CNBC Today On NVIDIA Stock, Micron Stock, SK Hynix, Alphabet Earnings - NVDA Update

[00:00:00]I was talking about SK. I got up really early in this. SK Hy Jinks is just Is that their name now?

[00:00:05]>> Yeah. SK Hy Jinks because you know I saw it was down big and I said, "Okay, we're going to have a down day." Um, we have been hijacked. There's no doubt about it. Ever since they came over, it's very very hard if they're down 7% for us to rally. Uh, even as there's good news for say an AMD, uh, good news potential for Intel if they're not selling that Ohio plant. Maybe Lip Bhutan has something up his sleeve. I just say I just cannot believe oil hits 95. Uh Heinix is down and it it translates into a down day for us. It's a shame that there isn't more to it.

[00:00:39]>> Uh yeah, I mean you did say last night that some of the upside margin surprise at SMCI, for example, should be good news and it that is up. This is >> Yes. And I I just continue to believe that uh that Nvidia is is a good stock to own. I know that people could say, well, wait a second, Super Micro, maybe they're making all the money. That's a great great news for Nvidia unless it's unless we have a situation where that's at the expense of Dell and I just don't think that can happen. Michael Dell, HPE, they're both doing really well. I think this is again a sign that Nvidia is going to do do terrifically, but >> you know, >> so we talked we've talked all week long about your patience for chip volatility beginning to Wayne, but last night you did say, "All right, if you do want to play that game, here are some names."

[00:01:22]>> Yeah. Well, look, I just think that you this is a a key group and you could say it's up to now like 30% of our market.

[00:01:30]So, I'm not saying avoid it. I am saying don't if you're going to go commodity, Micron is the best because it's really not that much commodity. I think Nvidia is incredibly cheap. I could argue that it's below 18 times earnings. U but and you know, I think that I think a lot of Intel going into the quarter. It's just that I continue to come back to stocks like a GM. I mean, look at what Mary Bar has done. I mean, the number everybody like BMW is pulling out of like the Paris car show. VW's laying off people after pledged a long time ago that never lay anybody off. And here's GM just up 5% yesterday. That's what I'm talking about. A six times earning stock up 5%.

[00:02:10]That is a lot better than owning SanDisk at this.

[00:02:13]>> I know you bought some Nvidia.

[00:02:16]>> So, I made a sec. Yeah. So I I made an initial purchase on July 7th at 198 for Nvidia. It wasn't based on anything fundamental. Everyone on the desk understands the strong fundamental surrounding this company. What it was was a recognition that as I've been advocating for the last several years, market structure is changing so dynamically in front of us right now. We are moving more and more towards this quant algorithm dominance in the market and that means the price is priority and the moment momentum factor becomes elevated. Steve does a great job talking about this. You went through a sideways consolidation period last year in Apple.

[00:03:00]Then you had the breakout. The breakout really was predicated on the momentum building. And I've seen the same thing happening for Nvidia over the last several weeks. It's literally tracing out a very similar pattern to what we witnessed where Apple went from 250 up to 330. So the breakout is unfolding right in front of us. I purchased again a second purchase at 207. As it moves higher, I will continue to buy it because I believe this stock is in the midst of a momentum breakout back towards 240 and it's nothing more than technically oriented.

[00:03:35]>> Weiss, what were you going to say?

[00:03:36]>> Yeah, I was saying let's just reset the narrative a little bit. There's not going to be an income line that says return on investment from AI cap capex.

[00:03:47]What it's going to be and what we've seen AI do, it improves productivity, it improves engagement. So when you see additional growth in a YouTube or in search, right, from Gemini, that's going to be a function of the AI spending. So, so the idea, the concept that well, you got to show the ROI on on on uh AI spending, it's just flawed. It's going to be embedded in the other businesses.

[00:04:14]Now, >> a great rule of thumb, Kelly, is invest in scarcity. Invest in scarcity. There's a scarcity of memory chip. There is a scarcity of compute power. Now, doesn't mean these stocks can't get overhyped, and I think some of the the memory names got overhyped early in the year, but the big hyperscalers, they're not hyped at all.

