Episode Transcript
[00:00:00] Speaker A: Just because it's AI doesn't mean, oh, it's like a magic playground and you do everything differently. No, pricing power is a very simple concept. We trade, all of us trade stocks in all sorts of industries and we understand the concept of pricing power and how meaningful that is, is to a stock's performance.
[00:00:21] Speaker B: New relic was first to market in, in this cloud optimization product set. That's what Datadog does, right? First to market, first only in actual implementation. The only ones that existed. And new relic and EWR, I believe.
NWR. God.
[00:00:45] Speaker C: I know. I mean.
Oh wow, you're right. 2016 to 20, 2019 pre Covid, they were just the ones in this space.
[00:00:55] Speaker B: What's the ticker? I can't even any wR.
[00:00:58] Speaker C: So like they're growing in 2016, 64%, then 2017 45%. They had a real 40 score of 50 plus in 2019. Then something happened.
[00:01:08] Speaker B: Are they listed? Because I'm not even pulling them up.
[00:01:12] Speaker C: Any n n e wr new relic? Yeah, yeah, they're. Did they get bought out? Because I'm looking on ticker.com. no, there's still estimates from the analysts.
[00:01:22] Speaker B: Okay, well they were 1st first to market. Right? First to market doesn't necessarily, I think to my point, first to market doesn't mean that you're gonna be the best, right. That's first and foremost, right. They were taken out like clean head off or taken out by Datadog because of their business, the business structure of the business plan. Their, their go to market strategy from a business perspective.
[00:01:51] Speaker C: Was new relic cloud agnostic or was it just Datadog?
[00:01:56] Speaker B: No, no, no.
Mirror image.
[00:01:59] Speaker C: So why did Datadog just succeed?
[00:02:01] Speaker B: Because of the business model. Because of the go to market. Like it wasn't a technology thing, it was a business thing. It was the, it was the business strategy of how they went to market in the enterprise. Right. Like they went to market. Like anyways, they were just way more aggressive.
They hit the channel, they hit AWS marketplace, which was I think probably huge. So AWS itself has a marketplace inside of AWS for AWS users. If you didn't know, you can buy products, other third party products through AWS, through what they call AWS marketplace anyways, I think. And then partnering with AWS to do something like that was, was probably core to the strategy, I guess. But whatever they did, it just new relic became like not a thing really, just not a thing. And you know, quite frankly, they just became like a non, you never heard them again. You really didn't. Right. It's not unlike any other product. Right. Like there are a lot of products. So I think to my point is there might be someone like a digital ocean who, and excuse me, because I don't necessarily know in the weeds on Digitalocean, but I believe what I did personally in the enterprise is similar to what digital Ocean does and that help other companies build their businesses, things like that.
There were a million others just like us. It was really down to relationships at that point. If you didn't like me for whatever reason, and you wanted to work with Stocktalk and you were building the next Apple like.
But maybe I helped build the last Microsoft. But you like stock talk better. You might go with stock talk.
[00:03:47] Speaker C: No, that's, that's the name of the game in the space. I mean, that's the reason SMCI so successful. It's because he's so buddy buddy with the CEO of Nvidia.
[00:03:57] Speaker B: No, he's not.
How many times did Jensen Wong mention Michael Dell in that last recently?
[00:04:03] Speaker C: But if you go back two years.
[00:04:05] Speaker B: Ago, two years ago, how many times did Jensen. How many times did Jensen Wong mentioned SMCI in that last keynote?
[00:04:11] Speaker C: I think, I think he's.
[00:04:13] Speaker A: Yeah, he did give a hat tip to Dell, but I mean, they are.
[00:04:16] Speaker C: Friends, they're cousins essentially.
[00:04:21] Speaker A: I'm sure they had, I'm sure they had a harsh text conversation with each other after you shout out Dell.
[00:04:28] Speaker B: I mean, I'll say, you know, from an enterprise space in the actual server. Compute. Look, SMCI is a great, like, it's most flexible platform, it's the most open platform in terms of like scalability if you will, but it's cheaper.
It's not like if you wanted to build something important, you built on Dell. That's how it is, right? That it's the best of breed. If you wanted to build something important, it was Dell. They're the best.
[00:04:54] Speaker C: Why did SMCI get such a head start on Dell within this, on the data center front? Sorry, I should probably be more specific.
[00:05:03] Speaker A: I think SMCI got broader demand than Dell, but not better demand than Dell, if that makes sense. Yeah, Dell. When you know what paper just said about the important products. That's absolutely true. Like the people that are building the world's premier AI creation products are not going to super micro computer to build those servers. I mean, they're just not. I don't think they are. And I think again, this is, there's going to be a volume player and a high end player in almost every one of these components. The same way we mentioned Nvidia and AMD, right? You have your high end player that makes the best of breed product, and then you have a high volume player that makes a cheaper product that maybe has some slight advantages. And that's exactly, I think, the same relationship between SMCI and Dell.
[00:05:50] Speaker B: I think SMCI has a place. Right? And I think Dell has a place also. But I will say, like, look, we built like the edge for Hulu, and Hulu was built 100% like SMCI rack servers on Arista network.
And that was a huge, they're huge builds, right? Huge data centers. So things like that. You're going to have SMCI, but pretty much everything else. Was Dell like pretty much everything else?
Yeah. I'll tell you, Dell's not dumb. They're not going to lose business to SMCI. SMCI you had to have. If you have a very. Here's the thing. If you have a very.
I work, I live in California. So we had this, we had this electronics store called fries. You guys might not know.
[00:06:41] Speaker A: Oh, yeah, yeah. In Texas too.
[00:06:44] Speaker B: Oh really? So they're out of business, but probably people listening have no idea what this is. But it's like if you go to a specialty retailer, you really had to know exactly what you wanted before you went in there. Cause if you tried to get help, God help you, right? Like you weren't getting any help, but if you were super geeky, you knew exactly what you wanted. Sorry. For anybody out there, you knew exactly what you wanted, you didn't need any help from anybody. You could go in there, you could get down nitty gritty, pick this up, pick that out, blah, blah, blah, blah, and put it together myself. And I'd be good to go on the cheap because I don't need that stuff. You go buy super micro, right then, right. But if, like, if you're a little bit more high level dell, that's how it is. Right. And that's exactly the comparison. Right? Like that's because if you try to get help.
