Google's New AI Chip Could Actually Dethrone Nvidia (Ironwood v7 TPU)

Josh: One of the most famous investors in the world, Peter Thiel, he wrote a book called Zero to One. Josh: Some of you might have heard it, some of you may have not, but it's all about Josh: monopolies and how much of an advantage having a monopoly has in the world. Josh: Now, what we've seen recently is a company named NVIDIA reaching a $5 trillion Josh: monopoly. It's the biggest monopoly to ever exist in business, and it's huge.

Josh: It's made tons of people, infinite amounts of money, but something is happening. Josh: Something is wrong. It appears as if that monopoly is starting to slip out of their hands. Josh: And in this episode, we're going to talk about why and what that means for the entire market. Josh: I mean, when you're a $5 trillion asset, the size of your company makes a meaningful impact on the market.

Josh: So when a company like NVIDIA loses hundreds of billions of dollars over a short Josh: period of time like the last month, we got to start paying attention to this Josh: because it's dragging everything else down with it.

Josh: So up here on the screen, we have some charts that I want us to walk through Josh: EJS. So if you could just kind of show us the difference between NVIDIA and Josh: who we believe to be the competition that is responsible for knocking these Josh: hundreds of billions of dollars off their market cap. Ejaaz: Yeah, so this really scary looking red chart that you have in front of you is Ejaaz: the last month's performance for NVIDIA stock. And it is down a staggering rate.

Ejaaz: 13, almost 14%, which equates to over $500 billion of market cap loss. Ejaaz: That's a billion with a B, which is just an insane amount of money for the largest Ejaaz: company or stock company in the world to lose. Ejaaz: So the obvious question that comes in is why and where's that market, Ejaaz: where's that money kind of flowing towards? Ejaaz: Well, I want to show you another chart, Josh, which is Google's chart. Ejaaz: And do you notice a similarity?

Ejaaz: Over the last month, it is up almost the same amount in percentage market cap Ejaaz: for a very peculiar reason, or maybe it's not so peculiar. Ejaaz: Josh, have you heard of these? You've heard of these things called TPUs, right? Josh: We're talking about this. Oh, there's no things called TPUs. Ejaaz: Yeah. There's no things called TPUs. You know, Josh and I like to kind of go Ejaaz: back and forth and discuss this a lot.

Ejaaz: In fact, we actually put out a bull episode on Google, which a bunch of you Ejaaz: watched a few weeks back. and I don't want to be running victory laps here, Ejaaz: but it turned out that Josh and I might have been onto something. Ejaaz: But I want to dumb down what's going on here, showed by this really hilarious Ejaaz: graphic or comic from the semi-analysis team. Ejaaz: And it basically goes, Google came out with this new rock, new shiny rock called TPU version seven.

Ejaaz: It's basically their version of NVIDIA's GPUs, but it's built by themselves in-house. Ejaaz: And it's actually really, really good. It gives you an average of 30% to 50% Ejaaz: cost savings for the exact same performance or equivalent of an NVIDIA GPU. Ejaaz: And it, in some cases, performs even better, up to one and a half to two times better, right? Ejaaz: And so you've got NVIDIA in the leather jacket here on the right,

Ejaaz: which says, actually, my ROC, my GPU is faster, right? And Google's like, is that true? Ejaaz: And then everyone ends up using Google's TPUs. And the point being made here Ejaaz: is for the longest time, Josh, NVIDIA held the monopoly on the AI training and Ejaaz: inference market via their GPUs. Ejaaz: It's all anyone and everyone could use to train their models.

Ejaaz: It was the only option that they had. And now Google presents a real threat Ejaaz: to NVIDIA's market dominance by presenting these TPUs. Ejaaz: Now, initially, they use these TPUs to train their own model in-house. Ejaaz: In fact, Google's never purchased NVIDIA GPUs to train their own models, Ejaaz: and yet they have the best models, which tells us that the TPUs is something Ejaaz: to really contend with NVIDIA's GPUs.

