00:05:23 · Saurav Shroff
[00:05:23] S1: Yeah. And that's the perfect question to ask. If I owned a monopoly on a service and that service unlocked the scaling of what I personally and maybe others believe to be the most useful and valuable technology ever made. And the supply and demand relationship of that technology is that there is drastically more demand than supply, which is to say the prices are extremely high, the margins are extremely high because there is more demand than supply. Any rational economist would say that it's dumb to sell launch services, the bottleneck, to anybody else. And so, actually, the future that I see is there's really two possible futures. Future one is that, we create competition, and I think this is the, probable future. We have some very good reasons to believe that that's the case. And then future two is we continue to fail to create competition, and the result is that all of super intelligence capacity is owned by one company that isn't motivated to reduce price, and isn't motivated to increase quality. And, you know, if we just ask ourselves, this is like not some kind of like revolutionary question, which future is better? Just about every single person in the room, except for the holder of monopoly, would say, the one with competition.
00:07:02 · Ty Morse
[00:07:02] S0: If you had to think through your own business, if your entire business relies on the ability to launch your product to Orbit, hopefully in a few years. Right. How do you think through, like, basically solving that problem or working with one of the other providers, so it kind of makes sense where you can scale at a reasonable rate?
00:07:21 · Saurav Shroff
[00:07:21] S1: I guess it's best to answer your question by breaking up the future into two relatively distinct time periods. We're gonna call the first time period, which is in the immediate future, the period where AI data sets are not the majority. And then we're gonna call... And we... I think that's, like, roughly now till, like, 2029 or something, or 2030. Then we're gonna call the period after that the period where AI sets are the majority. And when I say the majority, I mean the majority of satellites sent to space measured by their size or power. Okay. The aggregate size of power of all the satellites. During the first phase, our businesses really has no problems. As in, SpaceX, before exiting the launch market, which they recently did, sold lots of launch, using their current rocket Falcon nine to many companies, most of most of whom are our customers. And, there are other rocket launch companies who will be moderately successful in catching up to Falcon nine's capability, which is to say 10 to a 100... Well, I guess Falcon's higher than a 100, but 10 to a 100 flights a year, 10 tons per launch, and the economics of a rocket that is not fully reusable. And all of those things will be true over the next two to three years, and during that period of time, our products will continue to sell and continue to provide immense value to customers. So we're not worried about this phase. This phase one. Phase two is where there's some reason to be concerned. Let's look at what an AI dataset is, why it's better than a terrestrial data center, aka a data center on the ground, and then what's required to make it good on the rocket side. So AI data satellite, very simple. Take a chip, take a memory, basically take a compute module, not memory, take memory, sorry, take a chip in memory, and put it inside of a satellite that's quite a bare bones satellite that's extremely large and generates a huge amount of power, but is very simple in that it doesn't have, you know, great pointing accuracy, it doesn't have the ability... It doesn't it doesn't have very many unique capabilities. It's basically just a a powered shell. So just a box that has a huge solar panel, a tiny battery, some interconnection, you know, networking, devices, some attitude control devices, a small thruster, but basically a very bare bones satellite. That's what an AI data satellite is.
00:09:41 · Saurav Shroff
Roughly speaking, an AI data satellite needs to be about $5 per watt for it to be competitive with a data center on the ground, because the data center on the ground costs between 10 and $15 a watt, and lasts a little bit longer. Okay? So if you wanna make it better, has to be about $5 a watt, and that's all in. So that's building the satellite, that's every single component that's out the door and into space. So roughly speaking, to make a $5 a watt satellite, something like $1 per watt needs to be launched. Needs to be the launch cost. So if we break this down, and we look at the numbers, and look at, let's say, a 200 kilowatt class data satellite, this satellite should cost about a million dollars in total, of which something like 800,000 will be the cost to build the satellite, and 200,000 should be launch. If 200,000 is launch, and the satellite weighs something like 1,000 kilograms, which is quite optimistic, actually, for the weight of the satellites, actually very optimistic for the weight of the satellite, then launch needs to needs to cost $200 a kilogram. Right now, SpaceX, well, when they were in the market, would sell you launch on Falcon Nine for single digit thousands of dollars a kilogram, and it would cost them something like $1,000. So you can see how Falcon Nine is not a sufficient vehicle to make... It's five x off. Yeah. It's five x off. Exactly. Additionally, if you look at any of the companies that are currently deploying data centers at large, okay, look at OpenAI, Anthropic, any Neo Cloud, SpaceX themselves actually with XAI. They're deploying data centers on the order of sort of one to 10 gigawatts a year. So let's do some more math. If a 200 kilowatt satellite is one ton, and a rocket like Falcon Nine can carry about 10 tons to sun synchronous orbit, which is where AI data sets need to be in order to be useful, each Falcon Nine launch can carry two megawatts. What that means is that to get to two gigawatts, okay, which is a medium number in comparison to in comparison to one to 10 gigawatts is a thousand launches. So, Falcon nine is 10 x short on scale, and five X short on cost. And so what this means is that you need a roughly one order of magnitude improvement in both scale and cost, just to get to the baseline, where the AI data set is both better at cost wise, and even modest in scale. Right?
00:12:01 · Saurav Shroff
People talk about how AI data sets are the solution because, you know, solution to needing lots of AI compute because they have infinite scale, and this is true. More or less they have infinite scale, once you have infinite, you know, pseudo infinite launch capacity. But to get there from Falcon nine, you need five x cheaper cost and 10 x higher scale just to get to the baseline, and then you need a 100 x scale to get to, you know, appreciable capacity, and and a thousand x scale to get to really serious capacity. So so rocket like Falcon nine is limiting, and it's limiting because it's too expensive, and it's too slow to launch. The thing that limits its... That makes its cost high and the rate of launch low is the fact that the second stage of the rocket is not reusable, which is to say it gets thrown away on every launch. So, to launch it twice, have to build two second stages, which is time consuming, and to launch it twice, you have to build two second stages, which costs money. So, the solution to this problem that is known and has been known for decades is to make both the first and second stage of the rocket reusable. So, in simple English, rockets that are useful for deploying AI data sets are defined as rockets whose first and second stage are reusable. Right now, there are exactly two companies on Earth that are seriously developing a two stage to orbit, fully reusable rocket. One of them is SpaceX, who we already described has roughly no incentive to sell services. And the second is a company called Stoke Space, which I think is an amazing company that is also developing a rocket of similar... Categorically similar performance, although it's a bit smaller, which doesn't really matter. And so it is for this second stage of the future where we are immensely scared. Because, if you look at the optimal sort of the game theory optimal logic for each participant in the market, it's as follows. First, SpaceX has a rocket that works. Let's say they have star... Let's say Starship works in about a year. So let's say SpaceX has a rocket that works. They have no incentive to sell, they deploy their own data sets because super intelligence is valuable. Great. If another company makes a rocket, and that rocket works, and the other people who are also building rockets, and by rockets here, I'm talking about useful rockets for data sets, so reusable ones.
00:14:22 · Saurav Shroff, Ty Morse
The other reusable rocket makers are not selling services, then the game theory optimal to sit... The game theory optimal choice for them is the same. My rocket works. I have no incentive to sell it. Scale AI data sets because super intelligence is valuable. Then if another company builds rockets that it works, their logic is the same. So it's it's for this future that we're worried. [00:14:45] S0: So, basically it's never optimal for any of these companies to sell launch once?