Episode Transcript
[00:00:00] Speaker A: Truth be told, it's like I've always liked Google because Google was always had like the most potential upside. They were cheaper. Azure was amazing too. They were coming up, but AWS was just so good.
I was like, they're like bullies, man, because they're so good and they know it and they would just like you're saying like they would just tell you, this is what we're gonna do. And they would do it. And they did.
[00:00:30] Speaker B: Yeah. Three, two, one. Like that. We are live for the first ever episode of the Wolf podcast. The goal of this podcast is to perform deep dives into secular growth themes for the next decade and spot spotlight those hidden gems that might become mini monsters. So obviously, the first thing we're going to cover on this pod is what I believe is the biggest tech revolution of this decade, maybe multiple decades. AI. So of course we're going to bring on two guests that our experts within this field, stock talk and paper gains. So stock talk. Tell us a little about yourself.
[00:01:04] Speaker C: Yeah, so I am a full time trader and investor. I've been doing that for, it's going to be a little over eleven years now.
I was originally in medical school, a place called Baylor College of Medicine in Houston.
A lot of indian kids my age go to medical school. That's just what we do. But, you know, my third year, I just kind of came to the point of just being in love with finance and being in love with companies and stocks. And so I decided to take that leap and go to try to be a full time trader and thankfully it worked out and, you know, here we are many, many years later and I still love markets and companies and anything about the micro economy. I love it and I thought it fascinating. So, yeah, happy to be here and happy to talk about stocks anytime. So I think that this is a terrific slot to do that.
[00:01:57] Speaker B: What about you, paper?
[00:01:58] Speaker A: Thanks, man. Appreciate you inviting me also, by the way, and love being on with stock talk. We go back and forth all the time, but yeah, myself, I mean, full time trader as well, and investor, but my background, I think I live in Silicon Valley and my background is enterprise technology for, I mean, the better part of a decade. So before transitioning to trading, investing full time, this was my career, right? So coming from this space, I think part of my personal transition was the companies that I invest in today and that I trade today, they're all in this space. And it was kind of like I don't want to all kind of unfair being able to come from the home of a lot of these companies and know who's actually growing faster than who, who's got the bleeding edge tech before anybody else knew because I was helping build these companies from the ground up. Like, we literally set up Uber, like, we literally built Robinhood, literally built snowflake, and all the way back to Dropbox, if you know what. Not that anybody really uses that anymore. Sorry. But, but, yeah, that's my background. And the original data scientist that coined the term data scientist, those are my core crew in Silicon Valley. So it was kind of weird transitioning from that because it just became such a passion in that space. I was like, look, as an enterprise technologist, my passion became finding that next bleeding edge company that was going to do better than the next that determined my success in the space. And being able to transition that to the stock market was actually an easy fit. And it was just like, it was such an easy fit. At a certain point, it just, it didn't make sense to continue doing what I was doing when I could do it on such a bigger scale out in the market. And at the same time, a lot of my customers were asking, like, hey, they would ask me who should, this company is asking me to recruit me, what do you think? Right? Or, like, and all that kind of stuff. So having my, my pulse on what's going on the market has always been, for as long as I can remember, like, what's going on in the, you know, in the enterprise, who's up next, right? Like, and that, that's always been a passion. I've always had my hands in every little corner of that market. So, you know, just, that was my transition. So the topic is pretty near and dear to me, I guess. And, you know, from a practical stance, hopefully I don't get too much in the weeds. But, you know, that's, it's, it's at the core of how I got to where I am and the entire journey along the way.
[00:04:47] Speaker B: Did you wish you were part of the enterprise software space post 2020? Like, going back from what it used to be back in your day? Like, how different is now?
[00:04:57] Speaker A: So my original crew, like, if you know Mozilla, you remember Mozilla like that? You don't.
[00:05:03] Speaker B: I'm 30 years old, so I might be aging myself.
[00:05:05] Speaker C: Oh, my God.
[00:05:06] Speaker A: So the crew. So if you don't know what Mozilla is, the crew that, like, built Mozilla. Like, that was, like the original, like, crew that I like, kind of. So anyways, it was like before Chrome was chrome, but that was, like, disruptive tech back the day.
And like, that was before 2020. So, I mean, like, you know, it's fun, right? Like, that's all I can say. There's always been stages of different things. It's just they're their own struggles.
