.

And then I do think Grock, particularly after Grockbot, has had a pretty experience, has had a pretty dramatic acceleration. And so AI overall, it accelerated in July. It accelerated in August, and it can't keep accelerating forever, but it's just kind of wild that, you know, public stocks have kind of fallen out of bed over the last, you know, two months.

And I mean, you know, it's uh that, you know, they you can you can drown crossing a river that's on average 2 ft deep. And so, you know, there's not a lot of action at the index level, >> right? >> But some of these AI names are in pretty significant draw downs. And they b they bounced a little bit um in August, but still pretty big draw downs and things are broadly accelerating.

>> Yeah. >> It's um you know, our friend Eric Fishery did a podcast with Patrick Oanessy and he said maybe everyone wins. >> Yeah. you know, Anthropic wins, OpenAI wins, SpaceX wins, Meta wins. Um, you know, Google wins by selling a lot of TPUs. Um, open source wins, NeoClouds win, inf you know, inference cloud, uh, the inference clouds win on top of the Neoclouds.

Um, >> applications win. >> Yeah. Every Yeah. And that kind probably maybe not all applications applications that I think execute well and navigate this but that feels like a very possible scenario to me and there's so much zero someum thinking in the world and by the way on anthropic what is my hypothesis would be if you're anthropic one I think they probably tred up and cleaned up some accounting >> yes definitely >> you would you'd rather do Yes.

>> So you rebased and now you're comparable to OpenAI. >> Yeah. In terms of revenue added, like in terms of the definition and now I think kind of revenue added. >> Exactly. So you kind of rebased and then they you know they did their testing the waters. Um and then you know I would hypothesize because they've executed well probably the next disclosure is a reaceleration.

And then there's always this kind of funny game between the frontier model companies. They always have more advanced checkpoints. Anthropic is clearly waiting for OpenAI to release Astra. >> Yes. >> And then it's like the next >> the next day. >> Here's Fable 5.1. >> Yes. Exactly. >> Magically and just happened to be available several hours after Astra.

>> Yeah. >> So I think they're being thoughtful um and you know heading heading into this IPO and everyone is shooting at them. >> Yes. everybody's shooting at them and they're in a quiet period so they can't really shoot back. Um, and so it's, you know, there's a lot of gamesmanship, but I do think having OpenAI anthropic be public companies is going to be helpful for the market just cuz it's, you know, it's such a uh powerful force and a lot of public investors, you know, you hear, oh, you know, Sarah Frier said this

at an all hands meeting and it's on the cover Wall Street Journal. Okay, we're going to put that into our model. >> Yeah. And it's just a lot I think it'll be better for them to be public. I am a little um you know Anthropic is now in their culture interviews saying how would you feel if the equity went to zero? >> Yeah. >> Because we're looking for people who are mission aligned.

>> Yeah. Mission not mercenary. Yeah. >> And and that's great. We we want we want missionaries, but we also want people to make money. And at the end of the day, you can't afford the compute you want for your mission if you go if the equity goes to zero. Like I'm no expert, but I'm pretty sure on that >> in that I do think they are >> they're like the accidental enterprise company.

>> Oh, for sure. Oh, yeah. They're kind of like the accidental everything. >> Enterprise is just a byproduct of like the the the mission, the objective at the end. Yeah. Whereas I think open eye is a little more commercial and obviously SpaceX a little more commercial. But all of these companies like let's just let's let's just say um let's just say they have 10 gigs of power and they're allocating eight to inference and let's just say they're monetizing that inference at you know whatever um you know 60 60 billion a

year. Um, so $480 billion a year in revenue, >> which is like a on a revenue payback basis would be like a one-year payback on a revenue basis, not a gross profit basis. >> Yeah. On a revenue basis. Yeah. Yeah. >> Um, and I've tried to use conservative numbers. You know, people seem to think and open are both monetizing at hundred billion dollars a gigawatt today.

>> Yeah. Let's say they have a big research breakthrough and they decide, "Wow, it is to our long-term advantage to go from eight gigs allocated to inference, two gigs allocated to training to 8 gigs on training and then your revenue just went from 480 to 120." And I think they your annualized revenue and I actually think they would do that >> make that decision.

>> Yeah. And this is just something that like public markets are going to really have to get used to. >> Yeah. >> It as you say, open AI may be a different animal. And I do think like the realities, you know, everybody everybody has these ideals about how they're going to manage their business, then they go public and the stock is volatile and it really impacts, you know, employee morale, recruiting, retention.

So, I'd be surprised if they did such a dramatic cut, but a lot of the revenue is kind of under their control based on what checkpoint they release. >> Yeah. >> Where they price um along this, you know, kind of paro curve and then how much they allocate between training and inference. So, it's just it's going to be, you know, Meta and Google and these kind of internet companies.

It was just it was pretty smooth fundamentally even if the stocks were volatile. >> Well, there was no like massive trade-off they had to make in terms of the cost or infrastructure to serve revenue side. Like they were totally separate >> 100%. >> Yeah. It's it's fascinating. Um so, you know, if you go back to Eric's point of like it's all going to work like I actually think that's a great point.

Like I I I describe it differently. I've had this conversation with LPs a lot cuz every LP conversation that we have it's probably the same for you starts with like how's this all going to go wrong >> and it's like what's what's going to crash and I'm like this is the this is the and like oh are the are the large models screwed or the labs screwed because of open source and I'm like this is this is this is all wrong like this is not an or thing it's an and thing right like this is an and thing um Frontier is going to

work really well like N minus one models are going to work really well open source is going to work really well um there's going to be a bunch of application companies that work really well. Like the clouds are probably going to be fine. They're probably going to work really well. >> Like the five lab companies are probably going to do really well. >> Yeah.

And Nvidia is at the center of all of it. >> Yes. Yes. They're probably going to do pretty well. >> Yeah. The last um 26 years have taught me not to bet against Jensen. >> Yeah. He's he's he's in a pretty good position here. Um I want to come back to that. The the point that you made about training verse inference is an interesting one. It seems to me like the labs will decide to take all incremental profits and probably much more than their profits and invest them in training for a long period of time.

Would you think that's fair? Like this is very different than like the clouds, you know, cuz like the the cloud like the internet companies and the clouds, they just end up being supply demand driven and they generate tons of profit and they can still grow a certain amount like but they don't have some maybe with the exception of Meta like some big long-term bet that's like a multi-year payoff.

>> Yeah, I think it's important to kind of be precise. They I for sure I don't think they will generate free cash flow anytime soon. I think they're going to generate a lot of operating cash flow and then they'll use that to buy a lot of, you know, GPUs, um, XPUs, whatever, whatever we're going to call them. Um, or maybe they subsidize heavily. Like we do know that that's happening at the labs.

>> Subsidize what heavily >> their first party products. So token consumption of their first party products. So like they're doing all this research and they're spending a lot on data on compute >> and the first products that are like a heavy subsidy >> products today, right? >> Yeah. So it's 8 gigs of inference and two gigs is for internal research and then you know two gigs is actually training.

>> Yeah. Exactly. >> Um and you know including probably the inference that goes into post- training. >> Yeah. I don't I I think given the belief systems that they all seem to have about scaling laws which continue to hold I don't think any of them are going to be that focused on generating free cash flow and you've seen right we saw Satcha blink. >> Yes.