[00:04:36]>> Yeah, we're going to talk in a moment with a couple of brilliant commodities investors, Andrew. And some of this talk about scarcity reminds me of investing in commodities, which they they might disagree, but for the average person holding commodities goes back to the eric bet in the 1980s, holding commodities over the long run is not always that profitable. And so yes, they have scarcity now, but scarcity now doesn't mean scarcity forever.

[00:04:58]>> 100%. You're absolutely right. But I don't think that will be resolved in the near future. What is the difference between oil and and uh compute power is there is a lot of oil on the ground and lo and behold, we have a war, but oil goes to $100 a barrel and somehow someway we get that oil out of the ground and it gets to the right people.

[00:05:20]So I I I I think that's the key difference is how long until supply will catch up to demand. You know, ultimately the.com bubble blew when everyone that needed a router bought a router and then supply met demand. And I just think we're not there yet. And I keep going back to what I hear from companies over and over and over. Look at some of the, you know, the software names that have missed are the large enterprise computing companies. they're missing because they're saying that spending is going towards hardware, not their products right now. The companies are screaming this over and over. Kelly, I think >> I believe that it's real, but I would question the ROI just because on the on the possibility that compute is a that there that the output that the AI output is a commodity.

[00:06:12]>> Absolutely. I'm I'm making a bet that the the returns will come down the road uh for these companies. You've got very very smart people that are making this investments whether it's you know in Amazon or other big hyperscalers. So I think uh you have to invest and believe what do you believe in them or do you simply say I haven't seen the ROIC yet.

[00:06:36]I think there's an option on the sidelines for 10 years mean it should be your whole portfolio but I wouldn't throw in the towel on these stocks.

[00:06:44]>> Actually, we have the numbers. Mackenzie Sagalas has those for us.

[00:06:48]>> Mike, we're seeing shares fractionally higher. It is a beat on revenue at 119.8 billion versus 116.93 billion that was expected for Q2 revenue. Now, with EPS, this is a gap number of $911. We are not comparing that to the estimate here because in the quarter uh Alphets saw a $99 billion equity securities gain. Uh cloud revenue, this was the big question going into the print. We are seeing an 82% jump year-over-year to 24.8 billion versus the 22.24 billion that is that was expected for cloud revenue. And I've also got a read on capex in Q2 44.92 billion. Also beating the estimate there. I'm going to keep digging into these numbers and come back to you guys.

[00:07:29]>> Um Mac, thank you very much. Well, there you go, Gail. 82% year-over-year growth in in uh cloud revenue. I guess there were some whispers of plus 75 maybe at the outer end. So, uh obviously this is what you wanted to see.

[00:07:41]>> Yes. And it's one word, it's anthropic, >> right? The ramp in anthropic has been staggering. A company that started at less than 10 billion run rate at the end of last year is now at likely at more than 70 billion run rate six or seven months later. Guess what? Google and Amazon are their big compute providers.

[00:08:00]So that's flowing through and I'm guessing that the securities gain has to do either with the stake in Anthropic or SpaceX. Exactly.

[00:08:06]>> Two very good investments for Alphabet over the years.

[00:08:09]>> Yes, for sure.

[00:08:09]>> Yeah. Um Brent, what will you be We're all coming through the numbers at this point, but what will you be looking at to sort of glean whether that return on investment metric can be found in this release?

[00:08:23]>> Well, you're not going to find in this release, so let's not focus on that. Um but when you look at cloud right I think uh as Gil said you know the 10% beat on cloud was was massive the the whisper number was 75 the street was at 65 so 82 is a 10% beat searches in line at 17% growth and YouTube beat by 2 and a.5% um capex is basically right in line 44.9 versus street at 44.7 um so the only thing I'm seeing on the numbers uh is margin is a little bit lower 39 versus the street at 40. But when you look at the cloud beat, you look at search in line, YouTube being by three, capex, you know, right in line.

[00:09:04]Uh it it just it felt like it was right down the middle. It was stable, steady.

[00:09:11]I think the market was hoping for more, but you know, look, it was a it was a call it a 260 yard drive. It was not a 300 yard drive that we've seen from them in the past. So, it was it was stable, consistent. Uh, and I think that's why stocks trading off after hours.

