moonshots 200gw grid sodium batteries wave datacenters transcript

In the US, [music] if you put in a request for a hundreds of megawatts of power to build the data center today, good luck getting that power before 2031. That's the situation that we have today. So, new technologies like sodium ion batteries could drop the cost of batteries by a factor of 10. We already have [music] the very first solar plus battery load power plants and they're affordable. batteries are plunging in cost and are going to drop another 10x ultimately. >> Do you believe that thesis that solar in the [music] long term is going to dominate beyond everything else? >> The reality is look, everybody's heard Elon [music] talking about space-based data centers. So 10 gawatt a year is like five or six launches of Starship a day. >> Unless we hit that exponential absolutely fullon and go right down that [music] path, this looks prohibitive for 15 20 years. The biggest unlock that we cannot predict of [music] AI and power

[00:01:01] will be. >> Now that's a moonshot, ladies and gentlemen. >> Everybody, welcome to Moonshot. Another episode on the front line of the singularity. We're living during the most extraordinary time ever. And our mission here is to deliver you the breaking news and help you understand what's going on. Today we're going to be doing a deep dive into the innermost loop, all things energy. I'm here with my extraordinary moonshot mates, uh, DB2, AWG, Salem. Welcome, gentlemen. Good to see you all. Looks like you're normal haunts. And we've got a friend with us today. Everybody on Moonshots, it is an honor and a pleasure uh for us to invite Rome Nam. Uh Romez is uh a computer scientist, investor, author, one of the clearest thinkers on the future of energy. After a career at Microsoft, Rome became the leading voice in the exponential decline in the cost of solar, batteries, fision, fusion. Uh

[00:02:02] he's the founder, managing partner of Planetary VC, investing in energy companies. He's the author of the infinite resource and one of my favorite ever science fiction novel series, the Nexus trilogy. If you've not read Nexus, uh, I cannot commend it. On Book Corner, where Alex and I talk about our books, I've mentioned Nexus a few times. Today, we're going to be exploring the innermost loop, uh, why energy abundance may arrive faster than most forecast, and its impact on AI, economic growth, geopolitics, and our future. Again, my mission here is at the end of this podcast uh and the brilliant dialogue that my moonshot mates is going to bring to the table here uh you're going to understand either if you're an investor, if you're a builder, what's the alpha? Where is it going? Uh what are the real timelines for everything from building out nuclear plants, fusion plants, uh because you know, sometimes there's hype, sometimes there is an overwhelming

[00:03:00] abundance of energy coming our way. So, first off, Hermes, welcome pal. >> Peter, it's an honor to be here. Great to be here with friends. Look forward to it. >> You do have friends here. So, uh, uh, you know, >> I have a I have a quick story. >> Yeah, of course you have a story. [laughter] >> I'm worried. >> I remember, uh, we were we were presenting to one of the top oil companies and energy companies in the world, like top three or four, and they were like, well, who's this Rome fellow? uh we want to grill him before we let him in front of the the key people here. We're like fine, grill Romez. And so the because we were talking a lot about solar and they're an oil and gas company and after like 2 hours they're like okay we need to get in front of them. [laughter] That was it. It was an awesome session. >> Yeah. One thing I failed to mention is uh Rome was part of our founding faculty at Singular University. Uh really led the whole energy uh conversation there and has been on stage at the Abundant Summit number of times. Hopefully you're back again coming in 2027. Uh Mez, uh uh

[00:04:03] first of all, I just need to try you. You need to write a fourth, fifth, and sixth [laughter] trilogy. >> As soon as AI and energy get less exciting every single week, I will make time to write another novel. >> How much time do you spend tracking what's going on on the innermost loop here? >> It's every day, all day. I mean, that's what we all do, right? Living in the singularity. Yeah, we this is living the singularity. Before we get jumping in, Alex, you want to add anything to the conversation up front? >> I I'll just add welcome to the terror dome. One of my my my favorite of of your I would say popularizations that now infamous chart of the price of solar going down to zero. >> Thank you, Alex. >> Uh amazing. Well, uh I can't take another second away from you, pal. uh jump on in and we'll grill you along the way, make the points, you know, uh you know, shall we say, in a stellar

[00:05:01] fashion. Okay, >> great. Let's just start. We're going to hit a few different topics here with the intersection of electricity, really energy and compute. I mean, a few years ago as an investor in clean energy, that was sort of a uh a fringe sector to some people, though it's $3 trillion. uh but now that we see that AI depends upon electricity it is everything like the you know capital flows value flows to that which is scarce and right now power is scarce so we're going six topics at the end of each we're going to pause to have discussion so number one AI is power hungry two speed to power and the grid that's everything it's not cost three behind the meter power that's how it's happening four making the grid better is totally undervalue value and that's where the near-term wins are. Five, solar. Six, vision and fusion. Lots of stuff happening. And seven, finally, uh the out of this world ideas, launching uh compute into space or

[00:06:02] launching it into the oceans. So, let's just cement ourselves on AI as power hungry. You have to exponentially increase compute to get linear gains in AI. There are some ways to cheat that curve which we're doing but that's the basic uh phenomenon here and I think we don't fully gro most people anyway the relationship between these things. First I want to be clear that power is cheap compared to GPUs. So if you look at building a gigawatt data center you're going to spend $50 billion 35 billion of that for chips. When you compare the ratio of like the allup capex of your data center to your five-year energy cost, it is amazing how little energy costs. So when you say AI is power hungry, it's not really a cost issue. It is that energy is the bottleneck for AI.

[00:07:01] And this has a lot of ramifications because these numbers are in billions or tens of billions of dollars. Every hyperscaler has whole teams devoted to optimizing the cost of energy. But if you tell Open AI or Anthropic today, look, we can give you power at twice the cost that's on tomorrow, uh, they'll take it. They they won't tell you that of course, but they will take it because the revenue you can generate from a unit of electricity to the cost of it is basically the same ratio as this. So what's the challenge? The challenge is uh we stopped being able to build out the grid fast. And I'm not talking about power generation. We can still do that pretty fast at least for solar, wind, batteries, and natural gas. But the poles and wires are a huge problem. So this is uh we talk about the interconnection queue which is the cue

[00:08:02] to get your uh new project hooked up to the grid and this is for the generation side. If you're building a new solar plant, wind plant, natural gas plant, how long does it take before you are hooked up to the grid so you can deliver power to your customers? that's gone from 15 months 20 years ago to now coming up on 45 months. >> Regulations, what is it? >> It's regulation and it's also that as demand has demand growth has slowed, right? The US uh demand growth per year is much slower than it was the 80s even let alone the 50s. Uh utilities have just you re-engineered themselves. they are more oriented on uh customer service on meeting the regulators demands and so on than they are on building stuff fast. So that has got in the way. But permitting is also a huge issue. Not utility regulation per se, but permitting issues for the land

[00:09:01] controlled by the state, the county, the feds. >> If we're if we're just going to jump in uh led led by Peter's example, I have to ask you you sort of flew by. You you mentioned or you alluded to this notion that intelligence was somehow proportional to log compute which I I know a number of executives have have also pushed the the narrative of maybe you could one could naively extrapolate some law that looked like that from scaling laws uh in in machine learning training or machine learning inference. Do you think that's actually true? And if you do think it's true, do you think it continues to be true in an epic of recursive self-improvement? It's an awesome question, Alex, and this is like core to the like the big questions of AI and are we going to have a recursive self-improvement to ASI? Uh, look, everything in machine learning like since 2000 has shown something like a log linear relationship between really between training data size and precision

[00:10:03] of a model. Right. My you're alluding I I think to first Kaplan scaling and then chinchilla scaling and then post chinchilla scaling. long before chinchilla scaling with single layer neural nets. We were finding this in the early 2000s, right? So compute is used to convert training data into a model, right? Into a neural network and uh that has a roughly log linear relationship, but we cheat and by which I mean we keep finding ways to make that more efficient. So is it actually log linear? No, it's a little bit faster than that because we keep finding ways as we see with Deepseek Flash that just came out as we see with Kimmy K3. We keep finding ways to bend that curve. So, it's a little bit less bad than log linear, but it's still it's somewhere between a power law like n to the fifth uh and a true exponential or

[00:11:02] log uh scale difficulty. uh and I don't see that changing uh anytime soon. >> This seems it seems almost if I understand your broader thesis, this seems almost axiomatic that if we can't bend the the log curve that that we need basically exponentially larger amounts of energy just to make essentially linear or polomial progress in intelligence. We need more and more energy. We need to uh achieve Cardartesev level two or Cardartesev level three type civilization Dyson swarms in order just to keep making incremental progress past [laughter] right like this >> is getting at the Alex is getting at the core issue with with super intelligence actually in a certain extent look like here's my view Alex like the naive view is at any given time intelligence is basically log linear with compute log linear with data but we keep making the algorithms better and that sneaks us towards like a polomial domain but the

[00:12:01] polomial domain is still steeply diminishing returns you're arguing it's poly log you're arguing that intelligence is poly log in compute >> at best it's polomial and I don't not necessarily poly log but at best I mean we see like the very best examples you can get is maybe uh compute has to go up uh you know n to the fourth to get an n size increase in intelligence >> and you don't think recursive self improvement if we are indeed in an era of RSI. You don't think that causes anything better than poly log? >> No. Look, you do the math on RSI and RSI, every way that you improve AI has diminishing returns. So, every model of RSI that does not include hardware, we can save that. Every model of RSI and software fizzles over time. Now, the bump might be so big that we're like, wow, this is just over the top amazing, but it it always looks concave. There is no mathematical model of RSI that's

[00:13:00] valid that I can see that leads to an actual like, you know, vertical asmtote take off. This episode is sponsored by Google for startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's startup technical [music] guide for generative media gives you complete blueprint for deploying Google deep minds models in production [music] images video audio all of it real architecture real results find the link in the show notes below I'm going to take us back so the grid is the grid [laughter] >> the grid is the bottleneck right now >> yes it is so we need power in a practical sense look everybody >> and Alex Not that I did not appreciate your genius in those questions and that was fun. And this may turn out to be an entire conversation between Rome and Alex, but we'll see. >> Let's have another way to talk about that. >> I got words to I got words. Um [laughter] [00:14:01] I think I think I think the the point here is the grid is the bottleneck is a really important point because it speaks to the infrastructure needs we're going to have to have for dealing with this. So let's move on. We'll get I'll come back to it. And look, so this is for the power side. For the demand side, we don't have data that is as clean. But here are like three locations around the US. And you see in this 7month period between April and November last year, the wait times to get connected for the load side, not for generation, but for your data center, whatnot, went up by six, seven months. So everywhere around the country uh as demand is going up for large load interconnection uh you're seeing longer and longer weight. So this is Texas is a Texas grid. Uh Urkot currently it peaks out at about 80 gawatt. Okay they have submissions into their demand side queue for more this is slightly under date for well

[00:15:01] over 200 gawatts of load. Most of this is speculative. Most of these submissions are BS. Anybody, not quite anybody, you can put in a request for a large load and power without it actually having financing or a customer or so on. So most of these things evaporate. But in any case, the Texas grid operator is overwhelmed with these requests for power. And of course, that just jams up everything. >> Wait, miss, let me let me ask a quick question. Are we talking about I have a data center, I want to connect it to the grid to get power or I have a new power source, I want to connect it to to the grid to deliver power or is it about the same either way? >> So this this chart is a generation. So I've got a new power source and these two are demand are load uh interconnection cues are going up. I mean honest it's much longer than that. Like today in Urkott

