Dan Ives: "Investors Are Missing the Big Picture" (3 Top Tech Stocks to Buy Now)

Dan Ies believes investors are missing the bigger picture when it comes to AI, arguing that Wall Street is thinking too small about what's coming next. In this interview, the Yorkville Ives and company's senior managing director explains why the recent sell-off in big tech may be creating opportunity instead of signaling trouble. First, I'll play Dan Ies's interview in full without interruption. Then I'll break down his biggest insights, share my own reaction to what he said, and finally reveal my top three tech stocks to buy right now based on the trends shaping the future. Let's hear what Dan Ies has to say. >> Two mega cap tech stocks are getting trounced today. Both Alphabet and Tesla on pace for their worst day in more than a year and are dragging down the major averages. The reason here is that investors are just freaked out by their spending on AI. Next guest says, "Don't worry." Tan Ives of Yorkville Ives and Co. joins us. I mean, that's pretty much your mantra. Don't worry, be happy. But in this case, let's talk about Tesla number one. I mean, this is a company I was just reading its market cap is bigger than the next 36 biggest automakers put together. May is it just time for it to come down? >> You heard that on Power Lunch. >> Thank you. >> You're right. You're welcome. It's look the reality I mean they're they're they're not a car company. They when you think about from an investor perspective it's this is much more about AI disruptive tech and I think when you look at Tesla look the issue here continues to be and same with Alphabet capex investment for let's say in Tesla for physical AI when it comes to autonomous when it comes to optimist but you're not seeing in the near term and that continues to be this gut check moment >> the stock is down more than 14%. Does this mean that investors just don't buy it? >> I think patience is is wearing thin, right? Because from an investor perspective, if you put up the capex numbers, but then you show it, they'll get benefit of the doubt. And I'd say Alphabet is out is is a different story relative to the type of growth that they're showing on cloud. I think for Tesla, this is not just right around the corner. You have to ramp up robo taxes. You have to show the physical AI story. Look, that's all that Musk is doing. And I think there is a view here too where with SpaceX and now of course Tesla must you know the the two golden childs that he has you know where this ultimately heads. I just continue to view it that we are still in the third inning of AI revolution and this is just the beginning of those stories. We'll get we'll get to AI in a second, but to follow up on that, does Dan Ies of Yorkville Ives, by the way, think that Tesla and SpaceX ultimately merge >> and there's over an 80% chance by the end of 2020, by the end of next year that SpaceX ultimately acquires Tesla. It's something where >> you're so you're more bullish than the most bullish of Khi traders right now. Cali has those odds 10% before November 2026, rising up to 63% that it happens before 2028. Here's my question. Do you think that all these Tesla diehard champions always are starting to shift toward SpaceX? That's that's who they love right now. >> Yeah, I wouldn't I mean I look I think some which are your children do you love the best, right? So you could still have both of them, but I think from an investor perspective, it comes down to for Tesla, the the AI story is the future. It's not about deliveries, but you have to ultimately build it out. You have to have more cities, some robo taxi, and Musk, you know, on the conference call, I think there was definitely some caution, right? And I think maybe in some ways that's smart, but that's why the stock's reacting accordingly. >> $1.3 trillion. I feel like I should do like the Dr. Evil pinky. Go do it. When we do that, nobody's stopping you. >> A new movie coming out, by the way, apparently, which is the spending estimate on AI from these companies. Alphabet today saying they're going to spend more. Stocks down a little bit. In the previous hour, I posited to a guest >> that if they would have cut their spending on AI, the stock would be down a lot more >> than it is today. What's your take? It >> this is an arms race that's playing out and we're only 15% of the way through. The reality, >> will they ever make the money back on the spending? They have to. I don't. If they don't, there's no reason to spend it. >> I don't think there's even a question. And to some extent, the fact that they continue to spend on capex, and you'll see that with Microsoft, you see it with Amazon, the rest of the hyperscalers. It's because enterprises, they're lining up on the use cases, the consumer piece. You've seen Apple that ultimately is just starting. So, it speaks to blank. This is Vegas 1955 building the strip. I mean, no, that's essentially where they are. So for these companies, they will ultimately get on the chin in terms as the stocks, but they cannot be shortsighted relative to this capback arms race that's playing out. >> Vegas, if you didn't show profit, somebody was getting kneecapped. Intel reports after the bell today, what are your thoughts on it's all about the demand stories showing whether it's chips and Intel, whether it's hyperscalers because what that continues to speak to, it's our view this story is accelerating relative to demand. what enterprise are seeing whether it's memory whether it's chips or whether it's hypers scales that's what investors focus on despite obviously what you're seeing today in the market >> you're saying not everybody got out of the desert alive >> I'm I'm they keep discovering bodies as the water goes down so yeah that's >> but you had you had great Sinatra demar and every new every >> and now you have the sphere they want but your point is they they wanted the sphere in the 1950s but they couldn't have it they had to wait for the investment >> if you told someone sphere was coming 55 what would they have said >> the first thing you probably noticed is that the market was reacting emotionally while Dan Ies was trying to get investors to focus on the much bigger picture. Alphabet and Tesla were getting crushed after investors saw another round of massive AI spending. And the immediate reaction was simple. People started wondering whether these companies were throwing away billions of dollars chasing an AI dream that may never pay off. Dan Ies completely disagreed with that interpretation. His central message throughout the interview was actually very straightforward. He believes Wall Street is looking at the next few quarters while the biggest technology companies are building businesses that could define the next decade. Whether you agree with him or not, that's really the lens through which he views almost everything happening in AI today. One of the biggest topics was Tesla and I think this is where the conversation became especially interesting because Dan Ies once again made it clear that he does not view Tesla primarily as an automaker anymore. In his opinion, investors who continue valuing Tesla based only on vehicle deliveries are missing the larger story. Instead, he argues that Tesla has evolved into an AI company. Specifically, he sees it as a physical AI company. That means autonomous driving, robotics, robo taxis, Optimus, and eventually a future where artificial intelligence exists not only inside software applications, but also inside machines that operate in the physical world. Now, this is something that has divided investors for years. On one side, you have people who continue focusing almost entirely on declining vehicle growth, competition in electric vehicles, shrinking margins, and slowing demand. On the other side, you have investors who believe cars are simply the launchpad for a much larger artificial intelligence platform. Personally, I think this is probably the biggest debate surrounding Tesla today. If Tesla is simply another car manufacturer, then many would argue its valuation is extremely difficult to justify. But if Tesla successfully becomes one of the world's dominant AI and robotics companies, then suddenly investors begin valuing it much more like Nvidia than Ford. That is exactly the framework Dan Ies continues using. He acknowledged that investors are becoming impatient and honestly that part makes perfect sense. Markets can be incredibly patient when exciting promises are first announced, but eventually investors stop rewarding promises and begin demanding proof. That's exactly where Tesla finds itself today. Dan Ies described this as a gut check moment. Tesla continues spending enormous amounts of money developing autonomous driving technology, AI infrastructure, robotics, and robo taxis. The investment is happening today, but the financial payoff is still largely expected sometime in the future. Wall Street is asking a very reasonable question. When does all of this actually start producing meaningful revenue? Dan Ies basically answered that investors need to stay patient because these technologies are much bigger than what most people currently appreciate. Whether investors are willing to wait is another question entirely. I also found it interesting that he compared Tesla with Alphabet because although both companies are spending aggressively on AI, he clearly believes the situations are different. Alphabet is already seeing strong cloud growth which gives investors tangible evidence that AI investments are beginning to translate into business results. Tesla, meanwhile, still needs to prove that robo taxes can scale beyond limited markets and that autonomous driving can become a meaningful profit generator. That's a much harder story to sell when investors want immediate results. And honestly, I think that's fair. Vision is incredibly important in investing, but execution matters even more. The market doesn't simply reward ambitious ideas forever. Eventually, companies have to deliver. Dan Ies also said something that really summarizes his entire investment philosophy. He believes we are still only in the third inning of the AI revolution. He's used this analogy many times before and it continues to be one of his strongest convictions. His argument is that investors keep behaving as though AI has already matured when in reality we're still at the very beginning. Think back to the early days of cloud computing. There were years of massive spending before the financial benefits became obvious. The same thing happened with smartphones. The same thing happened with the internet. The companies that invested aggressively during those early stages often became the biggest winners years later. Dan Ies believes AI follows the exact same pattern. Personally, I actually think this is one of the strongest points he made. Whenever a major technological revolution happens, investors almost always underestimate how long it takes for infrastructure to be built. Everyone wants immediate profits, but history usually doesn't work that way. The internet needed fiber optic networks. Cloud computing needed gigantic data centers. Streaming needed broadband expansion. Electric vehicles needed charging infrastructure. Artificial intelligence needs enormous computing infrastructure. None of those revolutions happened overnight. That brings us to another