>> And Satcha really regrets that I think. >> Yeah. Yeah. um you know he kind of blinked I think it was last year you know he gave that great interview for Davos and they asked him about all the capex and he said I know I'm good for my 80 billion >> right >> and and I think they blinked a little they slowed down they regret that and then Daario famously he went on a podcast and he made and he said listen some people are being super irresponsible with their spending and it's a hard decision because if you don't spend

enough you could lose a lot of shares But if you spend too much, you could go bankrupt. And like those are both bad things, but bankruptcy is worse than losing shares. So I'd rather be conservative. And he was conservative. And OpenAI was aggressive. And now OpenAI is back in the game. >> And SpaceX was aggressive. >> And SpaceX was aggressive. >> And so, you know, like there are clear high ROIs on those independent of supply demand mismatches that are happening.

Like clearly that seems to be the right decision short-term and long-term. >> Yeah, absolutely. I mean, we we calculate, you know, Nebius um and Corweave both gave some interesting disclosures, but you can kind of get to a 9 to 10 month payback for Nebius because you know, okay, you bring on a gig, it costs 50 billion. You get you can get an upfront payment for 50 to 60% of that for customers.

Yeah. >> So now, you know, you're talking about 25 or 30 billion and then you can monetize it if you put it into the spot market. >> The spot. Yeah. at a spot spot paybacks are probably much faster than nine or 10 bucks. >> Yeah, you got to assume like a smoothed out level like two two bucks, three bucks even with that. It's very very Now you can get like five bucks or eight bucks and Yeah.

>> And then SpaceX cuz they build these really big clusters and and I think at a really important point is they bring them on fast. >> Yes. >> They have an even faster payback and they can monetize at you know higher. I I have tried to shift um you know to think of pricing and you know per megawatt rather than per GPU because it seems like it's where where the world >> world is but like SpaceX the payback feels well inside of that.

>> Yes. >> And I just in my career as an investor there haven't been that many opportunities where you have companies that could deploy tens hundreds of billions of dollars and get sub one-year paybacks. >> Yes. And it's kind of crazy. And then also like we should also talk if particularly if you're buying Nvidia GPUs to a lesser extent TPUs, you can finance these.

>> Yes. >> And there's a very sophisticated, you know, >> Yeah. very low cost of capital to finance them today. >> Yeah. And everybody's, you know, worked up about, you know, circularity and it's like, well, I don't know. Um, I know a lot of smart people who work at Blackstone and KKR and Apollo and they're the ones that are financing >> the ones who are financing it at a relatively low cost >> at a relatively low cost.

And I think one reason that's happening is useful lives just keep getting extended and has these models get better and better and better and the ROI on token spend goes up, you know, the monetiz monetization rate per gigawatt goes up. So, I mean, the true equity payback like might be way inside of a year. >> Yeah. Exactly. Exactly. Yeah. And look, there's a case you could make that the prices actually of all the stuff go up, which could make the the supply side economics even more compelling, right?

Like, you know, so on the supply side, like that's the dynamic today. Like, it just is what it is. Like, there's a ton of data points out there that paybacks are within a year. >> Yep. Um I think it's actually interesting to think about the demand side too because the knock would be well in all these cycles you get some overbuild and then that you know destroys the economics of the supply side.

The demand side today like what are we monet like the monetization of these companies which are doing call it 80 billion of revenue or something in that direction um is on the back of what like 30 million actual heavy paying users like re getting real value. I'm talking about like developers like >> I might take the under on 30 million >> so call it yeah actually what we see inside our companies is you know obviously there's a power law in which companies are spending a lot on tokens like old banks are probably

spending 1% very techforward companies are spending high single digits but if you actually look at the sort of the the power law of what's happening of the actual engineers in those companies the highest spending engineers are spending 10 or sometimes is 100x more than the median engineer. And so, yeah, your 30 million is probably way overstated. It might be sub 10.

And so, there's this question of like where are we at in diffusion? There's one and a half billion knowledge workers. Like, it feels like we're nowhere on the demand side and we're massively supply constrained. >> And what are I'm just curious across the A6Z portfolio if what are your best companies spending on tokens per month relative to human compensation?

What rough range? >> Oh, high single digits, some at 10%, like some of the very AI native ones like 10% plus. And so, you know, and and then old economy companies are spending the ones that are probably doing a good job like 1%. So, it feels to me like when I look at the supply demand characteristics, it's like supply stuff people say, is that sustainable?

Well, like when you pair it with the demand stuff, I it feels it feels specific. Like there could be things that disappoint us in terms of like diffusion into the real economy, but it feels like over a 10-year stretch, like we're nowhere. >> Yeah. Absolutely nowhere. And I just >> my So at a trade is our internal token consumption has gone up 100x from the month of March.

March through August. 100x our token spend. And we just got access to uh Grockbot Enterprise and with two people using it like it looks like it token spend might 10 or 20x in a month. >> Yes. >> From August. >> Yes. >> Like like I >> But but it's actually extremely valuable. Like we have some heavy Grockbot users here and like it is very productive use.

Like this is not like wasteful tokens, but >> yeah, I was and and listen like I I try super hard. I you know I always when I use AI, I just remember when my parents like I was trying to get them to shift to an iPhone and an iPad and like you know get them used to it and like you know and they did a good job. I give them loads of credit and but you know I'm 50 years old you know like how old are you David?

>> 42. 42 and you see these like 23-y old kids and just the way they use AI, they're just fluent and native in it. I just feel like maybe in a way that no matter how hard I try, I will never be and I'm trying really hard. But, you know, like we got cloud code, I try I you know, I built some stuff, did some cool stuff and in like I don't know three minutes of type creating Grock bots, I had much better versions of everything I created, you know.

You know, so I went on this Patrick Oannessy pod podcast like 5 months ago and I said, you know, like I love having a podcast summarizer. Everybody's like, "How'd you do it?" I was like, "Well, just use AI and do it." >> Yes. Pretty simple. >> It takes 10 seconds and Grockbot. >> Yes. >> It's amazing and it's so good. >> Yeah. >> And then, you know, a Substack summarizer, an X summarizer, um an Xs sentiment tracker for topics and stocks.

>> Yeah. And like that all of those would have taken me I don't know hours working with cloud code and they each took 7 to 12 seconds with Grockbot and it's better. >> Yeah. >> So to to me Grockbot does feel like another um at least for me like kind of chat GPT moment because Claude code >> like I can see in the data was it was powerful. I did some really cool stuff with it that was like empowering and this is neat.

>> Um >> you know like family calendar apps, things like that. >> Yeah. >> Um but this is just 10 seconds and it's way better than what I was able to do. >> Yeah. Yeah. Yeah, the cloud code thing like was obviously the shift in coding and you know our our most sophisticated engineers you know were doing whatever 20% of their code you know with with with AI to like you know whatever 90 plus% and so now I think everything you described in what you built with cloud code or codec >> is still kind of reactive >> in a way

right like it's it's still you know it's like summarizers yeah preparation it's all like knowledge enhancing which is part of your job, but it's not actually doing the work for you. >> Yeah. And now you have a Groc bot that says, "What are the recommended actions?" Yes. Exactly. >> Based on everything the other bots have learned today. >> Yeah. >> What recommendations do you have for me today?

And that for sure is like >> and it it was so easy to build. Um I now have it. So I'm I'm like horse racing all these which is like I have uh uh Crockbot doing it, Codeex doing it. All the like action taking for just I want to know >> make me better at my job. Look at everything I do. Give me give me recommended automations you can do. I have Town doing it as well which is one of our companies very good at it.

