This Is A Historic Buying Opportunity (98% Will Miss It)

If you put $10,000 into Nvidia when Chat GPT launched less than four years ago, you'd have over $120,000 today. If you invested that money into Micron just last year, you'd already have over 75 grand. Well, there's another kind of AI chip that's quietly changing which stocks are about to win big and making their investors very rich along the way. My name is Alex and I spent 8 years as an electrical engineer and AI researcher at MIT. And I never thought that this would be the next big battleground for AI. Let me show you what's going on and how I'm investing in it. Your time is valuable, so let's get right into it. For the last 4 years, data centers were priced as a GPU business. Accelerators from companies like Nvidia, AMD, and Broadcom are the product, and every piece of AI infrastructure was built around them. not just the power, the cooling, and the server racks, but also the networking chips, the memory, and even the CPU alongside them. But that's quickly changing. And to understand why, we need to understand the science behind the stocks. GPUs break math problems down into thousands of tiny pieces, solve every piece at once, put the pieces back together, and return the final answer. That's why they're so fast. But the trick is that not every calculation can be broken into tiny pieces in the first place. That's why many of Nvidia's CUDA libraries focus on transforming real world problems into problems that a GPU can solve. That's what they mean by accelerating different industries. A CPU works the exact opposite way. It can handle any kind of problem, but it handles one problem at a time. So, GPUs do predictable work in parallel while CPUs do unpredictable work in sequence. When you ask chat GPT or Claude or Gemini a question, it basically goes straight to a GPU. Your sentence gets chopped into tiny pieces called tokens, and every piece runs through the same neural network. Billions of numbers, each multiplied in the same pattern, layer by layer, the perfect shape for a GPU. So, the CPU hands the work over and then stays out of the way. But AI agents flip this script entirely. An agent reads your request, comes up with a step-by-step plan, makes a bunch of separate tool calls, writes code, and maybe even spawns sub agents to handle different steps along the way. The math still runs on GPUs, but everything else runs on the CPU, choosing what to do next, fetching files, moving data, and so on. Even when I worked on these kinds of systems back at MIT 10 years ago, which were way smaller and simpler at the time, the GPU was waiting while the CPU had to think. Agents push that to the limit, which is why the CPU is becoming the next big battleground for AI. And the battle is between the biggest companies with the most advanced technology in the world. Let's start with Nvidia. Nvidia has their Grace CPUs and superchips. The Grace CPU has 72 cores and the super chip connects two of them together. So, they act like one giant CPU with 144 ARM Neoverse V2 cores. But here's the big problem. Neover is the data center CPU core design that's sold by ARM. Nvidia only licenses it. So, Nvidia might be the king of AI CPUs, but the castle belongs to ARM. Nvidia sold nearly 2.5 million Grace CPUs to date. and every one of them pays a royalty back to ARM. Nvidia's answer is a chip called Vera, which has 88 custom Olympus cores that are designed in-house, making it their first fully custom CPU. Nvidia kept exactly one thing from ARM, the instruction set. That's the language the processor understands and the list of commands that software can give it. So code written for Grace can run on Vera without needing to be rewritten. That means Nvidia can keep every line of code their customers already wrote and stop paying ARM for the cores that run it. Nvidia already delivered the first Vera CPUs last quarter to Anthropic, OpenAI, SpaceX, and Oracle. On their latest earnings call, Nvidia reported over $75 billion in data center revenues for the quarter. Roughly $60 billion from compute and 15 billion from networking. When investors think about AI compute, they think about GPUs. But Nvidia's CFO Colette Crest said that they expect around $20 billion in CPU revenues this year alone. And that AI CPUs are a brand new $200 billion total addressable market for Nvidia. But Nvidia doesn't dominate this market the same way they dominate the GPU market. In fact, they have some serious competition from ARM, from Qualcomm, and from AMD. All three are massive chip companies and all three are making some very big moves. By the way, if you've ever wondered whether a stock is actually worth its price, you are not alone. Finding a company's fair value is one of the hardest parts of investing. That's why I use Propics by investing.com, the sponsor of this video. Each month, their tech titan strategy narrows the entire US tech sector of the market down to just 15 highquality stocks. The algorithm finds companies with the best mix of fundamentals, momentum, and guidance. When the data changes, the strategy updates, staying only in the highest conviction stocks. It also gives you the reasons behind every move, not just what changed, but why. You can click into any stock and see a full breakdown of the data to kickstart your own research. But the proof is in the pudding. Since going live, Tech Titans has more than doubled the S&P 500, returning over 180% in less than 3 years. Today, it's holding great stocks like AMD, Applied Materials, Qualcomm, and ARM. All of which I cover on this channel. And right now, investing.com is running a summer sale, which is their best price all year. And you can use my link below to get another 15%. Talk about a no-brainer. All right, let's start with ARM since they own the architecture that Nvidia's CPUs currently