Yeah, not happening. Right. Because the service is. That's the comparison.
[00:07:45] Speaker C: So I do want to pick a. Pick your brains about a name that I love. I think it's like a full on picks and shovel play. Just stupid valuation as dipped a bit recently, arm holdings. Does it scare you guys off that it doesn't really own an ip? And they're just like, I don't think that scares evaluation. I'm not the valuation.
Dump their shares for years.
[00:08:12] Speaker A: What scares me is it feels like another softbank pop that.
[00:08:15] Speaker B: So the only thing that scares me, Softbank scares me.
[00:08:19] Speaker A: Yeah.
[00:08:19] Speaker B: That's what I'm like, nothing else about scares me. The only thing that scares me is Softbank. And I think if you're an arm shareholder, like that's the only thing that should scare you to like scare you.
[00:08:29] Speaker C: Because of the way of their, they're going to dump the shares because they need the, well, whether or not they.
[00:08:35] Speaker B: Do or don't, that's not, that's out of your control. Right. But just the sheer fact that you are at the whim of a 90% shareholder.
[00:08:44] Speaker A: Yeah, exactly. And that's the thing, like people, some people like thin stocks. Like, oh, it'll go up faster. They'll go down faster too, buddy. You know, like that's what I always tell them. That's what I always tell those guys.
[00:08:53] Speaker B: Right.
[00:08:53] Speaker A: I mean I like, I like trading thin stocks too when they have a reason to go up, you know, but.
[00:08:58] Speaker B: Yeah, you know, it's, it's good to be there. Right. But like anybody, I would say just like if you like a company, you can love the company. The stock is separate the stock from the company number one. And if you want to be invested in the company, you can donate to their cause or if you want to buy their stock, go for it. But like, you know, you got to be just cautious. Right? Like just whenever, if we talk about these stocks and things like that, it's not that we're saying, hey, look, anytime is a good time to buy. We have metrics, right? You're going to look at your pes, your things like that. You want to, you know, a lot of us, you know, seasonal trends, you know, whether we like to buy when things are on sale. Right. Like buy when people are, are fearful, right? Like pick your spots, have your, I think this, the idea is to put your shopping list together if there's a fire sale that comes around, right? Like here are some names to go shopping for. That's it. Right. And I mean, whether they're not, whether they're on regular sale, they're on clearance or their end of life sale, who knows, right? Like what kind of sale, you know, just that that's what we're looking for.
[00:10:12] Speaker A: Yeah. And I think, you know, when it comes to arm it, almost like the Nvidia run from last year and what we saw with their earnings makes me want to look downstream as opposed to the other direction.
[00:10:26] Speaker C: True.
[00:10:26] Speaker A: No, I, I want to look at where are the peripheral beneficiaries downstream. Because the competitive relationships like we talked about are going to be very complicated and it's going to be tough to be like, this is the quarter to buy AMD. This is going to be their breakthrough quarter. You're not going to be able to see that coming. It'll show up in the numbers, and you'll be like, oh, wow. AMD's gotten the high volume portion of this market, and then you can act on it. But I'm looking downstream for me, I'm trying to think, when are the first real AI applications going to come out? Not the shit that we've seen. Not LLMs, but one of the first real AI applications are going to come up. What are the pricing power gonna look like on those? And before that happens, I'm looking at these picks and shovels, but in more of a hardware standpoint. Right. We had the full cpu discussion. Okay, what are the other components of building a data center that are gonna be in limited supply for the next decade? There's a lot of them. The problem is we just don't know what they are. Right. Hbm after the microns report. Now, we know that's an area where you might see supply shortages. We'll have to wait. This, this year might tell us maybe next year we'll have to wait till q two. I don't know. But paying attention to those earnings reports and seeing, oh, wow. Their pricing power picked up by 32% in a category. What happened in that category? Oh, my God. HBM went from, think about this. HBM last year was 5%, less than 5% of microns profits. At the end of this year, it will be over 20%.
[00:11:51] Speaker C: Geez.
[00:11:52] Speaker B: You want to tell them what HPM is?
[00:11:54] Speaker A: Yeah. High bandwidth memory. So, high bandwidth memory is super important.
[00:11:58] Speaker C: You know, then traditional, it's impossible not to have it. Like, you need it after.
[00:12:02] Speaker B: Yeah.
[00:12:02] Speaker A: And so. But it's traditionally not been in short supply because the types of modelings that require high bandwidth memory for having this offline, high bandwidth memory are very few and far between. But now they're commonplace. Everyone needs to build these things, and everyone needs enormous amounts of memory. And so the squeeze in high bandwidth memory is notable, but even that may not last forever. You know, you may see supply resolution in that category in q three of this year. I have no clue. Right. You have to monitor the data and be like, okay, there's still supply shortage. There's still a supply shortage. There's still supply shortage. Boom. Pricing power dropped off. What happened? Oh, these competitors came in, or, you know, the supply shortage ended globally, or a chinese supplier came in. Anything can happen. Right.
[00:12:45] Speaker B: So I think what's important, too is like, what if you're listening to this and you're listening to us and, like, really, like, listen to the way that we're thinking about things? And I can say, like, when I was young, my dad would say this weird. He would all say a lot, a lot of weird stuff to me, but, like, he always, you know, my family always into investing and things like that. But one thing that always stuck was like, follow the money, right? Follow the money. And I think it's just as simple as that. You'll see it in the stock prices. Follow the money. And when you see a trend, it's not that you want to go where the money is. That's not what you want to do. And that's not what we're saying. It's follow the money and then kind of draw a path as to where, where do you see that trajectory going? So if it's here, I want to go here, and I, and then I'm follow, I'm going into where the money is going to go. Right. And I think, you know, to the, to a lot of the conversation, the path isn't completely clear from the infrastructure place. What's crystal clear is that there are a lot of places that will hit every bucket. Right. And that today. Right. Today, what, the high bandwidth mammy, no matter what happens, gonna hit every bucket. Right. So that's happening today. Is there another place that's gonna happen next? Right. That's what you want to think about, right? Is there, you know, if, if, if Nvidia is there, does it continue to stay at the table? I think the answer is yes.