But, you know, at a certain point, you know, I don't know, I don't like, miss a lot of it either, because at the same time over there, it's like, look, they, I remember my first interview, I was like, what, what time do people show up? And they're like, I don't, you know, be there between sometime between like seven and ten. And I'm like, what? I did not compute. But. Cause, like, it's not, it's not a job, it's a lifestyle. That's the thing, right? And, and this market has a beginning, a middle and end. And I do enjoy that, right? So I do enjoy the freedom of having time with family, or at least trying to have the time with family versus like, getting calls in the middle of the night, something's out or, you know, you have a, you, you know, some fire alarms going off and you gotta put out, you know, this, this emergency and that emergency, those, those always happen. So it's less of an integrated life, if that makes sense. But, you know, in the enterprise that is very much integrated life, that does not, does not have a beginning or an end, that's for sure.
[00:06:39] Speaker B: You probably have such an amazing b's detector on like, enterprise companies who like, claim their AI or like, their tech is actually moats compared to.
[00:06:50] Speaker A: Sometimes I have a hard time holding back. I'll just say that.
[00:06:54] Speaker B: Cool. I guess we can start with our first theme. So, stock talk. Obviously this is a broad AI theme, but the way I categorize it is multiple stages. I know you've said something similar where first we see the hardware, then obviously the infrastructure, then the third, which is my favorite part, the application element where I think this will be the most amount of money made. But nobody knows when that third stage is going to come. So for me personally, I'm front loading it because I never know when that stage is coming. So I want to talk about if you also agree on what those stages are.
[00:07:30] Speaker C: Yeah, yeah. So, I mean, I think you nailed it on the head there. And, you know, I've talked about this at length before, really. And I think different people in the that are theorizing about how this will look going forward have different pathways of how we might get there. But I think when you simplify it, it really is a three stage process. And what we've seen over the past really two years mostly, and maybe even a little bit longer than that. But I think the public focus really hyper focused on this industry post chat GPT. It was this awakening moment where people started paying attention to the hardware that was being developed, and that has been being developed for the last decade in this space. It got a lot more attention, a lot more publicity, deservedly so, after the launch of chat GPT. But what we saw with Nvidia in the last two years is this ability to access the top point of the demand in this industry, where the first inklings of hyper demand are going to come from, which is, of course, the chips. And Nvidia, by virtue of having the best performing AI related chip in the industry by far, and they still do at that time, basically got the top down demand from all the biggest companies in the world, Microsoft, Google, anyone that wanted to build AI was immediately in a rat race to acquire, compute. And so that was really stage one. And that's where we saw this explosion in earnings per share for Nvidia, explosion in revenue, explosion in total demand. Right. And so all of those features really made Nvidia go on that enormous run that kind of started this entire conversation, and probably one of the main reasons why we're having this conversation today. But when you ask yourself, where does it go next? I think the simple answer to that is it's not done with the hardware yet.
And we've seen that because other competitors have started to perform.
And my favorite example of that, I think, is Micron, which I've talked about a lot this year. But Micron is a supplier of high bandwidth memory, and they've seen the kind of growth they've seen in high bandwidth memory in the fallout of the chip era has been enormous, and that's what led them to have a great guide in q, 120 percent gap up on earnings and has let that stock perform so well year to date. But they're not the last player in the stack, as that pricing power needle, as I like to call it, moves through the hardware industry. You will, the market will tell you where the supply is getting targeted and where there are shortages of supply, and those companies will benefit a lot. And the second stage, as you reference.
[00:10:15] Speaker B: Let'S stay on the first stage. So I fully agree with you.
It's like a game of hot potato on the hardware element of who has the pricing power. So we saw in Nvidia, now we're seeing the micron. Who do you think is the next component? Is it like the network element of, like, broadcom, marvel, that might start getting the pricing power, or is it going to kind of still stay within Micron for a while, like we saw with Nvidia for one plus a year? Or you also mentioned western digital might be the next one of those names.
[00:10:43] Speaker C: There was actually a note this morning out on both western digital and Seagate, which I think should be at everyone's top of the list. Not that the pricing power is going there, but from the perspective of if it does go there, then those are potential options. And the biggest thing we've seen from this perspective is this idea that you don't really know what quarter it's going to happen. Even the people that were speculating on Micron said this may take two, three quarters to progress, but now we've seen over time that it happened relatively quickly.