[00:09:27]>> Yeah. And and Gil, of course, the the capex for the last quarter was about in line. They're not necessarily going to give us a new number for that. So, what do you think is going to be the next, you know, the inflection in in street sentiment or what's going to uh kind of maybe add a little confidence if anything to Alphabet's story in the absence of that?

[00:09:46]>> So, I think a couple of things they can talk about are selling chips. Yeah.

[00:09:49]>> We're all excited about them selling TPUs. That's really a windfall. All they have to do is get a little bit more allocation from TSMC, mark it up, and that's a business they were never in before. So that's incremental to everything. And there's going to be a healthy discussion about Gemini. Why did Nom Shazir left? Why did other executives leave for OpenA and Anthropic? Can you still be the state-of-the-art model? That's a very important question. Nine months ago, Gemini was the state-of-the-art model.

[00:10:14]We were all talking about what we're doing in Gemini. Now everybody talks about what they're doing in cloud.

[00:10:17]>> How big of a business do you think the chip business could be? because Amazon actually outlined how big they thought the run rate on chips would be for them >> last quarter.

[00:10:25]>> Yeah, they did that because Google started selling chips. So, I would say that Google's TPUs are better than traniums.

[00:10:31]>> So, the market if Amazon thinks they could sell $50 billion worth of uh tranium, Google could probably sell more than that of TPUs.

[00:10:39]>> We got a couple more headlines out of the Alphabet report guild that I want to ask you about. The Gemini app has 950 million monthly active users. Um, and also Gemini models now process 22 billion API tokens per minute, which shows the power of of their AI model.

[00:10:55]>> Absolutely. Because they're trying to catch up to anthropic and even open AI in the enterprise market, right? That's the market when we talk about anthropic being 70 billion run rate, open AI being at 50 billion run rate. Most of that is enterprise spend. And those two are by far leading Google. So if they can drive even more revenue in that front, that means Gemini is worth it just for that.

[00:11:15]I think the tell tomorrow is going to be how well does Nvidia trade on the back of this increased spend. If it doesn't perform, maybe that's a bit of a tell because Nvidia has been trading great the last couple days.

[00:11:25]>> Yeah, one of the takeaways I have here is that uh they said they're going to expand use of third-party AI capacity in Q3. And what's interesting to me about that is that if you look at some of XAI like for instance and you know they are basically selling their compute. Meta just talked about doing it. they want to be neoclouds and at the end of the day Google's saying that they need more compute which I I actually would impute that that's probably pretty bullish right and so at the end of the day we know that anthropic has not um built out as much as compute as they need that's why they went to XAI that's why Google went to XAI they did those deals on the eve of the uh SpaceX IPO so it says something about Google and it's saying something very different about XAI they overbought they overbuilt now they have excess capacity and they need to sell that off because XAI is losing a billion dollars a month. And those two deals that they did, that's great. They're $2 billion a month. They don't start for a few months, but both sides have a threemonth out, and that could change very quickly. So, if Google and um Anthropic want to pull back on that, that would be a big problem for XAI.

[00:12:23]>> All right.

[00:12:24]>> Deep Water Asset Management's Gene Monster is following all of these moves and all of the conference calls. Um you're a hard worker, Gan. What's your big takeaway here in terms of what it means, what this all means? put it in a bag, shake it up for the AI trade tomorrow.

[00:12:39]>> Well, the most important piece obviously was related to what the Google capex guide was. 4% higher than the street.

[00:12:45]And that ultimately means that the numbers for all these capex infrastructure companies are going to be going higher. Uh we saw that in some of the after hours trading with some of the smaller companies like Coherent and Vertive all trading up one 2%. Nvidia's basically flat. But Melissa, the the simple takeaway is that this is really good for the infrastructure trade fundamentals. The question comes down to will investors give the trade credit?

[00:13:13]>> Hey uh Jean, you and I have talked about and you are a hardworking guy. Uh so thanks for being um when you look at the deceleration in earnings and sales and margins for Alphabet next year, you know, obviously that spend has a big part of the margin and the earning uh slowdown. How do you think about that as an analyst, as an investor? Like is that something that should be placed at least a discount on until you see enough reasons to actually, you know, see the potential for a reaceleration in margin improvement?