Is there another one that's coming? Yes, but how far down the road? And is it. No, it's not. That's what you have to weigh your odds on as the landscape starts to evolve. It's really about listen to what are the inflection points that are going to happen that will change the landscape? Right. And I think that's kind of what we're talking about. When Stocktot talks about shortages in the landscape. Right? Like shortages in the supply chain. Those are little inflection points that you can listen for when you're hearing people talk on, on tv or you're listening to your earnings calls or reading your transcripts or following up on the stocks that you own. Those are inflection points that should stand out to you as an investor and. And that should perk your ears up. Oh, this is a trend that I should start to pay attention to, and maybe I can follow this money and see where is it going to next? And you can use that thesis and play it to almost any kind of thing that you're doing in investing arena. But yeah, I think in this specific AI conversation, it's very much what needs to happen because if you're going to where the ball is now, you're going.
[00:15:28] Speaker C: To get, yeah, that's a full nature of the business. So that's why like if it's obvious right now, it's too late.
[00:15:35] Speaker B: This market moves just way too.
[00:15:38] Speaker A: That's why I was spending so much time in January on space, talking about Micron, you remember shot? Yeah, we're like, why are you talking about Micron? Like the stock is not moving with the rest of semis and I'm like, just wait, watch the quarterly reports, it's gonna happen. And you know, we finally get it. But yeah, that's the point. You can't wait for the ball to get there. And you know, I think what a lot of people, I don't know why this happens, it might just be psychology, but a lot of people look at the AI industry and for some reason they think it's going to function differently than every under other industry and the same fundamental principles apply. Just because it's AI doesn't mean, oh, it's like a magic playground and you do everything. No, pricing power is a very simple concept. We trade, all of us trade stocks in all sorts of industries and we understand the concept of pricing power and how meaningful that is, is to a stock's performance. And when you look in the AI industry, it's a function of one simple thing. What is the gap of your innovative lead over your nearest competitor? That's it. And the larger that gap, the longer you'll have pricing power. And the smaller that gap, the more hot potato it's going to be. Right? So right now, Micron has, they have pricing power, but it's about here when it comes to high bandwidth memory, whereas Nvidia's pricing power and GPU's. I came and stretched my hand wide enough. Right. And that's the difference is you're going to have components where Nvidia looks like they're going to have pricing power for a decade. If I had a guess. I mean, I don't know, but you know, they, they look so far ahead of the packet, it seems unreasonable to.
[00:17:00] Speaker C: Even, well, they innovate every two quarters like it's impossible to catch up to them. Yeah, exactly.
[00:17:04] Speaker A: And that's Jensen's, you know, master plan is that we're never going to stop innovating.
[00:17:07] Speaker B: Yeah.
Decide whether or not the market has priced in two quarters worth or two years worth or two decades worth, right? That's. That's what we have challenge of as, that's what our challenge is as an investor. But, um. But I think, you know, what's true is, like, data, right? Like, data as a whole. When we talk about AI data, just to shift a little bit, like, what we're talking about is, like, the ability to manipulate data. And. And that in and of itself is what, you know, unlike another thing dad said as a kid is, like, God only made so much real estate, right? But, like, data is constantly growing, right? That's the one.
[00:17:45] Speaker C: You can make money in thin air with data.
[00:17:47] Speaker B: It's the one thing in the world that never gets smaller. Nobody deletes anything, right? There's only more and more data compounding every millisecond of every day at an infant, like, infinite level, right? So the requirements to have AI, to use data or have any kind of, like, applicable use for the data is. Is growing at an infinite rate every day as well. So, I mean, you know what we're talking about. Yeah. There's going to be a ton of winners. I don't know if we, if we want to talk, if we have time.
[00:18:20] Speaker C: I was going to say this is a perfect transition to the data stock.
[00:18:25] Speaker B: Yeah.
[00:18:26] Speaker C: Like, for me specifically, you can, like, you guys can pick holes, but I think Snowflake is the no brainer pricing power, right?
[00:18:33] Speaker B: Like, there's a lot of database stocks, right? We say database stocks, right? So, like, data as a whole, like, AI is, like, the ability to, like, manipulate data, right? Then data we just talked about is the one thing that is always growing, is never like, it's just, it's just growing at an infinite rate. But what do you do with it? Is.
Is important, right? And as an enterprise, like a business, right? It's like, how do I. How do I make sense of this data? We have these. These things, like, Cisco just acquired Splunk, which is a SIM or a system event monitoring system. But every little piece, if you remember IoT back in the day, it's Internet of things. All these little transceivers or whatever, sending off signals. All this monitoring system in an enterprise, it's all sending these data signals to one. We call it a data lake in the enterprise. How do you take this data lake and boom, put it into a dashboard so I can do something with it, right? And. Or, like, my customer information and know, like, how do I. How do I like run my business more efficiently and things like that. So, yeah, I think Snowflake for sure. Like Snowflake, cloud based, cloud native, right? Like, that's, I think that's from a business perspective, because there are competitors to Snowflake that haven't come to market. I think, you know, you can call them out.
[00:19:58] Speaker C: Databrick.
[00:19:59] Speaker B: Yeah, bricks. So, like, I'll say Snowflake was one of my, like, largest. I was actually. So Snowflake and databricks were both my customers back in the day. And oddly enough, the team from, those guys came from, a lot of the team came from, like, Mozilla, and they all work together, by the way, so they know each other.