Ejaaz: But most recently, Josh, they've started selling these to other companies, Ejaaz: supposedly, to train their own models. And so we're reaching a point now where Ejaaz: Google and NVIDIA is a direct comparison. Ejaaz: And we're seeing that in the market share dynamics that are happening now. Ejaaz: You know, you've got NVIDIA losing up to $500 billion and Google gaining the Ejaaz: same amount over the same month. It's just pretty insane to see.

Josh: Yeah, I can't stress this enough, how insane that delta between the two stock charges. Josh: That's 26% combined in one month. So the market is really pricing in the fact Josh: that this monopoly is starting to crumble. Josh: Now, I think we have reasoning why that's not necessarily the case. Josh: That will come later in the episode. Josh: But for now, there is some real forces at play. I mean, EJs, Josh: you were talking about them selling TPUs.

Josh: This morning, I saw Morgan Stanley make this announcement. They said about every Josh: half a million TPUs Google sells can add about 13 billion in revenue. Josh: And Google is planning to sell 12 million of those over the next two years. Josh: So it's a significant amount of revenue that Google can expect to come down the pipe. Josh: And it's the first time that we're really starting to see a legitimate competitor

Josh: to the NVIDIA GPU cluster. Now, that's not to say the GPU is done for. Josh: There's a lot of competitive advantages to a GPU. Josh: I suspect they're not going anywhere, but there is now... Josh: Another market force at play. And when we see a market force kind of cutting Josh: in, it starts to price cascade and the monopoly slowly starts to fade.

Josh: I do want to give a brief history lesson, E.J. on the history of Google and Josh: their AI program, because what a lot of people don't understand is Google really Josh: is the godfather of AI from the beginning of time to now. Josh: And they've just had this problem where they haven't been able to actually build Josh: products that scale or sell products to users. Josh: But they've been doing this since all the way back in 2011.

Josh: And what we're seeing here is the original paper that a lot of people would Josh: conceive to be the first time that a neural network proved that it was work. Josh: And they trained a massive unsupervised model on 16,000 CPU cores. Josh: This was before GPUs existed on random YouTube frames. Josh: They didn't use any labels. They use no supervision. And then one neuron spontaneously Josh: learned the concept of a cat.

Josh: So this seems so stupid. It's like, oh my God, it can recognize a cat. Josh: But this was the first time in history a machine was able to identify something Josh: without explicitly written instructions. Josh: And that moment inside Google set off a light bulb that eventually led to them Josh: creating Google Brain, which was enough of a breakthrough for them to start Josh: creating AI inside of their in-house system.

Josh: So EJS, if you remember Google Translate, which has been around seemingly forever, Josh: Google Translate is a result of AI. Josh: That was an early test implementation of Google Translate. And what that actually Josh: enabled is they could suggest to sponsors...

Josh: Or advertisers on the platform, which companies are more likely to click, Josh: which users are more likely to click. And that created the whole AdSense model. Josh: It created, oftentimes when you type into Google search, it'll autocomplete for you. Josh: These were all very early versions of AI before we even realized what AI was, Josh: which led to the invention of the TPU almost nine years ago.

Josh: And the TPU is this vertically integrated chip that we see today taking over Josh: basically the entire world, one company at a time now. Josh: So they've been doing this. I mean, a lot of people don't realize the TPU has Josh: been around for nine years now that they've been iterating. Josh: We're currently up to version seven, which is the Ironwood TPU.

Josh: And it's just this incredible testament to the fact that Google actually has Josh: been doing this for over a decade now, almost 15 years.

Josh: And we're finally starting to see the fruits of their labor grow and be exposed Josh: in public markets. And my God, it's explosive. Ejaaz: It is insane that, you know, they've been working on this for over a decade, right? Ejaaz: And like that compounded value is really starting to show now because like, Ejaaz: I'm guessing like everyone back in the day was just kind of like, Ejaaz: what is this machine learning thing?