fascinating part of the interview. Dan Ies made an incredibly bold prediction regarding Tesla and SpaceX. He said he believes there's better than an 80% chance that SpaceX eventually acquires Tesla by the end of next year. That immediately caught everyone's attention because this would be one of the biggest corporate combinations in modern history. The hosts were clearly surprised by just how confident he sounded. Now whether that actually happens remains to be seen. Personally, I think that's one of those predictions that's exciting to think about, but investors probably shouldn't build their investment thesis around it. There are simply too many regulatory, legal, corporate governance, and shareholder questions that would need to be addressed before something of that magnitude could happen. Still, it's interesting because it reveals how Dan Ies increasingly views Elon Musk's companies as pieces of one much larger AI ecosystem rather than separate businesses. SpaceX dominates launch capabilities. Tesla develops autonomous transportation and robotics. XAI focuses on artificial intelligence. Neurolink works on brain computer interfaces. The Boring Company focuses on transportation infrastructure. Viewed separately, they each operate in different industries. Viewed together, they represent multiple pieces of a future driven by advanced artificial intelligence. Whether or not they ever formally combine, it's clear Dan Ies believes these businesses complement one another. Another point he emphasized was that Tesla's future is no longer about vehicle deliveries. That statement probably sounds controversial because for years every quarterly earnings report focused almost entirely on production numbers and deliveries. Now Dan Ies believes investors should instead focus on robo taxis expanding into additional cities. He wants to see autonomous driving continue improving. He wants to see Optimus robotics making progress. Those are the milestones he believes ultimately matter most. Again, I understand why investors remain skeptical. Autonomous driving has been promised for many years. Robo taxes have been discussed for years. Humanoid robots still face enormous engineering challenges. It's reasonable for investors to ask for more evidence before assigning trillions of dollars in future value. At the same time, if Tesla eventually succeeds, today's debates could look very different several years from now. Then the conversation shifted toward Alphabet and perhaps the biggest issue affecting every major technology company today, artificial intelligence spending. Alphabet announced even larger AI investments and the hosts asked an important question. What if these companies actually reduced their AI spending? Dan Ies didn't hesitate. He believes that would actually be viewed as a negative. That's a fascinating perspective because normally investors celebrate lower expenses and higher profitability. But AI has completely changed the rules. Dan Ies repeatedly described today's environment as an arms race. In other words, the biggest technology companies cannot afford to slow down simply because they want cleaner quarterly earnings. If one company slows investment while competitors continue building infrastructure, they risk permanently falling behind. And that's really the key word here. Permanent technology leadership often compounds. The companies with the best infrastructure attract the best developers. The best developers build the best products. The best products attract the most customers. The most customers generate the most data. The most data improves the AI models. Then the cycle repeats itself. Missing one generation of technological leadership can become incredibly expensive. That's why Dan Ies believes Alphabet, Microsoft, Amazon, Meta, and the other hyperscalers almost have no choice but to continue spending. He also made another statement that I think deserves attention. He said, "We're only about 15% through this AI buildout." That's an astonishing number when you really think about it. If he's right, then the overwhelming majority of AI infrastructure still hasn't been built. That would imply enormous future demand for chips, networking equipment, memory, data centers, electricity, cooling systems, software, cyber security, and enterprise AI applications. In other words, the investment cycle may still have years left to run. Now, whether 15% is the correct number isn't really the point. The larger idea is that we're still in the early phases rather than the final chapter. One of my favorite analogies from the interview was when Dan Ies compared today's AI investments to building Las Vegas in the 1950s. Before the casinos could generate billions of dollars, someone first had to build the hotels. Someone had to build the roads. Someone had to install the electricity. Someone had to create the entire infrastructure. Only after all of that existed did the city become what it is today. That's exactly how he views AI. Today's massive capital expenditures are essentially laying the foundation for future economic activity. I actually think that's a useful analogy because investors often forget that infrastructure spending almost always looks excessive in the beginning. It usually feels expensive before it feels necessary. Another important point he made was that enterprises are already lining up to adopt AI. That's significant because consumer AI gets most of the headlines. People talk about chat bots, image generation, and AI assistance, but the real money could ultimately come from businesses transforming how they operate. Companies are looking for ways to automate workflows, improve customer service, increase productivity, analyze massive