Chit Chat Stocks - Big Tech Investing Expert Rihard Jarc Tells Us Who Is Actually Winning the AI Race

Episode Date: October 29, 2025

On this episode of Chit Chat Stocks, we speak with recurring guest and Big Tech expert Rihard Jarc on the race in artificial intelligence (AI). We discuss: (00:00) Introduction (02:00) Amazon's AI Strategy and Anthropic Relationship (10:14) Google's Competitive Edge in AI (19:26) Meta's AI Monetization Strategies (28:24) Microsoft's Azure and AI Workloads (32:10) Understanding Neo Clouds and Their Impact (36:01) Nvidia's Strategic Moves and Circular Accounting (40:12) The Depreciation Dilemma of GPUs (52:19) OpenAI's Future and Financial Strategies (57:56) Predictions for AI Leaders by 2030 UNCOVER ALPHA: https://www.uncoveralpha.com/ ***************************************************** JOIN OUR EMAIL NEWSLETTER AND CHAT COMMUNITY: https://chitchatstocks.substack.com/  ********************************************************************* Chit Chat Stocks is presented by Interactive Brokers. Get professional pricing, global access, and premier technology with the best brokerage for investors today:  https://www.interactivebrokers.com/  Interactive Brokers is a member of SIPC.  ********************************************************************* Fiscal.ai is building the future of financial data. With custom charts, AI-generated research reports, and endless analytical tools, you can get up to speed on any stock around the globe. All for a reasonable price.  Use our LINK and get 15% off any premium plan: ⁠https://fiscal.ai/chitchat  ********************************************************************* Portseido is your best portfolio tracking & reporting solution that helps you track all investments in one place. We personally use the software to track our portfolio returns across brokerage accounts. Try it for free today: https://portseido.com/?fpr=ryan63  ********************************************************************* Disclosure: Chit Chat Stocks hosts and guests are not financial advisors, and nothing they say on this show is formal advice or a recommendation. Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to Chit Chat Stocks. On this show, hosts Ryan Henderson and Brett Schaefer analyze businesses and riff on the world of investing. As a quick reminder, Chit Chat Stocks is a CCM Media Group podcast. Anything discussed on Chit Chat Stocks by Ryan, Brett, or any other podcast guest is not formal advice or recommendation. Now, please enjoy this episode. Welcome into the Chit Chat Stocks podcast, a podcast to help you find your next great investment. Today we bring back on a recurring guest, Rahard Jark. Rahard is the founder of an AI startup that he eventually sold to a software company and is now a technology investor with fantastic coverage on the big tech space, especially in the age of this AI boom. He writes

the sub stack uncover alpha which if you are someone that wants in-depth knowledge on the big tech companies open ai nvidia all of these businesses and how the ai industry and the boom is going especially with how fast moving everything is you know gpu semiconductors all that good stuff i would check out that sub stack the link will be in the show notes won't include a link to that for the listeners. Before we get started, as I know, we're recording this on October 17. It's kind of in the start of earnings season. So if anything happens from now until then, we're not going to be referencing this on the show since we're not time travelers. But Rahard, after the intro, we're going to kick things off right with Amazon. We're going to go through all of the big

tech companies today. Well, we're going to talk about at least all of them except Tesla since it's not essentially in this AI race in the same way as some of these companies. We're going to try to hit as much as we can. We're going to go through Amazon, Alphabet, Meta, Microsoft, NVIDIA, OpenAI, even Apple, and then some general stuff around the AI boom, GPUs, potential AI bubble. Let's start out with Amazon, though. We got to start somewhere. What is Amazon's relationship with Anthropic, and what is AWS's strategy in AI? Because there is a big narrative out there that they're falling behind yeah first of all thank you for inviting me again it's always a pleasure to join you guys um yeah with amazon you know there is this narrative

that they're falling behind it's quite public by now i think we had also a few reports out there which kind of confirmed the thesis that they're a bit behind um so they do have i think most people know by now a significant stake in entropic it's supposed to be between 10 and 20 percent or something like that um they also are i mean entropic and avs are linked but it's not just amazon depending on entropic it's also the other way around um because there are info that like 80% of the traffic that comes to Anthropic is from Bedrock, so Amazon's kind of routing software which helps with the AI routing. And Amazon is diversifying, so from Bedrock I think a few months ago or a year ago it was like 190% of the traffic was towards

Anthropic and now it's a bit different because Amazon is also hosting open source models. Um, so I would say like Amazon is playing it more safely than many of the other cloud providers. And I think you're also seeing other cloud providers like Microsoft starting to play it safe while you have, on the other hand, Neo clouds and Oracle being super aggressive, making huge discounts and trying to win over market share. while you know even if you listen to Jeff Bezos he did a recent interview where he kind of said that he believes that we're in a bubble at least an industrial bubble so

basically an AI bubble and I think that kind of also shows in the way that Amazon or AVS is kind of going towards this although i think they will still benefit so as we have this glut of compute um or scarcity of compute um i think amazon will also benefit because they they do have power and they do have data centers which they can use so you know as microsoft is full as google is full as oracle neo clouds are full you also see the benefits uh in avs so i wouldn't be surprised if we see, so we're recording this before earnings, if we see acceleration of AVS in this quarter, but they are playing the more safer game, at least for now, when it comes to these AI build-outs and taking risks on companies and stuff like that.

