Transcript
0:00 R, show me that gun down. It looks like if you lie down, you're going to kick your feet through the wall. Like, dude. Yeah. Like if if I like if I have a if I have a night tear, my foot goes right through the wall. >> Yeah. Take a look at Take a look at the pole in the middle of the room. >> Rich dreaming about Brad Gersonner tonight just like fighting the wall and kicking the wall. inspector in there.
0:30 >> My room is fine. It's just that I got two two stickle beds, which was kind of weird, but besides that, the room was okay. >> That room is Look at that carpet. You know, that room's nice. Yeah. They just said, "Yeah, you break the shitty one." >> I know. Talk to Michelle. >> Yeah, I got to talk to someone. Okay, you guys ready to rip into it? You guys ready to start? >> Yeah. You know, >> everybody get in bed for the cold open.
1:00 >> Let me jump in. >> Hello everyone. Welcome back to another episode of Semi analysis weekly. In this episode, I'm joined by Jeremy and Rake, our experts from the data center model. We're going to talk about their article, data centers 2027, the year of acceleration, 50 gawatt in a single year. this one comes from a bit of a backdrop. We just the other week, Brad Gersonner from Altimter was showing our data on the All-In podcast and then his BG2 interview with Jensen and they were talking about how our forecast of 43 gawatts in 27 is too aggressive.
1:37 Well, we're going to dig into why that's not the case this in this and we're actually increasing the forecast. So, when people think that only about 25 gawatts are going to get built, we're going to go through exactly, you know, what the FUD is about. They talk about moratoriums and other political restrictions. They talk about power generation. They talk, you know, about all sorts of, you know, reasons why this might not be the case. But guys, I don't want to walk through it.
2:02 Let's talk through it with you guys. welcome, >> man. Thank you. Thank you. >> Thanks for having us. >> Yeah, we got a lot to lot to talk about today. It was a good one. >> Okay. So, before we get into the actual content of the article, how about we do lay the land and you guys give me a little bit of history on your track record with the data center model. Jeremy, can you tell me a little bit about the history of this model, when you launched it, and just talk about some of the forecasts that you've made in the past and how that's played out in terms of like fidelity of the model?
2:32 >> Sure. So, the model launched nearly 3 years ago now. we had a we published an article actually in March of 2024 to discuss publicly some of these results that we got from building the first iteration of that. so that article is still available today. is a AI energy dilemma rates for data center space whatever and so we start this article by sort of showing other market forecast out there and then putting our own which was materially ahead of many other firms like I don't know McKenzie or whoever else was making forecast these days a and so like that has largely of of course been proven right we've increased the forecast a bit since time but overall the orders of magnitude there. we were expecting back in early 24 again a material acceleration in 25 and then in 2026. the way we do this is always by combining several data points. so we use data from the chip side, we use data from the data center side, from the energy side. We always triangulate as much as we can through everything we can we can follow. another thing I could point you to is or article a few months ago called stopped saying half of US data centers all delayed where we showed this chart of our 2027 number and how it how it has been revised over the different versions of our data center model and real is that it has barely moved right so we we're always sort of expect we're always expecting >> sorry what it was the 2026 one though >> yeah whatever 26 27 people can can go Okay. Same thing.
4:11 >> It's all right, Jeremy. It doesn't matter which year it is. >> Yeah. Yeah. You can pick any year. It doesn't matter. >> All right. It's 2026. Sure. Yeah, exactly. So, it's been pretty extremely close. again, like we've been doing this for for nearly three years now. So, the the track record has been there now. the the methodology is actually not that complicated. you know, you just you just got to be thorough and and comprehensive and make sure you you you got everything. and so we obviously spent a lot of time and built a whole team to to ensure that.
4:44 But that's what got us there is now sort of we have extremely strong submitts pointing to 27 being a gigantic year many different subcomponents that we can talk about in depth. And so there we are after dear Brad called us out publicly and cut our forecast in half like no this is actually at least some number we made up there is extly behind it you know and stand by it.