amounts of data, reduce costs, accelerate software development. Those enterprise use cases could potentially create trillions of dollars in economic value over time. Dan Ies believes that demand is already becoming visible. That's why he expects Microsoft, Amazon, Alphabet, and other cloud providers to eventually justify today's spending. He also briefly mentioned Apple, suggesting that consumer AI is really only beginning. That is another interesting point because Apple has generally taken a slower approach compared to some competitors. Historically, Apple often enters markets later than everyone else. But when they finally commit, they usually focus on delivering a polished experience rather than being first. Whether Apple ultimately becomes an AI leader remains an open question, but Dan Ies clearly believes the consumer side of AI still has significant room for growth. Toward the end of the interview, the discussion shifted toward semiconductors and Intel. Even there, Dan Ies wasn't really focused on Intel itself. Instead, he kept returning to the same underlying theme, demand. That's the word he came back to over and over again. If enterprise demand continues accelerating, then demand for chips increases, demand for memory increases, demand for cloud infrastructure increases, demand for networking equipment increases, everything throughout the AI supply chain benefits. That's why he continues viewing AI as one giant ecosystem rather than isolated companies competing independently. Overall, I think this interview really reinforced Dan Ies's long-standing investment philosophy. He's willing to tolerate short-term volatility if he believes the long-term opportunity remains intact. He's willing to accept weaker quarterly reactions if the strategic direction still looks correct. That approach certainly isn't comfortable because it requires investors to endure periods where stocks can fall sharply even while management continues insisting the future has never looked brighter. But that's often what disruptive investing looks like. Whether you agree with Dan Ies or not, I think he made one point that's difficult to ignore. The market constantly swings between fear and optimism. One earnings report can erase hundreds of billions of dollars in market value overnight. Yet technological revolutions rarely unfold quarter by quarter. They unfold over years. If artificial intelligence truly becomes as transformational as many believe, today's spending may eventually be remembered as the necessary price of building the next generation of the digital economy. And that more than anything else is really the message Dan Ies wanted investors to understand. Now, let's dive in and look at the three top tech stocks that could benefit from one of the biggest technology investment cycles in history. The first stock I'm talking about is Taiwan Semiconductor Manufacturing, ticker symbol TSM. When people think about artificial intelligence, they often focus on software, chat bots, or the companies building AI models. But none of that exists without advanced semiconductors. Every major AI system depends on increasingly sophisticated chips that are smaller, faster, more power efficient, and capable of handling enormous computational workloads. That is exactly where Taiwan Semiconductor Manufacturing has built one of the strongest competitive advantages anywhere in technology. The company is not simply another semiconductor manufacturer. It is the world's leading pure play chip foundry, producing the advanced processors that power the AI revolution. Whether a company is designing processors for AI training, inference, cloud computing, or advanced consumer devices, there is a very good chance those chips are ultimately manufactured by Taiwan Semiconductor Manufacturing. That position gives the company an extraordinary moat. Building advanced semiconductor fabrication plants is one of the most difficult engineering challenges on Earth. It takes years to construct a single leading edge facility, billions upon billions of dollars in investment, and decades of manufacturing expertise that cannot easily be replicated. This creates incredibly high barriers to entry. Even if a competitor wanted to catch up tomorrow, they simply could not do it overnight. The expertise, manufacturing scale, customer relationships, and process technology have been built over decades. That is one of the biggest reasons I like this business so much. It occupies a position that very few companies can realistically challenge. Today, Taiwan semiconductor manufacturing controls roughly 73% of the global chip foundry market. Think about that for a second. Nearly 3/4 of the world's outsourced semiconductor manufacturing flows through one company. Whenever AI demand increases, that demand eventually finds its way back to Taiwan semiconductor manufacturing because someone has to physically manufacture those advanced processors. This is exactly why the company continues benefiting regardless of which AI products ultimately become winners. Instead of trying to predict which software platform dominates 10 years from now, Taiwan semiconductor manufacturing earns money by helping build the hardware that powers them all. That business model dramatically reduces uncertainty. Another reason investors continue paying close attention to Taiwan semiconductor manufacturing is its relentless innovation. Technology leadership in semiconductors never stands still. The company recently began shipping chips produced using its new 2nanometer manufacturing process. Now that may sound like just another technical milestone, but it represents a significant leap forward. These new chips offer higher transistor density, improved