Just funny how all of that works. But, you know, they're similar products, but the business, the business approach to how they went to market, totally different. Completely different. So we're databricks.
You're just buying the overlaying software application when Snowflake requires you to purchase the storage underneath it.
[00:20:44] Speaker C: Do you think it's because databricks start as a data lake when snowflakes start warehouse?
[00:20:48] Speaker B: No, no, no.
Well, like data bricks, basically. So, like, when I say storage, think of it like a filing cabinet. So, like, all of your data, if your data is like paper. Sorry, like mail paper, it goes into a filing cabinet. The file, like, you have to, you have to own, you own this. You bought, you have to buy the filing cabinet from Snowflake also. And then I have, I don't know, like, if you had like, a magnifying glass. That's data. That's databricks. You just buy the magnifying glass from databricks and you can look at your own filing cabinet to see what you have. But from Snowflake, you have to buy the magnifying glass and, and the filing cabinet from Snowflake. You can't just buy the magnifying glass. So their, their revenue capture is significantly more. It's, it's ten x, if that makes sense. That's, that's the difference in the business model. Does that make sense?
[00:21:41] Speaker C: It does. So would you say it's easier for Snowflake to kind of take some of databricks lunch in the coming years where, like, why, why don't we just do.
[00:21:50] Speaker B: It'S a similar story to like, an AMD or an Nvidia, right? Where it's like, it's, well, maybe not AMD Nvidia, but it's like if you already owned your storage, or, I mean, it depends on, I don't know. I mean, well, would you would you.
[00:22:02] Speaker C: Call Snowflake the Nvidia and databricks. Databricks the AMD where like. Yeah, yeah, that's a good comparison.
[00:22:08] Speaker B: Totally. Yeah.
[00:22:10] Speaker C: So I actually do want to bring it up to a database. You guys mentioned it. Mongodb. What's your pulse on the MongoDB situation for the database? Because they are very similar to Snowflake. And a lot of people love the idea of if you're creating a gen AI application, you're going to.
[00:22:26] Speaker B: Mongo has been around a lot longer than Snowflake. They were there first, for sure. They were definitely there first.
They were there first. I think they have a lot of legacy customers definitively.
Look, it's been a while, truthfully, since I've been in that, so I don't know. I don't know if they're still like, when I left those, Snowflake was just like they were taking everybody's lunch. And at the time, quite frankly, databricks was such a small player in the space, they were a nothing burger. So things could have changed since then. So that's the truth.
I'd have to look it up. But. But when I left it, that's where it was.
[00:23:07] Speaker C: So, Stockdog, what's your pulse on the software space?
[00:23:12] Speaker A: I think this is my bias in this space, and I think Snowflake is a great company, and I'm with you that they're going to be a huge beneficiary from this. I don't want to discount that. But my bias in this entire space, outside of the chips, which the chips right now being led by Nvidia, there'll be other components like we talked about. But when I look to the end applications, my bias is still with the biggest companies in the world. And I think if anybody's going to deliver world changing enterprise software products, I think it's going to be a company like Microsoft or Google. And I think when we think of soft enterprise software today and we think of the kind of offerings that are available in the market, I feel like we almost don't have a comprehensive enough view because AI is going to make software applications possible that people didn't even think you could do with software before. You know, there's. This is a new era of compute and being able to provide network level enterprise software applications that can do things like automate warehouses, which will tie into my next point about Amazon, or do things like control a fleet of humanoid robots, or do things like, these are things that we never even thought about ten years ago. You're like what are you talking about? Go watch iRobot. That would be what you would say. But now everyone knows a humanoid robot is coming within the next five to ten years. It's coming, it's here, everybody's working on it. Hundreds of billion. Yeah. Thank you. But I mean, it's coming, right? Somebody's going to do it whether Tesla does it or not. And so the point is there are new applications we're not thinking about. And I think in the software world, while I think Microsoft and Google have an edge just because of their capital, I think when you think beyond conventional software, I think the real winner in that non conventional software category is Amazon. They alluded to this like they always do in their shareholder letter, which I recapped on our spaces the other day. And Shai was there and I gave quite a long and passionate speech about it. But they alluded to this and they said, we are now. I think the word they use was hyper focused on delivering AI solutions across our entire business profile. And where our mind goes first is what me and paper talked about earlier, which is AWS can be a huge beneficiary. When you look under the surface and you look at their actual retail business, you forget how many applications there are. You're talking about everything from automating the factory worker to automating the factory floor itself, to automating the outbound delivery process, to automating package organization, to optimizing logistical routes for the quickest delivery possible. All of these things can be enabled by AI. And so Amazon under the surface, I think, will do the most real world AI work. The stuff that you see happening with your own eyes, right. That category, I think Amazon will undisputably lead. People will be mind boggled, I think, by the level of automation they have in the packaging and delivery process. By the end of the decade, people.
[00:26:15] Speaker B: Will be stunned, quite frankly. Dude, it's always funny. Like, to me, I was always like, Amazon's retail business.
I never really, that's the only reason why it's never really a big Amazon shareholder. I didn't really want that business to be totally fair. I only want AWS.
The problem of owning Amazon was Amazon.com. like, I want to own AWS, but I don't want to own Amazon.com.
[00:26:45] Speaker A: What I'll say to that paper is once they automate the entire delivery and packaging process you want on Amazon.com too, margins are going to go, right?
[00:26:55] Speaker B: Because I'm about to, I mean, yeah, when I was like, I'm looking at this whole situation like, oh, man. Just.
I want to root for Google, but too many fumbles recently. I just, like, I want to root for them.
They're doing well right now, actually. The stock price doing pretty good. But.
But I. But I.
But I.
I can't. I cannot dismiss Amazon. There's. I just can't. So anyways, so we're at the part. I want to fight it. Like, part of me wants to fight it, but I just can't.
[00:27:34] Speaker C: Right. The part of the show where I'm going to ask you guys, like, a bunch of questions, like, a handful of questions, but you have to give your answer, like, without thinking about too much is gut feeling of it. First one.