Ejaaz: Like, I can't imagine any kind of like a chatbot being beneficial to us Ejaaz: and then fast forward to 2022 chat gpc goes viral Ejaaz: and suddenly everyone's kind of raving about gpus and google's kind of Ejaaz: like quietly smirking and smiling not buying any of nvidia's gpus being like Ejaaz: hey we invested in this a decade ago and it's finally paying off which is just Ejaaz: kind of uh insane to to think about and like josh like they came up with the

Ejaaz: transformer as well right which Ejaaz: is like 2017 architecture exactly for this alarm so super cool to see. Ejaaz: Now, I want to kind of like step aside and kind of frame the narrative for what Ejaaz: we're about to discuss right now. Ejaaz: We're talking about Google versus NVIDIA, and there's many different ways that Ejaaz: we can kind of compare the two, right? Ejaaz: The most obvious one is through TPUs versus GPUs that you mentioned.

Ejaaz: And one of the biggest questions that I think listeners have on their mind, Ejaaz: Josh, is like, okay, well, if Google's going to compete with NVIDIA, where's the proof? Ejaaz: Like, who are they selling this stuff to? Ejaaz: Like, surely they can't be selling to any major competitors, Ejaaz: right? Surely they can't be selling to major companies. Ejaaz: So can they actually really compete? And I just have one article I want to share Ejaaz: with you, one little tweet.

Ejaaz: You might have heard of Meta or Zuckerberg, who is rumored to be spending tens Ejaaz: of billions of dollars in 2026 on Google's CPUs to train their llama or big Ejaaz: llama models coming up in the future. Ejaaz: Now, of course, you're not too unfamiliar with Meta's kind of progress recently, Ejaaz: or rather their spending budget.

Ejaaz: They've spent, I think, to the effect of $25 billion this year just to hire talent, Ejaaz: to train the model we haven't even seen the model uh to Ejaaz: begin with so the fact that they're planning on using google's infrastructure Ejaaz: uh supposedly to train their models is is Ejaaz: no easy feat and so you might be wondering well like why why would they choose Ejaaz: tpus over nvidia's gpus that's kind of like the standard kind of framework to

Ejaaz: to go down well i just want to show you the scaling chart which basically shows Ejaaz: that uh the tpu which is google's um infrastructure their gpu versus the GB300, Ejaaz: which is NVIDIA's latest GPU, Ejaaz: There's a significant cost difference, right? Ejaaz: If you were to use Google's TPUs, the IronWord TPU v7, you would save 30 to Ejaaz: 50%, depending on the amount of TPUs that you would use,

Ejaaz: in training your model. Now, when you consider that Meta's CapEx spend for the Ejaaz: next year, I believe is going to be something along the lines of $67 to $85 billion. Ejaaz: That is a lot of cost saving if you are able to use Google's TPU. Ejaaz: So from an economical sense, it makes a hell of a load of sense, right? Ejaaz: And then the other thing I was thinking about, Josh, is why would Meta kind

Ejaaz: of use Google's TPUs for their own systems, right? Aren't they directly competing? Ejaaz: Well, there's a secret kind of detail that I learned about this. Ejaaz: The way that Google's TPUs are designed makes it really performant for something Ejaaz: called recommender systems. Ejaaz: Now, a recommender system is the system that is used behind ads, Ejaaz: behind social media algorithms. Ejaaz: Meta is arguably one of the biggest companies which uses these things.

Ejaaz: So if they can have a hyper-performant TPU, train the AI model to use on their Ejaaz: own social media platform that will make it inevitably better Ejaaz: 30 to 50 percent less cost, it seems like a complete no-brainer. Ejaaz: And if you add this deal to the Anthropic deal that are purchasing 1 million Ejaaz: TPUs from Google, as well as another deal that we're about to talk about, Ejaaz: that's just insane. Don't you think that's pretty insane, right?