And how important is the Anthropic relationship? Because, and I think there was a report yesterday that they are projecting, and this is, I think, well in the hundreds of percent, revenue growth, $9 billion in revenue this year, or at least reaching annual recurring revenue of $9 billion by the end of this year, and then hoping to get over $20 to $25 billion in 2026. How important can that relationship be? Or is it maybe overrated by the investment community? No, I think it is super important because Amazon doesn't have their own models, their own, you know, the horse which they bet on is open source and entropic. So for them, either of those two have to come on top. But so far, like the entropic relationship

does feel natural because, you know, Amazon or AVS is really strong with developers and Anthropic is mostly used for coding, right? So it's like, it's a natural fit because it looks like, at least from what we are seeing right now, is that Anthropic has kind of gained a foothold in this coding environment. So they are, if you will, the enterprise version of this AI models where OpenAI is for now, at least the consumer version of it. So if you look at Amazon, they're targeting the enterprises, always have been, right, with AVS. So it is a natural kind of fit.

And, like, also Entropic is an important client of them for their chips, so for their homegrown chips, Trinium, which Amazon is a bit forcing Entropic to use them. But you need a big client using your chip So that you can develop and enhance the chip To be more effective So I think the relationship is important But yeah, Anthropic has its own Maybe limitations or having some trouble Now we'll see if they will get in the crosshair

Of the government because they're kind of like Trying to slow things down in terms of progress um so this might not be um what amazon is is really found about but um yeah for now it looks like quite a natural relationship and i think uh you know anthropics focus on one vertical or at least visually that seems that way on coding does seem like a smart strategy Is there any – when I look at Amazon's relationship with Anthropic and Microsoft's relationship with OpenAI, I basically look at it – well, maybe not as much with OpenAI, but as pseudo-ownership. I just kind of feels like they, when I think what's Amazon's big push into AI, I think it's anthropic. Is there any advantage to having them separate, independent, but it's just a

huge stake in the business as opposed to actually having them under your corporate umbrella? Or is this just basically to appease regulators? Yeah, I think at first it was maybe to appease regulators um but i think right now i don't think first of all that amazon or even microsoft would want to have an entropic or open air under their balance sheets because they're burning they're gonna burn a ton of cash going forward and you know so it helps them that venture is venture capital is funding those companies because they're then spending the checks on on their cloud businesses right uh and even if if they would want to kind of take over those companies i don't think i think both of those companies are now too big um to to to fall under

that well at least if if we continue on this path and don't come into a bubble territory where we get distressed assets um but i also think like the the ownership stakes of of amazon and even Microsoft I think people tend to think about that they own huge chunks of the business but after restructuring for example OpenAI I think Microsoft is going to get like a third maybe or even 30 percent of the business of OpenAI only so of the new for-profit entity which is like a lot smaller than the 50 percent that they had and even like if you look at Amazon even if it's like 10 to 20%, you're going to get deluded a lot because I don't think that if you intend to raise this trillions of CapEx, which we're probably going to talk about later in the

show as well, I don't think Amazon or Microsoft will be participating in those rounds because I think they're already exposed a lot and their free cash flow is tied up in this kind of build out of the new data centers and GPUs. So I think at the end, these percentages will be like sub 20s or even lower in terms of like just the ownership stake if everything goes according to plans. Okay, let's shift gears to Google quickly or Alphabet, I should say. I'm going to read one of your tweets here that I saw yesterday, I guess, or posts on X. You said Google is the only frontier LLM provider that has the full stack already in place and working. That includes distribution, AI model data, your own cloud, and TPUs.

You said if Google wins the consumer LLM race, it is not only bad for OpenAI, but also for NVIDIA. Google is the only one that is not totally beholden to NVIDIA. I guess let's maybe go through the stack there. um so yeah what are the different components that google owns in sort of that ai supply chain if you will and then how valuable are those tpus sure so if we go for this tech so first with model development so we have deep mind which is uh their ai lab um which is producing products like gemini like vo um so all of these different kind of products or models if you will so very similar to open ai we can we can say right so it's like this is the first um stack and then you have

gcp which is their public cloud um offering and gcp is also helping um of course deep mine because you know they have easier access to infrastructure so open ai is just now trying to build out these data centers where they are kind of like the owner or have a direct relationship with the suppliers so they they're not just beholden to the cloud providers and google already has this with with gcp and also in addition like you know uh all of the volume on gcp helps google's deep mind in terms of like their infrastructure because it it they can optimize it better because they have better scale so they can get better deals for tpus and stuff like that so then we go to tpus which is their hardware um so this is like their asic um uh