I fully agree. I think paper said this earlier where there's gonna be a consolidation within the tech stack. What specifics segment within, like, software right now you think will be the most vulnerable to that consolidation? Like, for me, specifically. Specifically, I think it's gonna be like the. The git labs or the devs ops or like the JFrogs type stuff, like those kind of companies.
So what's your. What's your answers.
[00:28:14] Speaker B: If there's a consolidation in the hardware tech stack?
[00:28:18] Speaker C: No, no. And then software. Come on. Hardware. I think they all, like, are different.
[00:28:22] Speaker B: Units with an apartment productivity, like Asana type stuff.
[00:28:27] Speaker C: Oh, so you think it's making, like, Monday.com would just be king or.
[00:28:30] Speaker B: That's like, toasted by CRM.
[00:28:33] Speaker C: Interesting. Okay.
[00:28:34] Speaker B: Yeah.
[00:28:35] Speaker A: Yeah. I would say this is gonna be a controversial answer, but, you know, I think potentially companies like HubSpot could get.
[00:28:42] Speaker C: I was just gonna say HubSpot, like, because the only reason Google got HubSpot was maybe the data and just. That's the only component. But, like, CRM, like, why wouldn't you just.
[00:28:51] Speaker A: You don't need.
[00:28:52] Speaker C: Yeah.
[00:28:54] Speaker A: If you were to imagine a 20 year future, that's a accelerated. I don't see CRMs anywhere.
[00:29:01] Speaker C: So why do you think Google made that potentially 50? I don't know.
[00:29:05] Speaker A: I think Google's in a look. I like Google on I own.
[00:29:08] Speaker B: This is what I'm saying about God damn execution.
[00:29:12] Speaker A: Their execution has just been poor. If I'm gonna be really bold here, and it's not an AI related take, I think Sundar Pichai should be fired.
[00:29:18] Speaker C: Interesting.
[00:29:20] Speaker B: You did it. He said it.
[00:29:22] Speaker C: Well, they're reorgan right now. I forgot this week they said we're going all AI. I think that's maybe his Hail Mary of, like, I heard you guys. We're gonna go.
[00:29:30] Speaker B: You know, it's not as bad as Apple's announcement. Hey, we're gonna. We're gonna go with the home robots. I don't know.
[00:29:38] Speaker A: The way Sundar Pichai butchered this AI rollout is like the equivalent to us all star quarterback, you know, getting seven interceptions at a Super bowl. Like, it's just been so sloppy that it's like, dude, this is the biggest moment in technology in the last 30 years, and you fucked it up that bad. Like, what are you doing, you know, for him?
[00:29:58] Speaker B: Right here's.
[00:29:59] Speaker A: Yeah.
[00:30:04] Speaker C: All right, my next question. How do you guys think Apple enter the AI race? Because they're pretty tight knit.
[00:30:10] Speaker B: You have no idea mentioned earlier. I'm just saying, LLMs on your laptops.
[00:30:15] Speaker C: You think that.
[00:30:18] Speaker A: Personal consumer devices. LLMs on personal consumer devices. And that's where it'll start. It'll be a Siri AI. I'm already going to tell you what it's going to be called. It's called Siri AI. They're going to have it on your phone and your MacBook. That's exactly what it's going to be. Okay. That's step one. That they're 100% going to release that. I bet my life on it today that they are. Will release Siri AI within the next year. But after that, the question is, what else can you do from a consumer facing perspective? And the answer is actually quite a lot. It's gonna depend on Apple. Apple's. Because everyone else is for focused on the corporate playground. Almost every major company is poor.
[00:30:52] Speaker B: Apple is not enterprise. Right. They're not.
[00:30:55] Speaker A: Apple's gonna say, what can we build for the everyday person where we can wow them with an AI product, but they don't need to, you know, solve world hunger. Like, it's. It's more of a, did you see.
[00:31:07] Speaker B: Did you see Meta's new release today? You go, meta.
AI.
[00:31:12] Speaker A: I think Meta has a huge advantage from a data perspective.
[00:31:16] Speaker B: I mean, huge advantage that Xai has.
[00:31:18] Speaker A: With social media is probably the best treasure trove of AI trading data available today, at least for the purposes of what these current models are doing. Right? These generative AI models. I mean, what's better than millions or billions of people having conversations about tons of topics? You can teach an AI to be almost animate within a very, very short period of time, right?
[00:31:44] Speaker B: Yeah.
[00:31:45] Speaker A: And so that's where I think the social media players are going to be very integral components going forward, either making licensing deals for their data with some of these bigger players or outright, in Meta's case, building it on their own.
[00:31:57] Speaker C: But, yeah, next question. What name? Let's just say they turn the mag seven to Elite eight down the line.
[00:32:06] Speaker A: What?
[00:32:06] Speaker B: Elite eight?
[00:32:07] Speaker C: I thought the 8th name. And that's category in a couple years. That's not really there right now. Is.
[00:32:15] Speaker A: Is. Is that is your version of mag seven currently already including Nvidia?
[00:32:19] Speaker C: Yes.
[00:32:21] Speaker A: Okay. Okay. Then. Then it's a harder question.
[00:32:27] Speaker C: This is my way of fetching the mini monster from your souls.
[00:32:32] Speaker B: That's.
[00:32:32] Speaker A: I mean to say, what company is going to be worth $2 trillion?
[00:32:36] Speaker C: Exactly.
[00:32:39] Speaker B: Are you ready?
[00:32:43] Speaker A: Bitcoin's a mag eight. That was a good answer.
[00:32:46] Speaker B: Let's go, baby.
[00:32:50] Speaker C: I would keep that one. I'll keep going.
What do you guys think the next frontier is after AI? I think it's quantum computing. I think that's, like, within five years from now.
What's your answers?
[00:33:02] Speaker A: I think it's further out than that.
I think what people forget is how long we've been building what we're just seeing now.
[00:33:10] Speaker B: Yeah.