Josh: Yeah. And going back to that chart that you just brought up earlier, Josh: which shows the cost difference, like if you're a big AI company spending billions on training models, Josh: Google is now offering a system that can cost only 25 to 50 Josh: cents for every dollar you'd spend on NVIDIA's best hardware Josh: and that is a huge deal because i mean Josh: when it comes down to it cost per compute cost per unit of compute

Josh: and training is so large when you're at the scale of these companies Josh: spending tens of hundreds of billions of dollars that 25 50 of the cost is massive Josh: and granted like you said they're not good for everything but if you're a company Josh: like meta who's building suggestion algorithms that's particularly good for Josh: this is a no-brainer and it seems to me like now the only threshold will be Josh: how quick can google actually create these manufacture them spin them up,

Josh: put them in server racks and get them online so people can start using them. Josh: Because this unlocks a whole new use case for AI that we haven't seen in the Josh: past that we'll see now because of Josh: the lower cost and also the increased efficiency of these Ironwood TPUs.

Josh: And Google's innovating quick, man. I mean, each one of these TPUs is coming Josh: out every single year and each one is significantly better than the last. Ejaaz: Every 500k TPUs that Google sell adds 10% to their 2027 Google Cloud Rev and Ejaaz: 3% to their at 2027 earnings per share. Ejaaz: That is insane. So they don't need to sell. Yeah, $13 billion.

Ejaaz: They don't need to sell near as much GPUs as NVIDIA sells. They just need to sell a couple hundred K. Ejaaz: And if this is just one deal that they're cementing with Meta, Ejaaz: can you imagine how much revenue they're just going to churn from this? Ejaaz: It was rumored that the Anthropic deal, where they're selling around, Ejaaz: I think it's a couple hundred TPUs to them, is going to earn them $50 billion. Ejaaz: Next year just to train Anthropics kind of like next forward model.

Ejaaz: So just kind of insane to see. Ejaaz: There is a counter thesis to this deal, which is, you know, I'm going to put Ejaaz: my tinfoil hat on here, Josh, which is Meta's kind of doing this so that they Ejaaz: can negotiate better terms with NVIDIA Ejaaz: or AMD to kind of get like better chip deals saying, hey, look, Ejaaz: we'll go with Google unless you guys give us a cheaper kind of route. Ejaaz: I think this is kind of like conspiracy theory.

Ejaaz: I mean, the metrics around Google's GPUs kind of prove themselves. Ejaaz: But it's just something to keep in mind. I don't want to get too much into my bold thesis here. Josh: I was going through a lot of the deals that we're surfacing today. Josh: One of them being with Foxconn and Google, where now Foxconn is responsible Josh: for building 1,000 server racks a week. Josh: Next year, they're doing 2,000 server racks a week.

Josh: There was an announcement earlier today where Google is now partnering with Josh: AWS, the cloud server, to provide more infrastructure. Josh: So we're starting to see, again, more of these deals that are happening around Josh: the Google TPU world, which is super fascinating. Josh: And then this leads to the final point, which is the head of AI infrastructure Josh: in a meeting from a few months ago saying that, Josh: Google must double AI compute every six months to meet its demand.

Josh: So there is no shortage of demand. There is no shortage of infrastructure. Josh: There is no shortage of support to get these TPUs out to the world. Josh: And what we're going to start to see is how big of an impact this really does Josh: have on a company like NVIDIA now that there is someone else in the market. Josh: There is a second seller for a company like Meta who wants to build massive AI systems.

Ejaaz: You could argue one of the most obvious bull signals to purchasing or investing Ejaaz: in Google stock was the fact that Berkshire Hathaway bought a three and a half Ejaaz: billion dollar stake in Google literally a couple of weeks ago. Ejaaz: And then, funnily enough, the leaked information around them selling TPUs to Ejaaz: Meta and them striking this deal with NATO kind of like surfaced, right? Ejaaz: So there's a lot of momentum behind Google right now.

Ejaaz: There's a lot of big, valuable investors and kind of infrastructure providers Ejaaz: getting behind the Google train right The momentum is palpable, to say the least, right?

Ejaaz: And this NATO deal is another example of it, right? Like, we're going from the Ejaaz: hyperscaler kind of consumer level to the government level as well. Ejaaz: So all types of organizations are treating this with a very high importance Ejaaz: that Google is going to play an inevitably big role here. Ejaaz: So then that begs the question, well, what's NVIDIA going to do about this? Ejaaz: Are they just going to continue losing hundreds of billions of dollars in their

Ejaaz: market cap? Or are they going to strike back?