energy efficiency, and greater performance. As artificial intelligence workloads become increasingly demanding, every improvement in processing efficiency becomes valuable. Training large AI models consumes enormous computing power. Running AI inference across millions of users consumes even more. Reducing energy consumption while increasing computing performance becomes a major competitive advantage for customers. During the most recent quarter, the new 2nanometer process already contributed 3% of total company revenue. That may not sound like much today, but this technology is still in its early stages. Management expects two nanometer production to become one of its biggest long-term growth drivers as more customers transition toward the newest generation of advanced chips. That is exactly the kind of trend long-term investors should pay attention to. You are not simply investing in today's manufacturing capacity. You are investing in tomorrow's technology roadmap. Another development that caught my attention was the company's continued expansion inside the United States. Taiwan Semiconductor Manufacturing announced another $100 billion investment into its Arizona operations. When combined with previous commitments, the company has now pledged approximately $265 billion toward its Arizona facilities. That is an astonishing amount of capital. These investments include advanced fabrication plants, advanced packaging facilities, and expanded production capacity for the company's cuttingedge 2n nanometer technology. Management believes this investment strengthens the United States semiconductor supply chain while supporting future demand for advanced computing. Personally, I think this is a smart strategic move for several reasons. First, governments around the world increasingly recognize semiconductors as critical national infrastructure. Second, customers want greater geographic diversification within supply chains. And finally, AI demand continues expanding so rapidly that additional manufacturing capacity may become essential over the next decade. Of course, these projects require enormous upfront spending. Some investors naturally worry whenever companies announce massive capital expenditures. But in Taiwan semiconductor manufacturing's case, these investments are often necessary because demand keeps increasing. This actually ties into something Dan Ies discussed earlier. He described AI spending as an arms race. I think Taiwan semiconductor manufacturing perfectly illustrates that point. If demand for advanced AI chips continues accelerating, manufacturers cannot simply stand still. They have to build additional facilities years before demand fully arrives. Otherwise, supply shortages could become even more severe. Another reason I continue liking this company is the diversity of industries it serves. Artificial intelligence receives most of the attention today. But advanced semiconductors power far more than just AI. High performance computing, data centers, consumer electronics, industrial automation, advanced manufacturing, autonomous technologies, modern communications infrastructure. All of these long-term trends require increasingly advanced chips that creates multiple growth engines operating simultaneously. one slowdown in a particular segment does not necessarily derail the company's long-term growth story because demand comes from so many different industries. This creates resilience. I also think investors sometimes underestimate just how difficult semiconductor manufacturing actually is. People often assume designing a chip is the hard part. In reality, manufacturing billions of microscopic transistors with near-perfect precision at commercial scale is one of humanity's greatest engineering achievements. That manufacturing expertise cannot simply be copied. It must be developed over decades. That accumulated knowledge represents an enormous competitive advantage. As artificial intelligence continues evolving, chip complexity will likely increase even further. Each new generation requires greater precision, better yields, lower power consumption, and faster performance. That continuous innovation cycle works in favor of companies already operating at the technological frontier. From an investment perspective, what makes Taiwan semiconductor manufacturing especially attractive is that it benefits from broad AI adoption without forcing investors to predict individual software winners. Whether businesses adopt generative AI, whether enterprises deploy agentic AI, whether robotics expands, whether autonomous systems accelerate, whether cloud infrastructure grows. All of those trends eventually increase demand for advanced semiconductor manufacturing. That makes Taiwan Semiconductor Manufacturing one of the foundational businesses supporting the entire artificial intelligence ecosystem. Instead of betting on a single application, you're investing in one of the companies making the entire ecosystem possible. That is an incredibly powerful position to occupy. For long-term investors who want exposure to artificial intelligence while focusing on durable competitive advantages, Taiwan semiconductor manufacturing remains one of the strongest businesses to watch. its dominant market share, relentless innovation, expanding manufacturing footprint and leadership in advanced process technology position, the company to remain highly relevant as AI infrastructure continues expanding over the coming years. If this resonates with you, you're exactly who this channel is for. Please hit the like button, share the video, and leave your thoughts in the comments. Subscribe to the channel so you don't miss out on the next important