The News Today On NVIDIA Stock, Micron Stock, AI Buildout - NVDA Update

CJ Moose of Canifice Gerald covers the chip sector. CJ joins us now for more. CJ, welcome to the program. Just take it from the top. How long can this cycle really keep on going? How durable is this cycle? A lot of people have their doubts. You're pushing back. >> Yeah, good morning. Thanks for having me. Um, I think you're hitting on the key um debate for all of semiconductors. Uh, the durability of of AI infrastructure spending. uh you know if you look at the supply side uh TSMC is effectively sold out until 2029 uh memory similar uh and then there's the demand side right and I think there's some fears around open- source modeling and the effectiveness of inefficiency of models in China and you know is that going to reduce the overall amount of spend uh but I think internally at the largest frontier models uh they see uh what their nextg uh models look like and and they are trying to get as much compute as fast as they can. Compute is sold out, right? We heard from Nvidia last week that they can only meet 70% of the demand that they have for calendar 27. They obviously have visibility into 28 and 29. Uh and so our view is that um you know this spending will continue until 2030 minimum. Uh but that that is the core debate. Uh you know if you're thinking that 28 is call at the peak uh then you're probably going to put a lower multiple on the entire group, right? But if you think this can extend into 2030 and beyond, then you know these stocks are incredibly cheap. >> How important are Nvidia's moves in funding various efforts in this ecosystem CJ to helping that supply issue? It's something they talked about on the call that the CFO did. Is this the lens at which we should view their investments of trying to ease some of the shortages and bottlenecks that are rife within the industry? >> Yeah, it's a great question. I think there's, you know, a couple points. Um, you know, specific to MediaTek, you know, Rick Sai used to be the CEO of TSMC. He's great friends with Jensen. Uh, MediaTek is essentially Nvidia's physical AI partner. Uh, and so this combination or this investment, uh, you know, makes perfect sense to me. Um, you know, I I I think the earlier comments around getting customers to buy into Nvidia's full system rack, even if they have to give up some of the custom silicon business, you know, is a strategy for Jensen. So, I I think, you know, when you look at these investments in isolation, this one makes perfect sense to me. They are their physical AI partner. More broadly speaking, you know, I think that uh Jensen is is doing two things with the investments. number one, he's securing his supply chain, you know, and I think it it is multi-year contracts plus um you know endeavoring to bring financial institutions to support the investments so that that becomes another competitive advantage for them. And then the other is just the simple notion that you know anthropic and open AI um have limited balance sheets. You know they're competing against the largest hyperscalers uh on earth. Um they have run out of compute. They they have visibility to demand for more compute to support their models. Uh and so in that uh backdrop you know they need to find funding elsewhere and that's where you know Nvidia has been willing to do it. So, you know, I agree more with Colette from Nvidia that this is not your typical circular financing. Uh this is more of uh a demand uh problem um in terms of just not enough supply. Uh and they're helping, you know, to to make that uh that that match up better. >> CJ, the the other part of this ecosystem that Nvidia has been very supportive uh be it vocally or with dollars is open- source modeling. They bought Hugging Face shortly after their earnings announcement. Jensen Huang himself has been out writing letters advocating for the ability of of American companies to be able to use open sourcing. How important is it for Nvidia and their continued growth that that access remains turned on that there are options of cheaper models for corporate uh global corporations to use? >> Yeah. No, I think you know the worst case scenario for an Nvidia would be the world or at least the United States and non-China um you know gravitates to a uh open AI anthropic only frontier model world right and and and that's where they get such great scale benefit uh that they will um you know look to produce their own silicon and and try to use less and less of Nvidia. So, you know, if you're Nvidia, what do you do? You know, you go full stack, right? Which means you're going to uh compete at every level of kind of the AI cake that they've described. And as part of it, it is providing the models. Um, if you look at their investments uh with the Neoclouds, you could argue that, you know, Nvidia is a virtual hyperscaler. They are absolutely competing with the likes of, you know, Amazon, um, you know, Google, etc. Uh and so here again on on the um model side, you know, they're going to actively work there and you know, if they can kind of push their CUDA software and then these kind of