That may happen for western digital next quarter. It may not happen at all. You know, we may not see any shortages apply there. So that's very, still very much up for debate. But those are candidates. Yeah. That could see a quarter or two quarters or three quarters of outperformance because of that pricing power.
[00:11:33] Speaker A: So I don't know that it's necessarily like to that to your question, and I'll try and try to simplify the infrastructure stack just, just like, as, like layman's term as possible. Like, if. If AI was a robot, right? Like the infrastructure stack is like the machinery of the robot. So, like. Like memory chips, things like that, are components of the machine that go into it. Then your application, if you will, is kind of like the programming for the machine. So, like, these components that we're talking about, the chips, they're going to go into all the machines. Nobody necessarily knows what program is going to be the staple program for AI, like robots in the future. So that's kind of like, you can kind of picture spots here and there, but I think where stock talk's going, when you look at, like, an Nvidia and where the market goes, where you look at Nvidia, there's no question that no matter what the lead application is moving forward, they're all going to have that one specific component in every single machine, right? They're all going to have that one specific micron component in every single machine. They're all probably going to also have that one western digital component in every single machine or broadcom component in every single machine to that end. Right? So I don't know that it's a single winner, you know, only kind of like, I actually, it's not right there's not one winner. It's not going to be that way.
You know, from an application perspective, there are going to be serious losers. That's what's true. Right. But there will be like major, major winners also. But it's not necessarily, you know, single, like one guy takes it all either. But I think at this stage, it's easier for the market to take a land grab on components that will definitively be in every single one of those machines, if you will, in stupid analogy, no matter who the winner is. So I think that's where we are in the market, if that makes sense. And then if there is a program or application that comes out that uses a specialized chip, let's say that phases out Nvidia, then at that point there will be a new winner, start, emerge. Start to emerge. But we're not there yet, if that makes sense. Let's say Tesla comes out with a new AI program and that only uses the Tesla AI chip at that point. Yeah. Okay. So Nvidia will start to lose a lot of market share because they're not going to be compatible with this new AI program from Tesla. So that's as an example. It's not until that type of pivot happens, and we're not even close to something like that yet.
[00:14:15] Speaker C: Yeah, I think when you talk about the hardware space, and since that's where we're starting, I think it's also important to talk about competition and this idea that when we see this pricing power needle move around the industry, there may be a main beneficiary and the, there also may be peripheral beneficiaries who get the market share not from your Googles and Microsofts, but from players that maybe can't afford the best product in the industry. And there was a lot of talk about the Mi 3000 chip from Nvidia that they. Sorry, from AMD, misspoke there. The Mi 3000 from AMD that they released. And people felt, hey, look, maybe this is going to be competitive with Nvidia's H 100, but the problem is three months after that, Nvidia announced their new chip. And so you have this process where the competitors are forced to innovate to put out a product to meet the leader, and then the leader just keeps innovating. So it's very hard. I think it's almost impossible to predict how long any of these guys are going to keep the pricing power needle. It's going to depend a lot on AMD's ability to recruit talent, AMD's ability to innovate much more quickly than they have. The rate at which competitors are showing up to this race is just too slow right now. And so that's why people have so much confidence in Nvidia, because they are putting out products that are just getting better every year. And so you're trying to catch the previous horse that already finished the race.
[00:15:40] Speaker A: You know, so what's, what's true right now is that there's only one, there's only one player at the table right now. That's, that's actually what's true. Everything else is kind of like their stories, right? There are stories of hoping to get to the table, speculation. The true fact of the matter is that there's only one player at the table and that's Nvidia. And until that changes, there's, you're, you're kind of just hoping so then you're, then you're left to speculate on who's next to get there. And, and, yeah, it's Nvidia or AMd. Sorry. And so that's, that's who's next. And you kind of just have to pick your spot, right? Like find out. Or maybe there's another competitor that emerges and you're going to have to wait for that type of headline catalyst or that pivot in the market to say, is there a new application that's going to come out, emerge.
Maybe it's an Amazon application or a Google Meta partnership that's requiring a different chipset or an Apple application that's requiring Apple specific chipset. That's the type of pivot or fundamental change that will have to change the story. And when something, if and when something like that happens, that's when you'll see, okay, new competitors merged, new player has arrived to the table. But until something like that has happened, there's only one player at the game.