[00:13:42]>> Well, you're hitting what is basically the kind of the key uh connection between Google and Tesla tonight is this margin decline, fractional mis margin for Google is bigger when it comes to Tesla. And this question about how should we think about margins relative to the broader revenue opportunity. CFO of Google said that they have had this caffeinated growth in Google cloud that going from 63 to 83% but they're going to have to go to third parties like SpaceX to continue to meet demand that's going to push margins lower. And so I want to I want to get to your answer to your question, Dan, is what does this mean? Is that it's really important these stocks are not going to go up unless margins are stable or moving higher. When it comes to Tesla, we had four quarters in a row of expanding out of gross margins X credits that just came to like a crashing end here. And so I think it's really important they don't have to go up into perpetuity, but they do need to go up and stay high for I think these stocks to continue to work.

[00:14:40]>> Genus Karen, thanks for being on. So, just to get at that margin a little bit more, if they they do have more demand than they can supply, um when do we get to a period where that starts to be somewhat more in line and we can really see what the margins are?

[00:14:58]>> Well, that's kind of one of the crazy parts about these Google numbers is that they're just to put in perspective, they did 25 billion in cloud revenue in the quarter. They'll probably do like 130 140 over the next four quarters. Their backlog in cloud grew 50 billion sequentially. It's now $514 billion. Now those some of them are several year contracts that they have. But Karen, when you look at those backlog numbers, when you have backlog numbers that are 3x what your next 12 months revenue are, it's almost hard for me to like conceptualize when we're going to get to supply demand equilibrium. And I think that's kind of the point here is that these companies ultimately are seeing this massive backlog and saying I'm going to spend whatever it takes to get there. So to answer your question, I don't know when we're going to get that.

[00:15:43]It may be we may be a year plus out before we feel like we get any sense of where that demand that that equilibrium is. What's most important on that margin topic is investors have to believe uh it can happen before the margins actually go up but have to have some confidence that they are going to go higher longer term. Um >> if we could take a look at Tesla's stock in the after hour session um a leg lower here. This is a massive capex year says Elon Musk on that conference call. The stock is down 5%. They originally guided Gan uh to $25 billion to 2026. So I guess it also follows along the line of of Alphabet. You said they followed along in terms of marginal. They're following along in terms of boosting capex apparently as well. Um, so is that a surprise to you that they're increasing?

[00:16:27]>> Well, this was the one. There's a lot of good things on this Google call. I had expected margins actually to be up, so I was wrong on that. I I was right on this this uh capex and it was pretty easy to get because we know how important this is for them. The key is not this year, that 25 billion number. We'll get the details when the CFO talks about the exact number. The key is next year. The street's looking for 21 billion. So, a step down, but that number likely could be up year-over-year because Elon was selling investors. I listened to the first few minutes of the call on this idea that we really that it's going to pay off. This is the biggest opportunity to print money ever kind of a theme when it comes to capex. And so, um, I wasn't surprised by it. And I think like another, you know, I mentioned that kind of connection on the margin, but there's also a connection between Tesla and Google, very easy connection, which is on that capex piece. And we've been waiting, we've been talking about the past year and a half for the some sort of a slowdown in this. We're just not getting it. And so I think what the simple takeaway is we're still very early in AI. It's hard to uh for me to wrap my head around that, but we're still very early. And I think what we're hearing is is is evidence of that.

[00:17:32]>> All right. I hope you're all doing well today and staying calm in this market.

[00:17:35]Today was a mixed day throughout the market following rising tensions in the Middle East. It was also a red day for many software stocks as investors nervously awaited Alphabet's earnings.

[00:17:44]I'm going to address Alphabet earnings in a moment, but really quick, let me cover some important news stories. At the end of last week, I mentioned in multiple videos that the market was misinterpreting the implications of the new Kim K3 open model from China's Moonshot AI. As I explained in that video, the model would lead to greater consumption throughout the ecosystem, which would ultimately result in greater compute demand, not less. Then this past weekend, Moonshot posted online essentially confirming what I said.

