Something big is happening in AI data centers as we speak. Something that most Wall Street analysts won't see coming until it's too late. And it's happening so fast that it doesn't even matter which AI companies come out on top. That makes the one stock I'm about to show you a great way to get rich without getting lucky. Your time is valuable. So, let's get right into it. First things first, I'm not here to waste your time. So, here's everything I'm going to talk about upfront. why data centers must make massive infrastructure changes to keep up with AI demand. An overview of Verdive Holdings, ticker symbol VRT, and how they make their money. Verdives's most recent earnings call, their catalysts and risks, and of course, where Verdiff stock belongs on my list of stocks to get rich without getting lucky in 2025, which has been outperforming the market by a large margin year to date. This is a once in a-lifetime opportunity. So strap in and let's talk about the big changes brewing in the AI market. And I'll do my best to avoid any industry jargon along the way. The biggest thing investors need to understand is that the costs for using AI are going up exponentially because of reasoning. When OpenAI released chat GBT 3 years ago, it was doing something called oneshot inference. All that means is when you give the model a prompt, it immediately starts generating a response. This one-shot approach has a lot of benefits like being fast and computationally cheap with predictable costs when serving millions of people. But it also comes with serious issues like providing different responses to the same question and getting stumped on complex problems and hallucinating instead of verifying its own answers. So over the last couple years, AI researchers have come up with new techniques to generate even better responses. And what most Wall Street analysts are missing is that these same techniques are the main reason for this massive cycle of data center upgrades. Which means that understanding them can help us understand which upgrades are actually in demand. Let me quickly walk you through three of the big ones. Chain of thought reasoning forces a model to break a problem down into steps, solve and verify its solution at each step, and then provide a final answer. This is great for a wide range of tasks that people tackle step by step today, from making shopping lists and travel plans to troubleshooting and financial analysis. But the trade-off is that chain of thought reasoning takes five to 10 times as many tokens to run as one-shot inference. Best event sampling is where you have a model generate multiple answers to the same prompt and then choose the best answer. For example, generate 20 titles for a YouTube video and then pick the most provocative one. or generate 20 different portfolio strategies for investing and then pick the one with the best risk versus reward. Or generate 20 variations of a resume and then pick the most impressive one. This is great for problems where quality matters way more than speed. But the trade-off is that you're spending tokens on every generation. So all of my examples cost 20 times the tokens of oneot inference. But this third technique is by far the most computationally expensive because it kind of combines the other two. Tree search is where a model compares multiple approaches to solving a problem and is used when the journey to the answer matters just as much as the answer itself. For example, finding the best strategy in chess depends on the order of your moves because your opponent gets to respond to each one or generating a business strategy or a project timeline where schedules and milestones matter just as much as the end results. In each case, tree search has to break complex problems into steps and think through multiple possible paths to the solution before returning the final answer, which can easily cost over 100 times more tokens than oneshot inference. But here's the real kicker. Much better answers also means much more user adoption. The number of people using generative AI has 15xed in the last 3 years. And the average number of prompts per person has 10xed as people find more ways to use AI. So 15 times more users multiplied by 10 times more prompts per user multiplied by around 20 times more tokens per prompt means we need 3,000 times more compute power to support generative AI applications today than we needed just 3 years ago. And that's just for large language models. The number of tokens per prompt skyrockets when we switch from text to video or to code for games and apps or to simulations for drug discovery or product design. The list goes on and on. And now that we understand the 3,000fold increase in demand isn't just coming from more users, but from ongoing fundamental changes to how AI models spend tokens, we can talk about how Verdive is supporting the massive infrastructure transition that data centers need to make if they want to meet all of that demand. I really think this context is important for investing. Warren Buffett became one of the richest men in the world by staying inside his circle of competence and investing in businesses that he understands. And right now, the most important thing for investors to understand is AI. That's where Outskll comes in, the sponsor of this video. 