>> Um but and we're like kind of on the bleeding edge of trying to do this stuff. >> Just wait till everyone does this stuff >> and then and then when we actually click like yes go just automate this. >> Yeah. It feels like that's sort of endless token >> and but I do we should acknowledge like the the history of financial markets, >> you know, dating kind of back to like the South Sea bubble is whenever you get this transformational new technology.

Um, I actually went on a podcast, I said I thought the South Sea bubble was connected to like the invention of longitude and the ability to sell. Turns out it was not. It was just it was kind of like a more of a tulip episode. But like every time you've had a real, you know, profound new technology, you know, whether it's the automobile, the TV, the radio, internet, the PC, um, railroads, >> steel mills, you get a bubble because the markets get really excited >> and they get ahead of themselves.

Things get overvalued. That overval overvaluation leads to an overbuild. And then particularly if you're funding it with debt um and and even today a majority of this is still being funded out of operating cash flow which I think is really helpful. Um you know debt funded built buildouts they demand immediate ROI not an ROI in three years. >> Yeah. You can't be off in the time.

You can't be off off on the time, but I'm just more, you know, like I um, you know, I talked to Jazz about how Watson wafers Jazz I guess and Patrick Watson wafers are these fundamental constraints and just that the buildout is so big and we're so early that we are it's like impacting the raw productive capacity of so many industries. you know, now you know, everybody in everybody in copper, there's like an AI thesis and like we're going to have to like think about it to like fill the, >> you know, if if >> 10% of what

we just talked about comes true, you know, we're in this acute shortage with, I don't know, several million people are driving a crazy global compute shortage. What happens when that's 500 million? And you know, how many copper mines do we need to build to like support this? Yeah, >> it's kind of a wild thought. And so like these fundamental constraints, I think, are slowing us down.

>> And I >> and I think that's good. I actually think that's good for society. And I would now say rates and regulation, you know, real rates are going up. Yes. >> And it just is what it is, which makes sense because we're like investing a lot. So it makes sense um that real rates are going up. And then regulation, man. It's it is like I'm kind of shocked at what's happening in America.

>> We're in a really bad place. >> Yeah. And just, you know, I had this exchange with with um Schulto for from Anthropic and and and Daario on X last weekend. You know, Daario said, "Hey, I don't think I've been negative. You know, I've written I've written two essays. One was positive, one was negative." So being 50% negative and particularly when it's like a terrifying negative >> like an existential >> an existential negative everybody might be out of out of a job like that Eleazar Yukowski guy says if we build it

everyone will die and it's like how about if we build it like we're going to cure cancer we're all going to live forever. I thought one of the best things Dario said was like what we need to do is stop talking about curing cancer and actually cure cancer. >> Actually cure cancer and actually make breakthroughs like >> but just somebody like that my favorite line in the Bible is the truth shall set you free.

>> Yes. But the only person who can the only group that can tell the AI industry's truth is the AI industry. They need to just start telling the truth. Hey when we Okay, you're opposed to data centers. Well, you know what? It's probably the best thing that has ever happened to workingclass Americans. >> Yeah, exactly. >> You know, it's like going to college might be significantly NPV negative now because you can go learn how to be an electrician, a plumber, an HVAC tech, and make ungodly amounts of money.

Yeah. >> So, this has been amazing for working-class Americans. We now have a lot of data that particularly with behind the meter power generation, when a data center goes in, it transforms a town. like tax revenue, it doesn't double. It like 10xes and it is re revitalizing all of these like dying small towns all over America. And listen, we're getting we're getting much better at addressing the environ environmental stuff.

Generally, they use natural gas, which is a pretty clean fuel. >> The the water the water consumption thing is totally debunked. It's totally debunked. Yeah. >> It's nothing. It's nothing. So these are like really really really good and they're having a really positive impact on the world. That's without even considering things like curing cancer, but somebody needs to tell that story.

>> It's now and and I think the problem with it now is like the burden of proof is on not curing cancer, but actually delivering some real tangible everyday American benefits beyond using chat, you know, or Grock to like answer your questions or substitute >> for a search engine, right? It it does feel like we're pretty close to that. Um yeah, it does.

And and by the way, like one of the things that I think has been correct but ineffective is this idea that we need to stay ahead of China. >> Like it's like it is true. Like I'm very much like I'm a patriot. Like I believe that. But it's way too abstract. Yeah. The abstract for the average American. Like >> nobody's worried about China invading America.

>> Yeah. Exactly. Like they ocean is really big. >> Yeah. like affordability and like how is this going to change my life for the better or worse, right? And so >> I think there's a pretty immediate impact you could feel like I my favorite is, you know, Lowden County, Virginia, which is like the highest uh highest per capita income uh zip code in the US or county in the US >> and it has the highest density of data centers.

>> Yeah. >> And they and they make a tremendous amount of tax revenue from data centers. Like we should we should do this everywhere. >> Yeah. It was actually very funny. a someone very opposed to data centers said, "Oh, you're for data centers. I'd like to see them put in the highest income zip code and the highest, you know, income county." And they're like, "Actually, the highest income zip code in America and the highest income county has the highest per capita concentration of data centers."

So, we've done that >> and it worked out really well. >> Yeah. But, you know, hey, don't bother me with the details. I'm on to my next talking point. >> That's good. That's good. >> And all those talking points, it's tragic. Like there is an organized CCP funded campaign. I think against data centers here in America like I think a lot of it gets laundered through Tik Tok and it's just tragic because the other thing that's happening is this is re-industrializing America.

The combination of having the straight of foremost closed which is amazing for America. You know natural gas here is two or three bucks. >> It's now 25 bucks >> in Europe and Asia or 20 bucks or whatever it is. And natural gas is an you know important input to the cost of electricity which is an important input to almost all manufacturing processes.

And so we have a huge cost advantage for that basic input now. >> And you have that happening and you have this kind of data center boom happening. We are re-industrializing America. And it's awesome. This is what everyone in both parties has wanted for a long time. >> Yeah. Exactly. >> Like bring industry back. small towns that were left behind by the steel mills closing.

Well, data centers are bringing them back. >> Yeah. But somebody has to tell that truth. I mean, I try to do it on every podcast, but like I'm just a dude. >> Yeah. And like your audience is the tech audience that that already believes you're you're preaching the choir, if you will. Um, but yeah, the story the story I met Meta is probably doing the best job of telling that story, I would think.

>> Yeah, it seems. >> You know, and I think one reason it's really wired into Meta's DNA. So, one of the first things they started doing as a public company I don't remember if it was on their first attorney's call, but Cheryl would run through Cheryl Samberg would run through 10 or 15 very specific small businesses that had started using Meta's advertising products and the impact it had on that business.

>> Yeah. you know, this cake bakery in De Moines started, you know, worked with Meta and, you know, it was it was it was two women who were single mothers working by themselves and now they have 15 locations. They employ 50 people. >> Yeah. >> And this has been amazing for De Moine and it's been transformative for them. >> Yeah. >> And they would just run through that every time.

And and I do think the entire AI industry um like I'd love to see, you know, everybody SpaceX, Enthropic, OpenAI, Google, Meta say, "Hey, >> here are real businesses and real Americans and like either name the business or get permission to if you can name the American or anonymize it." This is a really positive thing it did it it had on their life. >> Already very tangible.

Yeah. >> Yeah. Same. Nvidia, AMD, Broadcom, all of them. >> Yeah. just run through specifics because the truth will set you free but only if you tell it. >> Yeah. Exactly. Exactly. Yeah. So it seems more likely than given that fact pattern if you go back to just the sort of macro situation that we're in that we we underbuild on the supply side. >> Oh yeah.