[00:16:59] Speaker B: Well, does AMD even have a chance? Like you guys said, Nvidia had that first mover advantage and clearly their tech is superior and had that first mover advantage. But AMD, once they catch up or get to the table, like you said, there's going to be no pricing power.
[00:17:12] Speaker A: Because it's kind of like coming from the enterprise space, I'll tell you. So AMD has always had attempts to get into the enterprise server business, right? But it's owned by intel. It's just owned by intel. And the intel architecture, you can't just like insert a couple AMD servers into intel architecture in your data center. It's just not going to happen. It's not compatible so you'd have to rip and replace entire, entire infrastructures or server farms. And that's, that's not, it's not as simple as just inputting a couple servers.
And so competitors don't make it easy for you to get a foot in. Right. And so what that leaves you with is like you have to, you're left with entering the market with net new builds and customers that are looking to try something different. You're going to have to start at a small, at a lower price point most likely. And it's probably going to be with customers that are also in your same position that are maybe late to the party and are trying to innovate themselves and need to do it on a maybe a budget. Right. And maybe you catch, maybe you get lucky with somebody that catches a home run and is able to outrun, you know, somebody that's top of their game, right. But that's might be what we're looking at. We don't know. Right. I think with what Nvidia is doing, for all I know they could take over intel in the CPU business. I'm just going to say that, right, like there could be no more Intel CPU's. You'd be like Nvidia CPU, GPU. I would not be surprised if that was our future ten years from now.
I really wouldn't be.
[00:18:51] Speaker C: I think to the point of AMd. I mean, look, I don't think the company's dead in the water, but no, what we're talking about is really just the GPU component right now.
Nvidia has such an enormous lead that at the present it's hard to imagine anyone competing. And that may be the case for a decade. But AMD does have a couple opportunities. And paper kind of alluded to this just now, which is, you know, not every buyer in any market is a premium buyer, right? I mean, we've kind of become one.
[00:19:20] Speaker A: Nvidia server was like 50 grand for a little. Nvidia serve like little, like 50 grand is one little box if you were trying to buy it. This is ten years ago.
[00:19:31] Speaker C: Yeah, yeah. And now. And now aftermarket they're going for five, six x that sometimes. So the point is, is that the concept of a shortage of supply is interesting, right? Because on one side of supply shortages, we say, well, the leader now has more pricing power. But then on the other side of a supply shortage, we say, well, but there's not enough supply, right? That's why they have pricing power. So what does that create? It creates a dynamic where you actually do create a space for competitors because your product is priced where it should be priced based on the demand. And so, you know, somebody that can't afford to pay sixty k per GPU is going to be like, all right, they're going to knock on AMD's door and be like, well, we want to get into AI. We just can't afford the infrastructure from Nvidia. So, you know, we'll be clients of yours. Now, are those orders going to be smaller? Yeah, they're not going to be $25 billion orders like they used to be getting from big tech, but the orders will be smaller, but they, they will be higher volume also. So there is a slot that if AMD can make the second best generation product, they can fit in a higher volume market with consumers that just. Not even consumers, but businesses that have less capital to invest. So.
[00:20:36] Speaker B: So SMBs, you're essentially talking about like, if, like, for example, like the digital ocean, does cloud computing for SMBs.
[00:20:42] Speaker C: Absolutely.
Or even personal compute. Right. Or the average everyday person. Because in the future, we don't know what these chips are going to look like. But we may get to a point where the average everyday person can build an LLM on their laptop. We may get to that point within ten years.
[00:20:57] Speaker A: We probably won't know what Apple's basically going to be saying here for pretty soon.
[00:21:00] Speaker C: Yeah, exactly. They're going to be like, oh, build your own custom LLM with our new CPU. Like, who knows? You know, we may get to that, that, that point.
[00:21:08] Speaker A: But next month.
You brought up digital ocean, actually. And to the, to this conversation, you know, you're right. No, not, most companies aren't going to be able to do that. But I think that takes us to maybe the next layer of infrastructure is like, most companies don't even build on physical hardware today, if that makes sense. Most people, most companies are building on AWS to that end. Right. And I think, honestly, that's at the end of the day, I do like Dell, and I don't know if we have time to talk about Dell, but I will. But I really, you know, I've been a fan of Google for the longest time, but the truth of the matter is, the overall land grab winner, I'm actually going to go out on limit and say it's going to be AWS, right? Because AWS probably they're going to, they're the ones that are going to be buying these. It's not your, it's not the other companies, it's AWS. And what AWS was doing before I left, the enterprise really was, they're virtualizing all this GPU, right? If you think of the infrastructure stack and you think of servers, the name server, by the way, comes from like, a server serves an application, it serves a purpose, right? And GPU sits inside of a server. But you know, there's this virtualization thing became a deal because when you build a server, it was like you have this excess process, excess computer. You have to buy extra, and there's extra horsepower that doesn't end up getting used. It has to sit there and doesn't necessarily get used.