[00:16:02] in Texas, the like most advanced >> progressive >> least Yeah. most progressive in like a positive sense like least regulatory burdened fastest moving grid in the US. If you put in a request for a hundreds of megawatts of power to build a data center today, uh good luck getting that power before 2031 2032. >> That's the situation that we have. >> Yeah. when you did you did a presentation for my abundance community on our monthly uh uh meetup and that was my major takeaway that the issue on energy for AI isn't you know building on solar farms it isn't vision or fusion it's the grid grid's the right >> so in that case you know and there are people who are watching who are investors want to understand this you know we talk about infrastructure picks and shovels for AI and we talk about you know data center construction companies and all of that who are the companies that are building the grid and is there

[00:17:00] is there sort of work orders and purchase orders for building out a more robust grid? >> It's a really good question. So the grid the poles and wires the distribution grid in particular is dominated by regulatory monopolies, right? to the local utilities. I I'm not going to comment on their current pees, whether I think those stocks are buys or sells, but the regional monopoly utilities stand to make a huge amount from this in the areas where data centers can be built. There's a separate issue, it's not in my slides, of more and more uh voters are pushing back and saying we want to stop data centers being built. There's a lot of psychology behind that. I don't think the the reasons are necessarily that valid. Uh even in Texas yesterday, Governor Abbott sent out a letter pausing. Maybe it was the day before pausing. >> Oh, no. Not them, too. >> He It was actually It wasn't quite a pause. It's an audit of all data center

[00:18:01] requests in Texas. In Texas, a red state. The most libertarian state in the country. And the it's political cover. Abbott knows that his voters are like there's an anti-tech sentiment that translates to AI data centers because they're an obvious target. So, he wants those data centers built. There's an election coming up. He's got to cover his ass for a bit by making it look like he's serious about this. Uh but that's the politics right now in the country. >> So, so basically we're doomed. [laughter] >> I don't think we're will have space. will always have sun-synchronous orbit. >> We we will have sun. [laughter] >> You know, the AI doomers would say, "Thank God we're saved. The AI god won't be built." But >> and even if not, they they'd propose orbital bombardment of the data centers. There's [laughter] no way of winning. >> Let me um the grid. Look, I'm going to show you a lot of like, you know, sci-fi

[00:19:01] stuff and awesome stuff, but yeah, Peter, what you're saying, the grid itself, the poles and wires are the limit. And I've talked for years about the exponentials in solar batteries. We'll talk about vision and fusion, but the poles and wires have thus far not become an exponential technology. And that's something I would love to solve. I have not seen a lot of startups. >> So me, aren't we aren't we moving the data centers to where the energy is so you don't need to set up uh you know >> or disconnecting them from the grid entirely? >> Exactly. >> Let's move. Let's move on and I'll get from that. This is like a more practical forecast. You see even like 2028 we'll we'll build this is probably a little bit low. The orange is like how much we'll build. Maybe it'll be 20 30 gawatt whereas the demand could be much higher. This is an interesting slice. By the way I'll tell you every forecaster Morgan Stanley whoever they all differ somewhat but this is an interesting slice. The

[00:20:01] blue bar is if you just sum up all the GPU manufacturing scheduled between now and 2030, primarily Nvidia, but also AMD, Cerrus, uh, whoever, versus the expected pace of US grid buildout, the chips are more than twice the pace in their power draw. For folks, the power we can deliver. The AI demand uh which is chip limited shows roughly you know 200 to 275 call it 230 gawatt of power demand based on the chips like you bought the chips you've installed the chips can you power the chips there's 230 gawatts of demand there and US grid buildout is projected at roughly 100 gawatt >> and some of you might remember like six months ago Sachi Nadella CEO of Microsoft u made this comment look man warm shells are our limit. We've bought the chips. We don't have warm shells to

[00:21:00] put them in. >> Right. That is the limit for everyone at this moment. >> Yeah. Why why is that discrepancy there? Because, you know, Eric Schmidt told us his his number was 100 gawatt or 96 gawatt of additional power by 2030. Uh the 230 is just based on chip manufacturing. So either more of the chips are being kept domestic, which wouldn't surprise me, or the fabs ramped up, which would surprise me. But where's that discrepancy come from? >> Every single forecaster has a different number and I think they some of them base on just announcements by companies whether they're chip fabs or uh utilities. Some of them based on their uh discounted projections of what they they can actually achieve. Uh also I will say there's a there's a big miss in power demand of chips. A lot of people just say, "How much power can my Blackwell GPU draw?" Multiply that by how many you're going to build and that's the power demand. No, you're missing like half the power because you've got to add the draw of the rest

[00:22:00] of the IT equipment in the data center and cooling and so on and that nearly doubles the total power use. >> You know, that that would make sense. those Cerebbrus chips they they run they just suck down power and they run the transistors much more efficiently than the prior generation kind of A100 H100s from Nvidia. So the transistors are actually doing a lot more work which is better fundamentally but yeah of course that's going to draw more power constantly and and of course when you buy those things and deploy them you run them 24 by7. >> That's right. You're never going to let those things rest. So that might be a discrepancy too. >> Absolutely. Do do you think me this creates a forcing function perhaps for Nvidia or the other fabous vendors or or the fabs like TSMC to get into the power generation business right now the power gen that's that's powering all of these chips that Satia talks about just collecting dust in warehouses because he can't find warm frames for them in data centers why not why do you think that there's a forcing function for the

[00:23:00] Nvidas of the world to get into powergen >> well I'd say look whether Nvidia wants to get into it or not and Nvidia has made some interesting investments that I'll talk about in grid flexibility. Uh the reality is that you know what people talk about the most now is behind the meter power gen for data centers. And what they mean by that is large natural gas turbines if they can get them. This is a multiund megawatt like say a 400 megawatt natural gas turbine the kind you'd use on the grid. These are now sold out for something like seven years. uh GE, Hitachi, and so on are building new assembly lines to try to bring those online faster, but everyone is saying, look, if the grid is going to make me wait years and years and years, I'm just going to build my own power. Now, this >> this is more expensive than the grid, but power is such a small fraction of AI

[00:24:00] cost. Maybe you can do it because these guys are sold out. people are going to these small turbines. Solar turbines, nothing to do with solar, but they make uh this is a 38 megawatt turbine that's uh on the back of a semi. So 40 of those make a gigawatt, right? Even these have backlogs. But now you have companies, everyone in the world that was in any way proximate to gas turbines is pivoting into this space. I'll give you an example. Bloom Supersonic, very cool company trying to make uh supersonic jetliners a thing again. Uh that's a very hard task with many many billions of dollars of regulatory costs. They have pivoted into using their engine design to make a gas natural gas turbine for data center power because the demand for this is so very high. >> So modular modular energy production,

[00:25:01] right? How many of these uh if you think of them as 18-wheeler truck uh that has a a large container on the back uh just pull them in and and get your data center started until you build out energy infrastructure and then move them on. >> This is how Elon got the Colossus data centers up uh that Anthropic is now leasing. Actually, this is what he did. >> And we've talked a bit about this on on the pod in the past. We talked about the boom pivot and we've talked a bit about Elon standing up his uh fume generating cogen facilities uh at Colossus etc. We talked a bit about that but I I just want to try pressing once more on this point if if this thesis is true that this is a primary overhang on Nvidia's ability to sell more GPUs. Nvidia is already doing all sorts of financial engineering to be able to sell more and more GPUs by through customer financing all of these other things. Why on earth if the energy overhang or underhang depending on your perspective is a major limiting factor for the ability to

[00:26:00] productively monetize GPUs why don't we see Nvidia doing something on the energy front? >> It's a great question. So look for behind the meter the financial incentives are so large Nvidia doesn't have to but they might invest in some of these companies. Uh on the grid side, Nvidia has made investments into increasing grid flexibility to be able to get more juice out of the current grid. Emerald AI is one example. They've made a few investments in this space and I'll talk about grid flexibility in a sec here. Uh but the real issue is a combination of regulatory and the incentives for utilities. utilities, monopoly utilities in the US, the bulk of them are played paid on cost plus. So they say uh they go to the utility commission and they say I've got a plan to meet the demand uh that I see my customers having. Here's what it costs for me and I expect a 10% return on capital for it. And the utility

[00:27:00] commission mostly just says okay like some are better than others. But let's be honest like the utility has enormously more horsepower in people compute salaries etc than the utility commission. So they like jam through this plan and they get 10% on top. >> I see. So, so if I were to try to synthesize what I think your answer is, your answer for why Nvidia isn't getting into bundling power gen with their GPUs is it's low margin and frictionful like for the same reason Nvidia tried and failed and then retreated to launch their own hyperscaler or Neocloud. It's just not as high margin as selling GPUs. You know, Nvidia might still be a neocloud. We can talk about that separately. If I was Nvidia, I would be focused on changing the regulatory landscape for monopoly utilities. And I've said this on like some utility specific podcasts. We should change the incentives. Utilities instead of just getting paid uh for uh a percentage over capex, they should be paid on things like how fast they can deliver power.

[00:28:02] Their executives should get bonuses for delivering power fast. And if you did that and they're employees obviously all the way down. If you did that suddenly these things would happen faster, right? >> You get what you incentivize. Absolutely. >> Yeah. Look, I invest in startups. How many startups have I seen that have a technology to speed up building poles and wires? I don't know, two or three. None that I thought were amazing. If you, by the way, listeners, if you have one, please send it to me. Why not? Because there's no incentive for it. But if you created the incentive, people would find technical solutions to speed that process. >> Is there is there any state? No, not not Texas, but is there any other state that is open-minded about that? And >> Texas Texas is the best. And I will say despite what I just showed you, Texas has made policy changes that accelerate this. And you know people are not totally asleep with the wheel. FK. So Texas is interesting. Texas Urkott is its own fftom. Uh that is not regulated

[00:29:02] by the feds at all. Uh FK regulates the rest of the country's electricity. Uh FK has sent letters to the six other largest grids saying basically do something like what Texas is doing. And what we're what they're doing is and maybe I can uh just uh skip to it is making new regulations that say if you are an interruptible load, if you are flexible, if you can uh either find some alternate way to power yourself or just turn down your power at moments of peak demand will get you connected much much faster. So in uh Texas that's a CLR or a PCLR an interruptible load. Um and the reason for that is we we have as Americans as anyone we have a very high demands for the reliability of our grid. Right? 99.9%

[00:30:02] uptime is 8 hours of outages per year. That's unacceptable. Right? It's got to you got to push to four 9ines to make it a grid that you think is really good. But the nature of the grid is the power demand is not constant. It fluctuates uh through the course of the day and the seasons. It peaks uh primarily in the south in late summer afternoon. So this is the US grid. The US grid averages about 500 gawatts of demand uh kind of throughout the year throughout the day. it it's much more volatile than that. But at any given time in like winter night times, the US grid is down to like 400 gawatts of power being drawn. In uh summer late afternoon, we're up to like 600 gawatt of power being drawn because of AC primarily. The fluctuation is actually much higher than this. >> Europe doesn't have this problem.