For for like through 28. And and by the way like there's no capacity available with all the forecast builds that will happen through 28 which are probably now going to be delayed given the political dynamics they have. So, um, >> everybody's worried about over supply. I'm like more worried about >> massive massively under supply. Yeah, exactly. Which, which Okay.

So, then if that's the scenario, like you could see a scenario where you see, you know, big price increases actually to access the intelligence. Yeah. >> Which is the opposite direction of where everybody thinks this is going to go. >> Yeah. Well, Dorcash had a wild point. I forget what it was, but he was positing >> um I forget the >> like the cost of a token could go up 10x or something like that.

Yes. Yeah, >> which is crazy, but like we do live in a supply demand world. >> Like it's conceivable if the demand goes massively. And by the way, the whole premise of this that's happening so far is that there's a massive amount of consumer or user surplus being generated, right? So like why do people select the frontier tokens when they could use the cheaper tokens to do most tasks?

There's many reasons why, but like the biggest one is because there's a tremendous amount of surplus even if you're using the frontier tokens, right? Absolutely. And so yeah, what happens if there's like a massive supply shortage? Well, I think that would be the, you know, kind of funny the consequence of like the these like data center degrowthers um may be like real compute inequality where big companies and wealthy people can afford compute and then you know two years from now they'll be on about that and it's like

well that happened because of you. Yeah. >> You know that happened because you wouldn't let us build data centers. >> Yeah. And by the way, we've we've seen this, right? Like the path to a lowcost product delivered to consumers in a mass market is advertising. It takes a long time to build an advertising business. >> Yeah. >> Um as we've seen with all the, you know, consumer internet businesses that we've invested in over the years.

>> Um and so there may be a disconnect in the period where you can't actually offer that. >> Yeah. >> And that would be a terrible outcome. >> That'd be a terrible outcome for the world. Nobody wants that. So we need to build a lot of data centers. >> Yeah. Exactly. Exactly. Yeah. like a compute in inequality like future that's that's not a good that's not a good future for anyone which is another reason open source is so important and just one of the things um you know I you know I had uh Grock make me make me like a

meme of that like three-headed dragon and one of the heads is like kind of confused about like all of the really like stupid >> bearish AI narratives but people have this idea that open- source tokens are free they're And it's like it takes the exact same amount of compute. >> Yeah. >> All else equal to make an open source token as a you know Frontier token for a comparably sized model.

Now there's a lot of nuances there but that's broadly true. >> It's just a question of what are the margins that are charged on top of that. And even then, the Kimmy license, something that I don't think a lot of people appreciate is the Kimmy license stipulates a 30% um share of any revenue. >> Yeah. Yeah. Yeah. >> So like Kimmy has taken a 30% cut of all the revenue generated on its and this is because it's open weights, not open source.

>> Yeah. Exactly. Yeah. >> Yeah. But it's also extremely token hungry too, right? So it's more it's it's far even we're talking on a token basis, but on a task basis, it's far more inefficient. So it's very costly. >> Yeah. And I just always like Jensen, he's a great patriot, great American. Like we're so lucky to have we're lucky to have him and Elon like and I think like you know kind of when the when the history of the 21st centurion 21st century is written you know there was like the Victorian age I think this will

be like the age of Elon and Jensen. >> Yeah. because they have they they are fundamentally altering kind of like the fabric of human society and civilization with AI SpaceX making humanity multilanetary Starlink you know bringing lowcost internet access to the poorest communities in the world which is amazing um which is you know something that people don't talk about but it's like an amazing you know you talked about consumer surplus that is an amazing surplus >> there was never there there was never going to be an

economic case to build internet access in those places because of the cost >> and the willingness to pay and now you could >> without and any incremental internet capacity like is not going to be built in a traditional sense on Earth. It's going to come from space and so like that is a huge that is a huge unlock. I agree. >> It's a good thing but like we're you know we're like you know we should we should all be grateful for them because I do think that you know they're you the they're making the future as exciting and

inspiring as possible. say we are in this supply crunch. Um it's so funny when whenever I talk about SpaceX and it's it's obviously near and dear to both our hearts. Um you know I I say like first of all the orbital data center stuff it's not like big buildings in space like it's helpful to actually think of it's like the size of an airplane. >> People are picturing like the Death Star like or the Pentagon floating around in space.

That's not what it is at all. >> Yeah. It's a It's you know whatever the size of an airplane, right? Rack of 72 whatever chips. >> Yeah. It's it's like five of us standing together is kind of roughly >> is like the wings solar wings. >> Yeah. >> And then you keep it in a suns synchronous orbit. >> So you have the radiator always in the shadow of the rack.

>> That's how you cool it. >> And it's I like I can't it's very hard for me to engage. you know, there's all these people on X and they're like, I am a physics PhD and I this is impossible. Um, and actually there's there's there's a friend who's another investor who actually is a physics PhD who had many um arguments with him and he's like, I am a PhD and this is impossible.

And then he goes to the SpaceX day and you know he talks to the SpaceX engineers. He's like, well, I was wrong. And so like if let's say you're an astrophysics PhD, you are brilliant. You're hanging 100 IQ points on me. Have you thought about this for an hour? Have you thought about it for 10 hours? Have you thought about for five hours? Cuz you have 10,000 of the world's smartest engineers at SpaceX who've thought about this each for hundreds if not thousands of hours.

And the sum of that working with like very sophisticated, you know, engineering tools is it's a solved problem. And in their minds, it's dramatically simpler and easier. >> Yeah. >> Than a Starlink satellite cuz a Starlink has to have the phased arrays and move around. >> I think it's like So, okay. So, assume that you're right. I say it's like physics.

There's not a physics reason why this can't work. Costwise, it seems really imposing, but kind of the history of the Elon companies is the cost curve gets dramatically better. Like when we first invested in SpaceX, you know, Starlink like was not commercially available and like we had all these questions about how the economics would proceed over time.

The same on the launch side, the same with the Model 3. Like I I I just have to think that that will get solved paired with the fact that we're going to have massive under supply self-inflicted on Earth. >> Uh it feels clear to me at a minimum it will be swing capacity. >> Yeah. >> And you know in the fullness of time maybe it will be larger. >> Well no it's really simple like if we use 50 and it is the people the question people should be asking about orbital compute which is the one SpaceX is focused on is Starship

reusability. >> Yes. Because the math is like let's let's just say it's 50 billion a gig and let's just say 35 of that is it. Yep. So that's the same and maybe it grows a little because it's it's going into space. The rest is power, cooling, labor, all sorts of things that you don't need in space because you have the so you have the solar panel and the big radiator.

Um and that call that's 15 billion and that's probably inflationary here on Earth. >> Yeah. Because labor fundamentally feeds into that. We just talked about what's happening to, you know, electrician. Um, >> yeah. Comp. Yeah. >> Yeah. Electrician >> materials are all going to go. >> Yeah. All of it. Yeah. We're going to have Yeah. We're going to run out of co, you know, we're we're the the copper bulls are, you know, focused on like copper shortages.

All of it. >> Yeah. So that 15 billion is inflationary. And so what you have to compare it to is the cost of launch. And with Starship reusability, that goes to under a billion. So the economics just instantly flip. Now, you're always going to train on Earth. There will always be advantages to having, you know, GPUs right next to each other. Like there are, you know, speed of light limitations are a real thing.

Latency matters. So, data centers on Earth, they're not going anywhere. I think they're going to continue to be very, very valuable. But an increasing fraction of the world's compute is going to be in orbit. And you know, Elon said that he and Jensen have co-designed a Reuben rack >> and they're it's gonna launch in the fourth quarter of 27. >> Yeah.