smaller um enterprise uh industry focused models, you know, that's a real win for them in terms of, you know, driving, you know, adoption of their platform and and really, you know, going to first principles, that's what Jensen wants. He wants the world on Nvidia's platform. CJ, before you go, Danny asked a version of this question just last week. I'd love your reaction to it. Is there a bit of a disconnect between the cost of building out the ecosystem right now and the loss of pricing power for the frontier models? >> It's a great question. Um, you know, I think um I think the truth today is that the frontier models probably do about 30% of token generation yet earn about 90% of the economic profits. Uh, you know, I think true real intelligence will garner um the lion share of the economic profits and so as they continue to push forward great models, you know, I think they'll continue to continue to do extraordinarily well. Um but there is absolutely a need for um other models, right? You know, if you're if you're just going to ask, you know, this year where does Thanksgiving fall? Um you don't need a great model for that. And so you in the future, you know, we're going to optimize to the question to each uh you know, specific model that is best for that and offers the lowest cost per token. And so I absolutely think we're in a world of you know, closed frontier plus open, you know, will be our future. But the underlying numbers for tech are just astonishing. Semiconductors, 135% earnings growth. And then you have uh obviously the Piesta resistance last week, Nvidia's blowout numbers uh guiding double the revenue that analysts expected, 70% revenue growth and just offthechart sales and earnings growth. And he's talking a 20-year pipeline. The AI trade is alive and well and tech companies are really poised to be beneficiaries ex especially the smaller pick and ax plays. So what we see setting up is in a midterm election year while September October is historically the weakest months of those years in a presidential cycle. November and December are off the charts historically speaking. So, if we get that type of rally with the election out of the way and fears out of the way, I would expect tech to really do phenomenally well in the back half of the year, uh, the back quarter of the year. >> So, I know you're not a stock picker per se, but you just talked about Nvidia and the blowout numbers that they had and doubling revenue growth and the look ahead for 20-year pipeline. And we think about the MAG 7. Do you think that group is a good group or Nvidia in particular? Feel free to share. I mean, you know, for investors, they want to know, should they get in that group? >> Sure. Well, I think obviously Nvidia is the leader of AI uh unquestionably. You know, uh the news stories are circulating around Elon Musk and Open AI and obviously essential companies, but the company that continues to execute is obviously Nvidia. I personally have held it for a long time. I don't plan on selling it anytime soon. And to your point, we are actually stock pickers at uh at Money Flows. So, while I love the Mag 7, there are other stocks I really like uh such as Arista Networks. There's sort of the networking uh central nervous system of AI explosive sales and earnings growth. Uh they just reported quarter 2 revenue of 3.04 billion. That was up 37.7%. And as networking meets more and more demand with AI needing faster and faster communication, AET's right at the center of it. >> So then where's the right place to invest if that's the if that's where you're looking for growth right now? So we really like the chips and shovels trade and and with that look all the way down the supply chain. Look past even Nvidia to some extent although we do like Nvidia and look at who Nvidia is using to build their components which is really in South Korea and Taiwan. It's SKH Highix, it's Samsung, it's TSMC. These are names that traditionally have actually had worse margin than hyperscalers on the software side. And now that's shifted because the demand for memory and GPUs has just shot profitability up so much that even Nvidia in their you know amazing earnings call has said hey our margins might take a very small hit to like 71 72% because even though we will pass almost all the cost to our consumers we will have to eat a little bit of margin because of memory prices and that really tells you who the top dog in the supply chain is. You know, going back to what Joe said on Nvidia, you know, I did not like that 60% of their revenues this last quarter were account receivables. Like, why is that? Why can't these people just pay their bills? Why why does that need to be such a big number? And so, I'm trying to look look through the tea leaves and just take from the market what it's telling me and say, is there something bigger coming on here that's going to cause the bigger draw down? I don't know the answer at this point, but I think you can't just be polyiana about all of this and you need to be pragmatic as an investor. It >> is interesting. I mean, you get calls on Nvidia today, Melius, the argument