[00:18:07]Moonshot said that demand had already pushed close to the limit of their capacity and they were adding capacity as fast as they could. And then on Wednesday, we learned of an interview from Jensen Huang with Axios where he very clearly confirmed that open Chinese models like Kimmy K3 will lead to greater compute demand, not less. Listen in to what he had to say, and then I'll cover some more news on the other side.

[00:18:25]>> Simple question on the front page of the Wall Street Journal. Should American companies be allowed to use Chinese AI models? Absolutely. Absolutely. I there's a there's a misconception that somehow uh there are back doors that is somehow connected to to China in some way. You download the models. You could uh you could fine-tune it. You can uh enhance it. You can guard rail it as you desire. So this Chinese competition is coming fast and furious. What should US AI companies do? These China Chinese models are excellent uh open open- source models uh that are excellent should be used and so the markets misunderstood the impact of deepseek the first time it's misunderstood Chinese >> yeah it's it's misunderstood the impact of Kimmy again this time I think first of all with great AI open models it's great for the whole industry obviously when there's more if there's great AI even if it's open uh wherever it comes from there will be more use. Whenever there's more use, you'll have to sell a lot more Nvidia computers. We'll have to build more data centers. We'll have more services. The technology will diffuse into more industries. And so starting point is great models lead to great use which leads to great growth. And so that's just the starting point. Um that happened with Deep Seek. It's going to happen with Kimmy. Um, there's also a misunderstanding that open models could be uh adversarial to the closed models and that's also got it wrong. High token costs help drive demand for Nvidia's newest systems. Nvidia's newest systems drive token costs lower. Lower token costs drive greater consumption throughout the ecosystem which ultimately results in greater compute demand. Token costs are not a reason to be bearish on Nvidia because whether we're talking about higher token costs or lower token costs, Nvidia ultimately benefits from both. I know that sounds like a contradiction at first, but it's actually not as I've explained in recent videos. And it's very impressive what Nvidia has built here. In other news, overnight we learned that Wistan opened its first US manufacturing facility in Fort Worth, Texas, a 324,000 foot plant producing Nvidia's Grace Blackwell Ultra and eventually Vera Rubin Superchips.

[00:20:37]This is part of a combined $700 million investment in advanced US manufacturing.

[00:20:42]And now let's cover Alphabet earnings.

[00:20:44]I'm going to rapid fire important point from both the earnings report and the earnings call as it relates to capex and the AI buildout. Google Cloud revenue grew 82% year-over-year and operating margin rose to 35.6% which is up from 20.7% a year ago. Alphabet said they delivered TPUs to customers data centers for the first time in Q2. Cloud backlog was $514 billion which is up more than $50 billion quarter- quarter. Google Cloud is expanding its use of thirdparty capacity in Q3. That means they are still supply constrained. And Alphabet's CFO later confirmed that by saying quote we're still in a supply constrained environment regarding compute capacity investments in 2027. Alphabet CEO said quote we are seeing strong demand indicators. Also while leadership didn't mention memory specifically, Alphabet CEO did say something that is very positive for memory makers as he spoke about frontier models. He said, quote, "In terms of the frontier, we are both very committed and very confident of being at the frontier. For the next generation of Frontier, you're going to need much larger base models. We are now training Gemini 4, and we're being very ambitious with it. We will need Gemini 4 as a larger base model to compete at that frontier level. So, we are focused on executing on that well." His comments about larger base models are positive from memory makers. And now regarding capex guidance, which is the main focus as it relates to AI hardware stocks, Alphabet raised its full year 2026 capex guidance to the range of 195 to $25 billion, which is up in the previously announced range of 180 to $190 billion.

[00:22:05]Leadership said that the increase is primarily due to an acceleration in delivery of capacity to meet growing demand. And then Alphabet CFO said, quote, "We continue to expect our capex to increase significantly in 2027." And so make no mistake, this earnings call was positive for companies like Nvidia, Micron, SK, Heinix, and so on. The fundamental thesis remains intact. That said, I need to point out a couple things because I'm sure you're going to hear a lot about it from the financial press in the days ahead. First, while quarterly capex grew 100% year-over-year, free cash flow was down 20% on a trailing 12 months basis. And so we're going to continue to hear the ROI question from some market participants that said it's important to consider that cloud revenue growth of 82% is very strong and cloud operating margin increased notably compared to a year ago. And so while the ROI question will continue to circulate among market participants, let's not lose sight of the improving fundamentals because that's what really matters here. I think we're also going to hear some unreasonably pessimistic and ill-informed takes in the days ahead regarding the expansion of Google's TPU offerings, the sale of TPUs to thirdparty customers and the implications it has for Nvidia. I'm not bearish on Alphabet, so please don't misunderstand me here. As I've said many times on this channel, there's plenty of room in this market for multiple chip makers to succeed, and this is not zero sum. The world is compute constrained.