competitor to nvidia in a way so um but the thing is that everybody's doing their asic right now right so you have meta you have microsoft you have amazon but google's the only one which has a mature enough offering that is actually effective right so they're on i think it's like seven generation right now um and it's it's by far the most mature and kind of performance wise even alternative to nvidia because with developing of chips you need years you need the cycles of products to learn from your mistakes and kind of you know enhance enhance these products and make it useful um for for the for the workloads that you're powering um so they have the tpus they have tpus at scale so just um i read the last interview i read was from a google uh former

google employee who basically said that yeah we're buying nvidia but we're buying nvidia only because clients are kind of requesting nvidia on gcp and for all the internal stuff including gemini vo we're actually using tpus so even for training they're using tpus which tells you a lot because, you know, Gemini and their models are on par, if not even better than, you know, OpenAI's models. So they're frontier, right? And they were not trained on NVIDIA or inference. And this is helpful because, you know, if the supply chain shanks up

and you can't get enough GPUs or they become too expensive, whatever, Google has their own kind of vertical where they can get the compute and kind of continue to, you know, use the models and inference the models, so provide it to the users. So it's also good, like, when they, you know, negotiate with NVIDIA, you can always say, I have an alternative, right? So it's better to have, you have better negotiating power than if you're just Oracle or Microsoft,

who has very early stages of ASICs, where NVIDIA can say, it was the alternative, right? So I'm not going to give you a discount because you don't have an alternative. Well, with Google, it's different. Even on a recent podcast with Brad Gershner, Jensen said that actually we can put Google in a different bracket with their TPUs and that it's only them and Google which are kind of like mature enough to offer this kind of stuff. and with tpus they're really important because performance per watt um they're they're supposed to be really effective um especially for ai use cases and as i said the proof is it is is in the numbers so if google is using all of their internal internal processes and products and

powering them by tpus then that's the proof that it actually works right so yeah if google is good at anything, which they are good at a lot of things, it is efficiency in data centers and compute. I wouldn't follow up here, maybe on the consumer side of things. I've seen conflicting data out there. Some stuff, you know, it's moving quickly. It's not public for the most part. Is Gemini, from a usage perspective, from like consumers such as ourselves, are they

catching up to OpenAI and ChatGPT? Or are they still the tiny amount of market share? Yeah. Before we move on, we want to talk about our friends at Interactive Brokers. Interactive Brokers is our favorite brokerage platform. They make it easy to buy stocks, ETFs, options, futures, currencies, bonds, and more, all from a single, unified platform. And Interactive Brokers allows you to maximize your returns by minimizing your costs.

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Interactive Brokers is a member of SIPC. Yeah, so in the last, let's say, few months, they have gained a lot of ground. And it's because of NanoBanana and stuff like that, which they released. So products that kind of helped them propel. And even for like, I think it was two weeks, Google was on top of the iOS download charts, which tells you a lot because it's like, you know, when people say Google is on top, they say, oh, but it's like default on my phone, whatever. No, on iOS, Gemini is not default on your phone.

So these are actually actual downloads, right? and it was above chat gpt for like two weeks or even more and then now it's like on third place after openai and sora so kind of openai took the the helm again with with the release of sora uh so gemini is not there yet in terms of like just the usage but it's definitely gained a lot of market share and you know for google it's the right time to launch gemini free and if gemini free is better which some rumors are suggesting this it's really good then then gpt5 because gpt5 in terms of performance we can argue yes um what was the the leap from gpt4 um in my view it the real kind of leap was the routing system so that OpenAI can make it more effective to run the

model. So Google has an opening here to kind of reclaim the frontier model with Gemini Free. So we'll see. I think they're supposed to launch it quite soon, I think in a month or so. So that will be interesting how the market will take that. But we must not forget like AI overviews and AI mode like these are products that are high in usage so google is already showing you that they're serving i think they put out a stat of what trillion or something like that so it's a number so it's higher than trillions of tokens per per per month or per year whatever and that so the the trajectory of those tokens is really high because remember they are serving with ai overviews and AI mode, also these AI workloads and showing you that they can do it effective

without raising trillions of new capex to serve these models, right? So when you talk about Gemini, you have to acknowledge that Google has, in terms of all the usage, I think they're higher than OpenAI, if you look at their surfaces like overviews and AI mode. And it comes back to that infrastructure with TPUs and the stuff they built up for the last 20 years uh just powering google and youtube and what have you let's jump to meta we've got a lot of other companies to get to here the question i have for them is really besides you know advertising optimization which they've been doing for using ai tools for a long time now

what is their strategy for ai monetization because right now i guess i don't see much yeah yeah so with meta we have like as you mentioned so monetizing ai is yes you have ad targeting which they have been doing for quite some time with advantage plus which is not really let's say a gen ai workload so many would try to project it but i i don't think it's a gen ai workload it's just an ai workload right so it's different uh the thing that they can still do and are in the early stages is so generating creative for ads so this is different than targeting this just means that you know smaller advertisers can for very little cost make very compelling ads and the effectiveness of ads because the ad creative is is better

can be much more effective and with it the return on so the raw for advertisers and at the same time this means that over time cpms are going higher because the ads are more effective right um and this is unlocked for small advertisers and it also has bigger advertisers because now they can skip or at least use less of ad agencies and you know they have like 30 40 percent of the budget is for ad agencies, and if they can save that 30%, there were surveys done that most of those savings would go towards increasing ad budgets, again, affecting CPMs.