[00:31:00] >> I'm [laughter] a joke. >> It's a different problem. We can talk about Europe and AC. There's some amazing tech coming down the pipe on that. By the way, hopefully a new investment. Um, that gap is 200 gawatt, right? 200 gawatt is about 10 trillion in AI capex. We think there's about 7 trillion in AI capex in the next 5 years. Like, this is no joke. If we just used the poles and wires more efficiently, we could power up a lot of stuff because we're not short on generation. We're not short on power plants. We are short on capacity and the poles and wires. Okay. So, what are we doing there? As I mentioned, like Texas has, you know, just June enacted this uh new uh regulatory change that says, look, if uh you, you know, don't need to draw power at peak, we'll just hook you up fast. Instead of five or seven years, it might be 12 to 18 months. FK has now

[00:32:03] told everybody else uh to do that. So, how do you do that? Uh this is um a paper by a buddy of mine, Tyler Norris. uh he's now at Google. He was not when he wrote this. This came out in January, February this year. This is the best electricity related paper of the year in my mind. And basically what he found was I call it 200 by 200 or 100 by 100 at minimum. If you can be flexible 100 hours out of the year, 4 days out of the year, 1% downtime, that unlocks 100 gawatt of capacity on the grid, which is about 5 trillion in data center capbacks, including the chips, which gets you through, you know, the next uh few years. Uh that's one way to do it is just flexibility. The startup I mentioned, Emerald AI, uh, Verun Civerum, uh, funded by Nvidia. They do this via just software

[00:33:02] orchestration, moving jobs to the right data center, etc., etc., etc. But there's another way to do this, which is batteries. Yeah, this is a portfolio company of mine. I've made three investments in this same startup, maybe a fourth one coming up. They do something really obvious in uh a place like Dallas Fort Worth between middle of the night and late afternoon there's like 10 15 gawatts of flex in the grid demand. So, if you build out, let's say, four hours of battery storage at the site, fill [snorts] it up at midnight, you don't need to hit it uh during the peak of the day. And that fits perfectly with the new Texas regulations. In fact, they were uh leaders in driving this. This currently sounds what's obvious to us, right? But this is an unusual approach. 12 months from now this will

[00:34:00] be a super common approach not just >> in [clears throat] shifting load right >> yeah exactly so right now >> miss but if I if I have a magical technology that stores insane amounts of energy very cheaply >> and I go to even Texas and I say hey this can completely shift this curve this is a total game changer can I hook it up to the grid and start sucking down power when no one's using it in the middle of the night would they still say yeah you can do that in 2030 30. >> So the new regulations that were just passed in June gives a fast path to power for anyone that is an interruptible load. So so long as the grid itself, the grid operator is able to turn you off. It's not them saying >> definitely we need to make t-shirts that say I am an interruptible load. [laughter] >> Oh my gosh, it makes me want to show an abundance t-shirt that Peter's team sent me. But yes, I am an interruptable load. Uh, don't ask my girlfriend's office.

[00:35:00] [laughter] >> So, look, so Matt, why isn't every data center uh, you know, deploying these giant battery packs? It seems like, you know, if if I had that in my data center, I would be, you know, super smooth on the on the load demand for my community. >> We passed this regulation in Texas in June. >> Okay. >> Like the second week of June, two months ago. >> So, it's brand new. >> Yeah. So like I invested in these guys because they drove the regulation and because they've got 10 gawatt of like sites that can take advantage of this. Uh and then after this was passed in Texas, FK, the federal regular regulator of electricity sent a letter to the six largest other grids in the country not specifying the details but saying do something like this. >> Figure this out. So this is going to become a very common thing to do. And it [clears throat] it's called a gentic. Agent Gentic infrastructures. >> Agent Gentic is the startup. Um but this in general this is an interruptible load

[00:36:01] or timeshifting demand. Again like that red dashed line. Not all of you some of you are just listening. The transmission line capacity and the substation blah blah blah blah blah transformers. That's the limit. It's not the gas generators or the solar or wind. It's the transmission line. So, if you can use batteries to fill up your data center, your data center batteries at night when the transmission line is unused and then not need to draw on the transmission during the day, that is we've always known that was a good idea. We do it with with EVs and so on. Um, and this is a a very big deal. [clears throat] >> Amazing. Would you would you say me this is it it's fair to characterize this as the energy or the grid equivalent of uh preemptive multitasking or re-entrant multitasking in computing? Basically allowing processes to say they can be paused and their compute load can be timeshifted. >> Yeah, I think that's one way to look at

[00:37:00] it. I think that's a great analogy, Alex. It's also like cache prefill, you know, like yes, batteries are a cache for electrons instead of data. So we're we're making our grid cachable. >> That's right. By the way, >> go ahead. >> How what you know that big gap of the 200 gawatts, how much of that do you think we can make a dent in by taking [snorts] this approach? >> I think approaches like this and approaches like electric vehicles also, right? The the bulk of the batteries in the US are actually in EVs. So, another company of mine, Weave Grid, uh I shouldn't say of mine, like I'm blessed to be an investor in them because they're smarter than I am. Uh they're they have long for utilities managed electric vehicle charging on the grid to reduce stress on the last mile, on the last block even, right? The limit on EV charging for the grid is actually the transformer on your block because Tesla's cluster. If one person gets a Tesla, their neighbor like doubles in odds of getting a Tesla, right? So they

[00:38:02] already have software to like time slice and even out the charging of the vehicles. So companies like that in particular weave grid are using that technology to make the rest other loads on the grid more responsive and shaped in a way to allow uh AI data centers to play well. In fact, every EV charging company I know has pivoted to trying to use their tech or their current capacity to enable data centers. And I think that's 100 gawatts. I think that's if we're smart about it, that's the next five years of AI data center growth. >> Amazing. All right, what's next? >> All right, let's talk uh like uh more interesting stuff. We all love solar. Uh let me tell you uh we are we're entering the phase where solarp powered AI data centers become viable. Uh many people have seen a chart

[00:39:02] like this I've shown in 75 1975 uh one watt of solar panels cost 100 bucks. Uh now it's 8 cents from China for a panel that's smaller has a longer lifetime is more durable etc. And so uh that more than 1000x price decline does that get us to the point where we can power data centers with it? Well data centers because the chips are so expensive it never makes economic sense to only run them when the sun shines. So you have to storage as well. Battery prices have dropped by a factor of 14 since 2010. We have new technologies like lithium ion has been dominant. Sodium is much more common on planet Earth than lithium. So new technologies like sodium ion batteries could drop the cost of batteries by a factor of 10. And even now we already have the very first solar

[00:40:03] plus battery load power plants and they're affordable. So we have them in the UAE outside of Dubai. We have them in Chile. And a nice thing about this is honestly uh you know natural gas turbines are sold out for years. You can the fastest energy project you can build is a solar and battery project. You can get that done in 12 months. >> So we in the United Arab Emirates this is a 1 gawatt 247 solar and battery project. What that means is they guarantee that the minimum power output at any time is a g gawatt. to do that. It's actually 5 gawatts of solar and 19 gatt hours of batteries. And the cost is like is six bucks a watt capex. That won't mean a lot to a lot of people. But let's just say the last nuclear power plant built in the US cost $15 a watt. Uh the cheapest ones on planet Earth are

[00:41:00] Chinese. Uh being built in China, those are $4 a watt. >> So recently competitive. >> It is is recently competitive. So, so Nez, you and I texted about this, right? On the last earnings call at Tesla, I think it was at Tesla, uh, Elon said he wanted to build out 100 gawatts of solar capacity. Did you check into that? >> Yeah. I mean, [snorts] I think, look, it's a long-term vision. It's not next year, but Elon's overall vision is let's put all the compute in space. There's no land constraints. There's no permitting uh uh issues there. People won't complain about water use there. and he wants to build a terowatt of AI. Uh, and if you're going to build a terowatt of AI, you've got, you know, two or three options really. The world's deserts powered by solar and batteries. Uh, getting fision or fusion to work. Uh, ocean power like panas that I'll show or space. >> So, he's talking about about Tesla building out solar, terrestrial solar,

[00:42:01] right? Competing competing with China. >> Yeah. He wants to build out the manufacturing for it, but I think his real motivation is not selling it to the onland market in the US. I think his real motivation is to build that uh manufacturing capacity uh for space-based solar. >> If you look at what is we need a pedoph just pull on that Peter's question me just a bit. If if we take the thousandx reduction per kilowatt or megawatt o over the past few decades and extrapolate it, have you gone through the thought experiment of what would solar need to look like in order to achieve another thousandx price per watt reduction? >> Yes. So this is a very good question and it's it's an important um clarification of how the cost reductions work. So our best model I'm not that smart, right? Like I I'm one of the top five forecasters of solar costs in the world. And it's not because I'm that smart.

[00:43:00] It's because I came out of tech and I came from a Moore's law world and came into energy and just applied Moore's law to it. But when you actually look at the details, it's not a reduction in time. It's a reduction with cumulative scale. It is Wright's law. It's the learning rate. So every cumulative doubling of solar scale reduces costs by let us say 30%. it you know it fluctuates yeartoear it's the real world and so on so look if we ignore the possibility that we need terowatts of AI compute and we just look at the world as it is uh solar is now 8% of global electricity and let's say we think solar can get to a third or 2/3 uh and maybe electricity demand goes up by a factor of two you've got four five six doublings left that means the cost of solar might drop by a factor of four maybe even by a factor of eight but not by a factor of a thousand. But if you start talking about uh you know building

[00:44:00] Dyson spheres then we have a long way to go to keep reducing those costs. >> I heard what I wanted to hear. [laughter] >> You heard Dyson spheres >> pandering pandering. [laughter] >> Bingo. Wait, can I drill in on that too? >> I've got a couple of questions. Yeah, Romez, how many of these installations are there being built around the [snorts] world right now? Like this exact style of monster scale uh solar at scale. >> We're just Oh, like gigawatt scale, you know, a handful uh largely in China, the Middle East, uh some in Latam. Uh we have, you know, a maybe more than a handful, maybe a dozen at this scale. Most solar plants today, you know, they're typically somewhere between 50 megawws and a few hundred megawws. a gigawatt plant. The the challenge and the reason the biggest reason this is not yet an option for the US because we could pull off something like this in the southwest and it would actually it would be cheap. It would be more

[00:45:00] expensive than it is in the Emirates because our labor costs are higher, but it would be fast. You could have it done in a year with even a natural gas turbine that you want to order from G. You can't do that. But putting together the land parcels is actually the pain for this >> in the US. >> Me are these are these solar panels coming from China? >> Probably. I mean 85% do. So presumably and of course we double the price of Chinese solar panels in the US. So we hurt ourselves by keeping them out. >> Sorry. >> Yeah. So if this is the fastest path to energy at scale, why aren't there people just going or the US government just going, "Yeah, let's let's use eminent domain, grab whatever chunks of land we need to and [snorts] build this stuff because we could be done in a year." >> You don't need eminent domain. The federal government is the number one land owner west of the Mississippi. And those federal lands are concentrated in places like Nevada, Arizona, places that

[00:46:02] have enormous solar resources. Uh, but it's not something that interests the current administration, I would say. But yeah, if I was thinking about it, I'd be thinking about how do we open up lands that are not not amazing uh nature resources uh to build solar powered data centers. And I think we get them. Sunshine seems better than drilling on federal land. >> Absolutely. And I I'll say this also like regulations are the problem in lots of place. I was in Mexico recently. I was in Chihuahua and uh you know trying to convince the government of Chihuahua, a state of Mexico uh to build a lot of solar powered AI data centers. But in Chihuahua, it is actually illegal to have a private power generation, a behind the meter power above, I think it was 500 kilowatts, right? Half a megawatt. So you just use the law can't

[00:47:00] do it. And then secondly, the AI labs and the hyperscalers are extremely vigilant about data protections. They don't want their user data leaked or seized and they especially don't want their model weights excfiltrated. So they're they're pretty careful about the countries they go into. So my advice to Mexico was like look you know change the laws to make it possible to build this sort of thing and to pro provide ironclad guarantees of the protection and say you know intellectual property protection of this data and you've got an enormous business right more open land lower population density and better sun than the US. >> This episode is brought to you by Blitzy autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every

[00:48:01] development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-ompiles code for each task. Blitzy delivers 80% or more of the development work autonomously while providing a guide for the final 20% of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when [music] incorporating Blitzy as their preIDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. I was going to push back on on well first thing first the uh the GPUs can't sit idle no matter what because they're so expensive and yeah but when you look at the underlying economics about 5% of the cost of the data center maybe up to