You overspend. You buy a car that has 600 hp, you only use 300, but you want that extra 300 just in case you have to hit it pretty hard sometimes, but you don't ever really use it. That's how these servers builds work. But when AWS comes along and they virtualize everything, specifically GPU's, at this crazy cost, and they virtualize inference, they now have the ability to virtualize your graphic processing and gives you the ability to allocate portions of that to multiple applications.
[00:23:20] Speaker B: And so would you say that AWS might be the first, like, precursor of that inflection point towards the application phase of this?
[00:23:29] Speaker A: I think that's now that's happening, right?
[00:23:31] Speaker B: It's happening, but we're not seeing in the business spending and whether or not.
[00:23:34] Speaker A: The market recognizes that.
[00:23:36] Speaker B: But it's not getting reflected in the earnings, though, yet for AWS.
[00:23:39] Speaker A: I mean, it is like, so AWS has always had this issue of like, so they're going to incur the costs, right? And what's the last earnings report that they reported? Right. It's. It's like six months ago. That's what they just reported for. So we're looking at maybe three months of this type of AI kind of adoption that's coming through. And in that time, they're having to build all this new infrastructure. They're having to incur those costs. I mean, I'd have to look at it, but I'm telling you. But if this is going to happen, you're going to see it, and you're going to see it there first and foremost. And when AWS came out, the problem with AWS in general, and coming from the space, I'll say most end users were in a situation where they were overpaying. I can't tell you how many million dollar monthly bills that I took. And we just found that companies were overspending left and right because they didn't know how much they were spending because people would spin up machines and forget to turn them off. And. And that's just how the platform worked. And they would just let a 50,000 machine run for months and nobody knew what was happening. And AWS was getting that growth as if it was a thing, and then it got shut down. Right. And so that's, I think, out of the picture now, pretty much cleaned up and that's where. But now that's being backfilled with all this AI type of build out and newspaper. And I think that's kind of offsetting itself. And Jassy actually mentioned a lot of that recently. Right? He mentioned that the shift back to the cloud is on. In the last CNBC interview he did, he mentioned that what I'm talking about was called cloud optimization. That's what it's called. And cloud optimization was essentially, hey, look, you guys, my bill is way too much. I need you to cut that in half. That's what players like Datadog did. If you don't know what Datadog did, Datadog was just. Datadog is an application that sits on your aws, that tells you where your extra spend is going. It tells you, hey, dude, you have an extra $100,000 over here. Did you know that? Like, you might want to turn that off and that's what it does, right? So, like, it's incredibly valuable for a lot of companies and very important. And that's what had been happening for years and I mean, years and years and years. And I think that's finally coming to an end, but also being backfilled with a lot of this AI, right? And so as, as more applications come up, get spun up, right? And I think a lot of this, like, there's so many applications get spun up, you know, a smaller company isn't going to be buying $100,000, you know, box to run their company.
The business setup is AWS, right? It's some rocky whatever. It's Palo Alto networks. It's like, here's your infrastructure for SMB. If you want to set up a new company, this is what you do, right? If it's Azure, if it's AWS, it's not usually GCP, but maybe it can be. That's Google cloud.
But.
[00:26:42] Speaker B: So do you think these AWS is going to start targeting SMBs because they're caring about volume? Because who knows?
[00:26:49] Speaker A: I mean, AWS has always been there, right? Like, it's always been there, but they.
[00:26:52] Speaker B: Don'T care about SMBs as much because it's obviously just clients who like 1 million plus in revenue.
[00:26:57] Speaker A: They don't care about the SMBs because it's already theirs.
Does that make sense?
[00:27:03] Speaker C: I mean, I don't think that they're targeting them right now because, I mean, there's, this industry is going to be governed by. By capital, right? Like, when we first talked about this AI theme on spaces, when we talked about it a few times, and one of the first things I said was that people shouldn't get excited about the startups in this space because most of them aren't going to be startups for long, you know, and.