for Nvidia to go higher has strengthened. I don't think anybody necessarily takes issue with that. No. >> Um because if you obviously look at the results and listen to the guidance, what was it? They guide it to like 70% revenue growth. Right now, they looked out till 28, which they never look out. as far as they decided to this time and the street was at 44. So like wow that's an incredible number of now you have the buyback hanging out there. Um that's sort of the thing that Melius is is talking about today. I'm not sure if that's Ben Ritus or or not because I don't have his name in front of me but it it may very well be. Uh Wolf Nvidia can finally break out. We'll see. >> We'll see. >> Yeah. So, in a in an odd way, I think the effect of what we heard last week from Nvidia is going to place managers like myself in a difficult position because you potentially lose this narrative about the market broadening out and finding this suite of opportunities. In fact, the opposite over the last several days is actually happening. The market's get going back to being more concentrated. Why? Because Nvidia is stepping forward into leadership and you're seeing some of the other MAG 7 names participate in that regard. So that kind that creates a little bit of a difficult environment as you move forward. I think positioning is a really big question right now. And Jenny highlighted some of the software names. Well, the software names, they're benefiting because capital is going away from the momentum names. We'll talk about that later on. Anybody surprised by the lack of follow through from what Nvidia delivered? Court, you surprised? It's like if I told you that Nvidia was going to do what it did, which everybody expected, good numbers, good outlook, but then they dropped the 70% revenue growth on the market, which was like, wow, that's that's an an amazing number, but the the days after it wasn't like, well, tech the AI trade took off after that. Does that surprise you? >> Well, I think after you got that story, I think every the markets just turned to the Fed. That was like the next big thing the markets were waiting on, and you did get them come out, which was hawkish. And essentially everybody is expecting that that rate increase is going to happen which does put more pressure on her longer duration assets. But I think the bigger thing that we saw with Nvidia is that that AI story continues. The AI demand is absolutely still there and I think that's the biggest takeaway that you're going to get when you look at these kind of numbers. >> Anybody think that the data center debate is having an impact on the AI trade itself? I think some of it I I also think like AI is well I should say Nvidia is almost becoming a bank and that's also why I think there can be like an impact and a connection between interest rates and what Nvidia is doing. They may have amazing growth but if they're backstopping all the other growth like and interest rates go up. I think that has a a major connection and yes publishing a chart that shows the correlation between the odds of Democrats or Republicans winning the midterm elections. It's been very correlated to the AI trade. So in some ways that midterm pricing is showing up in these AI stocks. >> Yeah. But I mean at this point it's one of the few things that politicians and and the country can seemingly agree on is the growing number of people who don't want data centers in their backyard. Now you have and we're going to talk about this more in the next segment in the next block that now Silicon Valley is coming out in the defense of of data centers. I think they realize sort of what's at stake. Do you think investors realize what's at stake? >> Uh I mean I think investors who study AI understand what's at stake, but everyday people like some of them are benefiting greatly because they are providing the labor um or they are the labor for it and they're making more money um obviously from from all the demand. But then if you're you know that's why I think you had Gavin Baker actually put out an expose talking about like >> they're going to recycle their water. They're going to, you know, like they're going to provide bring your own power. Like that's it's actually putting, I think, the right pressure on how to build these things going forward. >> Is this Silicon Valley stepping up its defense of data centers as the political debate over the AI buildout grows louder? Kate Rooney joins us now with more. Hi there. >> Hey, Scott. Yeah. So, there has been this growing counter offensive in Silicon Valley, at least over the past few days here, pushing back on the growing national backlash against AI data centers. The clearest articulation that we heard over the weekend came from tech investor Gavin Baker. His initial post said any politician opposed to data data centers, I should say, was unqualified to hold public office. He later walked that back a little bit. He put out a six-part defense, arguing that data centers are not pushing up power prices. He talked about water consumption, said those numbers are misleading. The buildout, he argues, is creating