rely on. On July 29th, during their earnings call, ARM told shareholders that the initial version of their AGI CPU was already delivered to multiple customers, marking the end of a 35-year era. Ever since they were founded in 1990, ARM was the ARM dealer that never picked a side. They sold blueprints to Apple and Qualcomm, Nvidia and Amazon. And they collected up to 5% royalties on every chip while everyone else fought the war. That is until now. ARM recently launched the AGI CPU, the first chip they've ever designed and sold themselves, which means they make 100% of the revenue instead of just five. And right off the bat, this chip has some serious specs. up to 136 cores per chip running at 300 watts and built on TSMC's 3 nanometer process with Meta as the lead partner and co-developer. ARM claims that their AGI CPU has more than double the performance per rack versus X86 chips and they have over $2 billion of demand over the next 2 years. But they've only secured enough manufacturing capacity to meet around half of that. That capacity is being constrained by wafers, substrates, memory, and testing. All things that ARM never had to worry about when they were only selling blueprints. And that shift is already showing up in their numbers. Revenues came in at $1.3 billion for the quarter, which is up 22% year-over-year, with revenue from royalties also up by 22%. But data center royalties more than doubled, growing at least four times faster than the rest of the business. This was also the quarter where ARM stopped reporting remaining performance obligations. That's the revenue they have under contract but haven't collected yet, which usually gives investors visibility into their next few quarters so they can track and predict ARM's growth. In my opinion, this was the single most useful forward-looking metric that ARM published and they stopped the same quarter that they started shipping hardware. The last number that we got was $2.07 07 billion at the end of March, which was actually down 7% from the year before. But now we have to wait until their annual report next spring for the most updated number. Until then, I think gross margin is the number to watch. ARM went from collecting high margin royalties with very clear visibility to also having to worry about wafer costs, production capacity risks, and hardware-like margins. Investors should see real revenues from the AGI CPU in fiscal year 2028. So that's when we'll get a much better sense for their overall margins. But I think the market is already pricing in their chip sales to perfection. ARM's current price to sales ratio is close to 50. Not earnings, sales. That's almost 10 times higher than the semiconductor industry average. And their forward price to sales ratio is almost 39, while every other stock in this video sits between 4 and 14. Qualcomm is one of ARM's biggest customers and their forward price to sales ratio is under four. So, let's talk about them next. If you own an Android phone, there's a good chance that Qualcomm built the processor inside it. Their Snapdragon chips are in most flagship Android devices. Their modems were inside iPhones for years, and they collect some kind of royalty on almost every smartphone on the planet, even the ones running on someone else's silicon. They even make some chips for cars. But Qualcomm builds their Orion cores under an architecture license from ARM. Qualcomm also reported earnings on July 29th. Revenues came in at $9.9 billion with $221 of earnings per share. Their automotive business hit a record 1.6 billion, which is up 61% year-over-year. That's their 23rd straight quarter of double-digit automotive growth. Internet of Things came in at $1.8 8 billion, which was up 9%. But handsets came in at $5.1 billion, which was down 20% year-over-year. That decline is largely due to them having lower share of modems in the coming iPhone launch as Apple keeps transitioning to their own custom chips. Qualcomm's management said that this quarter marks the bottom for handsets and announced double-digit price increases on their chips starting September 1st. That also means the non-phone business is now carrying the company. Qualcomm guided year-over-year growth in non-handset revenue to jump from 24% this fiscal year to over 60% next year. And they specifically called out data centers as part of that growth. At their investor day back in June, Qualcomm set a target of more than $15 billion in data center revenue by 2029. This year, it's around $300 million. So, that's roughly 50x growth in just 3 years, and it would account for more than a third of Qualcomm's entire trailing 12-month revenue of $44 billion. Set another way, Qualcomm expects their new data center segment to account for roughly a third of everything it took them 40 years to build so far. Even though their data center revenue is small today, they've already lined up some massive customers. Meta signed a multi-generation agreement for Qualcomm's CPUs for their next generation server fleet and Satia Nadella confirmed that Azure will deploy Qualcomm's accelerators starting next year. Qualcomm's Dragonfly C1000 data center CPU also has some serious specs over 250 Orion cores across multiple connected diese, kind of like Nvidia's Blackwell GPUs. But here's the thing, Qualcomm has never shipped a data center CPU. Their custom silicon revenue starts later this year. The Azure accelerators land in 2027 and the C1000 CPU itself doesn't start production until the second half of 2028. So, the money is booked, the customers are signed, but the actual chip is still 2 years out. Like I said earlier, Qualcomm's forward price to sales ratio is under four, 10 times cheaper than ARM. So, while ARM's AGI CPU is already priced in, Qualcomm's C1000 CPU seems to be priced at zero, making it a good opportunity to