Ejaaz: And there's two frames of thought about this, Josh. Number one is, Ejaaz: so NVIDIA's next generation of GPUs is going to be around the Rubin architecture. Ejaaz: It's called Rubin, right? Ejaaz: They introduced a new spec, Josh, after Google's TPUs, their latest TPUs got Ejaaz: released, which upped a lot of the watts or compute performance for the Rubin architecture.

Ejaaz: Now, some might say this is just coincidental, but some might say this is a Ejaaz: general reaction to the fact that Google just has a higher performance TPU versus theirs. Ejaaz: And so they needed to kind of like up the metrics of their next generation if Ejaaz: they wanted to compete and appear attractive to their competitors or to their customers themselves.

Ejaaz: But then there's also the argument where it's just kind of like NVIDIA and Google Ejaaz: are kind of playing in kind of like different ballpark and they already know Ejaaz: this. They're playing different games. Ejaaz: The argument here in this tweet being that Google's TPUs are great, Ejaaz: but they're only for very specific niche use cases. If you have, you mentioned earlier, Ejaaz: the recommendation or search algorithm, then, you know, these ASICs are going to be really good.

Ejaaz: The benefit of NVIDIA's GPUs is that they're highly generalizable. Ejaaz: So if you wanted to train a model in a different way or test out a new method Ejaaz: to kind of like inference or train your model, GPUs are by far the best architecture Ejaaz: or the best infrastructure to use. Ejaaz: So you could argue that Google, that, sorry, NVIDIA is sitting pretty comfy. Ejaaz: And Jensen went on a show or an interview this week, basically saying that he's

Ejaaz: not worried about Google. Obviously, you expect him to say that, Ejaaz: but mainly for the fact that this is a positive sum game. Ejaaz: You know, Jevon's paradox, if you create more GPUs, it's not going to be a fact Ejaaz: that you have oversupply. There's just going to be increased demand for compute. Ejaaz: And I think Jensen knows this, and that's why he's just kind of running forward.

Ejaaz: The fact of the matter is, there isn't enough NVIDIA GPUs to supply the customers, Ejaaz: even if you wanted to, right? Ejaaz: He needs to ramp up infrastructure production. That's why he's been visiting Ejaaz: TSMC for the last couple of weeks. So I think he knows this and I don't think Ejaaz: he's too worried, but he's definitely sweating a little. I don't know if you think the same.

Josh: Yeah, no, I mean, I'm sure it sucks. It's like you were just running the show Josh: and now suddenly there's someone else who has a good product. Josh: It's not to say that it's going to harm the company too much. Josh: And I think for anyone who's listening, if you take away one thing from this Josh: episode, it's that both of these companies are going to succeed wildly. Josh: And there is going to be a shortage of supply for compute for a very long time.

Josh: If you believe that AI is as impressive and as important as a technology as Josh: it really is, then you also have to believe that all of the compute around us Josh: must be replaced by it and must have it embedded inside of it. Josh: In order to do so, you need to shift the entire technological infrastructure Josh: of all the hardware that exists over to infrastructure that supports AI. Josh: Everything. And we are just a fraction of a percentage through that transition.

Josh: So as a result, there could be many more Googles, many more NVIDIAs, Josh: and there would still be a shortage. Josh: Now, the question becomes, is there a short-term bubble? Are we overspending?

Josh: That is to be determined, but this is a good type of bubble. Josh: This is one that even if it does explode, we are left with unbelievable technology Josh: across the board and a scaling infrastructure that will continue to be able Josh: to support this new type of technology that's permeating throughout society.