5:17 So let let's try and walk through where some of this opposition comes from. Rake, like when you hear people who take our number and then cut it in half based on a hunch, what's the hunch actually coming from? Like is this purely moratoriums? Is this the supply chain? Is it capital? Like labor? >> I mean, it's a number of things, right? Like I think when you read a lot of the news articles or you read a lot of the like kind of sellside reports or anything like this, they all kind of hinge around the same I don't know like FUD I guess or like fearinducing topic where it's like the moratoriums are going to you know get rid of all the data center build out in the US like it's all over they're canled right and then you have like other reports coming out where it's like people not totally covering every data center in the US but rather taking headline numbers and saying oh well this headline number was there before but now this got cancelled from a moratorum and I mean it's like that and then the energy side of things where there's no grid connections anymore sure like you know these data centers are never going to get power there's there's a number of things labor you know like the actual buildout itself millions of things here but the kind of issue is is that nobody digs as granularly into it as we do right like Jeremy brought up that it's granular but what that literally means is we go sight by sight, building by building, right?
6:38 Like not even campus level, but building by building, permit by permit, power allocation by power allocation, buying satellite photos. We go through, estimate starts of construction, see when the whole how the project is progressing, when it should come online. It's hard to refute any of this, right? When when I'm physically looking at all of these data centers under construction, I don't know how I could haircut it, right? These are the numbers that are adding up when you count all of this. And so we start we have that and then we also address these same problems that people are worried about right with the moratoriums. We said okay then let's you know also count all of them and map all of them. We went to like you know over 400 moratoriums combined it with every data center that we had or like you know mapped into the region or the city whatever jurisdiction might apply and found you know like 10% of it was actually being affected out of all 400.
7:33 energy, same story, you know, grid headroom and then you lead into like behind the meter solutions where you know, maybe you don't have to have grid headroom in the first place. I can just build a on-site generation project, right? Number of ways around this. Point being is that these topics are broadly true, but they don't apply to every project. And when you dig into the like appropriate projects, the ones that are under construction, they all pass this bar, right? All of them pass the bar.
8:01 And that's kind of why our methodology can give us these numbers and why we have such confidence in them. >> Yeah. And and take me through the individual projects. Like one of the great charts in the article was just this from Durk to data halls one where you're tracking three individual projects from you know when they broke ground back in 2021 or 2022 to when they're fully built out and the data halls are available. Clearly these projects that we're talking about that are targeted for 2027, maybe moratoriums cover cancellations and to a smaller extent delays. Can you talk to me about the chance that half of these construction projects slip by a year, two quarters, enough to push them into 2028 or something? What's the risk of small delays resulting in a change from 27 to 28 or something like that? looking at all the data centers that we have before, right? Like we have thousands in the model, we've reviewed the thousands over and over. You get a sense of what looks like a delay, right?
9:03 Or what might constitute a delay or it's going to be, you know, maybe there's a winter storm, right? Like in northeastern US during like the Terraolf buildout or the Nebia's buildout, maybe there's, I don't know, like a equipment problem, right? Like the transformer blowing up at the core scientific site, right? There's a number of things that you can kind of see or you can kind of gauge from like public reports as well as you know overly aggressive timelines where you start to understand what the buildout actually looks like on a timeline perspective, right? And so it's in our view timelines at 12 months are like pretty aggressive, right? Like these are quick timelines, especially when you compare it to the historical industry. These are quick timelines. And so when anybody's guiding like sooner that 12-month timeline, it already rings a red flag. And then if it's a 12-month timeline, you know, from a developer that just came out of nowhere and like some of the permits are kind of like obfuscated, power source is offuscated, maybe we can't identify it perfectly, maybe there's nobody signing or being the tenant of the project. All of it kind of leads up into enough of a question where it's like I don't totally know how certain, right? So it's not to say that these things catch like don't catch us off guard. they can catch you off guard, right? Like I I didn't predict a winter storm, right? Like it's not my job.
10:25 but but the point is we can get close enough to where it's like, well, you know, we have enough of a filter to not let these longer these longer duration projects become 12-month projects in our methodology. >> Yeah, you're already considering the the potential for this. So >> yeah, >> just to build on that super quick. this is also why it's somewhat counterintuitive to apply a haircut to our numbers. We're admittedly we're being a bit conservative on some things, right? Like there are sites under construction right now and they don't add all their megawatts in 27, right? Or maybe they don't add mess and 27 at all in the case of some international instances, right? We're not being overly aggressive either, right? We're taking all of these factors into account and taking a reasonable timeline. And so adding a haircut on top of that is doing a bit of like double counting almost or you know doing the same work over again where we've already applied it. And so you end up with a I guess not our number but we we like to dig our numbers pretty good.