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All right, so 3,000 times the demand for tokens means data centers need to pack way more chips in the same amount of space, power them, and keep them cool. Around 90% of all server racks are air cooled today, but industry estimates suggest that up to 80% of that will eventually transition to direct to chip liquid cooling, which coincidentally is up to 3,000 times more efficient than air cooling. As a result, analysts currently expect the liquid cooling market for data centers to almost 5x in size by 2033, which would be a compound annual growth rate of 21% for the next 8 years. But if you watched my previous video, you know that Nvidia's Blackwell and Blackwell Ultra systems require liquid cooling, which means any data center looking to upgrade must transition to liquid cooling first. And since Nvidia is already shipping Blackwell systems, I think this transition will be much bigger and happen much faster than most market analysts expect. That's why I think Verdive Holdings is a solid investing opportunity right now. Verdive Holdings provides a wide variety of integrated end-to-end power and thermal management systems for existing data centers. For example, their Libra liquid cooling systems provide liquid to air, liquid to liquid, and directtochip liquid cooling depending on what the data center needs. Directtochip liquid cooling is where a heat conductive copper plate is physically mounted to the chip. That plate is connected to two pipes. One pipe brings in cool water to absorb the heat, and the other pipe moves the hot water away. And liquid to liquid cooling is where that heated water gets piped over to the building's chillers or cooling plant before being sent back to the server racks to absorb more heat from the chips. That's the two parts of the cooling loop required to run Nvidia's Blackwell GPUs as scale. Another special thing about Verdives's cooling systems is that they're modular and can be scaled to up to 600 kW of cooling per unit, which means that Hypers scale data centers can add liquid cooling to five 120 kowatt Blackwell racks at a time, or they can quickly retrofit their existing facilities to support them without other major infrastructure overhauls. That's why Vertive supplies critical cooling solutions to all three hyperscalers, Amazon Web Services, Google Cloud, and Microsoft Azure. Verdive also supplies core power systems like their Liber XL, which is a highcapacity uninterruptible power supply or UPS, which is specifically designed for hypers scale and cloud facilities because it supplies huge amounts of energy at very high efficiencies. And their Liber APM2 is a modular UPS that's designed to protect data center hardware from unexpected power failures or surges by instantly switching to battery power when the main grid loses electricity. That's what protects high performance computing and dense AI clusters worth billions of dollars from suffering sudden downtimes. And because it's modular, it can support any size of data center by growing capacity as the data centers needs expand. And now that we understand how Verdive makes their money, let's walk through their latest earnings, their biggest potential catalysts, and of course, their risks. Verdive reported $2.64 billion in net sales for the quarter, which is up by 34% year-over-year and 10% over their prior guidance. Their adjusted operating profits came in at $490 million, which is up 28% from last year and 11% over their prior guidance. As a result, their adjusted earnings per share came in at 95 cents, which is up by 42% from last year. Verdives adjusted operating margins went down by 1.1% from 19.6% last year to 18.5% this year for two key reasons. First, they're ramping up or acquiring new manufacturing sites, which comes with startup expenses, workforce training, and process adjustments before reaching normal operating efficiency. And second, they had to move some of their manufacturing and assembly operations to reduce supply chain risks and avoid tariffs on their imported components. I'm not too worried about this because these are one-time expenses that Verdives management expects to be resolved by the end of the year. If anything, this tiny drop in margins shows just how resilient the business is and how agile their management team can be when they're faced with new challenges and headwinds. Verdive breaks their quarterly earnings up by region. the Americas, Asia-Pacific, and Europe, Middle East, and Africa. Since they're focused on global expansion, 61% of their revenue comes from the Americas. 