[00:33:11] Speaker A: Forget how long it took to get here. You know, this AI isn't something that started in 2023. People have been trying to build machine learning models for, like, 25 plus years, right?
[00:33:20] Speaker B: I mean, since I was born. Right?
[00:33:22] Speaker A: Yeah, longer, like this.
[00:33:24] Speaker B: This. This journey. Like, our parents were probably working on it, to be quite frank. Right?
[00:33:31] Speaker A: Like, I mean, people and people in our parents eras were. And the thing is, is when you think about quantum computing, I think it's promising, but I think just no one's close, no one's even remotely close to making a real usable product that you can apply to multimodal applications.
We're just a law shot away from that. Do I think these companies might start responding in the next five years, like you said, and might start, their stocks might start responding? Yeah, that could absolutely happen. But in terms of these companies becoming like profit engines, we're quite a far away away from that, in my opinion, because think about how much further we've come just with the new gpu's from where computers were ten years ago. We are leaps ahead.
Now that everyone's so focused on this space, investing in this space, scaling this space, I think you'll see quantum computing get neglected a little bit from a capital standpoint, because so much capital is going to be flowing into what works now. And we already know you can train LLMs with these current generation of compute.
Now that we know that everyone's in a race to solve AGI, and I don't think they're going to look left or right until that happens. I think this will be. Maybe you can call it the horse blinder effect, where every company in the world is so hyper focused on acquiring computer and chasing the AGI dream that I think there may be a little bit of neglect to the quantum computing side. But I could end up being completely wrong. I still think if you want to be a binary speculative investor, you want to put some risk on the table and you want to have the quantity yolo shot to the moon. Yeah, I think I onq or some of those companies could have that Yolo shot to mood.
[00:35:11] Speaker C: Could IBM be part of the lead aid if quantum computing is actually.
[00:35:16] Speaker A: No, I mean, I think Google is probably number one in terms of quantum computing.
[00:35:20] Speaker B: Okay, so I have a. I have a bias. I'll just say, so you know what, coming from Silicon Valley, if I mentioned Big Blue, I was immediately kicked out of the room. I'll just say that.
[00:35:37] Speaker A: Really, really serious, dude.
[00:35:41] Speaker B: Yeah, it's dead. It's real. Like, no.
[00:35:47] Speaker A: I didn't know. I didn't know there was that much. That much IBM hate.
[00:35:50] Speaker B: But it's not hate. It's not hate. It's just like.
[00:35:56] Speaker C: I mean, do you.
[00:35:56] Speaker B: Have a customers are go look up who their current customers are?
[00:36:01] Speaker A: No, yeah, I see. From that perspective.
[00:36:03] Speaker B: Yeah, yeah, it's not. No, it's not there.
[00:36:07] Speaker A: I mean, I think if you're gonna pick a blue chip in the quantum computing space, it has to be Google.
Google's been working on it for the.
[00:36:14] Speaker C: You wouldn't put Nvidia ahead of Google?
[00:36:17] Speaker A: No, because I think when we're thinking about actually building quantum computers, I think Google's researching it for the longest, you know, and if I had to bet, I think they're the furthest along, but, I mean, it's impossible to benchmark these things. Right? Like, what am I going to say? Is Google 70% of the way there? Like, I have no clue. You know, like, we can't. We can't. We can't really, like, put our fingers on how far the progress is because we're in the stages now for quantum computing that we were in for modern AI GPU's like 15 years ago. So I just think we're so. I just think we're so early and. Yeah, like I said, maybe there's some investment opportunities there, but I think right now everyone's going to have their horse blinders on trying to solve AGI, and I think it's going to be an AGI rat race.
[00:37:04] Speaker B: Yeah, I think there's just going to be so many different layers to that. That, you know, it's not if you. You're going to miss so many opportunities if you like, skip over to the next one before this is done because it's just the beginning, man. Like just so early there. There's just so much. There's just so much meat on this bone to go. Like, that's. That's all I'll say.
[00:37:28] Speaker A: Awesome this thing is going to be.
[00:37:30] Speaker B: Unless, you know, all I'd say, all I say, bitcoin. Like, I think, honestly, if there was another space that, that I would be looking at, like that's. That was the only space. And I know people like get caught up in all this stuff, but it's. Anyways, you know, I don't, I don't.
[00:37:46] Speaker A: Want to make the. We should make the title AI podcast featuring a side appearance from bitcoin.
[00:37:54] Speaker B: I'm not into any kind of little applications over there. It's just very much like how we're talking here. It's like only the real core backbone of what's going. Not any over the top type of service or no services, no products, no, none of that. But core already in use, legitimate existing tech, ethereum, that kind of stuff. That's what I'm talking about. Right? We call layer one hyperscale. That's it. But nothing in the utility sector of the crypto verse. That's way too speculative. The way I like, he says, hey, you can buy a portion of this lake down here. Nah, cool.
[00:38:45] Speaker A: The way I like to think of it is we know where the proverbial house is of AI. We know what components are necessary to enable it. We know you need GPU's, we know you need high bandwidth memory, we know you need servers. We know these components, right? And so the proverbial AI house, we know where the walls are and the kitchens are. And imagine you have a little mouse running around that house, and think of that mouse as the pricing power needle, and you're chasing this mouse. It doesn't make sense to start looking for the mouse outside of the house. You know, it doesn't make sense. You already know where the boundaries.
[00:39:21] Speaker C: You got me there. That's a good analogy. You got me there.
[00:39:23] Speaker A: You already know where the boundaries are. You already know. He might be in the kitchen, he might be in the bathroom, he might be in my closet, but, you know, he probably didn't get out. You know, I saw him in here. I saw him in the kitchen. He was in the kitchen. Oh, and then the next day he was in the bathroom. So that's how I think of this pricing power narrative is there's so much ahead of us, you know, immediately ahead of us, where billions and billions of dollars are going to be made, probably trillions of dollars. It just doesn't make sense for me to take that leapfrog and say, well, where's the quantum computing opportunity? Because there's so much opportunity in AI that is happening now, that is seeing hundreds of billions of dollars in investment, that is seeing every major government in the world chase it like a rabbit. And so, as long as we're in that phase, I think there'll be plenty of opportunity in this space.