Josh: So is this a good thing yes is nvidia going Josh: to suffer maybe sure the headlines suck it's like okay Josh: we're not the coolest person in the world now there's someone else who's like also a Josh: cool kid but they're still going to continue to produce Josh: the best products in the world and i just to the point that you made Josh: earlier they're just different types of chips like um a Josh: gpu is very different than a tpu and a

Josh: lot of people also need to understand that the whole Josh: world isn't actually training ai there's still a lot of other things that are Josh: happening like graphics or simulation or financial technology Josh: scientific research tpus just don't do Josh: that and gpus do so there's there's a lot more Josh: going on to the story there's a lot more gpus being sold there's a lot of tpus Josh: there's enough for everybody and then there's still not enough for everybody

Josh: so i think in the long run like this is just great for both companies this is Josh: positive some uh there's a lot of excitement around this rightfully so because Josh: i think it's it's great there's another person stepping in but it's not the Josh: end of of anyone it's just the beginning for for so many of these companies still i. Ejaaz: Mean like don't take your and my opinions either, right? Why don't you just

Ejaaz: listen to one of the smartest men or smartest businessmen? Oh, we got Elon. Ejaaz: Yeah, we got Elon. And he was asked this question in this interview clip that I'm about to show. Ejaaz: This was released yesterday where he was asked, Elon, if you had to invest in Ejaaz: any AI companies today and hold it for a decade, what would you buy? Ejaaz: And you think, you know, Elon would shill his own companies.

Ejaaz: He didn't. He shilled two companies, Josh, Google and NVIDIA. Let me show you a clip. Ejaaz: I think, you know, Google is going are gonna be pretty valuable in the future. Ejaaz: They've laid the groundwork for, Ejaaz: an immense amount of value creation from an AI standpoint.

Ejaaz: NVIDIA is obvious at this point. Ejaaz: I mean, there's an argument that companies that do AI and robotics and maybe Ejaaz: space flight are gonna be overwhelmingly all the value, almost all the value. Ejaaz: So the output of goods and services from AI and robotics is so high that it Ejaaz: will dwarf everything else.

Ejaaz: And so, you know, you hear it there from Selfway is basically describing NVIDIA Ejaaz: as a sort of toll collector because you kind of like need to basically pay the Ejaaz: toll man for his GPUs to get access to the intelligence that you're trying to build. Ejaaz: And then Google's mode is kind of similar but quite different in the sense that Ejaaz: they create the GPUs, their own TPUs, but they also like kind of own dominance Ejaaz: across the entire AI stack, right, Josh?

Ejaaz: And just to kind of maybe like round things up, I was looking at these crazy Ejaaz: charts from the Financial Times this week, Ejaaz: which basically showed that Google's Gemini model has now almost caught up in Ejaaz: the number of users or monthly downloads that ChatGPT has, Ejaaz: which is just insane. That's the chart that we see here on the left.

Ejaaz: And then on the right, which I found the most interesting, is the amount of Ejaaz: time that each Gemini user is spending on the app using the Gemini model has now beaten ChatGPT. Ejaaz: This kind of blew my mind because I was like, surely everyone's still using Ejaaz: ChatGPT because people tend to use ChatGPT for their own personalized things. Ejaaz: They kind of like confer it, therapy, ask about personal stuff.

Ejaaz: That probably spends a lot more time, but it seems like the productivity aspect Ejaaz: that people are getting from task orientation-based AI stuff using Gemini seems to be extending.

Ejaaz: And that just kind of like shows I've heard anecdotes from friends you Ejaaz: and I were talking to a team member just before recording this and he Ejaaz: was like yeah I was talking to a bunch of my friends and they've fully switched Ejaaz: to the Gemini app so I think we're going to continue seeing this trend of Google Ejaaz: gaining the advantage not because of their infrastructure mode but because they

Ejaaz: like own all the popular apps that anyone and everyone wants to use and so all Ejaaz: they have to do is plug in their AI model with whatever app Gmail, Ejaaz: Maps whatever you might kind of think of and suddenly you have a really productive Ejaaz: useful app that you and I want to use every day. Ejaaz: Josh, you mentioned that you want to use down to banana or you're using down to banana, right?