financial investing update. Remember to do your own research before you invest in any stock. The second company on this list is one that many investors are only beginning to discover. Nebus Group, ticker symbol NBIS. Unlike the first company we discussed, Nebius is not manufacturing semiconductors. Instead, it is building something that could become just as valuable over the next decade, artificial intelligence computing infrastructure. That may not sound exciting at first, but think about what happens after the chips are manufactured. Those processors need to be installed inside massive AI data centers. They need networking, cooling systems, software, cloud infrastructure, GPU clusters, storage, fleet management, everything required to train and deploy modern artificial intelligence models at scale. That entire ecosystem requires enormous computing capacity and demand is growing faster than almost anyone expected. Nebius is positioning itself right in the middle of that opportunity. The company has transformed itself into an AI cloud infrastructure provider focused almost entirely on supporting AI workloads. That strategic decision could prove incredibly important because artificial intelligence is creating a completely different type of cloud computing demand compared to traditional enterprise software. Training advanced AI models requires thousands upon thousands of GPUs operating together. Running AI inference across millions of users requires even more computing resources. As businesses increasingly adopt AI, the need for dedicated AI cloud infrastructure continues expanding. Nibbius wants to become one of the companies supplying that infrastructure. One aspect of this story that immediately stands out is the company's strategic relationship. Nebius has become an important infrastructure partner in helping deploy next generation AI cloud capacity. This relationship extends far beyond simply purchasing hardware. The companies are collaborating on AI factory designs, inference infrastructure, Agentic AI technology stacks, infrastructure deployment, and fleet management. That tells me this is a much deeper partnership focused on building long-term AI infrastructure rather than simply completing hardware transactions. Perhaps the most eye-catching part of that relationship is the investment itself. Nibbius received a $2 billion investment to help accelerate its infrastructure expansion. That capital is intended to support deployment of more than 5 gawatts of AI computing capacity by the end of the decade. 5 gawatts is an enormous amount of computing infrastructure. To put that into perspective, we are talking about facilities capable of supporting some of the world's largest artificial intelligence workloads. And this is exactly why many investors are becoming increasingly interested in the company. Artificial intelligence demand has shifted from simply asking whether AI works to asking who can provide enough computing capacity to support global adoption. Infrastructure has become the bottleneck. The companies capable of solving that bottleneck may enjoy years of sustained demand. Another development that caught my attention was Nebia signing a massive infrastructure agreement worth 12 billion beginning in 2027. The agreement also includes up to an additional $15 billion in dedicated computing capacity if needed. Think about what that means from a business perspective. One of the biggest risks for rapidly expanding infrastructure companies is building too much capacity before customers arrive. That can create expensive underutilized assets. Nebus appears to have addressed that concern by securing long-term demand commitments that provide meaningful visibility into future revenue opportunities. Personally, I think this is one of the most underrated parts of the investment story. Building AI infrastructure requires enormous amounts of money. Having customers already lined up significantly reduces uncertainty. It gives management greater confidence when making large capital investment decisions. Speaking of investment, let's look at the financial numbers because they are astonishing. During the first quarter, Nibbius generated $400 million in revenue. That alone would be respectable for a company still scaling its business. But what really stands out is the growth rate. Revenue increased an incredible 684% compared to the same period a year earlier. Growth at that level naturally attracts investor attention. It tells us demand is arriving much faster than many expected. However, there is another number that is even more surprising. Nebas spent approximately $2.5 billion on capital expenditures during that same quarter. That is an enormous amount of investment for a company with a market value of roughly $53 billion. Most businesses simply cannot sustain spending at that pace. At first glance, some investors may even find that number alarming. After all, spending billions before generating equivalent revenue can look risky. But context matters. The overwhelming majority of those investments went toward acquiring GPUs and building AI infrastructure. In other words, management is not spending aggressively because business is weak. They are spending aggressively because they believe demand will continue accelerating. This goes back to Dan Ives's comments about the AI arms race. If AI infrastructure truly becomes one of the world's most valuable assets, waiting too long to build capacity could actually be the bigger mistake. Of course, investors should still monitor capital spending carefully. Infrastructure businesses can become capital intensive very quickly. Management must execute well to earn attractive returns on these