jobs. It's boosting tax revenue. And then the most politically potent argument by Baker. He says the US cannot build out compute and infrastructure here in the US. We are basically outsourcing the next industrial revolution to China. We also heard from Nvidia CEO Jensen Wong chiming in. He amplified that message adding that AI is bringing manufacturing back to America. He called it the reindustrialization and he said that is after decades of offshoring in tech. He did also underline the industry needs to earn local support and then keep creating some of these local benefits. But Scott, I did report last week that this entire data center backlash becoming a big deal for IPOs. It is expected to be a key risk factor in anthropics as one at least when I'm according to sources that I'm talking to and we expect that to be coming in the next couple weeks here. >> Well, that's really interesting to actually see that in front of us as that uh highly anticipated IPO gets gets even closer. Kate, thanks so much. That's Kate Rooney. We're back with Big Technologies. He's Alex Canowitz. So, let's go to what Kate was talking about first. The the Gavin Baker post on X Jensen Wong quote tweeting that with his long sort of defense of data centers in his in his own right. The Wall Street Journal piece today had the prior show interview the author of that basically that big tech was blind to the backlash. How do you see this issue? Yeah, it's a very big problem for anybody involved in this AI buildout. And the fact of the matter is is that Silicon Valley has done a terrible job communicating what it means to have AI in your life. Both from the software standpoint and the buildout, right? They talked about how it's going to take your job, kill your company. Now, it's going to be in your backyard. What's it going to do in your backyard? Most Americans think that it's going to make your energy prices go up. It's going to hurt your quality of life. It's going to increase pollution. And when you stack that all together, it's not a surprise that 70% of Americans are opposed to data center buildouts. And of course, politicians are going to seize on that because they need just, you know, 51% to win elections. And if you see 70% of people on the side against building data centers, then you just jump and go ahead with the with the tide on that front. The president's post today on truth so social is is interesting in that it goes after it seems the the people who are against data centers in their own backyards suggesting and I'll quote from the post. The only reason that communities throughout the USA should not want data centers is if they want to end up being backwards and poor goes on to say quote if we kill the golden goose you will only have yourselves to blame. I mean, this is not sort of targeting the tech industry for doing, in your words, a terrible job of selling this issue to the American people. Doesn't necessarily attack the politicians who are probably seizing on the angst uh in the way that they're messaging a ahead of the midterms. What do you make of that? >> Yeah. Now, this is the deeper issue underneath, right, which is not only has tech done a poor job messaging about the benefits of AI to Americans, but also a lot of Americans are feeling a lot of pain right now. So, if you're somebody in Indiana, for instance, you can read all of Gavin Baker's really good reasons for why AI and Jensen's really good good reasons for why AI data setters are going to help your community. But if you're not feeling real economic prospects and you see this these buildings try to come into your community, by the way, they're ugly. uh they they don't employ as many people as factories did and you've been de-industrialized, you're going to oppose them. And so I think Trump's positioning is very interesting here. And you know, obviously he doesn't have any more elections to run. If I was down ballot from like a Republican candidate attached to Trump or if I was somebody who was endorsed by him, I wouldn't be happy about this because ultimately the politicians are going to have to fight these battles in these local communities. And I think there's nothing less that voters want to hear than you're having a tough time economically. Silicon Valley is going to put up these huge faceless buildings in your backyard. You don't know if your energy prices are going to go up. And by the way, stop whining about it. Everything's going to be okay. >> Uh we haven't gotten to talk about Nvidia together. So, let's talk about Nvidia and how it relates to the broader tech conversation right now. Can we finally put to rest the argument that we are in an AI spending bubble? >> You know, Marley, my view certainly is that I think you can put that to rest. You see Nvidia, of course, it's been called so many different things, but basically it being the 10th pole that holds up the broader AI trade. I mean, to say that they beat last week is, I think, a really serious understatement. You have to be confident in the AI trade. Now, so much has been made of this question. Are we getting ROI on the AI trade? I think you