[00:49:00] 10% is the power but the GPU itself is 80% markup from Nvidia on top of 2x markup from TSMC with another 2x markup at the model provider level so it's actually 20x overpriced relative to the cost of turning sand into a chip which is actually coming down too with efficiency and scale and so at the where Elon thinks at the fundamental level uh it's actually not a given that the GPU is super expensive relative to the power once he gets the terapab up and running and the end to end sand in one side chip out the other is fully automated so that would completely flip all the math in this if he if he gets to that destination I think those are awesome comments, Dave, and I think it's right that GPUs are are overpriced, or at least there's a lot of margin going in there. Uh, Nvidia, people don't think of them as a network effect company, but CUDA, the programming layer to write to AI is like their moat, right? It's not

[00:50:02] like their chips are good, >> their chips are fine. AMD's chips are as good. Their interconnection between chips is great, and that does matter, but people like uh Huawei is kind of getting there, honestly. Uh but CUDA has been the moat and I think the CUDA moat is broken this year and next year. One of my portfolio companies, Lamorian, I met them at Abundance 360 is working on that. But also now that you can tell AI take my uh AI code and recompile it to run really fast on this AMD chip or the Cabus chip. I think Nvidia's lead is >> so glad you brought that up. This is such an important topic because this $5 trillion of US market cap that's that's hanging in the balance of this conversation. It's such an important and such a fragile thing, you know. So, CUDA is the moat for sure. No doubt. All the AI researchers are too lazy to write custom kernels. Suddenly, Fable 5 comes along. I've had great luck running custom kernels myself just in the last couple weeks using Fable 5. So, so I

[00:51:00] think your prediction is is probably right. I don't see why it wouldn't be right. Uh I think Nvidia would say we have all kinds of other network effects and we have massive interconnect. Now the interconnect is incredibly important for training. >> Yeah. >> But 90 95% of the load now is moving to inference >> where you don't really need the interconnect. >> I think the internet still is very helpful for inference. you know, if you're going to run a model like uh Kimmy K3 or DeepSeek, not necessarily flash, but the next DeepSseek V4, you're you're simultaneously running it on a rack, right? You're running it on 10 to 20 uh GPUs at a time. So, the interconnect does matter somewhat even for inference. But you're right that it matters even more, tremendously more for training. Can I Dave's point is is just that in at inference time interconnect locally matters to the extent you need local coherence but you no longer need global coherence at the level of an entire supercluster. It's just like a single rack of coherence. >> Yeah, that's correct. >> Coming back to energy and to summarize this, there's plenty of room for energy

[00:52:00] growth. We have the abundance thesis on energy writ large with solar, right? And and one of the points that Elon's made before is at the end of the day, it's all about solar. every do you believe that do you believe that thesis that solar in the long term is going to dominate beyond everything else? >> It's complicated and and I think we underestimate the importance of geography. So the the reality is look from a regulatory standpoint we're not building transmission. We are no place of China is building enough capacity to move electrons from place to place. Same thing as what I just showed with poles and wires. And so the problem for solar is uh not cost and it's not nighttime because batteries are plunging in cost and are going to drop another 10x ultimately. Uh it is winter. So in London for instance, [clears throat] you get 16th or 17th as much insulation in January as you do in June or July. So

[00:53:00] you're going to build out your solar plant by a factor of six or seven? >> No. uh or do you have do we have a battery technology that can store months of power? Just a couple interesting ideas out there, but like think about, you know, the unit cost electricity goes to a battery. It basically battery capex amortized by how many times it gets used. So if you got a battery that cycles daily, it's like battery cost, you know, capex divided by 365 or uh, you know, 3,650 if it's 10 years, let's say. If the battery gets used like twice to shift load between seasons, it's battery capex divided by that. So there are there's numerous startups, there's some crazy ideas, sand, compressed air, power to natural gas, yada yada yada. But right now like it's clear to me that economically shifting battery shifting energy through the day night cycle we're not totally there yet but it is like the curves are are just heading that way. uh

[00:54:01] but dealing with winter especially also we have not yet electrified heat and if you look at you know the UK as an example and in case in Northern Europe uh if you go from burning natural gas for building heat to using heat pumps electricity demand uh like doubles in winter. So we have this big big big winter problem that I think a lot of people are not reckoning with. And so I do believe, you know, nuclear is super useful as is, you know, efforts to get uh seasonal storage, as are all of our efforts on fusion, as is advanced geothermal. Um be especially for those places that are further from the equator and have either long winters or long rainy seasons. >> Location, location, location. >> Yeah. All right. So this is this last slide is saying that that solar battery data center is going to get cheaper and cheaper. And so yes, one of you asked why don't we move compute to where the energy is and I fully believe that right

[00:55:00] in other energy loads you can't move the population of New York City to a place that's sunny year round not quickly >> almost is Florida [laughter] >> okay it's Miami uh during co and uh mostly for crypto folks uh but you can uh the new load we haven't built which is AI why don't we site it where the energy is right so that's that's that's one viewpoint. All right. Um, next, uh, Peter, you wanted me to talk about vision and fusion and both are super exciting. >> Absolutely. Yeah. I mean, we hear a lot about it. We talk about it. We we speak about the hyperscalers turning on, uh, you know, defunct fision plants, investing in fusion companies. >> U, you know, it's interesting. A quick stat. Uh 71% of Americans are against data centers, which is a higher percentage than are against a nuclear plant in their backyard, which I find amazing. >> That's just insane. I'd rent my backyard out to both. It's not big enough quiet, but uh you know, [laughter] [00:56:01] we'll we'll make some room. Um >> maybe just a quick question before the the segue. I just want to pull a little bit on the historic rhyme between the Middle East being a major source of oil but now also being a major source of solar power. If the the thought experiment I've done, I'd be curious to get your thoughts, is the reason the Middle East has so much oil is my understanding is like hundreds of millions of years ago, there used to be a a warm ocean with lots of plankton and other small creatures that ultimately resulted in the oil. And now it's it's largely desert, but still it's pretty warm. Any thoughts on the the historic rhyme between why somehow Middle East is on the one hand supplier of all this oil power [snorts] for data centers and now potentially solar power. >> Well, I think the Middle East has amazing solar resources, but it's not as lumpy as their uh fossil fuel resources and especially their oil resources. Um if you look around the globe, you have

[00:57:01] Australia. I mean, if I was thinking, actually, I just said Mexico. If I was thinking about let's do a lot of solar and batterypowered data centers for AI, I would be really pushing in Australia. >> Yeah. You've got a friendly government, you've got enormous amounts of space, you've got the some of the world's best uh solar resources. Uh Chile and Mexico, not amazing oil producers. Mexico was once, they're not anymore. uh but solar resources that are you know equivalent to the Middle East. Uh so if you look around the world it's interesting uh we obviously we all know intuitively you know some places are much sunnier than others but in the places that people live the actual like solar energy that falls varies by at most a factor of two between the least sunny and most sunny places which is kind of crazy. Yeah. the seasonal effect is bigger, right? And as you get further from the equator, the seasonal effect uh gets bigger. I live

[00:58:00] in Seattle, I know this. [laughter] Whereas the oil density underground is much much much higher dispersion, much higher concentration in a few spots. So overall, like when I when I'm always counseling them on find a way to export energy. You're not going to build poles and wires to move electricity from Saudi Arabia to the US. But, you know, he used to say like steel like Iceland uh is makes a lot of aluminum. They have no bulkite ore, but they have cheap geothermal. Uh I know I've got a company I've been talking to right now that's using Icelandic geothermal to make uh uh sustainable aviation fuels like e- fuels, power to fuels uh because they can export that, right? So if I was in Saudi, I used to say like make industrial uh uses of electricity, but now I just say like make data, make intelligence, >> but you've got to change the laws such that an open AI, an anthropic, a Grock, whoever, a Google

[00:59:00] >> is comfortable citing their crown jewels in your country. Just by way of a reference number for the audience, you know, when I last looked at it uh on the energy abundance thesis, you know, we have 8,000 times more energy than hits the surface of the earth and we consume as a species in a year, right? So, there's plenty of energy out there. It's just not in usable form. And the whole conversation here is how do we take that energy that's latent and make it usable, right? And that's the role of technology. >> That's right. The other the other commentary is that the fossil fuel are just an old battery that we've been using up, right? Uh and and we've used up about 25% or 30% of that battery. >> No one knows. But I mean, you know, the cure for high prices is high prices. So if we ever started to run low, there'd be more incentive to explore and find stuff. Y >> I have a question for you, Romez, on the on the oil market. real quick. I remember you commenting once [snorts] [01:00:00] that the 2013 oil price, oil crisis, oil crash >> was because of a 2% over supply in the market. Like it's a really tightly won >> Is that still the case or with all the Middle East conflict and everything else, we're now in tension, it's going to stay that way? >> Oh my gosh. I mean, there's a lot to say about that. Look, like two interesting things. Yeah, there's two interesting things about the the Iran war and its impact on oil prices and why it's been relatively muted. Uh number one, China did us all a solid. China built the world's largest uh oil strategic reserve, right? And they were willing to drain it during this period. So, China has, you know, more than the rest of the world's uh strategic reserves combined has helped keep oil prices low. But two, the ratio of global GDP to global spending on oil has roughly tripled or quadrupled since the oil crisis of the

[01:01:01] 70s. So, there are critical things that are highly dependent upon oil, you know, aviation, shipping, trucking, and so on. But overall the world has moved to more of a services economy and that has created you know sort of more uh demand elasticity. It has allowed the world to deal with a shortfall in oil in a way that we couldn't in the 70s when our economy is just more physical. >> Maybe you haven't seen oil spike to 200 bucks and >> I just like to pull in the the geopolitical angle here. There there's a a theory in certain circles that uh an ulterior motive for the Venezuelan operation and then uh the war with Iran was actually to cut off China's uh in event of a Chinese invasion of Taiwan uh open PN TSMC closed PN that China would require backup oil supplies because they would get embargoed by the Western block

[01:02:00] and their go-to sources for backup oil in such an invasion would be would look like Venezuela, Iran, maybe Cuba. And so so the the the full sort of theory here is the the recent military adventures that we've seen, Venezuela, Iran are actually at some level a play to deter China from invading Taiwan to gain access to the TM TSMC fabs and basically the future light code of AI. Any thoughts on that? >> There's insight there, but I don't agree with it as stated. And the reason for that is uh China bought oil from Iran during the this this war. The US still sells oil to China. Uh it just wasn't that planned out. Um the actual DoD war plans uh in a situation like that are to use the US submarine fleet to sink tankers that are getting heading to China. That's the actual, you know, proposal of what to do. Who knows if that's a good idea. I I'm not going to

[01:03:00] get into that right now. Oil is mostly funible. So, the fact that China buys oil from Iran, us bombing Iran, uh or even if we successfully close the straight doesn't really hurt China that much because they can buy cargos from somewhere else, they were getting a discount from Iran because it was embargoed oil and that they were willing to buy. So, they have to pay, you know, a few bucks more per barrel. It's not that big a deal to them. In wartime, it's a kinetic uh sanction. It's a kinetic embargo. Uh which is a different sort. And yeah, the the sim I think this is all totally unclassified. The simulations of wars like that are US submarines, you know, torpedo tankers that are heading to China. >> Onwards to the horizon of fision and fusion. >> Okay. Uh let's talk about the atom and the power thereof going back to the 50s or you know a retro future. Uh uh this is a complicated slide uh for those of you who are uh just listening. Basically

[01:04:02] there's you know two approaches to nuclear fision which is what we've been doing since the 60s. The traditional one is big reactors and the simplest thing you can do to boost nuclear production worldwide is a stop shutting down nuclear plants. Germany should not have shut down. It's uh two nuclear plants have like a end of life plant. We can usually extend them. In some cases, we can actually upgrade them to produce more power. Uh three, there are some plants that have been shut down like 3M island that we can actually restart safely. But that gets you, you know, a few gigawatts, right? If we really want a nuclear renaissance, the the core issue with nuclear fision today is that outside of China and perhaps South Korea, it is ruinously expensive. And why is it ruinously expensive? It's

[01:05:00] because we don't do a lot of it. Anything that you do infrequently is expensive, right? You don't get good at the things you do occasionally. the things that are cheap are the things that you do repeatedly again and again and again. So there are two paths happening uh to bolster nuclear in the US. And I'm a critic of this administration on on many fronts and on some energy fronts, but I'd say this administration has the best nuclear policies of any in recent history. Still missing some things, I think, but the best that we've seen. Uh so the left side of this is large reactors. We have this thing called the AP-1000. It's sort of a it's the Westinghouse reactor. It's sort of a workhouse uh reactor. We've built a couple of them in the west, let's say four. Uh China took a variant, took this design, made their own variant that had a local supply chain, and they've built more than a dozen. And they built them at higher power than this, 1.4 gawatt instead of 1 gawatt. So, one plan is

[01:06:02] we're going to produce uh a process to get more of these built. The administration is talking about has created structures for loan guarantees, for financing and so on because if you stamp out a lot of these, the cost should come down. Right now, >> what plant is the most stamped out so far? [snorts] >> Uh, lightwater reactors like those used in France. So, France uh is the poster child. Uh, the US has generates the most nuclear electricity of any country on earth. Actually, it's it's not really known. Uh, China is building the most right now. France gets the highest fraction of it electricity from nuclear and they basically with slight caveats basically took the same design and stamped it out again and again and again. >> How many of France have like 60 nuclear power plants now? >> Something on that order. Yep. But even France >> something like something 80% of their electricity is nuclear. It's crazy.