investments. Fortunately, Nebius appears financially prepared for this expansion. During the same quarter, the company raised approximately $6.3 billion and ended with a cash position of about $9.3 billion. That strong balance sheet provides significant financial flexibility instead of constantly worrying about funding future expansion. Management can remain focused on building capacity while demand continues growing. That financial strength also provides an important competitive advantage. Artificial intelligence infrastructure is becoming one of the most capital intensive industries in the world. Not every company can raise billions of dollars to expand. Those that can may eventually widen the gap between themselves and smaller competitors. What I also like about Nibbius is that it benefits from several different AI trends simultaneously. As AI models become larger, companies require more computing capacity. As enterprise adoption accelerates, businesses require more inference infrastructure. As Agentic AI expands, computing demand increases again. Every major AI trend ultimately creates additional demand for cloud infrastructure. That means Nbius is not dependent on one single product becoming successful. Instead, it benefits from overall AI adoption across the industry. Now, I do think investors should recognize that Nbius is probably the highest risk company on today's list. Unlike mature technology leaders, this company is still in the rapid expansion phase. Its aggressive spending strategy means execution will be absolutely critical over the next several years. If management delivers, today's investments could generate enormous long-term value. If execution falls short, investors could experience significant volatility along the way. That is simply part of investing in earlier stage growth companies. Personally, I think Nimbius represents an interesting balance between opportunity and risk. It is certainly not the most predictable business on this list, but it may also have one of the highest long-term growth runways because AI infrastructure demand still appears to be in its early innings. If artificial intelligence continues expanding the way many analysts expect, companies capable of providing reliable AI cloud capacity could become increasingly valuable over time. That is exactly why Nibbius has earned a place among my top tech stocks to watch right now. This video is brought to you by Value Stocks Investing Master Course. If you're looking to grow your wealth by investing in solid, undervalued stocks, but not sure where to start, I created the Value Stocks Investing Master Course to teach you how to identify great companies, make smart investment decisions, and build a portfolio that lasts. Click the link in the description and pinned comments to get the course today, and take control of your financial future. The final stock on today's list is Micron Technology, ticker symbol MU. While most investors immediately think about processors whenever AI is discussed, processors alone cannot power modern artificial intelligence systems, AI models constantly move massive amounts of information while they're being trained and while they're serving millions of users around the world. That information has to be stored, accessed, and processed at incredible speeds. That is where memory becomes absolutely essential. Without enough high performance memory, even the fastest AI processors cannot operate at their full potential. That makes Micron one of the most important companies supporting the next generation of AI infrastructure. The company develops advanced memory and storage solutions used across data centers, enterprise computing, personal computers, mobile devices, automotive technology, and many other industries. Its business revolves around two critical technologies. The first is nan flash memory which stores information even after devices are powered off. The second is DE RAM which temporarily stores active data while computers are performing calculations. For artificial intelligence, DE RAM has become especially valuable because AI applications require enormous amounts of fast memory to process information efficiently. As AI models continue becoming larger and more sophisticated, demand for advanced DE RAM continues increasing. That is one of the biggest reasons Micron has experienced such extraordinary business momentum. The numbers speak for themselves. Micron has become one of the strongest performing companies in the market this year, delivering a remarkable gain of approximately 240% making it one of the top performers in the S&P 500. But impressive stock performance alone does not make a company a good long-term investment. What matters is whether the underlying business is actually improving. In Micron's case, the answer appears to be yes. The company's latest quarterly results were exceptional. Revenue reached approximately 41.45 billion during its fiscal third quarter ending in late May. That represented an extraordinary 345% increase compared to the same quarter a year earlier. Very few companies of Micron size are growing at that pace. Even more impressive was what happened to profitability. Net income increased roughly 1,400% to more than $28 billion. Earnings per share jumped dramatically from $1.68 to $2467. Those numbers demonstrate something very important. This is not simply a company benefiting from temporary excitement. Demand is translating into real financial performance. Personally, I think that distinction matters. During every major technology cycle, investors eventually separate companies generating headlines from companies generating actual earnings. Micron is showing meaningful financial improvement alongside