21% comes from Asia-Pacific, and the other 18% comes from EMEA with solid sales growth in the first two regions while they're still investing in the third. But this channel is all about investing in advanced technology. So, I took some time to reorganize their revenues by product segments instead of by regions. Just to be extra transparent, these numbers are from my own analysis and they are not from Verdive or any other official source. I did the best I could, but make sure to take them with a grain of salt. Thermal management and cooling systems are responsible for around 1/3 of Verdives's quarterly revenues today. This is also their fastest growing segment, growing by around 25% year-over-year thanks to massive demand for liquid cooling in AI data centers as they transition to Nvidia's Blackwell systems. Power systems are currently Verd's biggest product segment, accounting for about half of their total revenues. Just like with cooling, the need for efficient and scalable power solutions isn't going away, which is why this business unit is growing by over 20% per year. Physical data center hardware like racks, cabinets, and enclosures make up another 10% of Vertive's revenue. And they're also seeing almost 20% growth. And the rest of Verdives's revenue comes from software and services for power and cooling management, which is probably growing much slower because other data centers and especially the hyperscalers all have their own internal ways of monitoring and managing these things. And just for a gut check, these numbers line up pretty well with Verdives's guidance for the year, which shows net sales increasing by around 24%, operating profits going up by about 28% and free cash flows going up by around 23% all year overear. But that doesn't mean there are no risks to Verdives's business. Verdive faces ongoing risks from supply chain disruptions, manufacturing transitions, increased costs, and tariff headwinds as they ramp up new production facilities in North America to be closer to their biggest customers and avoid tariffs. Any delays in reaching full operational efficiency could impact their costs, their delivery timelines, and ultimately their profit margins, especially when AI customers require rapid deployments and flawless execution. Global AI infrastructure is also an incredibly competitive industry right now with many major companies racing to launch new liquid cooling and power management solutions for the next generation of data centers which are owned and operated by some of the richest companies on the planet. If Verdiff doesn't stay on the bleeding edge and keep exceeding customer expectations, their biggest customers will find another company that will. And finally, becoming a global company exposes Verdive to the geopolitical risks associated with Asia and the EMEA, including foreign regulations for data protection, localization, foreign tariffs, and national security hurdles. For example, changes in the US's relationship with China could impact Vertive's supply chain and total addressable market. In my opinion, most of Verdives's peers have these same risks. So the real choice is either accepting these risks or staying away from data center infrastructure stocks altogether. There's no right or wrong answer here and every investor needs to do what's right for them. But here's what I'm personally doing. And if you feel I've earned it, consider hitting the like button and subscribing to the channel. That really helps me out and it lets me know to make more deep dives like this. Thanks. And with that out of the way, here's my personal stance on Vertive stock. My key takeaway on Verdive right now is that they're firing on all cylinders. Their quarter 2 earnings exceeded expectations on sales, on operating profits, and on earnings per share. They're raising their guidance on every metric that investors care about, and they're deploying capital to keep growing their capacity to serve the accelerating demand for AI infrastructure. Tariffs, supply chain challenges, and competition are all real risks that every company needs to manage. But Verdives's management team has shown that they can navigate those challenges and still come out on top. I've also talked to Vertive's employees at multiple conferences now, and they all seem genuinely excited for the future of the AI industry and for their place in it. Not to mention that Jensen Hong has called out Verive as one of Nvidia's key data center partners in several of his recent keynotes. And while they do have the highest forward price toearnings ratio among their direct peers, they also have twice the earnings growth of their next closest competitors, Rockwell Automation and Emerson Electric. Discounted cash flow models like Simply Wall Street's calculate the fair value of Vertive stock to be about $150 per share, which implies about a 20% upside from today's prices. So, for all the reasons I've covered throughout this video, I'm moving Vertive Stock up two spots on my list of stocks to get rich without getting lucky, even though it's still underperforming the S&P 500 by a few percentage points. I also ended up moving CrowdStrike up two spots for the same reasons. I've been a shareholder for years now, and I think they're another core AI infrastructure company, but on the software and security side, and I think that AI infrastructure stocks will outperform the market over time. As a result, I ended up moving Amazon and ARM down two spots on my list. And I'll keep reassessing things as more news and earnings come out. And if you want to see what else I've been investing in, check out this video next. Either way, thanks for watching to the end, even though I gave you everything upfront. And until next time, this is Tickerol U. My name is Alex, reminding you that the best investment you can make is in you.