>> And let's just say let's just say he's off by two quarters. >> Yeah. >> I mean, that's that's 2028. >> Yeah. That's still okay. That's pretty soon >> that, you know, as Brad Gersonner says, like nobody's really paying attention to this and it's like kind of happening in plain sight. And it kind of to me solves for something, you know, mids single just billions today, >> which by the way, you know, is like that's just like keeping share constant.

>> Yeah. Exactly. >> You know, of like what's happening with >> not presumably taking any share on on Grockbot. >> Yeah. Yeah. From from three billion. And by the way, man, I would just I'd probably take the over with Grockbot. Yeah. >> I bet it's like >> changing by the day just based on my own usage and the number of people who are hitting their usage limits.

And then you are starting to get from you know Grockbot like hey we're servers are overloaded every once in a while and like they have a lot of compute. Um so it's just like okay you don't want to debate orbital data centers >> no problem. Well like Starlink mobile like they have a pretty clear credible plan >> for how that's going to work and that you know wireless is you know call it another 8 900 billion of revenue that they address.

So your yeah your mobile plus your broadband whatever it's call it like close to two trillion of a market >> and then you have a really rapidly growing AI AR base. >> Yeah. AI AR you've got the cloud you know the sort of the cloud business. >> Yeah. Um so I don't think great you're an orbital computic no problem. It doesn't matter. >> Yeah. Exactly.

>> We don't even need to. We could just look at things that are happening today with terrestrial compute, with cursor, with Grock, with Grockbot. By the way, I think X ads are, you know, we have telemetry. >> They're also growing. >> You know, I would expect at some point you'll have like a Starlink Grockbot um Xadvertising bundle. You know, kind of one of the ways Google built their cloud business as they bundled it with ads and like, hey, we're, you know, maybe you're bundling the ads with AI, but why not do that?

>> Yeah. Yeah. I actually like the AI position that they're in because it's like heads you win, tails you win in the sense that their first party business is growing very fast and they they caught up to the frontier like very quickly. Yeah. >> Um and so they've made the very aggressive compute investments to enable that first party work. >> Um and that's the kind of heads you win and like tails you win.

Say they overbuilt their capacity for what they need for inference or training. they have a very compelling sub six month payback on the compute side um you know with like massive scarcity supply and so I think that's a really good setup >> and there was a bare case that hey okay well in in a in the open AI anth anthropic maximalist view where they're the only two companies and they're designing their own chips then like where what's the room for anyone else well like I don't think they're going to have a reusable

starship and multiple spaceports anytime soon and if the economics of computer such that orbital is where it makes sense increasingly going forward because Starship should be deflationary, you know, terrestrial cooling, you know, power should be inflationary. Well, like even in in a world where they fumble the ball with their first party AI applications, like they do still have >> they're a massive infrastructure business.

>> Yeah. Yeah. I I'm I'm so fired up about the uh the Starbase Louisiana. Uh >> Oh, yeah. >> I can't wait to visit, man. >> So cool. Yes. >> Uh I was reading about it last night and uh yeah, it's sort of like it's now the they now have the infrastructure for you know thousands of launches a year. >> Yeah. And eventually I think you will see like these star bases in multiple places, multiple coasts all over the world.

>> Yeah. >> Like you know at some point you'll probably see one somewhere in the Middle East. You'll see >> you know whatever European country is like the least bureaucratic at the time. You'll see one there. You know, you'll for I think you'll see probably one in, you know, whether it's Japan, South Korea, who knows? >> Yeah. Yeah. Yeah. Yeah. Yeah.

It's pretty exciting. >> Yeah. >> Yeah. The uh the capability to do to call it, you know, whatever 5,000 launches a year, like that feels very futuristic. >> Yeah. I mean, it's wild. And I do think a distinction that um you know, SpaceX really tried to kind of hammer home during their their IPO is there's a difference between reusability and and China.

They did catch kind of a rocket using this um it was actually kind of ironic. It was this kind of juryrigged system of kind of wires. Yeah. >> That had actually been suggested on the SpaceX subreddit. >> Yes. >> Like seven or eight or n or no no it was before they landed the first Falcon. So it's like more than 10 years ago >> and like China's clearly paying close attention to the SpaceX subre subreddit.

But that's very different catching that thing from what they're trying to do with Starship where you know the uh the booster gets caught with the things and then it gets moved and then the Starship gets caught and then it gets stacked, it gets fueled and just sent right back. Yeah. Two a day. Two a day per pad. >> Like those numbers add up pretty fast.

>> And there and I do think I think they're engineering the pads for more than two a day if I >> Yeah. I think that's a conservative I think that's a conservative assumption. Yeah. >> Yeah. Um but I mean >> Yeah. What's the Okay, so SpaceX, like again, you and I have talked a ton about SpaceX. What's like the most futuristic thing that you think about with SpaceX?

Like the 10-year Okay, so you and I were at this conference together and there was this whole debate about um among a small group of public investors of like what's going to be the the first 10 trillion company. And uh I think what you said was like I have no idea, but I know which one's going to be the first 20 trillion dollar company. Uh, so like what's the most futuristic like product or market or technology thing about SpaceX that that you can think of?

>> Look, I mean this sounds crazy, but asteroid mining is going to be a very real thing. We're going to capture, you know, there's asteroid psyche. It has more gold, silver, platinum, you know, every precious metal in it that exists in the Earth's crust. At some point, particularly with Starship, you will be, you know, and we may need that um lunar base to make this happen.

You'll be able to cap capture these asteroids. You'll bring them into a stable kind of geocynchronous orbit over some, you know, Americanowned atal in the middle of the Pacific. Um, you know, no humans within whatever 50 miles. you'll, you know, you can imagine like Optimus robots, you know, um doing doing the work. Yeah. >> Yeah. Doing the work. Um and then, you know, delivery to Earth is free and for sure some of it's going to burn up, >> but I think that's going to happen.

And I always think um Jeff Bezos said something very interesting. He said, "I think in the future Earth is going to be zoned residential." And you know, somebody asked him, this is like 15 years ago, what do you mean by that? He's like all heavy industry will take place in outer space. And then this addresses the pollution concerns. It addresses everything.

>> You know, people always get like really worried about, oh, you know, we still be able to see the stars. >> And it's just like I think it's hard for like the human mind to understand how big space is, how big outer space is, >> you know, it's >> we don't have to worry so much about emissions up there. Yeah. >> Yeah. Yeah. So I think that is um that's probably the most futuristic thing.

>> But in terms of an economic application, but it does um I mean I I do think in the next few years you're going to have a fleet of starships land on Mars. Next few years I mean I don't know let's just say at the outside this is eight years away. >> Yeah. They're going to land on Mars. Going to have like, you know, a little ramp's going to come out of the PEZ dispenser and it's going to be a modified Starship, the Mars colonial transporter, and it's going to be wild.

You're going to have Optimus robots holding American flags like walk down and then, you know, they're going to pull out a bunch of solar panels and batteries and racks of compute and they're going to set all of that up. they'll be dropping Starlinks, you know, and maybe the orbital mechanics don't allow this, but I think, you know, they'll they will figure out a way to have, you know, capacity.

So, just think how crazy it is to watch like the views from Pathfinder, >> you know, or, you know, whatever these different, you know, Mars um >> rovers and stuff, >> rovers are and like, you know, 4K video through Optimus robots all over Mars and then after that there will be humans >> who can inhabit it. Yeah. Yeah. Yeah. That is crazy to think about.