So, you know, so you have this effect in terms of AI monetization, and then you have the second one, which I think is also really big and important. It's monetizing WhatsApp and other messaging services because now you already see it from open AI and trying to do this. So with e-commerce kind of filled into these chat surfaces, right,

where you can monetize it better. So Meta can go from just selling ads to maybe actually selling and taking a take rate on everything that's sold to the user from using their product, right? So if they ask Meta AI, okay, what's the best sneakers right now? And somebody then asks, oh, but I want them for running and I want them to be, I don't know, color, et cetera, et cetera. And they pull in the actual purchase order, right, that they can do it.

Meta can take a percentage of those revenues and it's not an ad, it's actually take revenue, right? And then you also have WhatsApp customer service. So I think this is a big vertical. As I researched, customer service is just the outside of, so not internal customer service. It's a half a trillion market per year, right? So all of the customer service companies.

And with AI, you can replace all of that industry or at least most of it. And I think that's a big lift for Meta and brings new revenue, which is like more sales revenue again. So, and then you also have, we must not forget with Meta AI, they get higher intent ads so they can start to surface ads similar to google um because they

have higher intent they have other information than just you know uh social um and with higher intent they then own the full vertical so they can go to an advertiser and say yes we can send you brand advertising we can send you social we can also send you high intent ads right so you can service the the whole at kind of vertical in one platform which is really valuable uh and the last part i will mention also is like meta ray bounce and ar i think you know from what we have seen ai will be a really important navigation system for these glasses and it's so more in the voice realm where i think is is the real usage not just in like text but kind of having smart glasses and then saying hey matter can you i don't know can you calculate this that i'm seeing

here or can you you know do stuff and stuff like that so i think having a important and capable ai model is also where you will benefit with smart glasses right aside from the smart glasses initiative which would i imagine i guess it's slightly more speculative in terms of adoption When I think about – of all the companies on this list, it feels to me like Meta has the shortest path between AI training and revenue recognition because of the efforts going towards advertising and maybe Google as well. But if I'm understanding you right, that first pillar that you talked about, not the ad targeting but the ad generation, is that basically – let's say I'm a small business that sells, I don't know, protein bars and wants to target men in their 20s or something like that. Is the idea then that you can go to Meta and you can say, here's who I am, here's the customers I'm looking at, create me an ad and obviously use your targeting efficiencies? Is it like basically just offloading all the work to them? Yeah, exactly.

So it's like you can even, I think it's even easier. So they even have like, I'm not sure if it's in beta or if it's already in production, but a tool that you can just send your link of your website or the product that you sell. And then they can suggest to you actually who your audience is, who might additional audience be and what the ad should be like. But then also as you kind of input it, right, so that you leave the AI to do its work and the AI can hyper-personalize the ad so that if somebody likes, I don't know, if athletes are your target, somebody likes, I don't know,

basketball, somebody likes, you know, football, whatever. So it's different kind of ad creatives that can be created on the fly and make the ads more effective. So, yeah, you are kind of leaving it to the ads, to the AI system to kind of fully do targeting and creative at once. But in terms of like the company that benefits the fastest, I think the cloud providers will still be the ones because they recognize revenue faster.

And then it's, yeah, the ad companies, which should benefit from this and already are partially, but it's also like if you, right now you're seeing, because Google is also transitioning to AI and the usage of search is going down, you are seeing a lot of businesses having trouble with organic traffic from Google. So they are starting to pay up for search ads

and they will also start to pay up whatever they can get exposure. So they're going to start bidding up the CPMs also on social because they're going to try to replace the traffic that has been lost, right? So I think if surge goes away or partially goes away, then you will see all other surfaces benefit from higher CPMs

because the advertisers will just have a harder time to reach people because so far, you know, OpenAI and Gemini surfaces are not yet displaying ads or at least not that much. So until that happens, you can see a bump in CPMs from all the other industry players. Yeah, that's an interesting sort of byproduct is the rise in potential cost per click for those both Meta and Google as well. Let's shift to Microsoft real quick. I think Azure has been seen, I think, as basically the market share taker over the last – and I think that's playing out in the numbers as well – has been seen as sort of the market share taker among the big three hyperscalers at least over the last, I'd say, six months. And I think a lot of people are positioning them as sort of the – well, them and Google Cloud as sort of the AI cloud, the cloud that's benefiting the most from the AI workloads.