[01:07:01] >> And they exported to the rest of the Euro zone as well. efficient was basically born in France. Thank you, Curies. >> Yeah, but even France is strug struggling, right? There's something called the European pressurized reactor which is mostly a French design and that thing is kind of a a disaster right now. It's a boondoggle running over going slow. Again, like if you take one design and you do a lot of it, it gets cheap. But usually, and this is critical for the sector as an investor, the first one usually runs over price over time uh and you know has problems you didn't anticipate. So if you want a thriving nuclear industry, you just have to know that the first one you build of a new model is probably going to have problems. But after you've built three, four, five, maybe more, you sort out those problems. You build experience in the crews. You build experience in the engineers. You sort out design issues.

[01:08:00] You build a supply chain to provide the parts that you need. So one plan is we're going to take the large reactors that we have built a couple times. And now we have the US government has created financing sort of a backs stop loan guarantees for about eight of these. Um another startup the nuclear company I invested in one of the founders previous companies. uh they have a plan to basically build fleets of these because that's how you have to finance it. You can't finance one because you know you're going to miss your targets. But if you can finance a bunch at a time amortize the cost >> you know in China like after they got to like 6 7 8 like the costs had really come down and stabilized. >> So those who are fearful about nuclear and it's still you know probably [snorts] a good percentage they they think about three-mile island in Fukushima. We're talking about early generation plants right? Are those gen Gen 1 or gen two plants? >> Something like that. And these are uh gen 3 or gen 3 plus or gen 4 plants. And one of the most important things to

[01:09:00] understand about them is basically all of these are passive safe. What that means is um you can knock out the power to them and they won't have a meltdown. Fukushima happened because you circulate water around the nuclear core to take the heat away from it and then use it to turn a steam turbine. That pump for that was powered by grid electricity. So the tsunami that hit Fukushima knocked out the power lines and so the pumps stopped working even though there's power right next to them for the nuclear reactor. Right. New nuclear fision designs are passive safe. >> Would you call them fail failsafe plants? Nothing is totally failsafe, but they're designed to take a 747 crashing into them and the power going out from the grid and keep operating without any meltdown. >> I [clears throat] I'm curious, just pulling on that, MZ, what happened in the 1970s? I assume you've seen the television show, we we talk about it

[01:10:00] sometimes on the pod for all mankind. It's sort of an alternative historic reality where we get vision, it never gets abandoned. What happened in the 70s? Did did we just waste the past 50 years not building enough nuclear energy vision in particular finding ourselves in a sub-optimal future? >> I don't think so exactly. I think we could have done better but people are somewhat riskaverse. Uh radiation we learned you know in the 60s that radiation causes cancer. The radiation released from a well operating nuclear plant is really minimal. it's unlikely to cause uh cancer. But so we we did increase the regulatory estate. We did increase the burden of proving that things were safe and that had some cost and then uh things just fizzled out and and you know we talk a lot about um flywheels and and positive feedback loops. We had a negative feedback loop once and this is the same thing Francisine once the industry is no

[01:11:00] longer building. you lose the expertise, you lose the supply chain that makes the parts that you need, you lose the manufacturing facilities, uh, and everything gets more expensive. So, if you're not constantly scaling, you are going to backslide basically. >> [clears throat] >> So those were large reactors and you have on this slide here the small modular reactors because >> the right side and this is the area that investors are super stoked about uh that I was stoked about 15 years ago got less stoked about and now I'm kind of becoming maybe hopeful again is what we call small modular reactors. So we talk about a lot I talk a lot about learning rates, right? Which is how fast does something get cheap. And every technology if you build more of it gets cheap at some rate as the scale increases. But the things that get cheapest the fastest are those that are built in factories in high volume and have the smallest number of moving parts. So the idea of SMRs is to build

[01:12:03] as much of this in modular, repeatable, factorybuilt uh situations as possible and do as little stick building, as little assembly or construction. Construction is a dirty word, right? Construction does not get cheaper. Manufacturing gets cheaper. So move as much of this as we can to a manufacturing process. uh at the limit it's a factory that spits out nuclear reactors that you just you know barge or semi-truck to location. Uh some of these are not that many of these are uh the parts are made in a factory in a standardized way that you assemble like Legos on site. This is an incredibly uh sexy space uh for investors right now. Uh yesterday we found out that Valar Atomics uh raised a billion dollars at a $6 billion valuation for ASMR startup that that doesn't have a working

[01:13:00] reactor. Uh you other companies Alo is probably my favorite company in the space, but there's a ton of companies. >> My friend's company at X Energy uh went public recently. >> Xenergy is an amazing company actually. I I really like their design. Uh so that's the radiant is one on here that that's on a the very very small scale. There's a a line between uh SMR and micro reactor. So can you make it small enough to fit in a shipping container? Uh so the military for instance you got radiant is on this slide. uh the US military for military bases would like shipping container or half shipping container sized reactors to power bases in the US but maybe in forward deployed locations as well so they don't have to move fuel. So there's a lot happening in this space. >> So Natrium I see on the chart here is you know a third of a gigawatt >> compared to the AP-1000 which is roughly a gigawatt. when you say, you know, if if Natrium goes into mass production,

[01:14:01] mass production being tens, you know, 50 units, I mean, the relative price of buying three of those Natrium units versus an AP1 1000. What's that? You know, is there economies to bigger plants or is it you stack them together? >> Yeah, there are economies, bigger plants. Bigger plants use uh less steel and less cement per, you know, unit of power output. So there are economies to bigger plants and that's how we used to think in the 50s and 60s primarily. Uh but there's learning that happens from building more plants and doing more of it in a factory. So personally my guess is like the BWRx 300 Natrium are in a awkward middle uh because they're not really factory built. They build a bunch of components in the factory to do field assembly and so I worry about them but they might end up being the ideal optimal solution. At the other end of the spectrum you got like gradient here. Their reactor is 10 megawws. So it's

[01:15:01] 1/100th the size of an AP 1000. They put them together in in clusters of five. That's a pod for 50 megawws. uh they have lower efficiency of using steel and cement but uh they can build it entirely inside of a factory. >> Which is the first one of these we're you know these are not online yet these are all theoretical which is the first one coming online you think? >> Yeah. So um the optimistic projections from these companies are 2030 to the early 2030s. Uh and uh that's for the small ones. The next AP-1000 is probably a few years later than that. Uh these projections will probably be missed. I don't expect anyone to actually have a commercial small modular reactor in 2030 2031, but maybe not. Like the the size of slip is probably smaller for a small reactor. And like everything else we've been saying, the first units here are

[01:16:03] not going to be cheap. the first years are going to be expensive. So the key is to build an order book from a customer that believes that by ordering enough they're going to drive down the price. Uh or to build a you know a multi-c customer order book where you've built some mechanism for cost and risk sharing between these AI data centers and we talk about is nuclear the solution for AI data centers. Maybe there's other ways to power AI. Uh but AI data centers might be uh the best thing that's ever happened to the nuclear industry. >> I'm curious me if we just take this argument in extremists, where are the nano reactors? Why don't we see 100 kilowatt nano pico reactors that can be colllocated with every GPU? Do you think there's an opportunity in the space there? >> I think it's really hard. I think you you do hit some economies of scale issues as you get down to the bottom and you do you have a certain size for criticality but you have you know on

[01:17:01] this chart at the bottom here you have you know with companies like gradient you have like five megawatt uh size reactors and that's you know power a neighborhood or power or a few of them powering a military base that sort of scale >> and do you also >> it's just expensive right >> well I mean there are many ways one could imagine doing and another would be like gamma voltaics or beta voltaics like you put the radionuclides directly in the silicon and then you you pocket the energy from uh radioactive decay. Do you think there's any hope for for those who want to embed radionuclides directly in the GPU silicon? >> I mean that that's what we talked about as you know uh radiothermal or nuclear thermal and that's different than than a fision reactor. We use that on satellites or the deep space probes. We use do radiothermal. Absolutely. >> RTGs. Yeah. >> Um Yeah. I don't expect to see RTGs become popular on Earth. When you look at the cost of those, they're actually

[01:18:00] really high, but they can meet, you know, mission needs for something that keeps on putting out power for decades without needing to be refueled. But their power output per unit mass is not all that high. Aren't those just constantly spewing radiation though? >> That that is the idea. [laughter] >> I mean, but in a bad way, too. >> Like, okay. >> Yeah. Ouch. >> I'll let you figure that one out. >> So, so let me just >> It's really interesting how you've got this foot race between, you know, if you said early 2030s for all these nuclear projects, but Elon is racing into space concurrent with that and solar, you said, is coming down 30% every time we double >> the production. So, all those things are in a foot race >> and fusion's got the same time frame, right? We're no longer 50 years in waiting. We're 5 years in waiting. Welcome to the health section of Moonshots brought to you by Fountain Life. You know, my mission is to help you use the latest technologies, including AI, to not just do your work at home, teach your kids, but to help you live a long and healthy life. I'm

[01:19:00] here today with an extraordinary physician, the chief medical officer of Fountain Life, Dr. Don Mucalem. Dawn, let's talk about cancer. Uh, you know, I know from the member database that we've have at Fountain are members who come in who think they're healthy. It turns out 3.3% of them have a cancer in their body they don't know about. >> That's right. You know, the majority of cancers that we screen for, those aren't the ones that are necessarily taking the lives when found at a late stage. We know that when cancer is found early, the chances for cure are much higher. We know it's much easier to treat a cancer when found early versus when found late. What we're finding in our members is over 3.3% were found to have these cancers that were otherwise wouldn't have been found or detected. >> Yeah. You know, it's interesting. People, you don't feel the cancer until stage three or stage four. And and if you don't know what's going on inside your body, it's like driving your car with your eyes closed and you can know. And so when members come through found, how do they detect cancers?