11:28 >> Yeah. I mean look the other thing is we're obviously quite a lot on the ground. you know we travel the world going to conferences talking to all the folks actually building these facilities and so we also get sort of the on the ground insights from folk that are actually doing it. they will tell you for the most part these days that it's very challenging to build these things that they're facing a lot of community push back that they're struggling to get labor and so on and so forth. On the other hand, the timelines that they're targeting are getting shorter and shorter, right?
11:59 And so many in many cases, folks tell us, hey, I'm expecting to have this ready you know, by mid 2027. And so in our number, we purposely add delays of like one to three quarters depending on whatever we're observing just because we expect stuff essentially to be delayed by default because of all of these challenges. >> Yeah. Okay. So, so my favorite chart from the article actually went site by sight across 40 sites. It's really impressive. it's kind of clear from this directly that these are massive sites with a ton of buildings. They are all under construction. They're all counting towards the 27, maybe not all of their megawatts as you're saying in 27, but they are contributing towards the total forecast. a couple of people have commented on a few of these sites. Maybe first just give me your reaction to the size and scope that you're referring to of all of the forecast and how the even just these 40 is still not even the full complement of data centers that are under construction worldwide right now.
13:03 It's it's still under 50% of the data centers that globally that are shown on screen here. but also that there are, you know, individual sites in here that some people know better than others that maybe have some high-profile delays. And you can talk through the difference between an outright cancellation and a delay and why things are still going to come in in 2027 and not be around 25 gawatt and closer to 50 as you guys are saying.
13:32 >> Yeah. Look, there's there's two things. One is like when is the first phase of a site going to be delivered to like how fast will the site ramp to full capacity. some of the projects that we show here in the specture we assume much more conservative ramps than others. Example Oracle New Mexico we were the first in the market to talk about all the issues that they're facing on that site and obviously that has been proven right. All the media is all over it now and they are calling force measure and whatnot. so they're obviously facing tremendous challenges to get power to that to that facility. and that's why we assume a RAM that is much slower. So if you look at a picture you see that essentially the whole campus is under construction over a gawatt of IT capacity under construction right now.
14:17 but our forecast is more conservative than that because of because of the the challenges we've identified. So the share of megawws that goes into our 27 number for this specific camp is actually fairly low. another one some Twitter accounts commented on our ramp on cruso in in in children. folks saying that we we were assuming there's a whole gigawatt that is going to be that is included in our focus and placement. That's wrong. we have under 200 megawatts as of the latest version published. and and and so yeah I don't know folks just making up stuff. it's not actually accurate.
14:54 we assume these things ramp over time because you're not going to go from zero to you know 300 megawatt some of these buildings are 300 megawatts 200 400 you don't go from zero to 400 stuff gets ramped over time and you know if you've ever been to data center you know that which we do a lot so we actually know how that stuff works >> yeah makes sense okay talk to me a little bit about the leading indicators right because this is actually not like a forecast that you guys just created two weeks ago I mean this has been pretty consistent for a number of months if not years at this point considering that the model is years old and you guys have been tracking 27 as it comes into fruition. Like if we're if we're forecasting for 2032 right now, this depends on leasing and pre-leasing activity that comes right now and we expect it to increase, not decrease because like there's only so much you can track when it's that early stage.
15:43 But right now, like if something's going to be built in 27, there is construction activity happening. So talk me through like how you started a forecast for 27 maybe a couple of years ago and then how it how you track it through to how it plays out right now. >> Yeah, and I want to say that like that's also the reason why we have different models to track the whole ecosystem. so for example around the data center topic we have the energy model, we have the industrials model. there's plenty of suppliers that are exposed to projects at different phases of that project. and we sort of try every single one of these companies and have been extremely successful in breaking the strength in order for some of these guys. Like one example, we published a big deep dive on our industrials model.
16:23 This company called Sterling Sterling they do early stage construction right they do the groundbreaking site work. So obviously that happens first. It's the first thing that happens when you see these when one of these projects starts getting built is you do some of the early site work. so this company we can track again like at the product level essentially. and so we've been pretty good we're actually really good at predicting that their orders were going to surge which they indeed which is exactly what happened. then there's many other companies down the down the supply chain. So for example all the equipment electrical equipment cooling equipment we also track that very closely that happens afterwards.