could look at Microsoft Google Amazon obviously Nvidia is a piece of that. And so I think you have to say we're confident that the market is getting the answer it's looking like uh that it has wanted so long here and it starts to say okay well where do we go from here? What questions do we have on the horizon and that's really going to be you know of course uh what we have to think about going forward. So that's a name that I definitely see value in. Micron's another one. Um we've talked a lot about Micron but there's so much pent-up demand uh in that bottleneck of DRAM and HVM high bandwidth memory. We talked about the capex spend we expect expect next year. There's only a few names that can produce the enterprise chips necessary. Micron is on that list and expected to get a large portion of that spend. All right, I hope you're all doing well today and staying calm in this market. Today was a red day throughout much of the market as tensions in the Middle East rise. Oil move higher while stocks move lower. That said some AI hardware names were slightly positive on the day. I want to cover three things in this video. First, I'm going to cover today's Nvidia news. I'll share an interesting experiment we learned of this past weekend regarding token costs and then I'll cover memory news after that. On Monday, Nvidia announced an expanded partnership with MediaTek to expand collaboration across multigenerational AI factories, local AI computing and automotive. Under the expanded partnership, MediaTek is to adopt Nvidia's Envy Fusion, allowing customers to more easily integrate their custom XPUs with Nvidia systems. By adopting the NVLink fusion platform, MediaTek will provide hyperscalers CSPs and Frontier model companies with a pre-validated path to develop custom XPUs and bring them into Nvidia Envy link connected rack scale AI factories. This is a big deal. Also, as part of the deal, Nvidia has invested $3.5 billion in convertible bonds issued by MediaTek. The companies will also continue to collaborate on multiple generations of NVIDIA RTX Spark and DGX Spark PC chips. And they will also develop platforms for AI powered softwaredefined vehicles in the era of physical AI. By far the biggest piece of news from this announcement is that MediaTek will adopt NVLink fusion. As a reminder, with Envink Fusion, companies can integrate their custom accelerators with Nvidia systems and remain customers within the Nvidia ecosystem. That way, even if a customer develops a chip that's better for specific workloads and Nvidia's GPUs, they can simply integrate those accelerators with NVIDIA systems via NVLink Fusion and remain in the Nvidia ecosystem. Now, this announcement from Nvidia and MediaTek is especially interesting because MediaTek is involved with Google's eighth generation TPU program. We already know that Amazon's Tranium 4 will adopt NVLink Fusion. And as I said many months ago, I would not be surprised if we eventually see Google TPUs integrated with Nvidia systems via NVLink Fusion. The fears about Nvidia losing market share are very overblown and completely missed the point. As I've said repeatedly, this is not the time for Nvidia investors to worry about market share. And on the topic of Google, Alphabet also participated in MediaTek's bond offering along with Nvidia. MediaTek's adoption of Envy Link Fusion is very interesting as we could eventually see a situation in which Nvidia benefits from the success of Google's TPUs as well. Again, if a company wants to use their own accelerator, that's fine. Nvidia can still sell them the surrounding infrastructure. To be clear, at the time I'm making this video, we don't have confirmation of Google's TPUs integrating with Invalink Fusion, but Monday's announcement from Nvidia and MediaTek makes that possibility much more viable both technologically and commercially than it was before. And again, I think we may eventually see TPUs integrated with Nvidia systems via Envink Fusion. Also on Monday, Crowdstrike launched Falcon IQ to operationalize Project Quilt Works at machine speed. Project Quilt Works is powered by Frontier models from OpenAI and Anthropic as well as Open Neatron models from Nvidia. Nvidia's open neatron models power the agentic engine at the heart of Falcon IQ to validate and prioritize code vulnerabilities then remediate them in runtime at machine speed. Falcon IQ uses more than 50 agents to automate the most time-intensive workflows in assessment, prioritization, and remediation while giving partners the flexibility to build and tune custom agents for the unique needs of every customer they serve. Cyber security represents another major valuable use case for agentic AI and I think we will see notable growth in this area moving forward. It's very interesting because with cyber security, we're talking about agentic systems running continuously. Think about what that means. We're essentially talking about a workload that is likely to drive persistent 24/7 inference demand. A large number of agents working persistently around the clock, driving inference demand. Think about the implications it has for