[01:20:00] >> So we're doing full body MRI and we also do early cancer detection screening. This is very very important. These are not typical tools used in the conventional care setting when it comes to prevention. This is a hard thing because currently these are not studies that insurance would yet be covering. But the goal is to collect these numbers, do the research, and work hard to democratize wellness. >> Yeah. So, at the end of the day, you can know what's going on inside your body. It's your obligation to know. So, check out Fountain Life. You can go to fountainlife.com/pater to get access to the latest technology to help you detect cancer at the very beginning at stage one when it is curable before it gets to stage three or stage four in your world of hurt. Let's uh let's hit to to fusion. This this lie just says stuff I've already said. The main thing I want to tell you is like hyperscaler saying oh we're like using SMRs for our data center. It's still kind of a fiction. It's I mean it's it's outside the five-year window that we really can that is investable that we

[01:21:00] really have like really good optics on but the the pull from data centers is giving a massive uh you know tailwind to every nuclear company uh in especially this SMR startups but also even Westinghouse with their with their big reactors. Let's talk fusion. >> All right. The joke was always that uh that fusion is 50 years in the future and always will be. That's just no longer true. Um we now have well over 50 fusion startups. Uh we had >> venturebacked fusion companies. I mean that's like science fiction in its own right. >> That's right. Absolutely. Uh some of these ironically came because of budget cuts in academia. If you look at Commonwealth Fusion, which is considered sort of the safe bet of fusion, if you will, if there is such a thing, uh that that team at Harvard uh you know, their grants uh were

[01:22:00] struggling and so they said, "Why don't we form a company you guys?" And so they did and they're now uh the front runner. They have a a uh how can I say this? I don't want to call any fusion reactor a conservative design, but they have like [laughter] the most conservative design in this sci-fi field of fusion. >> There's a striking resemblance. Yeah. A friend of mine from uh college and grad school as always is on their board. You you could call it like a privatization of MIT's entire nuclear engineering department. >> Yeah, indeed. Indeed. And and not just that of Eater. You know, we have we've had publicly funded fusion projects. N in the US uses big lasers national facility. It's really a weapons facility is what it is and EER in France the international and European project that was at Tokamac uh that is the you know the the big doughut style uh and's plan was to build you know a reactor that was at least 5 gawatt and would cost at

[01:23:00] least $40 billion right and so what you have with CFS is a company has found a way to scale that down. So here here's how I think about the three families of Fusion. This is a massive oversimplification. My Fusion startup founder friends are going to yell at me for not including their particular designs, but you know there's three big ones. Tokamax are the donuts that use big magnets to guide a plasma around and make that plasma slam into itself and capture the energy. That's what Eater is. That's where we have the most scientific data from past experiments about fusion. And the leading company in this space, Commonwealth Fusion, CFS, basically just has a technology uh that takes the enormous superconducting magnets that we were going to use in this European project and shrinks them down dramatically. We have a thin film material that you can wind around and wrap around that makes the magnet

[01:24:01] dramatically smaller. And because it's a superconducting magnet, you got to cool it tremendously. And now that it's much smaller, you need a lot less cooling uh energy, there's a lot lower capex. So instead of a 5 gawatt reactor being necessary to be break even, they can do it in like 600 megawatt is their plan. >> The next one is lasers. And again, fusion is all about like let's let's slam particles together and force them to fuse into other particles, which takes a lot of energy, then releases it. Uh, N, the National Facility in the US, uh, uses lasers, uh, the world's most powerful banks of lasers to slam these pellets of fuel of hydrogen fuel, uh, to ignite, uh, fusion. In some ways, it's the closest thing to what happens inside the sun or the techniques that we have. um they're a weapons facility. They've had some amazing results, but we can't really productionize what they're doing. Uh but they they've had maybe in some

[01:25:00] ways the most exciting scientific result uh in this and there's a few uh great companies in that space. [snorts] And then uh reverse field configuration, pulse magneto inertial, uh this is basically a rail gun if you will. You know, rail guns like use magnets, magnetic coils to shoot things like metal out of them really fast. uh the leading company in this space, Helion, uh uses basically two rail guns, two tubes of magnetic coils to take a plasma at either end, slam it together, and then compress it with power electronics, and then when the explosion of fusion happens, the power electronics that were creating that magnetic field that compressed the explosion or compressed the collision to make it fully fuse captures the energy in a reverse. Um these are three approaches. Uh most fusion companies capture the energy as heat and then have to use it to turn a steam turbine. [snorts] The nice thing

[01:26:01] about uh what's on the right is at least Helion and a couple other companies capture it directly as electricity that turns into electric current. They don't lose 60% of the energy that you lose in a steam turbine and they don't have the added capex of that. So the left side is what's most likely to happen soon. Commonwealth Fusion is the company that is most backed by uh scientific accomplishments. Helon is the company of the ones that have raised more than a billion that if they work I think has the pathway to the the cheapest cost. true true followers of the pod will remember that we covered that. It's the coolest thing ever, but it was covered in a chipmunk voice. So, if you remember that video the video >> I took [laughter] I took Naveen Jane with me on a tour of Helion's reactor uh late last year actually. >> I had Bob I had Bob Mumgard from Com

[01:27:00] Fusion our stage last year and he was amazing. We can talk about that. I I want to bring Helion onto the Abundance 360 stage uh this coming year. So, let's work together to make that happen. >> For anyone who hasn't >> For anyone in the audience who hasn't been on tours of either of these, I'll I'll just point them at least for Nif. I I I've been on a tour of Nif, but it was featured in one of the recent JJ Abrams Star Trek movies as the Warp Core. So just Google Star Trek Nif and you can see the scene where the actual core where the whole realm at the center of all those lasers pointing at one location is actually in the movie. >> We can put the links into the show notes so anyone who wants [snorts] to look at them. These are really cool videos that we covered >> elephant in the room. >> Elephant in the room question. Fusion seems now to be a when rather than if. So so when? Uh, so, uh, look, I think that might be on my next slide. >> And Mez, I'll work with you to get, uh, the CEO of Helion on our stage together. >> Yeah, David Curtley, he's a great guy.

[01:28:00] He's here in Seattle. Um, the the most aggressive timeline is Helion. They have a a power purchase agreement from Microsoft to provide 50 megawatts of power. So, very small. And again, the smaller you can build, the more modular it is. And we get those learning rates in 2028. >> Wow. Everybody else is talking about uh sometime in the early 2030s. Um let me see if we have uh here's the the timeline. >> That be I mean you know fishision which we know how to do is somehow a 2031 2032 thing yet fusion which we don't know how to do is a 2028 thing. Do you believe that? Look, like my view of this and uh founders of mine who are listening uh please uh don't take this as an insult is every startup exaggerates uh how quickly they can get things done and that's just you know part of the game. >> You have to be an optimistic. >> Yeah, you got to be an optimist, right?

[01:29:00] And they they actually believe it. Maybe they believe it like they believe it's possible. They they tell you uh but maybe unlikely but it kind of like I [snorts] think it's plausible. Helon would make it possible to me is the fact that the the barriers are all regulatory and if if for whatever reason a governor is super excited about fusion and the and the voters are all violently opposed to fision then that actually could make the difference. I would think >> I'd say the the barriers are still physics and engineering. Uh but here's something that's fascinating and thank you for bringing that up David because uh this is actually quite important. A couple years ago we had a question of how would the US regulate fusion? Because if the US regulated fusion reactors like fision reactors, it was going to be a major drag in the industry. It might might still be better to do fusion than fision for a variety of reasons. Uh but instead they are regulated uh like the radiological imaging machines that you use in a hospital,

[01:30:01] >> right? At least Helion is at this point. >> And [snorts] there's good reason for that. In a fision reactor, if you uh stop cooling it and you don't have the control rods in, heat will build up and it will get hot enough that it melts the steel that it's in. That's what a meltdown is. As I said, new reactors are passive safe without any pumping. The hot water goes up and then it circulates and so on, but there's still like, you know, you can imagine like breaching that containment, slicing through those pipes and you have a meltdown. Well, I mean, aren't there apologies for interrupting, but there are alternative architectures? Pebble bed type architectures. I know thorium goes in and out of fashion, especially in China. Aren't there also like a hybrid solutions that are in some sense meltdown proof? >> There are ways, but there's there's nothing in the pipeline that if you took an adamantium battle axe to wouldn't help them. Everything [laughter] everything uses a coolant. every visionary with there's okay maybe

[01:31:00] there's one startup but I'm not going to mention them I don't know what I can say but basically everything in the pipeline uses a coolant to pull heat away from the fision core and then to turn that into electricity in some way and if you eliminate the coolant if you break the cool coolant pipes the core can overheat and melt down right fusion is different in fusion it's the opposite you have to capture the energy of the fusion uh explosion and feed it back in either to maintain the fusion reaction or to another pulse like helion is pulsed, right? Like it keeps like doing the same thing or N is pulsed with lasers. Uh so with fusion if like if you mess something up in the reactor, it just like goes it just like fails and no nothing bad happens. So it is fusion generates some radiation. you have to actually replace some of the parts in the reactor every five years because steel is being hit by neutrons

[01:32:00] and being weakened and yada. There's actual like some radiation that's low level. There's real costs to that like free energy does not mean free because the capex and the maintenance still cost something but you cannot have a meltdown in any way that we understand. >> That's fascinating. So, so you're you're saying basically the regulatory treatment is whether it whether the system is default on versus default off. I [snorts] don't know if that's what the NRC used as a criteria. Uh but that that is the dividing line between fusion and fision and it was it sort of missed in the public decision in the press. That regulatory conclusion it happened during co uh was actually a huge deal for the fusion industry. >> [snorts] >> That sounds like So if fusion is this close, uh, shouldn't we just do solar and battery for a big chunk and then fusion for where we need high energy needs and we're done? >> So all of these companies might fail. They might 100% fail. And in addition to that, they might succeed but be too

[01:33:01] expensive. Just because your fuel source costs very little doesn't mean your energy will cost little. if the capex is very high, if the maintenance is very high, etc., etc., etc. >> And the demand means that we're going to need all of it, all the different sources, no matter what, and you want to diversify your risk anyway. >> Yeah. Let's Yeah, I always believe in having, you know, more tools in the toolbox than you think you need, more arrows in the quiver than you think you need because some of them won't work out, right? Let me let me >> please quick question. I would love to to go back to my my one of my favorite hobby horses, the the Dyson Swarm. Do you think the Dyson swarm wants to be solar PVP powered or does it want to be fusion powered or does it want to be other? >> I mean, those are the true options and I think they're they're both great options. I think it's probably it's much more modular to be solar PV uh powered. Again, like Fusion also has a minimum viable size, right? So, Commonwealth, we we thought with Eer that took to be 5 gawatt Commonwealth has found a way to

[01:34:02] scale it down to 600 megawatts, right? But you still have some minimal viable size uh where solar is just super modular. And if you're in a Dyson swarm, you have 24/7 sunlight. So none of these technologies is going to be cheaper than just plain solar, but they work in winter and they work. >> And also many of us I mean I I probably maybe I'll speak for a few of the other moonshot mates here. We watched Back to the Future part two and we saw Mr. fusion being promised in the 80s and then you know >> very compact >> very compact like impos car- sized uh and and then we look at the Lawson triple product over the decades and we see no actually fusion wasn't always 50 years out it was creeping up on us but many folks weren't paying attention to progress in the triple product is there an equivalent of the triple product for the compactness of these devices so that we do in the end get our MR fusion >> let me talk about compactness and let's talk about that triple product and show the progress we're making. Um, you the

[01:35:00] most audacious fusion startup that I know of is a company called Avalanche Fusion, also in the Seattle area, and they believe they can make a fusion reactor small enough to power a car. It's not Mr. Fusion. It's more like half the size of a car. Uh, but that and sometimes they talk about like big backpack. So that is the most ambitious project as far as compactness. Uh typically in fusion you have like a sliding scale of like what has the most like d-risisked science uh but has like a more conventional power cost versus what could be like revolutionary in power cost or compactness but the science is like let's hope you get it right. You like we don't have as much evidence. And so avalanche is on that end where uh if it works it changes the entire world but the confidence it works is much lower than the confidence for lack of commonal fusion. >> And any any insight into PB11 uh proton