17:01 and and and that can also impact the company both ways can be sometimes they're delivering sort of ahead of schedule and so these guys see strength and you see their revenue destroying the quarter. we've also had times where to industrial model clients. we talked about potential supply chain delays meaning that some of these sites are late and we've also flagged several sites in our model that have been delayed by ship ship equip equipment shipping challenges and supply chain challenges. So that's another thing we can try. energy also of course very long lead times. Everyone knows the gas turbines are multiple years out. There's a bunch of other solutions for sprocketing engines notably u that have shorter lead times and that's another indicator you can track to understand the timeline of these projects. So there's essentially this waterfall of things that you can track that are more or less binding and we look at all of that to ensure our timelines are accurate. now I would say the two ones we presented most most strongly in our article self-built construction starts pretty trivial. You just got to track every single building and when they're starting construction of the building. and you can see if you I don't know if you've se before but how the number goes up quarter after quarter. if you understand the timeline which the stuff is getting built that a strong indicator as to how large 27 is going to be relative to 2026. the other one is pre-leasing which means hyperscalers, neoclouds, AI labs signing lease contracts with data center operators. This one is actually even earlier because typically you sign a lease then you raise that the timing can vary too leases can be signed at different moments of the life cycle of a data store project but generally speaking it's a bit earlier and tracking that extremely closely as we know and every quarter we sort of you know forecast them before whatever is published by folks generally be extremely accurate as well u helps us you know understand ahead of time again what's going to get built under these binding contracts that cannot be cancelled. Yeah, and this is just a really big number, Jeremy. Ju just double double click on the over one trillion of data center leasing that's been signed that drives a lot of the forecast from the, you know, credit capital and markets model that Dan and the guys are working on. We we just talked about it a week ago and we're going to be doing more of this, but like this has been a pretty big story in the news recently, just how big the scale of some of this is.
19:26 >> Yeah. Look, there's a bunch of indicators you got to track get at the at the building level to get to that number. things like what is the pricing, what is the contract term, escalator, that kind of stuff. some of these deals are public. So if you look at all of the crypto miners for example, companies like digital core scientific, you can see the speed at which their backlog has been increasing and is now in the tens of billions of dollars. but the thing is there's plenty of these companies that are private, right? And so the public markets don't have a good sense of all the contracts that are being signed between companies like QTS or Edcons or aligned and so on and so forth Vantage with all of these leading hypers skaters or AI labs right and that's stuff that we track extremely closely and by having a good sense of all of these private companies and tracking them every single one of them one by one then we can essentially like gather the data and put out these numbers that maybe other folks were missing. but are I think a crystal clear indication of the strength to build up that we're going to see.
20:30 >> Awesome. Okay, Rick, tell me about logistics, man. when we talk about modular data centers, we wrote a whole article on Lego data centers and how these things go up. You're the guy who stares at a lot of satellite images and watches these things. The trend seems to be that the the change in the satellite images is going faster, not slower. Right? I one of the charts that shows Google self build and how they have changed their design for the electrical side put it out faster for the modular sites. Can you talk me through that this is going faster not slower over time?
21:06 >> Yeah, I think this is one part of the buildout that's a bit overlooked to be honest, right? Where if this were like traditional data centers maybe labor would be called into question, maybe timeline would be called into question. But for us in our mind the arrival or not even the arrival but like the larger scale utilization of modular deployment is going to be the what's the word I'm looking for like the the reason that this works and the reason that this happens right when you look at traditional timelines of 18 months compared now to say like day one's timelines where they can go down to 9 monthsish for you know any number of 100 megawatts if you'd like you can look at bright ray also down there in Southeast Asia which can build in like 6 months right you can look at now the anthropic reference designs also which are going to be employing modular right modular is basically becoming more and more widespread across the industry you're going to see build times drop you're going to look at the meta tents you're going to look at the new Amazon buildings you're going to see these buildings basically just pop up out of nowhere right these guys this This is the this is the you know the project Houdini program right where it's I think it's 6 gawatts a year for the next like two or three years was the stated goal like maybe 6 months ago by them these are the reason that this buildout works right without this you'd have a lot more labor intensive like build out right we have a I think we did the math in one part of the article where you see that if you have your MEP like your more electrical side of the fit out within the data hall. If you have this more modularized, right? For example, say I take the power hall, right? And I just imagine like a literal shipping container and I just slot it into the actual hall like the shell of the data center and I plug in a few things. This demands much less labor than, you know, having 20 electricians in there trying to like actually coordinate everything and quote unquote stick build the entire hall. And so you can imagine this just on a much grander scale. This is the reason why this works, right? Of course, right now we're working with the industrials team to write and do a competent letter, a competent newsletter on the labor for the 27 buildout, but so far I mean everything points to the fact that modular is what's making this work and you can see it across the industry really. Yeah, I would add again that if you if you actually visit data centers, you know, and some of the big ones as well as some of the two, three year old ones as well as some of the smaller ones, you could clearly see the difference in the way how many of these new builds are fully designed and fully optimized to go as fast as possible on the build time, on the ramp time, the commissioning time, absolutely everything they thought of for an accelerated timeline. And again, like many folks tell us, I'm going to pull this off in 6 months. we purposefully haircut a lot of these assumptions.