[00:23:16]That means there's already enough room in the market for multiple chip makers to succeed. And on top of that, the total addressable market is growing by double digits percentage annually. So, there's already enough room for multiple chipmakers to succeed, and the TAM is growing at a strong clip. On top of that, the success of the TPU does not mean the demise of Nvidia. Not even close. Nvidia's platform is flexible with the largest install base. As software changes, which it does frequently, Nvidia's platform adapts to whatever's happening in the market. You cannot do that with a custom ASIC in the same way that Nvidia can with their systems. Additionally, developers choose which platforms they build on. The vast majority of developers want to build on Nvidia's platform. Nvidia brings customers to the hyperscalers.

[00:23:54]Therefore, the hyperscalers, including Alphabet, will continue to purchase Nvidia's latest systems in large quantities. Alphabet leadership even mentioned Nvidia by name on the earnings call by saying that they offer Nvidia's new Vera Rubin platform. And so, again, there's plenty of room for multiple chipmakers to succeed. This is not zero sum. The world is compute constrained and the TAM is growing at a strong clip.

[00:24:13]On top of the already constrained conditions throughout the industry, you also have to remember that Google has to deal with many of the same bottlenecks that Nvidia has to deal with. And given the strong demand throughout the industry, there are constraints throughout the supply chain. Alphabet is not immune to those challenges. TPU success is positive for Alphabet. And at the same time, I don't expect Google's TPU to take meaningful market share away from Nvidia anytime soon. Now is not the time for Nvidia investors to be concerned about competitive market share dynamics. The world is compute constrained and the TAM is growing in the double digits annually. Therefore, nearly all viable compute that can be produced will be sold given the constraints throughout the industry. Now is not the time for Nvidia investors to worry about market share. Also, very briefly on the topic of TPUs, I've seen some popular accounts online that incorrectly assume that the majority of Google Cloud revenue came from TPUs during the quarter based on this text from the earnings press release. That assumption is incorrect. It's important to remember that cloud services revenues and cloud product revenues are two separate things. And so, while Google Cloud generates product revenues primarily from the sale of TPU systems, that does not mean that TPU sales represented the majority of total cloud revenue. On the earnings call, leadership clarified that the vast majority of their cloud backlog is from GCP agreements, not from TPU sales, but TPU sales are included in the backlog number. Looking ahead, we have more Hypers scale earnings with Meta and Microsoft earnings scheduled for July 29th and Amazon earnings scheduled for July 30th. Overall, I'm expecting each of the hypers scale companies to provide strong guidance and commentary regarding capex this earning season. As for Meta, I'm expecting them to announce strong capex guidance. I know there was a bunch of hoopla on July 1st after Bloomberg reported that Meta was developing plans for cloud business. Some days after that report, Zuckerberg clarified that they do not have excess compute. It's just that some of the deals are very attractive and Meta could charge a premium if they rented out a portion of their capacity given the constraints throughout the industry. Meta also recently announced they are expanding their Hyperion data center in Louisiana from 2 gawatt up to 5 gawatt. Last earning season, Meta CFO said that they continue to underestimate their compute needs even as they've been ramping capacity significantly. Plus, Meta Super Intelligence Labs just recently launched Muse Image, Muse Video, Muse 1.1, and a new model API. Meta is not dropping out of the AI race anytime soon, and I expect their capex guidance to be strong. As for Amazon, I'm also expecting strong commentary and guidance regarding capex. Amazon CEO Andy Jasse spoke at length last earnings season about Amazon having very high confidence that they will monetize the capacity they're bringing online. As a reminder, AWS is monetizing new capacity as soon as it comes online. Last earning season, Jasse said, quote, "The faster AWS grows, the more short-term capex will spend." And then on July 1st, AWS raised GPU rental prices by 20%. And they made that decision based on supply and demand. In other words, demand is very strong and outpacing available supply.