[00:40:09] Speaker B: Unless there was already a multi trillion dollar market that might be evolving today. Yeah, that could be entering the current market. There's that possibility. That's the only one where there's a new house coming up, your new neighbor. That's all.
That's all I'm saying.
[00:40:26] Speaker A: Maybe. Maybe they'll build the neighbor's house more quickly than I expect, but I'll be.
[00:40:30] Speaker B: Pleasantly, hey, you know what? But your neighbor's going to come visit, and you're going to go visit your neighbor. That's what I'm saying.
Yes. Yes.
[00:40:39] Speaker C: Well, we're at our time. Thanks, guys. I love the content. First off, this AI, like content is exactly what I think a lot of those listeners need, because there's just so much misconception out there on, like, AI clearly blew up last year, and now you're seeing how many companies are claiming there can be beneficiaries from AI, and there's gonna be a lot of fakes out there that won't exist in five years. I fully agree with that.
[00:41:02] Speaker B: Yeah. Okay. I know you're closing it out. There is one like, there. If there was a ticker named AI, I would be wary of something like, oh, my God.
[00:41:11] Speaker A: I've been very open.
[00:41:13] Speaker B: If your ticker was called AI, and your ticker also used to be called Iot when that was, you know, a thing that might be a cause for concern.
[00:41:25] Speaker C: I did forget a point. I do think we left out a name that I think we have to at least comment on that since we'll chop this up.
[00:41:32] Speaker B: Right, cut. Because we will chop this up. We should definitely stick that in there somewhere.
[00:41:37] Speaker A: No, we are.
[00:41:37] Speaker B: We are. We are.
[00:41:37] Speaker A: We are.
[00:41:38] Speaker C: All right. Three, two, one.
What do you guys think about the biggest or maybe the most polarizing name within the AI space? You either love it or you hate it. The name is Palantir.
[00:41:54] Speaker B: I remember Palantir before it was public. Right. Just so you know, Palantir portrayed in the private sector at about 975, like forever.
And it made this crazy ripper run, uh, to, what was it? Stock talk, like 40 something dollars something, 40 something dollars monster run. And I think that I rem. And it was just like, oh, we're going to the moon. And I remember it as, you know. Uh, look, I think of it as a very heavily government focused company. Um, to me, if I compared it to like a snowflake. Snowflake plays in the commercial sector, commercial enterprise sector. Palantir played in to me, that's how I separated him. Palantir would play in like the government type sector. Wrong, right or indifferent, whatever. Wrong or right. But yeah, I think Palantir is great.
But I never saw them in my personal experience come close to playing in the commercial enterprise.
[00:42:57] Speaker C: Well, that was obviously pre AIP, which is their new platform that launched last year. Have you looked into that?
[00:43:05] Speaker B: No.
[00:43:06] Speaker C: So that's a newer thing where it's showing insane customer growth.
[00:43:10] Speaker B: Like, I mean, I mean, I would, I'd have to look into it, but I would say like early growth is kind of like if someone told me that IBM cloud grew a thousand percent year over year, I would say, okay, so you went from one customer to ten. Good for you.
Yeah, I had to stick that in there. Yeah.
[00:43:33] Speaker C: Ivy, you love IBM.
[00:43:35] Speaker A: I want to volunteer shareholder, but I mean, I think, I think there is a niche that they can control. I think from a government standpoint they have a good shot at getting a substantial amount of business.
[00:43:47] Speaker B: Yeah, I agree. I think you have to have a very special skillset to work with the government. Let's say for example, Snowflake will never have that.
[00:43:55] Speaker A: Yeah. Volunteer as.
[00:43:57] Speaker B: Yes. Will never have that.
[00:43:58] Speaker A: Azure will working for the DoD for, I mean quite a while. Right. And the government for quite a while. So they have the procedures in place to, you know, safely manage data, et cetera, the clearances in place. So I think from a defense standpoint, which AI will be a huge part of defense too, you know, defense, national security. I think there is a role they will play. I'm not a shareholder, but my cousin actually last year, literally a year ago, went almost all in on this stock. It was like $8. And so he's happy now. Um, he like slapped, he was calling me and he's like, you need to buy some, you need to buy some. He's like, this is the lows. And he was right. And he's not even a trader. Like he does not trade or invest at all.
[00:44:37] Speaker B: Oh, I think we all have that cousin.
[00:44:42] Speaker A: You need to do this.
[00:44:44] Speaker B: And for once they were right. Right?
[00:44:46] Speaker A: Yeah, he was right.
[00:44:48] Speaker B: But I don't know if they sold it.
[00:44:50] Speaker A: He does not want to sell it anytime soon.
[00:44:52] Speaker B: Well, yeah.
[00:44:53] Speaker C: Do you? Our favorite hype man just made this comment like just a week ago, Kathy woods said that pounds here can actually be a real threat to Microsoft as the operating system within enterprises. Do you think there's a. No, no shit, no chance.
[00:45:08] Speaker B: An operating system?
[00:45:09] Speaker C: Yeah.
[00:45:11] Speaker B: What to, like what Mike.
[00:45:13] Speaker C: Like bi competitor to Mike. Because Microsoft essentially owns enterprise space. Like, there's no competitor. They think that Palantir could potentially catch up to that where they have to.
[00:45:24] Speaker B: Worry about, like, I guess it depends on what they're talking about. Like SQL Microsoft sequel, like, or like Vi platform, like business intelligence. I'm not really sure.
[00:45:32] Speaker C: Yeah, yeah, it's bi.
[00:45:34] Speaker A: I mean, maybe if Elon Musk became.
[00:45:35] Speaker B: C, it's a very small subset of that os, I guess.
[00:45:39] Speaker C: Well, the key to Palantir is it unlocks all these things once it's like, you start using it. So the bi is small right now, but that could turn into a massive thing down the line.