24:05 but it's still extremely impressive when you actually visit these sites and see what folks are doing to accelerate while keeping the bar high on quality and and and certainty of delivery and so on and so forth. >> Yeah. And I mean I I think if people aren't I think the whole kind of point here is somebody might say you know like you know how do you measure modular adoption in this case? It's like, well, we have it on the industrials tracker.
24:30 But the other thing is that if you if you don't really follow suit in the modular buildout or like this kind of design strategy, you will probably not be allocated the labor that you need, nor will you be competitive within the buildout market, right? If I can offer you a data center in 12 to 14 months, I'm really not worth as much as the guy that can offer to you in 8 to 9 months. And so, it's kind of going to be able to it's going to start forcing people's hands in this direction. And we're already watching, you know, we're watching people do interesting things, right? Like I'm watching Bright Ray is talking to multiple NeoClouds right now to start selling just entire data center modules, right? Not not the like, you know, one to two megawatt crates, but the like actual hall that you can ship and install into your core and shell if you'd like or I mean with the core and shell from Bright. But people are going to keep coming to these folks that can provide this equipment. People are going to keep buying it. I think this buildout is exceedingly led by the modular aspect.
25:30 >> Yeah, makes sense. How about the the balance? I mean, we put this behind the pay wall in there to be clear, but it seems like generally speaking, people are trying to call this shot. whether you're going to have accelerators and an overbuild of data centers or whether you're going to be constrained on data centers and have a over supply of accelerators or whether it's going to be a perfect match. There's maybe one comment to make there that we know about is just how how many people overdeployed GPUs and then u use power capping and it seems like power like the power envelope is still a constraint for a lot of these whether it's grid connected or behind the meter. There's just only so much power you can bring on even if you have the physical space and the chips available. So you'll be power capping GPUs to fit in the envelope. with how much the construction timelines are reducing in the modular sites. Maybe you guys can just say high level like you think there's going to be a lot more data centers built in the next couple of years. Right.
26:25 >> I mean look it's it's obviously tough. The I would say generally speaking the our forecast for data centers is slightly easier in the sense that it's based on infrastructure signals that you can track ahead of time. chips can be slightly more volatile. but overall we also have like a lot of very strong indicators pointing to like what's going to happen in in 2026 and 2027. I would say generally speaking we're a bit more worried about the risk of over supply of data centers relative to chips than the other way around. we're already sort of over supply of chips today as we speak.
27:07 so it's it's always one one always has to be slightly bigger constraint than the other the other and if you want to deploy something if you want something like right now it's easier to get I would say GPUs than data center megawatts but when we compare how these different supply chains are expanding into next year and especially in 2028 we do see a risk for 2028 I would say flipping and potential data center over supply so that's going to be the thing we we watch the most most closely just how fast can chip supply chain expand? and I would say that's obviously a strong positive to things like capex in terms of like you know investing in new semiconductor fabs, buying new equipment. and that's the type of stuff we've been flagging all clients for, you know, several months already.
27:53 >> So let's wrap on this one, guys. Great job taking us through all of this. Super helpful. we've obviously covered all all sorts of aspects of this from the moratoriums to the labors to the electrical equipment to the cooling equipment to the actual construction progress. Like there's all sorts of things that play into a data center arriving on time that we think we cover in in great detail. I know you guys do. let me get your direct reaction to people like Brad Gersonner showing our chart with an old forecast to Jensen which basically says like you're going to build too many chips and not enough have enough places to put them. and Jensen kind of just like taking it, acknowledging it. Yeah. Yeah. And moving on in the conversation like where do you think the sentiment comes from? And maybe you can just respond directly to that.