[00:26:52]As Jasse said last earning season, the faster AWS grows, the more they will spend on capex. AWS is clearly growing and so I expect strong capex guidance from Amazon. Now, let's talk about Microsoft because I think this is the most interesting of the four this earning season. I want to remind you of a few things. First, Microsoft will be reporting results for the end of their fiscal year, and so they're likely to provide commentary on the earnings call regarding capex over the next 12 months.

[00:27:14]This is going to be a very important earnings call for the entire AI ecosystem. As a reminder, last earnings call, Microsoft guided fiscal Q4 capex at $40 billion. They also told us that for calendar 2026, they expect to spend $190 billion. Again, that's for the calendar year. And so calendar 2026 would include the third and fourth quarters of fiscal 2026 as well as the first two quarters of fiscal 2027. And so if Q3 capex was 31.9 billion and let's just assume Q4 is 40 billion as Microsoft guided that leaves $118.1 billion that Microsoft intends to spend in just the first two quarters of fiscal 2027. That would be an average of roughly $59 billion per quarter, much higher than their capex so far. What's the reason for that increase? There are two reasons. First, Microsoft is investing heavily in additional capacity for their cloud business. And secondly, Microsoft stated earlier this year that they want to have their own state-of-the-art models in-house by 2027, and they're going to need a lot of capacity to do it. As I said repeatedly ahead of Microsoft's last earnings report, I thought their capex guidance was going to be notably higher than what many market participants were expecting.

[00:28:15]That turned out to be correct. Now, I'll be completely honest, I don't know what they're going to say on the earnings call regarding capex over the next 12 months for fiscal 2027. If I had to guess, given the fact that they need additional capacity to compete on cloud, they need to have enough capacity to train their own state-of-the-art models and also what we're seeing in rising component costs, especially in memory. I think we're likely to get strong next quarter capex guidance. But I just want you to know that market participants main focus as it relates to capex is what Microsoft will say about capex over the next 12 months in fiscal 2027. That is what will likely have an impact on the stocks of companies like Nvidia, Micron, SKH, the Neoclouds, and many others. There's some important nuance in Microsoft's AI strategy. And so, we need to listen in to the earnings call to get a better understanding of what's going on. If I could only listen to one earnings call from the four major hypers scale companies this earning season, I would choose Microsofts. What they say about capex over the next 12 months will likely determine how tech hardware stocks trade the next day. Overall, I'm expecting all four of the major hypers scale companies to report strong capex guidance and important commentary regarding AI monetization this earnings season. I don't know what's going to happen in the short term, but from a long-term perspective, I am very confident that Nvidia will be worth much more in future years than it is today.

[00:29:20]When Jensen was on the Lex Freedman podcast not that long ago, he was very seriously raising the possibility of Nvidia becoming a $3 trillion revenue company in the near future. If that happens in the coming years, then it is very plausible that Nvidia could one day be worth tens of trillions of dollars in market cap. That might sound crazy, but that's what Jensen is implying when he raises the possibility of Nvidia becoming a $3 trillion revenue company.

[00:29:41]I guess the question at that point is what multiple the street will be willing to give Nvidia. I don't know the answer to that question, but I truly do think that Nvidia will be worth much more in future years than it is today based purely on the fundamental growth of the business. Based on everything I'm seeing, the world is still computed and I expect that to continue at least through the first half of calendar 2028.

[00:29:59]In a computed environment, developers will use whatever viable compute they can get their hands on. Today, there are no GPUs that are sitting dark due to a lack of demand. Like, there was fiber sitting dark due to a lack of demand at the height of the dotcom bubble. Back then, companies were laying fiber in the hopes that use cases and demand would eventually show up. Today, we are seeing the complete opposite. As I've said many times, when market participants compare this AI revolution to the dotcom bubble, they ignore the fact that the internet is already here this time. This means that mass adoption of the technology and new use case development at scale are immediately possible. We don't have to wait years for it to show up. It's already here. The world is compute constrained which means there is not enough supply to satisfy demand. New capacity is utilized as soon as it comes online. The hyperscalers are monetizing capacity as soon as it comes online.