rising AI demand that gives investors something tangible to evaluate beyond future expectations. Another reason I continue watching Micron closely is that memory demand tends to increase as computing workloads become more advanced. Every new generation of AI models requires larger data sets, more parameters, longer context windows, greater inference capacity. All of that requires more memory. In many ways, memory becomes one of the hidden engines powering artificial intelligence. It may not receive as much media attention as processors. But without high performance memory, the entire system slows down. That gives Micron an important role within the AI supply chain. Another interesting point is that despite Micron's incredible performance this year, the stock has experienced some recent weakness. Now, some investors immediately become nervous whenever a fast growing stock pulls back. I often view those moments a little differently. Temporary pullbacks sometimes provide opportunities to evaluate whether the underlying business has actually changed. In Micron's case, the recent decline appears to have been driven more by broader market sentiment than by deterioration in the company's business fundamentals. In fact, there may actually be another positive catalyst developing. Industry observers have pointed to encouraging signals coming from semiconductor equipment demand. Commercial lithography capacity is expected to expand significantly over the coming years. Why does that matter? Because increasing manufacturing capacity often reflects confidence that semiconductor demand will remain strong. If chip manufacturers are preparing for higher production volumes, that suggests continued demand throughout the broader semiconductor ecosystem. That includes memory. Of course, no investment is without risk. Memory has historically been one of the more cyclical areas of the semiconductor industry. Prices can fluctuate. Supply and demand can occasionally become unbalanced. Profit margins can expand rapidly during shortages and contract when supply catches up. That is simply part of the business. However, artificial intelligence may be changing that cycle. AI workloads require increasingly advanced memory technologies rather than simply larger quantities of standard memory that creates opportunities for companies capable of producing premium products that command higher margins. Micron has spent years investing in exactly those higher value technologies. Another reason I like this company is that its products reach far beyond artificial intelligence. Yes, AI is driving enormous growth today, but memory remains essential across nearly every major computing platform. Enterprise servers, consumer electronics, automotive technology, industrial automation, edge computing, cloud infrastructure. These long-term markets continue expanding as digital transformation accelerates around the world. That diversification provides additional resilience over time. As an investor, I also appreciate companies that occupy positions within technology ecosystems rather than relying on a single product. Micron does not need one application to succeed. It benefits whenever global demand for faster computing increases. That broad exposure creates multiple long-term growth opportunities. When you step back and compare all three companies we discussed today, an interesting pattern begins to emerge. Taiwan Semiconductor Manufacturing provides the advanced manufacturing that makes next generation AI chips possible. Nebius is building the cloud infrastructure required to deploy and operate those AI systems at scale. Micron supplies the high performance memory that keeps those systems running efficiently. Each company occupies a different layer of the artificial intelligence ecosystem. Rather than competing directly against one another, they complement one another. That is exactly why I think these three businesses make such an interesting combination for investors looking at the long-term AI opportunity. One company manufactures the foundation. One company builds the infrastructure. One company provides the memory that powers it all. If artificial intelligence continues expanding over the next decade the way many experts expect, every layer of that ecosystem could experience meaningful growth. Of course, no one knows exactly how the market will perform over the next 6 months or even the next year. Stock prices will continue moving higher and lower. Investor sentiment will continue changing. Quarterly earnings will create volatility. That is simply part of long-term investing. But when I evaluate companies, I try to focus less on daily market headlines and more on whether the business itself is becoming more valuable over time. All three companies we covered today appear to be strengthening their positions within industries that should remain highly relevant for many years. That does not guarantee investment success, but it does provide a solid foundation for further research. If you want exclusive stock tips, in-depth analysis, real-time trade alerts, and free investing guides, join the Stocks Galore Patreon today and take your investing game to the next level. Our members get full in-depth analysis on most of the stocks mentioned here. Head over to patreon.com/stocksgalore and become part of our growing community of smart investors. Link is in the description. Now, I'd love to hear from you. Which of these three businesses do you believe has the strongest long-term competitive advantage? Taiwan Semiconductor Manufacturing, Nibbius Group, or Micron Technology. Let me know your thoughts and your reasoning in the comments below. 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