What is – I guess, A, do you see that as true? Is that the case that they're kind of the leader as in an AI workload world? And then what is Azure's plan as OpenAI has kind of somewhat publicly now gone non-exclusive? I believe they're working with Google Cloud as well. What's the relationship like there? Yeah, so correct. Azure has been gaining ground, but I would say that Azure has been gaining ground

even before we had the AI boom. So before OpenAI, already Azure was taking market share. Because of their relationship with enterprises, they're kind of bundling with other products like Office, like European systems and stuff like that. um and yeah i mean there are a lot of alternative data sources that that show that asia is continuing to kind of build um and take market share but i think it's also like it would be interesting to see asia numbers x open ai because i think you know open ai as much as it's a positive

for for microsoft it can also be a problem because if you if you're if you're tied too much to one client then because it's so big and because their you know compute demands are so high you might end up not serving your other clients and i think the you know the the the kind of difference that you saw where open ai is now using other cloud providers is because of that fact because i think microsoft said like okay we already have like one third of the company we are serving a lot of their workloads but now we must also take care of other clients and you know kind of hedge our bets to not be exposed 100% to the success of OpenAI and I think Microsoft is also being smart so because they're seeing that you know the cloud

industry like if you said for you four years ago that somebody can attack the modes of the free hyperscalers i would say you're crazy but today we're talking about you know neo clouds and and and even private companies like open air raising hundreds or 300 billion half a trillion for data centers and i think investors need to be careful in analyzing the landscape so if you suddenly don't have free players anymore that can offer you ai compute or compute in general but you have the neo clouds you have open air who's doing their own data centers you have xai again with their own data centers but rumors that they're gonna start selling compute as well um you have oracle so suddenly it's not a monopoly or a free free free player uh oligopoly but it's actually like a

distributed market then the margins are going to be under pressure and you're already seeing this with you know reports out there oracle and their margin you're kind of nice now saying that yeah we will be able to achieve 35 gross margin but let's be honest it's 35 gross margin that's that's not really good for me as as an investor in in what's supposed to be a monopoly business right um aws has 35 operating margin so yeah it's a big difference can i pause here pause your heart and ask when you say neo cloud what exactly does that mean is that just referring to basically oracles and core weaves of the world yes so nebius core weaves um all of the smaller kind lambda labs so you have a ton of these smaller clouds if you if you will that nvidia has

funded or helped get gpus because they also want to reduce the risk of customer concentration and now these neo clouds do have if you think about it just from a ai workloads perspective they're not that far behind from many of the hyperscalers in terms of just the capacity, especially if you now consider like this AI CapEx and letters of intent from OpenAI and stuff like that. So if this actually gets played out in the next three to five years, you might end up with, you know,

NeoCloud or Oracle and everybody else having similar kind of, you know, data footprint as, as some of the hyperscalers. And that's, that's a risk, right? So I think Mike, but I think going back to Microsoft, right. Just to, just to end that argument, I think what they're seeing is that at this point, it doesn't make sense to build crazy at the crazy pace that we're building right now. And they want, they say, okay,

I want to keep the client relationship because the client is, is saying to me uh i need compute i need compute and microsoft saying okay i'll get you compute and then this sign deals with neo clouds uh who provide the infrastructure but the client doesn't need to know that it's run on core weave let's say right so it's he still so microsoft still keeps the relationship with the client but they get to the risk because if the data center build out, so if, I don't know, amortization costs of GPUs are bigger than they are projected to be or anything like that, then the risk of that goes to the balance sheet of the Neo Cloud, not to Microsoft, right?

So I think Microsoft is hedging and saying, and then if we have a bubble and if it pops, then we can get distressed assets. And then, you know, if Microsoft is not too exposed, they can then buy up those Neo Clouds or let's say the value of those neoclouds is mostly in power, so the power commitments and the lands of data centers that they have, they can buy up those assets and then again be in a monopoly market. But if we continue with this space, then it's risk for all of the free. So both Microsoft, Azure, AVS, and GCP.

so. This episode is presented by our brand new partner, Port Sido. Do you know what your actual investment returns are? Well, if you're like me, then the answer is probably no. And that means you need to try Port Sido. Port Sido is the ultimate portfolio performance tracker. With Port Sido, you can easily aggregate your various brokerage accounts and instantly see your actual investment returns. That includes all your investments too, stocks, ETFs, even crypto, if that's your thing, you no longer have to guess what your returns are. With Port Sido, you can find out in minutes whether or not you are actually beating the market. And that includes a dividend tracking dashboard and even tracking of short positions. I have been looking for a

tool like this for a long time because I was sick and tired of tracking it manually and Port Sido has finally built it. If you want to find out what your real returns are, check out Port Sido. The link will be in our show notes. all right let's move on to nvidia it's obviously the giant in the space different player because they're selling to all of these companies that we talked about what's developed over the last few months maybe a few quarters or longer are these i guess the proper definition maybe isn't this but circular circular accounting deals where for example they sign a hundred billion dollar commitment with OpenAI. And then OpenAI is going to potentially turn around and take this money

that's flowing from NVIDIA's balance sheet to OpenAI, and they're going to buy NVIDIA chips. What is there, from your perspective, why are they doing this? What's the strategy there? And why is it necessary? Yeah. So first of all, NVIDIA definitely has the cash flow. So right now, the only company that has big cash flow, free cash flow is NVIDIA because everybody is buying their accelerators, GPUs. Why are they doing it? I think the real reason is, you know,