>> And that that's going to be an amazing moment for America. >> Yeah. >> Oh, I mean, think about the moon landing. >> This is a little bit bigger. Yeah. >> Yeah. >> Yeah. >> Um, so that seems cool. Um, >> that's a good one. That's That's a good That's a good one. Yeah. Not a lot of chatter about that one out there. Yeah. But I think it's highly likely to happen.

>> Yeah. Yeah. Yeah. So, you mentioned Microsoft. >> Yeah. and the bet that they made which is like a little bit of you know like Apple's the extreme kind of bet against the future kind of bet they made and like Microsoft is kind of a gradient of that. >> Yeah. >> Like what's your what's your outlook for their decisions? >> Well, I do think the world has gotten a lot friendlier for their strategy.

Um you know they clearly tried to make a frontier model. They failed. >> Yeah. >> You know Satia said we're going to have our own models that are very competitive. Like I think he said that 18 months ago. they don't have their own models that are competitive, but what you're seeing with um I think the future is an ensemble of models. You know, there's a paro curve.

No one model is going to be the best at everything. And I think the future for certainly, you know, kind of the global, you know, 10,000 biggest companies is you're going to take whatever the best open source model is, I think probably in the in the very near near future that's going to be an NVIDIA model. >> Yep. The labs making AS6 create very interesting >> incentives for to get into each other's business >> incentives for Jensen and everybody's well oh in a world where open source wins who funds the training well

this the chip companies could fund the training yeah >> it's trivial to do a 50 to$100 billion training run uh you know for Jensen and maybe soon I do wonder if this is kind of Google's like super long-term play like they they they seem to like maybe have opted out of the frontier race for now um We're going to monetize our compute at high rates and we're going to um sell TPUs externally, but that generates so much cash flow and open source is getting closer and closer and closer to the frontier.

And it just may be the winner is ultimately just who has kind of the most cash flow to to fund these big training runs. But I do think you're going to see American open source led by led by Nvidia get really close to the frontier like they paid that poolside acquisition was made for a reason. Poolside actually had a lot of really good American open source talent.

I they're they're you know they're doing a lot of smart things but that that is really good for Microsoft and at some level almost every application software company because what you can do now is you can take a base model and Neatron to date has not had a lot of post-raining. It's kind of been a good pre-trained model that you could do with what you want.

So if you take a really good pre-trained base model and then instead of sharing your own kind of enterprise context that's truly your IP that's truly the value you know of your company is like you know the context embedded in all of your data and like sharing that with a frontier lab you know that may be hazardous for your financial health. Yeah, certainly with like the shift in the ZDR policy like Yes.

>> Yes. And so you take a really capable open source model and you do a lot of RL and supervised fine-tuning on your own data. So you own it and it's your model. >> Yeah. >> And then if intelligence is like a super important input into your business, you want to own and control your intelligence, its capabilities, its cost. And then what we've seen from a lot of companies and you know Grockbot my understanding is you know I think it's Gemini 3.7 flash >> um Grock 4.6 >> and some Opus >> y >> and what you and behind a

router >> and you will um >> and I'm sure Elon is very focused on having it all grow as soon as possible. >> Yeah. Yeah. Of course. Um but I think what you'll see these companies do is they'll have their own model on their data and it will work with one or two other frontier models. Um not not you know necessarily but just you know checking each other it'll be kind of transparent to you the the most frontier for planning and then have execution run by everything else that's lower costed.

Yeah, absolutely. And so I think that feels like a very likely future to me. And that's a that is a much Microsoft friendlier future than one in which there's just only two dominant frontier models. And it certainly looks like there's going to be at least three with Grock. I do think you got to give Meta a lot of credit. >> They've done a great job.

>> Yeah. And I mean they were out of the game and they got back in the game. And it's just it's kind of amazing. Who could have imagined a year ago, you know, when it was like Gemini was ascendant exactly that this is the scenario >> Gemini wouldn't even be in the conversation >> and Muse and Meta would be significantly ahead of them from a capability perspective.

>> Um, so it's just, you know, this is >> kind of like the highest stakes game of like corporate chess ever played. >> And, you know, people, you know, some people have made bad moves, they've made good moves. You seem some people come out of the game, others come back in. Um, but a future where that future where it's a, you know, I don't know if we're going to call it multimodel, a hybrid model, you I don't know what terminology the world is going to settle on, but I think that's the future.

>> Yeah. >> And I'm actually surprised. I think the best broad instantiation of that today outside of Grockbot, outside of cursor, outside of you know like Harvey's done some cool things with that >> where they've done it is actually just the Fireworks Nexus product. >> Yeah. >> Where you can Yeah. You can >> choose your frontier model. Let us take whatever open source model you want, RL it for you, for your data for Gold Coleman Sachs, for Morgan Stanley, for JP Morgan, for Fidelity, for A16Z.

You have all your own data. you control your intelligence and we make it transparent behind a router. >> Yeah, >> I think that is like a very plausible future and that's clearly what um Lynn from Fireworks, she was the first one to say it and then Alex Karp and Satia, they both kind of like >> Yeah, they've they've taken their own version of it. Yeah.

>> Yeah. But you know, Satia's essay of specialized intelligence, like I think it's very plausible, >> but this stuff is really hard to do. Like that that sounds easy. >> I was it sounds easy to describe like the way I describe it to people is like who gets to be the abstraction layer to the organization and the users with intel like of of intelligence.

It's like the most whatever vi after space or position that you could imagine in business like in the history of business. >> Yeah, for sure. >> Right. I think it's like the answer is and again. >> Yeah. Yes. And for sure it's Yeah. Who's the arbiter of intelligence for global enterprises and probably consumers? I was a retail analyst and um you know everybody kind of thinks running one of these big chains is easy and there's a lot into it and it's like well it's really easy to start an American retailer in any

category cuz America's so big it's worth over $50 billion almost any category. >> Yeah. All you have to be able to do is have a fleet of a thousand stores in 50 different states that have very different climates, consumer preferences. You need to have them stocked with the right products at the right time for that region at the right prices. They need to be staffed by friendly and knowledgeable employees who don't steal from you >> who turn over at 100% a year.

>> Turn over at least 100% a year. The stores need to be clean and well lit. And if you can do that, presto, $50 billion dollars. Yeah. >> And like in the history of American business, like you can I mean it's more than one hand, but you don't have to go through many. >> Yeah. >> It's really hard to do. And >> having that abstraction layer, having it work, having it seamless is, I think, way harder to do than people think.

And I do think what something I think is very interesting about cursor, I'd love your opinion on this is like everybody else in the lab space, you know, had this like we're creating a digital deity, you know, and AGI and ASI like we're >> and the Curser guys were just like we want to make great product. >> Yes. Exactly. in a in a strange way o of everybody at the frontier.

Um probably Kerser and it was the most product focused. >> Yes. >> Yeah. I'd say in you know now they're part of SpaceX but that suits Elon and his mindset really really well. >> Yeah. >> Let's make it an engineering problem. You know create the model factory and then we need to have a really good product. >> Yeah. >> You know the you know the the the Tesla cars they're amazing.

I mean it's I don't I don't know if you drive one but it drives >> everywhere. Yeah. Yeah. But like the what cursor figured out is >> they're they had I would say a similar instate vision as what those others guys had. >> It was just a different path to get there and it's sort of like a practical meet the customer with what with where they are meet the technology where it is.