28:35 >> I mean I think it's >> I mean I think >> I think it's easier to feel like what's happening right now versus know how that feeling is going to evolve into like you know end of next year. So 12 15 months from now. Right now it's crystal clear that there's more supply of chips than supply of data centers. Again, you talk to anyone that's will want that looks to deploy AI infrastructure, they can get access to GPUs, they cannot get access to land power shell in the next three, six months. so I think the constraint right now is crystal clear and so obviously we want to make sure the situation is is solved and so I think that's why Jensen absolutely wants to make sure this doesn't happen. also I mean Jensen has a long history of being kind of a supply chain you know extremely smart about supply chain and he can be aggressive as well and so we've seen him securing tremendous amount of supply like you know 2021 to secure GPUs for the crypto mining ba which obviously crashed so there can be a bit of a cyclical aspect but you know overall it makes sense it makes perhaps the company slightly cyclical but the whole sector of semis is cyclical anyways so it doesn't change too much his company's in extremely good financial health and I think he's just like writing these massive checks to secure supply from the memory supplier from the logic suppliers and he's just really good at securing supply from these guys and I think he he wants to make sure he can build as much as he can and have no constraints and so yeah it makes sense to pressure everyone in the supply chain to build more >> and I think the the other thing I'd add on this too is I think I think a lot of it comes from people maybe operating on the not not the most solid foundation of like information right It's one thing for you know it's one thing to understand that like you know yes mortoriiums are like slowing data center buildout yes it's true grid connections are as well labor is as well equipment supply chains as well all of it's true but being able to measure that like accurately is a different story right there's I don't know if there's anybody else out there that's really I think just like as a as an aside Jeremy Did you say that we were like looking at over supply in 2028 before I continue?
30:57 >> I didn't say formally I'd say it's the main risk as we get into 2028. >> I was going to I was going to start talking about that but I don't know. >> Yeah, let's just move on on that. but yeah, no. So I finished my thought. yeah, I think the other thing here is that a lot of people are operating on not the most solid foundation of information when they come to these conclusions. Yeah, I mean look, all of all of Wall Street all of Wall Street sort of tells us like you know you guys are plain wrong and obviously some of the great investors out there like Brad, but he's obviously not alone. he just did it on a big podcast, but many other folks tell not you guys are way too high.
31:38 and there's a lot of data sources out there that have data center forecasts that are materially u smaller than what we project. and we're familiar with a bunch of these and you know like a lot of these cloudcoded forecasts that track data centers and that I don't know just prompted cloud and be like track all of these sites. there's like three, four or five of them that have numbers that are 2x more than ours and and and some of our clients you know tell us hey these guys are lower and just tell them like you know we don't we didn't prompt prompt or or right like there's more that goes behind that. so I would say generally speaking, a lot of sources that probably aren't really basing on accurate information. unfortunately, and obviously every single CEO also just telling, folks that a right now the biggest constraint is again like N power, it goes back to sort of the sentiment driven by what's happening right now.
32:31 >> Yeah. And maybe if I could just say something directly, what set me off on this one is that like a month ago, the guy gets on stage and presents to a YouTube audience now of 330 thousand people, followed by this one from 4 days ago to 265,000 people in counting. Cites our data and then just says it's wrong. >> Says, "Yeah, I don't think so." Like other stuff and say it's different. Sure. cite our data, provide specific critiques to it. Great. we can always learn on offhand. This is the forecast.
33:04 We think it's wrong. Seems a little strange. Glad you guys could, you know, respond directly to some of that in this article. And I look forward to walking through 27 and then continuing to see if the track record that you guys have on the data center model continues to hold true. >> Yeah. I mean, just to be clear, like the goal is not to respond to like one one person or whatever the goal is. it's a huge topic that obviously people ask us all the time and our our institutional clients obviously have been aware of how we do things and what what what we've been projecting and I think we just wanted to give a piece of that to our broader audience and put the content out there and see you know how folks would would react. but yeah again like the point is we're extremely bullish in terms of like how big the infrastructure builder will be in 2027 and we think we have a rock solid indicators about that. Yeah. And I mean it's, you know, it's not the it's not the first time we've gotten the feedback that, hey, your guys's numbers are insane. Like, we don't know what to do with these numbers. Nobody agrees with these numbers. so it's not the first time. So, we wanted to like directly address that whole thing, honestly. Awesome, guys. Okay. Well, great job today. Appreciate you taking the time to educate everybody as always on what you what you spend all your days doing and how accurate it is.
34:17 Appreciate it. >> Cheers, John. All right, we're done now. Can you smile for the camera quickly? Smile for the algorithm. Come on with some teeth rake, buddy. >> Can you what, sir? >> Smile for the algorithm. Smile. Look at the camera and smile. >> On the thumbnail. Okay, good job.