if you look at, we went from OpenAI and all of these AI startups raising, let's say from zero to 10 billions, we had venture capital. So we had the Sequoias and we have all of those companies, venture capital flooding these companies, from 10 to 30, you normally get somebody like SoftBank, right? And now you're going into a realm where these companies are trying to raise

hundreds of billions or even trillions of dollars. And who is going to invest or lend them money? Well, probably the only company that has enough cash is NVIDIA maybe apple right um and for nvidia it's important like there was a stat from dylan patel who who runs the semi-analysis team that one third of nvidia's gpu cells go uh so the end customers of one third of of the gpus that are being ordered are open ai and entropic so for nvidia it's really really important that these two clients can continue to get new capital otherwise you might end up with a problem in terms of your growth slowing down so i think nvidia's motive here is

to help their most important customer continue to get new capital because if they put their name on it they can get let's say easier although i'm not sure how easy it is to raise that kind of amount of money right but they can get it easier if they have nvidia is also part of the deal i think that just shows us that we're at the quite late stage of the cycle where if you will the last lender or investor is nvidia and we're also seeing this you know we're starting to see a lot of these debt deals where now gpus are being sold to an spv who then rents the uh the gpus to to somebody like open ai or xai or whatever right and the collateral of that debt is the gpu or the data center um and again here here is the problem because gpus are fast depreciating assets especially as nvidia

went to a one-year product cycle, right? So we're starting to see these creative deals, which I am worried about because I think it shows that, you know, we are at the late stage of the cycle, at least when it comes to CapEx and these crazy commitments. So NVIDIA has a lot of cash.

They probably don't know what to do with it, but at the same time, they want to prop up the ecosystem for it to continue to kind of function, right? even even if nvidia it's not the first deal so nvidia is active in supporting core weave they also have a deal with core weave where if uh i think it is for seven billion if core weave in x years doesn't have enough demand for some capacitive nvidia chips they will be the backers of that so they will take on that burden of of the unsold compute which is again like

you know showing the creativeness or the late stage cycle that we're in um so yeah let's talk before we move on to another company let's talk the question from twitter that i thought was quite helpful and essentially just said they wanted to know your thoughts on the impacts of any changing depreciation schedules for gpus you mentioned the rapidly depreciating assets there just what your thoughts there and how it plays out over the long term with this industry yeah so i recently wrote an article on uncover alpha um covering some of these problematic areas and one of them was the the amortization rates of gpus and the problem is that you know people and the cloud companies are so the usefulness of life for these gpus are mostly um being extended towards five to six years

So I just ran the numbers just for comparison. So Microsoft, they have server networking equipment over usefulness of life is four to six years. Oracle just bumped their usefulness of life for GPUs in 2025 from five to six years. Amazon this year reduced the usefulness of life from six to five because they're saying technological progress is faster. Then we have CoreWeave, who's six years, Meta, who's five and a half years, and Google, who's six years. And this is networking equipment and GPUs together,

so it's not just GPUs. But what's important here to understand is that up until 2024, NVIDIA was on a two-year product cycle, right? And since Blackwell, so they're now on a one-year product cycle. And this changes things because each generation of accelerator is much more efficient in terms of tokens per watt. So from Hopper to Blackwell, Jensen said it himself, the ratio is that Blackwell can do 10 to 20x more tokens per watt than the Hopper generation can.

And why is this the problem? The problem is because we're also running out of energy. So we have, you know, everybody's scraping for gigawatts of energy. And if you have limited energy, and just think about it, for now, we just had incremental selling of GPUs. But now we are entering an age where the data center are built out and you have demand, but you don't have any more energy. So you can't open new data centers,

or at least it takes years for them to be opened. So what do you do? Then you have a GPU and you can say, okay, if I replace the old GPU with this GPU, I'm talking GPU, but it's really accelerated. If I replace it, I get 10x more tokens. Even if I get 5x, 2x more tokens, right, even if we're more conservative, you can serve 100% more compute demand, which you want to do, right? um so the problem becomes that you're saying that the gpus are five or six years useful i don't think that's true i think the real number is more than two to maybe three years of usefulness but if that's the correct number so you have also industry experts saying this so

grok uh the ceo of grok he's saying one to two years right uh but if this is true if this turns out to be true then the the amortization expense is should be double of what it is today and what this means is that every company that is in this space is uh not accounting their cost correctly and the amortization expenses are double and why is this ratio should be higher right yeah so the p ratios are higher right and why is this so important so before data centers were not that big you know they were big in terms of like an expense a capex expense or on the balance sheet but now they're really big right so it becomes such an important part of the business that it will affect the bottom line very very much so right so it's like um the topic of what

the correct usefulness of life for for gpus is or accelerators is should be on top of minds of investors because especially like the business models of many of these neo clouds core weaves and other if you change it from six to three they're already making losses but the losses are even bigger so and especially if you consider the debt deals where gpus are correct collateral right so that's even worse right so it's like um this could be a problematic area for the whole industry which is systematic not just um surface level so i want to spend a little bit of time here because i think this is a very hotly debated topic and it's obviously very important so when i picture what's going on here the whole value chain like all the capex that's going on