get in early, at least for long-term investors that are willing to take a risk on a brand new chip from a company that just pivoted to data centers. But if you want to bet on the current king of CPUs instead, let's talk about AMD next. And if you feel I've earned it, consider hitting the like button and subscribing to the channel. It really does help and it lets me know to make more content like this. Thanks. Now, let's talk about AMD's AI chips. On July 20th, Microsoft announced that they'll deploy AMD's Helio systems on Azure, pairing the Instinct MI455X GPUs with their sixth generation Epic CPUs, cenamed Venice. Let me break that down for you. Helios is a rack scale system, which means that AMD is selling an entire rack. Accelerators, CPUs, networking, and software, all wired up and optimized to work together, delivered as a single unit. Microsoft is coming out with three new kinds of virtual machines based on AMD's hardware. the NDMI455XV7 for AI inference on Helios itself, the Azure HDV2 for Agentic AI and data pipelines, and the Azure HXV2 specifically for semiconductor design. Here's why this is a big deal. Cloud providers only create and offer virtual machines at scale for configurations that they plan to run and rent out for years. So, Microsoft is basically committing to AMD's racks much more aggressively than any normal purchase order could. They're putting AMD's technology on the menu as a permanent product line. Helios is already in production, and leading AI companies are going to deploy these systems at gigawatt scales. Just to be clear, 1 gawatt is roughly the power output of a large nuclear reactor. Open AAI signed a deal for 6 GW worth of AMD GPUs. Meta signed a deal for six more gawatts of Helios racks running Venice. Anthropic signed up for another two gawatts and AMD committed up to 5 billion worth of equity to Anthropic that same week. And here's where we come full circle. AMD's Helios racks have 72 Instinct MI455X GPUs and 18 Epic Venice CPUs. That's one CPU for every four GPUs. Almost every Wall Street analyst models GPU sales, but almost none of them account for the 18 powerful and expensive CPUs that are shipping with every rack. CPUs that are becoming more and more necessary to power AI agents and CPUs that have zero competition because Helios comes as one integrated package. I think the entire way we measure and predict market share is about to change. The old way is counting units. how many chips or dollars every company sold versus their competitors. But the new way is counting tokens and watts. Each company's share of AI power deployed and the amount of tokens their systems are generating per watt. Open AAI, Meta, and Enthropic are signing up for 14 gawatt under AMD. That's a pretty big deal if it all actually gets deployed. But there are three important details to the AMD story that investors really should remember. First, AMD is paying a serious sum for those gigawatts. AMD gave OpenAI warrants for up to 160 million shares, and Meta Platforms 160 million more, all priced at one penny each. That means they're giving away up to 20% of the entire company to secure these deals. And they invested another $5 billion into Anthropic on top of that. Second, these deals are not guaranteed. There are a lot of performance milestones along the way and OpenAI and Meta still have to actually deploy these chips and racks. So, all that is still in front of them even though it's all already priced into AMD's stock. And third, AMD just reported earnings right as I'm recording this video. Their revenue came in at 11.5 billion, which was up 50% year-over-year. Data center revenues came in at $6.7 billion, up 107% year-over-year and now accounting for 58% of AMD's total revenues. They even guided next quarter's revenue to roughly 13 billion. That sounds great until you compare it to Nvidia. I know I'm beating a dead horse here, but it's important to know that AMD is five times more expensive than Nvidia by PE ratio and three times more expensive by forward PE ratio. And AMD's multiples have only been going up with each earnings call, while Nvidia's have been coming down. I'm not saying you shouldn't buy AMD stock, but I am saying you should understand what you're buying if you do. Hopefully, this video helped you understand that AI CPUs are no longer standalone chips. They're a core component of the infrastructure for Agentic AI and a big battleground for every major semiconductor company. And AMD's CEO, Lisa Sue, just confirmed on their earnings call that demand for accelerators and CPUs keeps growing faster than anyone expected. Funny enough, the two companies sitting at the center of it all are actually Meta Platforms and TSMC, neither of which sell any CPUs themselves. Meta is ARM's lead partner for the AGI CPU, a flagship customer for Qualcomm's Dragonfly C1000. They bought 6 GW worth of Helios racks from AMD, and they're one of Nvidia's largest AI infrastructure customers. So, if you hear that AI spending is slowing down, Meta is the company to check first. And all four companies rely on TSMC to make these chips in the first place. AMD's Venice, Nvidia's Grayson Vera, ARMs AGI CPU, and Qualcomm's Dragonfly C1000 are all made on TSMC's most advanced nodes. So, if they have any delays, supply constraints, or somehow fall behind, every company we just covered will feel it, too. But as for me, I'm betting that Meta spending keeps growing, that TSMC keeps producing, and that AI agents are here to stay, making data center CPU stocks a great way to get rich without getting lucky. And if you want to see even more stocks I'm buying to get rich without getting lucky, check out this video next. Either way, thanks for watching and until next time, this is Tickerol U. My name is Alex, reminding you that the best investment you can make is in you.