compute demand in Nvidia. And I don't see a situation in which that demand decreases over time. I actually see it increasing over time as threats become more numerous and complex. I would keep an eye on cyber security as another valuable use case that drives a considerable amount of token demand. Speaking of token demand, I noticed this post from Open Router over the weekend. On July 27th, Open Router started a 50% off promotion on GPT 5.6 Terra and 5.6 Luna. Then a couple days later, Open AAI shared efficiency improvements on GPT 5.6. And then one day later on July 30th, OpenAI decided to pass savings along to customers and cut its list prices for Terra by 20% and Luna by 80%. So from that point onward with a combined price cut from OpenAI and the promo from Open Router, Tara was effectively 60% cheaper than its launch price while Luna was effectively 90% cheaper. Following the change in prices, Terra token usage rose 5.6x while Daily Luna token usage jumped 13.8x. During that time, the price of GPT 5.6ole remained unchanged and as you can see from the yellow line on the chart, Soul usage remained essentially flat. Soul is essentially the control in this experiment. And then on August 17th, Open Router gave Soul its own 50% discount and usage immediately shot upward. There are a few interesting details we can glean from this experiment. First, as I've said repeatedly on this channel, lower token cost will result in greater usage. That's undeniable based on this experiment. And whether you're generating open- source tokens or closed source frontier tokens, you need infrastructure to generate the tokens. That's where Nvidia comes in. Greater usage results in greater compute demand, not less. Put simply, as token costs come down, usage increases. and as a result compute demand increases. Secondly, something else we can learn from this experiment is that the substantial discounting of the less capable models did not result in any meaningful decrease in usage of the leading frontier model. Look closely at the yellow line on the chart and notice what happened when Luna and Terry usage skyrocketed. During that time, sole usage remained relatively stable. Keep this in mind when you hear talk and headlines about lower token costs and cheaper models. As I've said previously, I think there will always be demand for leading Frontier Intelligence, even if there are cheaper models available. And thirdly, something else we can glean from this experiment is that Soul's usage remained flat throughout the experiment, but then jumped notably near the end of the chart when Soul received its own discount on August 17th. The fact that Soul usage was flat throughout the experiment and then jumped notably at the end when Soul received its own discount reaffirms the thesis that lower token costs will lead to an increase in usage. There's a fundamental reason why Nvidia is driving token costs lower by X factors with each new generation architecture, as well as driving token costs lower via software optimizations. Nvidia benefits from high token costs as that drives greater demand for Nvidia's latest systems. Nvidia's latest systems drive token costs lower. Lower token costs result in greater usage throughout the ecosystem, resulting in greater inference demand. Greater inference demand ultimately results in greater compute demand. And of course, Nvidia sells the compute. Nvidia has positioned themselves to benefit from both high token costs and lower token costs. And Nvidia is intentionally driving token costs lower because they will benefit from it. Token costs are not a logical reason to be bearish on Nvidia. As a side note, this is fundamentally different from oil during the shale revolution. Back then, there were some investors who argued that lower oil prices would result in greater demand. That ultimately did not work out well for many of those investors. But AI is fundamentally different. There are far more use cases for AI than there are for oil. With AI, there are thousands of use cases and potentially millions of endpoint applications. Think of it like this. There are not many new use cases that could be unlocked as a result of increasing oil production. However, there are many new use cases that can be unlocked as a result of bringing down token costs and increasing token generation. And some of those use cases are very valuable. When valuable new use cases are unlocked, like what we saw earlier this year with a coding, usage skyrockets, inference demand inlects higher, and that ultimately results in greater compute demand. And in this AI revolution, new use cases are going to be unlocked much faster than in previous economic booms because this is all digital. And contrary to the internet bubble, new use case development at scale and mass adoption of the technology are both immediately possible because the internet is already here this time. Digital demand grows exponentially. Physical infrastructure simply cannot keep up and it likely won't be able to catch up for multiple years. So to summarize, lower token costs drive greater usage. Greater usage leads to the unlock of new