[00:45:49] Speaker A: Her words, they could get into the space, but are they going to displace Microsoft? I'll bet my life that that will not happen.
[00:45:56] Speaker B: There's only one person for them to displace in the government sector and that's Microsoft.
[00:46:00] Speaker A: So I mean, in certain sectors they can. Yeah. You know, in certain, in certain areas they can. But overall, I mean, Microsoft is the juggernaut of juggernauts in that space. And, yeah, I don't think, I don't think that needles moving much.
[00:46:13] Speaker C: So I heard mixed reviews from both you guys and Palantir.
[00:46:16] Speaker B: Sounds like, I mean, I, so here's, I, I think that it's another one of those where it's, if you like the stock, you like the stock. Right. But I do think that it's important as an investor to understand, like, that your entry point matters. You know, like, it, it does. So it, I like the stock at certain levels and I love the stock at other levels. So find out the level that you love the stock and love it for what it is. Right. Like we've had, you know, we talk on publicly all the time about stocks and I've had people call, oh, I got an average price of Nvidia at 950 a share, blah, blah. And, you know, well, okay, what's your time horizon? You know, and if your time horizon, that's what's important, your time horizon and that's the, that's the, that's the key to the whole story here. Because even, okay, so let me, let me back it up a little bit. Your price point doesn't even matter if your time horizon is long enough. Right. Just because inflation sucks.
If your time horizon's right, that's what's most important. Right.
And I think as long as you understand that and it's not something that you're looking at every day or every week or every month, you know, then that's, that's what's important. Right. But you can't be looking at these things if you're investing and you're looking at it every day or every week, you're not investing. That's not investing. So just be truthful with yourself, I think at that point, and understand what you're actually doing, because if it is something that you're looking at on a regular basis, then, then you're trading and that's not conducive to investing. They're two totally different, unrelated, like non compatible skill sets, quite frankly.
[00:48:07] Speaker A: Yeah. I manage my investing account dramatically differently.
[00:48:09] Speaker B: Yeah. They're not compatible.
[00:48:12] Speaker A: I don't add and remove stuff from my investing account. What I would tell people is all the stocks we talked about today, and this is probably a good place since we're in the close to the wrap up, but I think all the stocks we talked about today, keep in mind that if you're the type of person that's going to buy one of those stocks and expect it to go up 500% in a quarter because of AI, you're doing it wrong and that's not going to happen. Most likely, maybe one of them will, but that's most likely not going to happen. And you have to be patient with this theme. And if you're not the type of person that's going to monitor the quarterly results, comb through the report and actually do some analysis on where the pricing power is and where these different factors are, you're not going to be able to keep up with the theme anyway. In that case, you just buy an ETF and call it a day. But if you want to put in the work, if you want to put in the work, there is a lot of opportunity here for people that are convicted and do the work and do the analysis. There's going to be a lot more microns in the future that are going to have these big earnings moves that hold well and that benefit from this theme, this mega theme, the secular theme.
[00:49:17] Speaker C: Well, I appreciate you, Stockdoc, for saying that we are wrapping up. Thank you both for joining. On the first ever podcast episode of Wolf Podcast, we covered AI. The theme, my favorite theme for next decade, covered 15 to 20 companies that we think are gonna be real players. And we also called out some fake ones that you guys should not even touch.
We're fortunate enough where Stocktalk and paper have their own services. So if you guys love the content we talked about on this episode, which again, AI is in the early innings, what we're saying right now is easily going to transform in the coming years because that's what these kind growth themes are like, where it's this right now, but we have no idea what's going to turn into. So stock talk, you want to go first and where all the listeners can like, kind of see the content you give out and the service that you have.
[00:50:09] Speaker A: Yeah, sure. Yeah. So you can find us at Stock Talk weekly on X. We're mostly exclusively on X. We do have an instagram, but we rarely ever use it. That might change in the future. But at Stock Talk weekly on X, we just run a, I call it a one stop shop for traders and investors. We have news, earnings reviews, catalysts. I'm the head of the research team there myself. So we do research every morning. We share that research with our subscribers, all of our stock picks. And I also run a daily livestream there where you can hear my wonderful voice for 6 hours a day. So if you're interested in hearing more rants from me, that's a great place to do it. We have some great technical analysts in there, too, Danny Naz, who's been trading for over 30 years, and we have a research team with over 60 years of combined experience. So plenty of great stuff there. Come check us out anytime. Again, that's at stock talk weekly on x.
[00:51:03] Speaker C: Popcorn to you. Paper.
[00:51:06] Speaker B: Oh, nice. Yeah. So I find paper gains.com.
we have like a join now link right at the top.
What I can say is, like, we are pretty diversified. We have, we have about like 15 full time traders and we do, we do a lot. Right. So if depending on where you are in your trading slash investing journey, we absolutely can meet you wherever you are, whether you're beginning or you're a veteran, we have something for you right from crypto just to equity, to futures to stocks and mostly options, quite frankly. We focus a lot of training. We do have a lot of long term investing just like this. A full section within our server. We're just doing some, we call spring cleaning right now where we're cleaning house. We have some cash, like, lined up, and we're writing up a bunch of stuff on where we're looking to deploy and when. So we have a lot of that on deck. And again, weekly trainings on our website. We have a new newsletter that's for free. So I would suggest probably just signing up to that. Again, papergames.com free newsletter. We drop something a couple times a week, every week, and you'll be able to keep up to date with everything that we're doing. And then we're going to open up a new kind of like mastermind. We call it the school of games, where we go through trainings. It's kind of like a quarterly thing. And we'll give you weekly trainings on everything from options, bringing you from very beginner level all the way to being able to know everything that we do from an advanced proof perspective, too.
[00:52:39] Speaker A: Awesome.
[00:52:39] Speaker C: Well, damn, you guys both got squad.
[00:52:42] Speaker B: Well, appreciate you guys for sure. Definite squad.