anytime you see a big boost in capex at amazon or aws specifically what i'm picturing is they're standing up a giant warehouse they're filling it with a bunch of basically computer shelves or server shelves and the biggest asset the biggest cost in there is gpus and i think we had a guest on here a while back that said these are the fastest depreciating fastest depreciating assets in human history so in my mind i'm thinking like this can't possibly on the one hand there's so much innovation going on that's great but it's leading to faster depreciation schedules i would think like if if if you just improved your product cycle from two years you as in nvidia and now it's every six months or every eight months or whatever

that means the depreciation schedules in my head should be shrinking right because you've got new ones but are they able to repurpose the gpus are they able to make like let's say i bought the newest iteration of nvidia's gpus today two years down the road can i just offload those to a less compute intensive workload like is that is that what they're basically doing yeah so you're correct in terms of data centers so 60 of the cost is the gpus at current rates so you still have like 40 percent or 30 percent so 60 to 70 percent is the gpus so the the 30 percent is still the data center which is like is an asset that you can appreciate for for longer cycles but yeah there are people saying the argument oh but they can use it for internal

workloads yes but this is only for a handful of companies so you have google which has their own search you have meta which has their own you know social media you have amazon and you have microsoft but a core weave can't repurpose it for internal workloads they have to sell it on the market right and right same same with oracle and also even with with companies like that google meta and they're repurposing it because they couldn't get enough of it and they had space for it right but right now what's happening is that you know um when they fill it out the opportunity costs just become too big for them to ignore right if they can serve serve 3x 5x more than with the old gpu then they should be replacing it right and at the same time you have electric

prices surging because everybody's building data centers so with with the gpu you don't have just capex you also have opex right you also have um opex costs with electricity and now let's not forget it's it's hard to repurpose you every new generation of nvidia has liquid cooling so you have data centers uh that need liquid cooling so you're not going to be so if we talk about this from three years so in the future let's say three years from now people will still be using blackwall yes but they will have to have liquid cool data centers and the the the people that have liquid cool data centers there are not a lot of data centers that liquid cool most enterprises don't have it only the hyperscalers have it and some neo clouds and bitcoin miners

and stuff like that right so it's like um this only works if you have a company also inside of your company um that's using those internal workloads and if you're basically selling incremental new gpus and if you're not already stacked in terms of like space and energy and everything like that right um so yeah that that's and even when people say like yeah but they're still using h100s or even a100s a100 is two generations from black hole it's it's not six years or three or five years it's two generations right so we're talking about three years in terms of product years right because nvidia has bumped up um their their product cycle right um so it doesn't make sense for gpus to be six years old assets so usefulness

of life being six years old but that would mean that in terms of product a g so a gpu that was launched in i don't know 2018 2017 is being used right now you even have a report today from the information and let's take this report with a grain of salt but still having internal documents showing that oracle had problems leasing out h100s until open ai came and take took the compute so you also have to imagine like if there was an open ai and tropic would the market still be so would the prices of h100s which is a basically a one year old product cycle um product still be this high or are these two companies you know inflating the whole market because they have so much demand and they just want to meet demand because they are also like losing money so for

I think it was a stat for every dollar that's being spent on change GPT and open AI, they're losing $3. So if this ends, you can end up with a lot of compute which should be repriced differently than it is today. Because you have two companies basically driving the whole economy. relatively i think again alphabet seems to come out ahead even though they're not going to quote on quote win if you know the demand collapses as as could potentially happen but that's a great segue to the growing elephant in the room even though the revenue is significantly smaller than everyone here but they dominate the news cycle they dominate the spending projections it is open AI, if you look at their business plan that they've released or leaked out there, they're

going to be losing, I think, cumulatively burning $100 billion, if not more, through 2030, but they seem to have the financing to back them. They have a trillion dollars worth of commitments to all these different companies. It seems like they went from just using Azure to, okay, we're going to try to use every company possible to build out not only our own compute, but having cloud partners. I say all this stuff because I want to ask what you think OpenAI's business looks like in 2030. What could happen here? What's the potential outcomes? All right, folks, before we move on, we need to tell you where we get our financial data. Fiscal.ai. Fiscal.ai is the complete stock research platform

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The link will be in the show notes. yeah i mean um first of all open ai definitely you know is the the google verb for llms so it has established a brand which which helps them a lot but i think at this point where we are at you can see it from just the last few months they're trying to juice up everything to boost engagement and to you know keep the user growth there and why are they doing it of course naturally because they will have to raise hundreds of billions if not trillions of dollars to meet the the purchase intent letters that they send send out to all of these companies um so even altman if you listen to him he says yes we're in a bubble but at the same time we got something real here

right this is from ben thompson's blog and you can sense it that he he's like if capital markets either that's venture public are going to continue to give us money we're going to take it because of course more the more money you have the better your outcome is going to be whatever if it's a bubble or if it's not a bubble right um so and even like you have to think about Microsoft was the kind of first backer of OpenAI. We talked about this before, right? And they have in their agreement, so Microsoft can always deny OpenAI's request from other. So OpenAI says, Oracle has offered me this compute for this price.