use cases. Valuable new use cases cause token demand to increase further. Greater token demand ultimately results in greater compute demand. Now let's cover some memory news. The information published a story claiming that China's CXMT has begun small volume production of HBM3e with Alibaba and Cambercon both testing the product. Yields remain an issue and CXMT is still several years behind the big three memory makers at the leading edge, but this is a meaningful step toward a domestic Chinese HBM supply chain. I want to provide a disclaimer and say that this has been an unreliable source in the past regarding Nvidia China rumors. And so I have no idea if this story is true or not. I'm just bringing it to your attention so that you're aware of it. We also have some rumors that are relevant to both Nvidia and Memory Makers, a well-known technology supply chain analyst from TF International Securities posted on X saying that it appears Nvidia has revived plans for Reuben CPX based on their industry survey. You may remember that Nvidia essentially stopped talking about Reuben CPX after they struck a deal with Grock and announced Nvidia Gro 3 LPX at GTC. Reuben CPX was originally supposed to launch at the end of 2026, but it essentially got brushed aside after Grock 3 LPX was announced. Anyway, according to the post, Nvidia has revived Reubin's CPX efforts, changed the design, and production is to begin in the first quarter of 2027. Now, what's notable as it relates to memory makers is that the new version of CPX reportedly has upgraded memory 168 GB of HBM 4 versus the original CPX's 128 GB of GDDR7. According to the post, CPX must be paired with Vera Rubin, NVL72, and Nvidia recommends a 1:1 ratio of CPX to Rubin. CPX handles prefill and KV cache creation, then passes the data to Reuben via Ethernet RDMMA for decode generation. The idea is that this would be the highest cost performance solution for long context prefill. We'll have to keep an eye on this one to see if we get confirmation from Nvidia. The next GTC keynote is scheduled for October 21st, so maybe we'll get details then. In other news, Soul Economic Daily is reporting that Samsung's memory business division has allocated about 70% of its production capacity through 2031 to long-term agreement volumes, according to industry sources. We also learned that both Samsung and SKH Heinix are pursuing capacity expansion since it appears that the memory shortage is unlikely to be resolved quickly. SKH Highix is weighing the possibility of setting up a joint venture plant in Japan with a local partner. And Samsung is reviewing a plan to convert the only foundry line at its Pione campus in memory facilities as early as next year. Now, by the time you're watching this video, there's a good chance South Korea's export data for the month of August has already been released overnight. That data should give us another read through on memory pricing, especially since both Samsung and SKH Heinix are based in South Korea. I just want to give you a heads up because unfortunately the data isn't available yet at the time I'm making this video and because of how long it takes to make these videos, I'm not going to be able to cover that in this video. But the August export data could have an impact on how memory stocks trade on Tuesday. So, I wanted to make sure it's on your radar. Looking ahead, Jensen is scheduled to speak at the Goldman Sachs Communicopia and Technology Conference on September 10th. and then Jensen is scheduled to speak again at GTC Berlin on October 21st. Now, in case you're new to the channel, I want to make sure that you have at least a basic understanding of the underlying long-term thesis. So, let's cover that. Now, 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. 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. 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 compute constrained and I expect that to continue at least through the first half of calendar 2028. 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. 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. This AI revolution is fundamentally different from the do-com 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 revenues surge. I wish both anthropic and open AAI were public so the public could see the ramp in their revenues. 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. 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 computed 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 aic 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- 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 3 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 and remains in high demand. Vera Rubin is rolling out to customers. Nvidia Gro 3 LPX is in full production. 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 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. At least that's my view of the situation. Quick note before I wrap up. 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, Finnvid. 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. Thanks for watching and hopefully I'll see you in the next