Josh: Yeah, there's a there's an important shift that I found that has happened recently Josh: that hasn't happened before, which is I have Gemini on my home screen on my phone. Josh: And that to me is very high signal because I've been resistant of it because Josh: it just hasn't been good. Josh: And while it's still not great, I think the ChatGPT app is engineered far better than Gemini.

Josh: It is good enough to make me want to use it. So I went from not being a user Josh: like I would really I'd use Gemini 3 Pro on desktop whenever I had a hard question, Josh: but I wasn't reaching for it. Josh: And Nano Banana Pro, it really was the killer use case that had me like, Josh: oh my God, I need this quickly accessible and in my pocket at all times because Josh: it is so far superior to any other product in the space like that.

Josh: And I think as Google starts to roll out these products, as this is something Josh: that we talk about a lot with OpenAI, where they're really good at creating Josh: innovation and wrapping it in a product and selling it. Josh: As Google gets better at doing that, I really, I strongly suspect Gemini will Josh: continue this trend of taking over broader and broader people.

Josh: Because when you think about how many monthly active users google Josh: has it's like gigantic they're one of the few in the Josh: world that actually has more than than chat gpt and open ai Josh: and if they can convert all of these services to Josh: pack ai into it into one coherent service Josh: and package that's incredible we talk about a lot of times like with meta for Josh: example the they had their awesome hardware product but no one really wanted

Josh: to use it because the ecosystem sucked well google has like the best ecosystem Josh: ever it's funny on my even on my iphone i have an iphone hardware with software Josh: from Google because their software is so superior. Josh: So as they're able to integrate these top tier models into all the products, Josh: this is a serious shift. And I'm very bullish on Google.

Ejaaz: Yeah, I don't think we're going to see this trend reverse. We already know that Ejaaz: Apple is going to be using a Google Gemini-based model in their phone for Siri. Ejaaz: That's right, yeah. And we know that we're going to start seeing a lot of Gemini-based Ejaaz: apps just kind of like appear in our regular day-to-day. Ejaaz: One other final point is like when you compare like Google versus OpenAI, Ejaaz: remember OpenAI still isn't profitable.

Ejaaz: Google is massively, massively profitable, so they don't need to turn on ads.

Ejaaz: They don't need to kind of like like demean the Ejaaz: user experience in any way they could just keep giving you the stuff for free Ejaaz: and gaining millions and millions more monthly active Ejaaz: users whereas open air at some point is going to turn on ads and when they turn Ejaaz: on ads it's going to be an inferior performance it's going to be a inferior Ejaaz: product to some extent and that might shift to more people using google gemini's

Ejaaz: products and google knows this so they're willing to just kind of sit back they Ejaaz: own kind of every infrastructure layer and they're just going to see how things play out.

Ejaaz: But I think that is it for today's episode. Ejaaz: Super exciting to kind of like see where Google and NVIDIA ultimately end up. Ejaaz: In my opinion, I think that both companies, to your point earlier, Ejaaz: Josh, are going to do extremely, extremely well. Ejaaz: It's a positive sum game. And the fact of the matter is there is not enough compute. Ejaaz: There's not enough energy to feed the compute that both of these companies are pushing out.

Ejaaz: So I think we're just going to see both these companies grow into two of the Ejaaz: largest and most valuable companies in the world. Now, I need to take a quick Ejaaz: victory lap for all listeners here who aren't subscribed and who haven't rated our show just yet. Ejaaz: We released an episode about the bull case for Google. Ejaaz: What was it? Two months ago now. And a lot of it has now played out right now.

Ejaaz: If you'd invested in Google back then, you would have participated in the hundreds Ejaaz: of billions of dollars that their market cap is up relative to NVIDIA right now. Ejaaz: Now, I'm not going to say that we triggered it. Maybe we did. Ejaaz: Maybe we didn't. But if you want to hear more bull cases like this or more alpha Ejaaz: in advance, subscribe to us, rate us, give us a thumbs up, give us feedback. We love it.

Ejaaz: And we will hear more from you or we will, you will hear more from us rather Ejaaz: on the next episode. See you then.