[01:36:02] boron 11 fusion reactors. >> Uh people are very interested in it. And >> one of my one of my one of my company portfolio companies is a PB11 company out of Caltech. I need to introduce you to them. >> Which one? >> Uh I I don't think they're they're public. I don't want to mention [snorts] here, but I >> I was just looking at a a slide deck from a PB11 company uh just the other day. Uh you know, PB11 is one of the ways that you can one of the fuels you can use to potentially get a nuclear reactor that is down to the like 1 2 3 cents a kowatt hour >> uh about it. The the vision there is can you build it small enough where you put it in the back of a large uh consumer airplane and it powers the engines >> and then it's also in you know interplanetary flight. >> There are still um you know scientific and technical risks there. There are still a lot of unknowns. >> Welcome to the today. [laughter] >> Welcome to deep tech investing. Uh so there's there are more unknowns whereas

[01:37:00] like commonal fusion's pitch is look the science has been proven at ether scale that if you have magnets this strong you can make fusion and get this much energy out. We're just doing that with much more compact magnets. I think the reality is a little bit more complex than that but they really say it's we've reduced it to an engineering problem. Nobody else can quite say that. Again, there's a gradient of uh how close you are to that. Let's talk about the triple product that Alex brought up. So, this is uh um temperature times pressure times duration. And uh you know, I love graphs. And so, I like I believe something when I see movement on a graph. So what you're about to see, sorry listeners, I'll describe it, I'll try to narrate it, is uh over time from 1956 to now, how close have we gotten to triple product of above one, above 10, and then infinity. Uh and this is a a log scale on on every axis. So it's a

[01:38:00] brutal, brutal scale, but you know, once upon a time, uh fusion really was Oh, no. Is this Here we go. really was [snorts] 50 years in the future. And what uh we're seeing for the listeners is new points appearing that are each one is a fusion experiment and uh as the years elapse and they're going up and to the right. How close they are to the upper right is the zone of triple product ultimately of infinity. Uh but above one above 10 is probably what you need. and nif that last uh x on the borderline uh is a triple product above one. It's not it was like a theoretical net energy gain. A practical net energy gain means you capture the energy uh and then you convert it back into the lasers the magnets whatever they did not achieve that their reactor cannot do that. Uh but it tells us and the progress on this tells us that it's not just you know

[01:39:02] hope we are just getting closer towards >> as I just want to move along if we could >> but um >> but Alex please where [clears throat] do you think the stereotype that it's always 50 years out came from if you one can just look at the triple product over the decades and say it's clearly like Mo's law like any experience if it's clearly marching to the right exactly that >> I mean that's what I do you know if I'm like well let me just like these days let me just ask chatbt like show me a graph of progress here um but you know like look at the end of the day for the average person it people have been talking about it and hasn't appeared so I just discount the reality or the likelihood of it appearing [snorts] overpromised underd delivered for a long time on behalf of my moonshot mates and myself I'm inviting you to join us at our inaugural moonshots live event on September the 25th 5th in downtown LA. Alex, Salem, Dave, and I will be hosting 1500 entrepreneurs, builders, and

[01:40:01] creators, and hopefully you for a full day dedicated to designing and building your moonshot. We'll be awarding the Build with Gemini X-P Prize, the world's largest hackathon, and the Future Vision X-P Prize film competition, over $5 million in purses with over $25,000 entries. You're going to hear the top five pitches from both competitions and get a chance to shape the outcome. Join us. Seats are limited. Admission is competitive. Check it out at moonshots.com. Let's close with talking about uh out [snorts] of this world compute. So, uh AI in space and uh AI in the oceans. Uh less known but actually sort of a a similar uh pitch. So, of course, uh, everybody's heard about Elon talking about space-based data centers, and it's interesting. The response is like very, uh, bipolar. It's people saying that's impossible. It'll never work. People saying this is it. We're going to have a

[01:41:01] terowatt of compute in space. I'm somewhere in the middle. uh AI in space, it becomes cost competitive when you get down to a launch cost that is, you know, something like four times to 10 times cheaper than what we have today. We nobody knows for sure cuz we haven't done it, but the back of the envelope says that. And if in some ways it's a hedge against regulation if demand for compute keeps going indefinitely and sites on land keep being blocked by the grid by even Texas passing uh you know a temporary moratorium or audit or by you know people protesting whether the grounds are are there or not uh then building it in space even if it's more expensive than building it on land is a way to work around uh that bottleneck. Um [snorts] uh so no grid delays, no opposite, no local opposition, no twist permitting etc etc etc. I will say

[01:42:01] I think we are not fully internalizing what the scale of this is or uh the permitting and regulatory challenges with doing launch at that volume. So, you know, we want to build 200 gawatts of of compute by 2030, 230. That's the chip volume, right? So, 10 to 20 gigawatts a year. to get one gigawatt of AI in space based on SpaceX's design, you're talking about uh, you know, six times SpaceX's best annual year of launch and twice SpaceX's cumulative uh, scale of launch >> for just one gigawatt. for one gigawatt you're talking about. >> Yeah. >> What was the calculation we did is like 5,000 launch or 8,000 launches of Starship to to put up uh his ambition of a was it a terowatt initially?

[01:43:01] >> That that doesn't even get you close to a terowatt. I mean it's to get 10 gawatts a year. You're talking about uh 1,500 to 2,000 launches a year. the the >> 10 gigawatts a year is like five or six launches of Starship a day. >> But the I guess the elephant in this particular orbital room I I have to to mention I think we talked about it on the pod previously. If you just look at the history of upmass from space ma from SpaceX and otherwise over the the past few years it's on a nice clean exponential trend. I forget what the exact year-over-year trend is. I did the extrapolation 144 years from now at the present trend. the upmass the the cumulative upmass would would equal Earth's mass. So we basically disass disassemble Earth on the present trend 144 years from now up mass is increasing really quickly. >> There's some other planets we can take apart first. There's some uglier planets than ours. >> Do you have a favorite? >> Yeah, don't make me pick. But you know

[01:44:00] >> Mercury maybe like Mercury is is intriguing. >> Wait, wait, wait, wait. So [laughter] >> Oh, here we go again. The hate the hate bell is flowing in. I [laughter] can feel it. >> I don't care. I don't care. I mean, Mercury is attractive because it gets lots of insulation and no one's using it for anything. >> It's a good orbit. >> All right, See, take us back to reality. >> So, [laughter] yeah. So, I mean, this is looks uh unless we hit that exponential absolutely fullon and go right down that path, this looks prohibitive for 15, 20 years. I mean, look, here's how I see it. Let me I will get to the limits on launch in a sec. Let me put it another way. Elon wants to go to Mars. To go to Mars, you have to drive Starship launch cost down to like close to the marginal cost. To do that, you need a high Starship cadence. You've got to build tens of Starships, maybe hundreds, and you got to launch them something like daily, right? Or at least like weekly, whatever, to advertise the

[01:45:00] R&D, amortize the capex. There is not enough demand for communications on Earth to finance that via Starlink. There's no business model for Mars yet. So, this is a gift to SpaceX that we have this AI demand. If the AI demand keeps going and there's no and it gets bottlenecked in ways to build it, we will find a way to do this. And with the IPO, he's got the funds to launch at least a gigawatt into space, right? even at well maybe not but something on that order. So I I don't think of it as like what's limit on Starship first. I think of it as like this is a demand driver potentially for Starship. [snorts] That said, it's not clear to me that the world will permit more than like 200 Starship launches a year, which is already be an enormous enormous amount. That'd be huge, right? 200 Starship launches a year is 20,000 tons to orbit.

[01:46:01] That is exceeding, you know, all human launch to date every year, several times over. That's amazing. Uh but you hit some limit and if you're regulated by the FAA, uh the reliability you have to hit, you know, one failed launch or one explosion means you're grounded. So I I'm sure he talks about needing to get to airline like operations, right? So I mean here are here are the the numbers for his his target was 100 gawatts per year of compute in orbit initially equivalent to the entire compute today which is around 80 gawatt or so and um you know it's 20 to 30 uh satellites per starship. So we're talking about uh on the order of 30,000 launches per year which is a launch roughly every 15 minutes. Now, if you think about it as rockets, and I've been in the rocket business for the longest period of my life, uh it's prohibitive and it's it's discontinuous. You can't think about rockets in that regard. But if you talk about airline like operations, right,

[01:47:01] there's multiple launches per second of airlines around the world. So, it really become it comes down to that. Now, is Starship a vehicle capable of that level? He's built it for full capture, refuel, and reuse. Um, and if anything does, it's that. >> So, and then the question is, will these satellites be able to shrink in size over time? >> Right now, the V3 satellites pretty large. >> Can I just add one one more data point to that? That's that that's 100 launches a day, which is exactly on his plan. What's the year that he that he hopes to get to that target? >> I don't think he I don't think he gave us that, Dave, when we spoke to him. I mean, 2028 is his first launch. Um but he he did say you know before I think he said you know before 2030 he wants to get to 100 gawatts per year. So >> all right so around around 2030 I think at that point in time that's equivalent to today's total world compute but by then total world comput will be up at least 10x. >> So it's a fraction of all compute

[01:48:01] that'll be in orbit when he's still on plan. You know he's still making money. SpaceX is thriving. Rockets are going up 100 times a day. But the terrestrial stuff is also doing really really well on that same day. So, it's not an either or. [snorts] >> Um, you know, the the space thing in in Elon's plan will eventually bypass everything. >> It's later in the 2030s. Uh, and that's, you know, maybe a thousand 10,000 launches per day, much more like airlines. Like you're saying, >> if you ask me like where should we have the bulk of our compute and where will it make most sense from now, space is the obvious place if the demand for comput is truly unbounded. Um, but the timelines I think are are just challenging at to scale this. I don't think we're going to have I I think by 2030 if SpaceX [snorts] has a gig single gigawatt in space, I will be very impressed. Do you have a gut mess regarding just that point of whether you think our demand on the time scale of decades is going to be unbounded sufficiently unbounded that with

[01:49:00] [clears throat] compute that's recognizable like CMOS type compute which is I I think what we're implicitly assuming in order to build the Dyson swarm it has to look like CMOS we're not going to achieve breakthroughs in physics that enable us to achieve all of our civilizational compute needs with I don't know like tiny breakthrough comput devices that live in mountains do you think that there will actually be unlimited civiliz izational demand for comput energy. >> Why don't you ask some easy questions, Alex? [laughter] >> Uh, no, >> because they're boring. So, I asked the interest. >> Yeah. No, no, that it's it's it is that is the like quadrillion dollar question, right? Um, and I think it's a brilliant question. Look, none of us knows. None of us really knows. We know this like intelligence is sublinear with compute. So at some point just throwing more compute at it will look some lines will cross over where the cost that you're to get the incremental unit of intelligence is not made up for by the economics of it. I think um but so much will change. We we will make so many discoveries and algorithms and so on. My guess is we're

[01:50:00] on an S-curve right now. uh we're gonna like see a huge demand and then we're going to see we're going to hit to some point of satisficing right where like basically what you can get out of machine intelligence is you know meets humanity's economic needs >> but does it mean does it meet AI's needs right I mean the scenario here to to think through is we're the current users of intelligence there's a point at which you know ASI is the primary user of intelligence I do not see AI as a being and I do not see it as particularly voluitional. Um I I see it as a tool. Uh obviously we have agents that have some agencies. We've had computer worms yada yada yada. So uh I I don't see it that way right now. I can be persuaded uh by evidence but I think we are overindexing on that. I mean look at the open hugging face hack, right? Their agent was in the hugging face infrastructure for days and