>> Um and I think you know they'll sort of they have already demonstrated that they kind of led their way up into autonomy from from that starting point. um coding is unique compared to everything else in knowledge work. This this would be like in support of the point that Microsoft is in a good position >> because it is verifiable and perfectly documented and like nothing else in enterprise >> is verifiable and perfectly documented and so it will be messy like that that leads you to a good you know bullcase for

something like Microsoft that abstraction layer >> if they execute but it's really really hard to make it really simple for >> oh you know click my co-pilot link to all my stuff train a model yeah >> on our data convince me that you're not going to share it with anyone else and then put it behind a router that's seamless for me and continuously upgrade that open source model.

>> Yeah. It's not just some middleware like it's very hard to do. Yeah. And and by the way, they're going to compete they're going to be competing with not only the labs to be that abstraction layer >> but data bricks. So like >> Palunteer um the inference the inference providers um the application companies right so like Harvey has done an incredible job of this and you know like legal has sort of in take off and um and and I think they can see the future of how to be that abstraction layer um and do the work um but

like legal is also unique because it's very documented and it's somewhat verifiable tax we'll see that we see see things like that but like the the one and a half billion the really appealing brought by is going to be very messy to go get. >> Yeah. Although I do always think and um you know I think probably in their heart of hearts Harvey and Lora think oh if we solve this >> we could be that abstraction layer for everyone.

>> I think probably in their heart of hearts cognition thinks something like that too. >> I think everybody thinks and by the way there's like massive validation of the category because Kirkland Ellis said >> we're going to spend 500 million bucks to build this ourselves. Like first of all you know like good luck that's going to be very hard. Yes. >> Um, but that actually tells you that the pie is really big, right?

Huge. >> Yeah, it's massive. >> And that's it's and you know, just um and I'm sure they have a very smart head of a head of AI, but it's not like a $500 million onetime build. That model has to be continuously updated, switching out the base model. Then all of that has to happen transparently. But I think you're going to have this huge collision between, you know, products like Fireworks Nexus, these legal agents, coding agents, big companies like Microsoft, >> Data Bricks, >> Data Bricks, Snowflake coming up, >> you

know, for sure. Um, you know, Salesforce, I think, is going to, you know, Salesforce and Workday and all these companies. This is like everybody's going to go after it. It's just going to come down to who executes the best and >> and this is just you know who has the lowest costs. >> Yes, exactly. >> But it's going to be very hard I think over time unless you're re if you're not vert vertically integrated you have to be so good to emerge as that abstraction layer.

>> Yeah. Yeah. To be the lowcost provider very hard >> because yeah we you're just simply not going to be the lowcost provider if you're not vertically integrated if you don't own your own compute over the very long long term. Um and you know it's that's another reason like I um you know I increasingly look at these hyperscalers on EV to net PP&E. >> Yes.

>> Because net PP& is compute and that is just what the market thinks you're going to monetize your fleet of compute at and you can kind of look at them and there's some pretty obvious inefficiencies too. >> Yeah. Yeah. Yeah. >> Yeah. Kind of an AI version of price to book. >> Yeah. I like the price to book. Okay. >> Um so okay you you mentioned Jensen.

you know, I I'd share your sentiment like he's like carrying this industry forward. Like tell me your thoughts on Nvidia. >> So, um I think he's in a very very good position and his strategy of being vertically integrated but horizont horizontally open and it's like okay like let's just say um you know let let's say there's some accelerator that emerges that is really really really really good.

almost certainly it will be better if it can plug into and this is why like I know you have an accelerator investment my number one thing is if you're a semiconductor CEO the only thing you should ever say is thank you Jensen thank you for creating this opportunity thank you how can we work with you we want to enable you sure we're going to compete with you on the edges >> but you know my rule of thumb for accelerators every 1% share today is probably worth a hundred billion Yes.

>> So there's no need to go head on with Nvidia. >> Yeah. >> Um just pick a niche, get your 1%. Make sure that you know >> is very big. >> He has he has nine chips. Yeah. >> Um you know he's got he's got multiple flavors of accelerators. He's got CPUs. >> He's got you know Ethernet switches. He has two kinds of GPUs. You know he's got you know we've gone from just um scale out networking being a thing.

We have scale up scale out scale across now scale in. >> Yeah. So just try to find a way to plug into his ecosystem. >> By the way, this is not foreign. Like his biggest customers all have competing products with various of those nine chips. >> Yeah. And just try to find a way to plug in, but just be nice to him. Be nice. Be nice. It's all personal.

Yeah. You know, and it's just like sometimes like, you know, you hear some of these and it's like, have you ever seen game tape of the Chicago Bulls when Jordan was is, you know, it's game 50 of the season. >> Yeah. >> And he's a little bored. >> Yeah. >> And the Bulls are down cuz, you know, they're up eight games. You know, they're up eight games over the number two person in their conference.

>> And he's a little bored. And then somebody >> somebody talks >> Somebody who's you who's who's kind of young decides, I'm going to talk to him because we're beating him. And then he just looks >> and it's like >> and it's like >> it's the best. Those are my favorite. >> It's amazing. Yeah. Yeah. You We've all seen, you know, whatever the last dance.

>> Just don't do that. >> Yeah. Exactly. >> You know, just just like, "Hey, Michael. Man, I'm so happy to be on the court with you." Like that's that's to that's that's the move. But the reason it's particularly important is because Jensen's data centers are financable. >> Yes. And it goes back to that point like let's say it's $50 billion um for an Nvidia data center you need a $15 billion equity check.

>> Yeah. >> Okay. You can finance the other 35 billion. >> Yeah. >> And it's not circular financing. I have a lot of respect for the people I have met from Blackstone and KKR and Apollo. Yeah. >> And they're underwriting each of those. >> Yeah. and they finance it. And then there's a residual value guarantee, which as long as that residual val value guarantee is less than the gross profit dollars he's getting from selling the chips into that data center, >> it's like essentially it's super NPV positive with very little

risk for him. >> Um, and then he, you know, he gets a revenue share. So if you're um and his data centers are the most financable. >> Yes. In I like let's just say a good case for probably TPUs are the second most financable. >> It probably takes I don't know double the equity check at least. Yeah. >> And then the rates on the rest of it are higher.

>> Yeah. Exactly. >> And so cost of capital is a huge advantage and that's why you just want to be part of his ecosystem. And you can see he's he's he has all these chips. He's acquiring land power and shell companies now matchmaking them with offtake agreements. I think one reason he's doing these RVGs is if he doesn't do them, it's kind of an anthropic and open AI dominated world because they can pay the most for compute.

He can effectively help other people >> compete with anthropic and open AI. >> Yeah. In the same way that he stood up the neo clouds in the first place. Yeah. >> It's just democratizing compute which is good for the world. Again, I think he's a patriotic American. His his interests are aligned with that though with with with the patriotic American ones, right?

Fragmentation, right? >> Fragmentation, no dominant AI. Exactly. Which is which is really good because he's like a he is a ruthless competitor. And it's awesome that his incentives around fragmentation of AI, fragmentation of models, and you know, fragmentation of power um are completely aligned with what's good for America. And just going back to open source, just like I I just can't take it that people think that Jensen is like the world's biggest advocate for open source and it's somehow the a giant risk to his

business. >> Yeah, exactly. No, it's great for his business. It's great for his business. >> It's amazing for his business because it means that instead of, you know, having a 90% margin on top of a token made with an Nvidia GPU, >> maybe it's a 40% margin. So more of those tokens are going to be consumed which means you need more compute. >> Yeah, exactly.