Are you willing to match it? And Microsoft can say yes, and they have to go with Azure. But Microsoft is saying no. and they're having so if anybody microsoft has even access to open as ip right and sacha has over the years proven he's very smart he's not like he's not super safe he's he's trying to get market share he's trying to make google dance and everything right um so if you think about it like why is microsoft denying all of this compute that they can be serving could be serving right because it's not like compute that's out there right now it's like compute is going to be built

in three five years so microsoft could do it as well right and i just can't get past the feeling that we are that microsoft's trying to hedge right because we are entering the numbers that don't make sense anymore right and openai has said yeah please be be patient we're gonna come out with new deals my bet is that my bet is that they're going to come out with some also electricity deals so even if it's a smr also nuclear or if it's gas plant or whatever because they need the power right but still as long so the capital markets has the button on all of this if we get around from open air where they can't raise what they wanted to raise the market will start panicking in my view because then you know you suddenly have those two companies that can't fill in the

all of all of the all of the um purchase orders that they send out which means that all of the expectations for oracle which stock price jumped 40 percent when the letter was sent for amd for nvidia for everyone so everybody's connected to the fate of these two companies um and if you ask me what's so if i go back now to what's gonna be open ai in 2030 i have no idea because it can end really bad or it can end up like we're in some ai god mode or whatever right so um but it's definitely something we haven't seen ever right and even though i'm technologist by heart the numbers just don't make sense at this point anymore for me and that's why i'm more cautious yeah i think that's a really detailed view sounds like there's certainly some

at a minimum concentration risk and all this spending uh i wanted to talk apple but a i don't know if there's that much to talk about but also b we're bumping up on time here so we want to ask our final question to you if you had to pick one today i know this is kind of a tough question because i'm pretty sure you own a couple but if you had to pick one today which company do you think will be the biggest winner of this ai race by 2030 of the ones we talked about today by 2030 okay are we talking about which company is going to have the biggest market share or or are we looking at an investment perspective as well so let's look at your favorite investments okay today like what do you you don't have to rank them but what do you like and what do you

dislike you know valuation does matter at this point my number one is google and the reason is we talked about it it has the full stack and i think the tpus are something which will be Google's most important assets to date and they have a lot of assets so that's saying a lot because they're already showing us that they can serve a lot of inference on scale which nobody else can

and they don't have to raise trillions and I think that will be really important because I think we will come to a point which Opinion already hinted where Opinion will have to raise prices and at that point you know google can go in this game and say okay we're gonna cut that and we're gonna cut it or we're gonna keep it free or whatever right and if if the models are similar in terms of performance and everything you want to talk about it and you have to pay

for something and you don't have to pay for for the other thing and it's the same then it's a big benefit also till 2030 we will have to all of these companies will have to transition at least partially to the ad business model and there's no other company besides meta that's really good with ads and that's google right so it's like they have the relationship with advertisers they know the surface and then you you are in their ballpark so you're in their game right so um and also gcp right i think you're gonna see gcp win a lot of deals because tpus will be able will be priced cheaper and people will not be so reluctant to just go to NVIDIA.

Because right now NVIDIA has, so from multiple former interviews and stuff like that, the notion is kind of like the clients are saying, I want NVIDIA because nobody is getting fired for choosing NVIDIA. Right. But if that's too pricey and you have an alternative, and as the market is shifting from training to inference being a bigger portion of the pie you know the costs are are really important and then the tpu can become

you know a really important asset and people will say okay no let's for inference let's also use the tpus right um which are a lot cheaper so um i think the moment for google is quite there and they're not yet priced because of the risk of ai disruption search disruption but even with search disruption we have already figured out that the ai market the lm market is tam is a lot bigger than just search because it's not just information retrieval it's like agents agentic use cases all of the other stuff and if open ai is able to you know raise trillions they're probably going to be valued at what one two trillion then you can't say the deep mind is not valued at least half a trillion or or even more right and then you have the full replacement of search but again

even search search still is the backbone of many of these llms so it might not be the front end surface for users but it will still be very important to be the back end and not to mention all the other ai stuff that google deep mind's working on which includes waymo but there's plenty of other things medical biotech what have you and it comes back to again i think this is the biggest theme from this episode is the infrastructure advantage yes yeah i agree i agree rahar thank you for joining this uh episode once again for the listeners that have listened to this episode enjoyed your thoughts they should definitely go over to uncover alpha what's a 30 second elevator pitch and what you do over at that newsletter

so i basically do deep dives into these companies into the specific sub-segments like tpus like stuff like that uh and and i i focus it all also on alternative data sources so i'm trying to source as much so former interviews data from you know uh job employment stuff like that so trying to read as much alternative data and all basically be transparent and source it based on as much that data as i can so it's not like it's not just my opinion it's kind of you know it's opinion but it also a lot of um insights from from these all of these sources so yeah all right beautiful thank you once again let's hit the disclosure and get out of here we are not financial advisors anything we say on the show is not formal advice or recommendation ryan i or any podcast guests

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