And I don't mean that to say, like, people shouldn't invest in them. What I mean by that is that all of the power is in the hands of the people with the capital to build multibillion dollar data centers. That's it. That's the whole name of the game now. And there was a great quote. It was somebody from perplexity AI. The CEO wanted to poach a meta AI researcher, and the first thing he said to him was, do you have 10,000 h? He said, if you don't, I'm not coming. And the guy was like, the guy was like, we can't possibly afford that new currency, right? Why would I bring my talents somewhere where you don't have the infrastructure to do what I want to invent? It's that simple, right? It's like, so this is only further consolidated power with the Mag seven. The Mag seven have infinite capital. They all do. And by virtue of having infinite capital, they can provide this infrastructure for those players. And so I think SMBs are just the cherry. Like, there's a watermelon of the biggest companies in the world that are nowhere near where they should be on AI, right? I mean, you have accounting firms now, KPMG, which is an example. I brought up spending $2 billion, their biggest investment in company history, an accounting firm to automate the accounting process. So this has just started. You know, every major business in the world will look to automate as much labor as possible. And to paper's point about AWS, Amazon's directly interested in silicon. I mean, you guys remember last year, they launched their own in house chips. I don't know if you guys remember the tritium. I forgot the names of them.
[00:28:59] Speaker A: I mean, they've tried a lot. I remember working with Amazon, stock talk.
It was just so funny. It's like if there was a competitor out there that was so good, it's not like it was. The immediate thing was like I would see immediately, boom, Amazon creates their own instantly.
[00:29:19] Speaker C: Tryanium last year.
And they said the reason they designed it was because there's a gpu shortage. So now this hasn't been talked about much, whether or not didn't exactly, whether or not successful. The point is, is they've directly expressed an interest in acquiring compute because I think the exact quote that was said was by Andy Jassy was silicon underpins every single one of our customer workloads. It only makes sense for Amazon to have as much control as possible in this area of innovation. That was the exact quote. I just read that off the article. So he, he's already told like the beautiful thing about Andy Jassy, which he's done so well, is he is willing to show his cards to the industry.
[00:30:06] Speaker A: Yeah.
[00:30:06] Speaker C: He'll tell you on a shareholder letter years before they even start get the ball rolling. He did this with healthcare. He's good. He's done this this year with their other new initiatives. He's saying it directly about cost cutting. He basically gives you the game plan and then says, watch me do it.
[00:30:22] Speaker A: Yeah.
[00:30:23] Speaker C: Then a year later, Amazon is more efficient business than ever. And so, yeah, I think Aws is.
[00:30:28] Speaker A: That'S always kind of like how they work.
I mean, you know, and, you know, truth be told, it's like, I've always liked Google because Amazon has been, I worked as a, as like a, we call like cloud reseller, right? And Google was, always had like the most potential upside. They were cheaper. They were like equal. Azure was amazing too. They were coming up, but AWS was just so good.
I was like, dude, they're like bullies, man, because they're so good and they know it and they would just like, you're saying like, they would just tell you, this is what we're going to do and they would do it and they did. Right. But it's, it's just true, right? It's just, it's just what it is. It's, they're, they're that good, right? And they're, they're that, they're that nimble too. They're able to like innovate, move that fast. And like, I mean, so I would say, like from that land grab perspective, AWS for sure. And then maybe there are other people. And then you, have, you mentioned digitalocean, which is a services provider for AWS, services for somebody that wants to build on AWS, their company, and maybe isn't as in tune to how to use AWS because it's such a complex platform. You have to be very specialized if you really want to be able to utilize it to the best of its ability, you would bring in someone like a digitalocean or something like that to help you deploy. Um, so I think there, there are probably companies like that that would help out utilizing something like a datadog.
[00:32:01] Speaker B: Well, the theme I'm getting from you guys is AI isn't like a rising tide lifts all boat boats, like, for the listeners right now. Like, you need to be very careful because they might have a spot in AI, modern AI stack right now, but that's going to soon get thinner and thinner. So, for example, digital ocean, like you just mentioned, like, do they even have a chance in the cloud computing space?
[00:32:24] Speaker A: No, no, no, no. They could be taken. Well, okay, so there, there are some companies.
Let's. Can we do new relic and datadog for a second?
[00:32:33] Speaker B: Beautiful song.