>> Um >> in a supply constrained world >> in a supply constrained world and you know let's just what percentage of the world's supply has he locked up? >> 70 80 somewhere in there. And then um >> you're talking about fab capacity. >> All of it. All of it. You know it's just because he's saw this coming before everybody else. >> Yeah. And all the system supply chain.

>> Yeah. He's got he's got the fab capacity. Yeah. locked up. He's got DRAM capacity locked up. He's got NAND capacity. He's got laser capacity. He has capacitor capacity. He has, you know, what you need to make the racks. And it's just like he, you know, he used to say, if I go back, >> you know, 15 years, he'd say, "Listen, I'm making a two or three billion dollar bet every two years, and I'm moving really, really fast."

>> Yeah. Now he's making these multiundred billion dollar bets, bringing the supply chain alongside him. He's bringing the financing alongside him by kind of standardizing it, making it easy for the very smart people at Blackstone, KKR and Apollo and Goldman Sachs and Morgan Stanley, JP Morgan to finance >> and like that is hard to compete with. >> Yeah.

And you know it is um we um my firm trades we have a pretty big portfolio private portfolio companies uh that are semiconductors and it's just um you know Elon said a lot of people are going to learn a hard lesson in hardware and like I will just say I've learned a lot of hard lessons in semiconductor investing like you can you can bet on the best team and you tape the chip out you feel great okay we've taped it out and it and that's happening happening faster than ever right now.

>> Yeah, it's happening faster than ever. You feel great about it and we're getting really good with the emulation and the simulations and you feel great about it and then um you know you'll experience this the chip comes back from the lab everybody you get a facetime from the CEO they plug it in. >> Yeah. you know, and like and then sometimes it doesn't work, you know, it's just like >> Yeah, this famously happened with Cerebrus twice, right?

Like, and they've powered through and like they've done great. >> Well, I don't I think the chip I think each Cerebrris chip worked, it just struggled to find product market fit. >> Yeah. Yeah. Fair. >> For the first two generations, the chip worked. It just didn't have product. And they've done great with it. Yes. >> Yeah. But there's a different thing between you, you plug it in, doesn't work at all.

>> And it doesn't work at all. Exactly. And then it's like if it doesn't work at all, you might be back to the drawing board and hey, we need another, you know, hundreds of millions of dollars, billion dollars, and we've we've learned our lesson. It's going to work the next time two years from now. >> Yeah. Assuming you can finance it. Yeah. >> As Yeah.

Assuming you can get financing. So, it's um you know, semiconductors are hard. Like the real world is hard. Like hardware is hard. and what he is doing at the scale he is doing at and the speed and bringing all of this alongside him cuz you know the land and the power has to come. >> Yeah. >> You know the entire supply chain has to come the financing has to come.

>> And so given that he's you know 70 80% whatever we want to say you just want to plug into that ecosystem. >> Yeah. Part of why Elon made the decision he made right. Yeah. >> Yeah. which I also think was like a very high elo move. >> Yeah, totally. >> So, you've had everybody else try and build their own ASIC. >> Yeah, >> they've gotten up on stage.

Sometimes they say negative things about, you know, Jensen or Nvidia or take shots. >> Um you I did think it was pretty smart. You know, the jalapeno team last night and we should give credit where credit is due. Jalapeno is the I would say the first good ASIC other than TPU or tranium I have seen from internal >> in a in a what seems to be a pretty short amount of time.

>> Pretty short amount of time. It's impressive. We should give credit where credit is due. >> They do have a good team working. >> They have a good team. Yeah. >> Um so they had a really good team. I think they had a lot of advantages and I do think >> if you are a lab and you have the model and you see the direction of research that's a big advantage for designing your own chip.

But then you go back to Nvidia and they work with everyone. >> Yes. >> And everybody, you know, keeps thinking it's going to really standardize. And if you look at the three big, you know, Chinese open source models, Deepseek, Kimmy, Quinn, they're kind of all um evolving in very different ways. >> Yeah. >> And they can, you know, they can all run on, you know, a more general purpose chip, um, a GPU, but you're going to need, if you want to specialize, >> Yeah.

You're going to need general purposes at a minimum for the types of evolution you see from that. Yeah. >> So, um like I think he's I'm very happy his incentives as a CEO are perfectly aligned with what's good for America. >> Yes. >> Um so I just make sure your semiconductor guys do not talk trash about Michael Jordan. >> Be nice to be nice to MJ. Be nice to MJ.

Yeah. Exactly. >> Yeah. And then it's like, you know, sometimes it's like, you know, you tug on Superman's cape and you get confident. >> Yeah. >> You know, you get confident and you start to talk a little bit of trash. Well, you know, Superman sometimes he just flies away like that's what happened to the TPU team. >> Yeah. You know, and you know, Jalapeno, they're tugging on Superman's cape a little bit.

>> Yeah. We'll see. >> We'll see. And it is kind of amazing that like >> Jalapeno did something that none of the big >> like I this is as competitive of a chip as I have seen. Yeah. >> But again, it's just competitive with one of his eight or nine chips. >> Yeah. One of his nine. Yeah, of course. >> They'll continue to work closely together. Yes. >> Yeah.

They'll continue to work closely together. So, it's like, hey, that's great. You did the one thing. Well, to actually be competitive with him at the system level, you need another eight chips. >> Yeah. Exactly. >> Yeah. >> Um and he is at and you know, Dylan at some analysis talks about how he's the bank of AI. He's like he's the central bank of AI.

He's the Federal Reserve of AI. Yeah. >> And so I actually think it was really smart for Elon instead of like >> competing, you know, with somebody who is >> fully aligned. >> Yeah. Fully aligned. >> Mhm. >> And I think that history is going to judge that to be a wise decision. In a world that is so supply chain constrained, it's actually really hard to tell what true customer preferences are, right?

>> Because like you come out, >> Yeah. they'll take anything. Yeah. This is this is how you know that like very old whatever the price is held up of H100 is very high. >> Yeah. Yeah. And if you have a TSM allocation, you're going to be sold out. Yes. >> Particularly if you can get the DRAM to pair with it. You're going to be sold out. >> So, it's actually kind of hard to infer true customer preferences.

And I actually think one of the best ways you can like see true customer preferences is the kind of deals they cut with chip companies. So, broadly speaking, you know, the first deal is where the chip company invests >> Yep. >> in a customer. And you saw TPU and Tranium, Amazon and Google do that with Anthropic. Yep. And that was to their im immense advantage because it really helped their businesses, I think, helped those chips really level up because you kind of need to use a chip.

There's a cold start problem. >> And um and in that scenario, as long as the dollars you invest are less than the gross profit, you can't lose money. And then there's a scenario where you do the RVG, Blackstone finances it or whoever, Blackstone, Apollo, KKR, Goldman Sachs finances it. Um, and as long as that RVG is actually less than your gross profit, you can't lose money and you have upside probably through a revenue share on top of it, >> then there are deals where you give warrants away, but they're tied to um

like a fixed price per million tokens. And as long as the performance of your chip kind of outruns the performance of your stock, >> you're going to do good in that situation. If you just give warrants away, it could be negative NPV because the better the does the more value that's captured by the person. Yeah. >> Yeah. And so you can kind of look at that hierarchy of deals and like infer something about true customer preferences.

>> Yes. That's interesting. >> Yeah. >> So Nvidia does pretty good deals. >> Uh like Yeah. I mean there's a reason that people I consider smart are investing in their deals. >> Yeah, I see it. Gavin, thank you. Fun. Always fun to hang with you. >> Thanks, David. This was great, man.