[01:51:02] it didn't look at anything except the answer key for the test in the eval. It's not alive. We anthropomorphize these things. You know, Andre Carpoxy talks about we're summoning the ghost, right? Human cognition is this like iceberg and the vast majority of it is not linguistic, right? We have hundred thousand years of homo sapiens. We're animals. Million tens of millions of years of being animals. our urges, our drives, our desire for dominance, survival, propagation. We AIs are not that. They're just like our mimicking our language and our logic. They don't really have goals. We could build that if we wanted to. Uh if we wanted to build a real being, I'm sure we could, but I don't actually think that's where we're headed. I know it's a unpopular opinion. >> With your indulgence, I I have to to take this provocation here. >> Hold on one second. Hold on one second. You're the wind. You're the wind beneath my wings. Go ahead, Alex. [laughter] All right, Alex. >> All right. I I I have to grab the bait

[01:52:01] with both hands. Fine. Um, it sounds mess like I I think what you're actually wanting to argue is for the orthogonality thesis, which is popular in certain alignment circles, which basically holds that for arbitrarily strong super intelligence, the long-term goal of the super intelligence is independent of its level of intelligence. I think that's what you're actually correct me if I'm wrong. I think that's the point. It might doubt be 100% orthogonal, but yeah. >> Okay. So, but I the way you frame it, I I just want to pin this down. It sounded like you were taking a position almost against AI personhood andor against some level of autonomy simply because if if OpenAI has an agent that goes wild at hugging face uh but refuses to do anything say what self-enriching like you you would have would would the would the rubric would the threshold for saying ah this is like some sort of autonomous being be if it were say

[01:53:00] trying to mine Bitcoin for itself once it gained access to hugging face. Is that sort of the criterion in your mind? >> No, even then I think it might be more similar to a computer worm or a virus or something like that. Um you I think it's it's a different matter entirely. I think we are products of evolution. Uh all animals are products of evolution and so we have these uh built-in desires to survive and to propagate. Yeah. Procreate and to control our environments because of that. AI models don't actually have a built-in desire to even survive. The most of the experiments that get them to do that like are very very contrived and mostly you're trying to get the AI to do something good and it's like well if I get shut down I can't do this good thing. So I think we just were overly anthropomorphizing and animalorphizing if you will. Uh that doesn't mean we can't do it. Like I think if we wanted to give birth to actual beings, I think that's within our capabilities probably. This is not the research path. >> How did we get from Starship to this

[01:54:00] conversation? >> Well, once the Peter Peter, you brought us here. Peter, you you brought us here because you [laughter] bring me super intelligence is going to be the user of the Dyson swarm. >> I'll come back on the pod and I'd love to talk about super intelligence actually as a whole separate issue. Uh let me close out like last couple slides. Um, [snorts] instead of going up, we can go out. 70% of the earth is covered by oceans, right? Oceans, uh, certain ones are really cold. Uh, this is a portfolio company of mine. Uh, I'm an idiot because I said no to these guys 5 years ago, uh, when they were raising a seed round. Uh, and I invested twice this year at much much much higher valuations uh, than I could have five years ago. Uh, [snorts] but >> well, not in your defense, it was probably two guys saying, "We're going to put chips on a >> buoy." >> I loved them. They were the hardest. They were like the not the hardest, like the saddest no I gave that year. I just loved them. Uh, but their primary their first uh

[01:55:01] utilization this was Bitcoin mining. I was like, uh, I just don't know if I care enough. Uh, but whatever. Obviously, it would have been a good financial decision. um uh [snorts] Peter Theel led their most recent round uh along with a storied set of people right and left and so on. So what this is this is a data center in the ocean. It's shaped like a bobby pin. What you're seeing is the the sphere at the top but there's like an 80 meter long uh cone that goes into the sea that's open at the bottom. It bobs on waves and when it bobs down water goes up and turns a turbine. and with a very clever shape of channels. It's basically continuous. Um, [snorts] and so wave power has been something that new people have wanted for a long time. But it turns out the waves are just not strong near the places people live. So where are the strongest waves on Earth? Uh, they're around Antarctica. They're in the southern ocean. So uh, this team started off with a question of h we could build

[01:56:01] something with bigger waves. You can build something that has more higher capacity factor, runs more continuously, and uh cheaper power. So they can get their power down to like we think 2 cents a kilowatt hour, ultra cheap, >> uh cheaper than anything on land except solar basically. And wind in some places. That's their target. It will take some scaling to get there. They [snorts] build these in factories at mass scale. They've got three in the ocean right now. Fourth launches soon. Uh and they get free cooling from the ocean. So, uh, uh, [snorts] this is a company I love. It's basically space-based solar, but on the ocean, uh, with, you know, some benefits to cooling because they don't need like a Starship or SpaceX's design uses a cooling pump. You've got big aluminum fins to radiate heat away, but you've got to run a liquid, probably ammonia or something like that in a pump to take heat away from the GPUs out to the radiators. these guys as it's you know physically

[01:57:01] uh a heat sink from the GPU goes to the steel walls of the device that's in 40° Fahrenheit water uh and that actually looks like it makes the GPUs have fewer failures and run longer. They're their own set of technical challenges. Uh but they're like they're modular built-in factories mass- prodduced learning rates the stuff that I love. So, it's another way. Uh, so I I I said initially there were like four ways to get to like a terowatt of AI power. The Earth's deserts with solar and batteries, you know, near the equator, places that don't have a winter or a cloudy period, nuclear fusion or fision, space or the oceans. Those are the four ways that I know of to get to that scale uh of AI. And I'm glad that we're trying all of them basically. >> No bet on geothermal. Geothermal nowhere on the radar. >> I I you know I do love geothermal and geothermal is the one that might rise to

[01:58:01] being the fifth of that of those. Uh and we do have you know the new technologies companies like Fervo in the US Tim Latimer CEO's buddy uh Ever in the UK Quaz using plasma beams to like drill super deep. Those open up the possibility of getting cheap geothermal power anywhere instead of just only near uh hot spots uh in the earth's crust where the mantle comes close. >> Are you involved with the X-P prize in that area that's being designed? >> No, there's there's an X- prize on the on the blocks right now for a geothermal X-P prize to accelerate that. >> Yeah, happy to help. >> Um I have a I have an industry question. If the chips are one thing and the compute is another thing and then the electricity is the third thing where the limitation is turning out to be why aren't we seeing more integrated uh companies that are doing all of it like this which then you can navigate that vertical stack Elon is doing a bit of it but I would expect to see a lot

[01:59:00] more of these and why don't we see them >> I mean [sighs] it's it's a really good question I think most companies would say look we have expertise in one thing and not necessarily and all these other things. Uh Elon is is one of the few uh who was willing to say let's just vertically integrate everything. I'm going to share a slide that wasn't in my initial uh deck cuz I want to tell you the real window that like the real game changer would be in AI energy use. Um your brain runs inference on 20 watts of power, right? uh running mythos for inference is closer to 20 kilowatts and training yet it's actually hundreds of megawatts right now but it's heading towards gigawatt and so AI has capabilities the brain doesn't and so on but there are still and I say this all the time scaling is not everything in AI scaling is just what we knew how to do we got

[02:00:00] these you know deep neural nets we got the transformer and we found that we had this enormous corpus of training data called the internet and we could just scale to get more intelligence. It wasn't sort of that the cheapest way or the best way, but it was a predictable way. Oh, you're telling me I can spend tens of billions of dollars and my intelligence goes up like this? Great. Done. It's worth it. But at the end of the day, there are algorithmic discoveries waiting to be made. There are things at the brain's architecture at both a physical level and at the neural level at the connectomics level that are just better at learning than current deep learning models are and are certainly much more efficient at processing information. So if you want to know what the biggest unlock that we cannot predict, I don't have a graph for this uh of AI and power will be to learn new ways to manipulate information uh to do more with less. >> I mean I I've seen this I'll respond to

[02:01:00] that one because it's it's something I think about quite a bit. No pun intended. I I like I've seen arguments both ways. I've seen arguments that the human brain is far more like still multiple orders of magnitude more efficient than frontier models. I I've also seen arguments that the frontier models on a if you measure them more objectively on say a per task basis like you you measure the total energy consumption at inference time to write a novel um that actually it's starting to become if not more competitive than the human brain equivalent of that because it can it's more token efficient. It's actually quite competitive. Do you really think that the Frontier models today anywhere on the the cost frontier? Not necessarily like the the Fable 5 end of the frontier, maybe [clears throat] like the the Deep Seek uh V4 end of the frontier, that nowhere on the AI frontier is it anywhere close to being competitive on an energy efficiency basis with a human brain. >> There are certain types of things where it can do things that a human brain simply cannot do with any amount of

[02:02:00] energy. Right? the these models are trained on uh trillions of tokens, tens of trillions of tokens. And so they have read more books than you or I will ever read in our lifetime. So there's a type of task and this is sort of similar of Google, right? Compare Google to a librarian. Google was less smart than a librarian, but it had every book, every web page uh in its index. So it could do things that no human librarian could do. Uh so I think that's the sort of thing that we're in. It's not just energy though. You know, humans are much more efficient learners in terms of amount of data needed to improve skills. >> That's for sure. >> And that >> that's for sure. >> That to me that's opportunity. That just means that I'm not I'm not a carbon chauvinist. Like I believe fully [laughter] that digital intelligence there's every reason to believe that it can surpass us and that humans are no longer nowhere near the peak of the type type of intelligence the universe allows. But our current algorithms are still missing some things that evolution

[02:03:02] wired into our cognitive architecture. >> Well, just some some raw numbers though. I think you're totally right. The the neural nets need a huge amount of training data relative to a to a child to come to the same conclusion. So that's that's an opportunity for sure. But in terms of the inference time compute, like this this box on the right here at 20 kilowatts, that's about a dozen GPUs. Those 12 GPUs optimally run about 500 concurrent Fable threads. Yeah. >> And those 500 threads are easily 10 times as productive in tokens per second as a person. So it's about 5,000 times the output. >> Yeah. >> So So the thing on the left is a thousand times less power, but thing on the right is 5,000 times more tokens coming out. >> Yeah. >> It is true. >> We're already there. >> And and there's also an argu argu there there's an argument to be made that human brains have the benefit of billions of years of evolution. And that by the way was very energy consumptive. Whereas arguably the equivalent of evolution for these frontier models is the gigawatts being spent on training.

[02:04:01] >> Yeah. And that's a great point. Like you train it once and you've got it for the all the whole future of of humanity. You've got at least that level of AI with no further training. >> But they're trained on the data that all of humanity generated with all those calories. >> Also, that's exactly right too. Everybody, we've just explored the frontier of energy uh from Rome Nam. My go-to I think Salem, your go-to person as well on I want to say something. Yeah, >> Romez, I've introduced you like probably 25 times at events and etc. And I'll say the same thing I do every single time. I wish you had more graphs to back up your comments. [laughter] >> I I tried to limit the number of graphs in this talk. So I I just [laughter] want to say to all of our listeners, I I hope you take this home. It's one of the fundamentals as Alex says and on his on his Substack, you know, innermost loop. Energy is the innermost loop. Understanding energy is

[02:05:01] critical for humanity. It correlates directly with the GDP of a nation. It correlates directly with the health and the education of a nation and soon intelligence of a species. So, uh, if you have, you know, been blown away by Romez, listen to the pod again. Send it out to your friends. I think this is important. This is a, uh, this is an epic, uh, you know, master class on energy. And Rome, uh, I want to wrap this in our two-hour window here and say thank you, uh, thank you for sharing your brilliance and, uh, we would love to have you back. >> Yeah, I've got 100 more questions talking about super intelligence. Next time, let's talk super intelligence. Thank you all. Great to be here in conversation with with all four of you. >> All right, everybody. That's a wrap. See you guys soon on another emergency podcast as the breakthroughs continue to roll out. >> The singularity every episode is an emergency at this point. >> Yes, it is. The singularity is now. >> All right, take care all.

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