[00:30:42]Each of the hyperscalers spoke about being supply constrained on their most recent earnings calls. Additionally, many of the clouds are building out into contracted demand. They're not blindly building in the hopes that demand will eventually show up. No, they're building out because they have signed contracts and in some cases significant prepayments from their paying customers.

[00:30:59]This AI revolution is fundamentally different from the dotcom bubble and 2026 will be a pivotal year for the AI industry thanks to the rapid adoption of agentic AI and the proliferation of agentic systems in the world's leading enterprises. The leading AI labs revenues are surging right now. Agentic coding and the implementation of agentic systems in large enterprises are new use cases that are increasing inference demand significantly that subsequently is increasing compute demand. The rapid adoption of agentic AI is why we're seeing an inflection in inference demand. It's why we're seeing the leading AI labs revenue surge. I wish both Anthropic and Open AAI were public so the public could see the ramp in their revenues. Anthropics ARR has surpassed 47 billion up from $9 billion just at the end of 2025. Open AI is growing rapidly as well. I think the leading labs surging revenues may be the initial proof point that grabs market participants attention and causes them to realize that there will be a clear ROI on AI infrastructure. I think the leading labs surging revenues will also help assure investors of the longevity of Nvidia's growth since these labs revenues are directly tied to compute.

[00:31:59]If they had more compute, they would have greater revenues. It really is that simple. Demand is not the problem. The problem is a lack of supply to meet the demand. As I've said previously, I expect the world to be compute constrained at least through the first half of 2028, possibly longer. And so regardless of what happens in the short term, it's important for long-term investors to remain focused on the fundamentals, maintain a long-term perspective, and remember that we are only in the early stages of aenic systems being adopted at scale. This will increase compute demand significantly. And after that, the next surge in compute demand will likely be fueled by physical AI. We're no longer talking about digital agents performing digital tasks. With physical AI, we're talking about physical AI agents performing physical tasks in the real world. Nvidia CFO has called physical AI quote a multi-t trillion dollar opportunity and the next leg of growth for Nvidia. This industry will fundamentally transform society and Nvidia has positioned themselves to benefit massively. Nvidia sells the hardware for the data centers where the models are trained. They offer omniverse where the models are taught and tested and Nvidia also sells the hardware that allows ondevice real-time inference through Nvidia AGX allowing robots to have intelligent interactions with the real world even when they are not connected to a data center. Notice that Nvidia is taking a holistic platform approach to physical AI and they're embedding themselves as the underlying foundation supporting all of it. Over 2 million developers are already building on the Nvidia robotic stack and this is not getting enough attention. As for production ramps, Blackwell Ultra has ramped quickly and remains in high demand. Reuben is on track to launch in 2026. Then we're expecting Nvidia Gro 3 LPX in the second half of 2026. Later on, we're expecting the launch of Reuben Ultra in 2027 and Fineman after that in 2028. We have a clear data center product roadmap stretching into 2028.

[00:33:33]And Jensen believes that AI infrastructure spending will reach 3 to4 trillion annually by the end of the decade. That means Jensen is expecting growing AI demand and an expanding total addressable market underpinning all of this. I don't think we are anywhere near any type of bubble bursting type of event. With all of this in mind, I seriously think that Nvidia still has plenty of runway ahead of it and I think this company will be worth substantially more in future years than it is today.

[00:33:55]At least that's my view of the situation. Quick note before I wrap up.

[00:33:58]All of the compilations on this channel are edited by Finn Vid with original structure and commentary. Occasionally, the same edits appear elsewhere on YouTube. If you're looking for the original version, it's always here on this channel. Thanks for watching, Finn Vid. I appreciate your support. Remember to stay calm in this market. Remember to maintain a long-term perspective and do not make any hasty or irrational decisions. With all of that being said, I hope you all have a great rest of the day. And I'm curious to hear your thoughts about Nvidia in the comments below. Please leave a like on this video so more people will see it. And while you're down there, please consider subscribing. It's free and you can always change your mind.