Dan Ives: "The Biggest AI Money Hasn't Been Made Yet" (Top 2 AI Stocks to Buy Now)

Dan Ies believes the biggest money in artificial intelligence has not been made yet. In a recent CNBC interview, the Yorkville Ives and company partner and senior managing director shared why he thinks the AI revolution is still in its early stages, what it means for companies like Alphabet, and why AI infrastructure could create massive investment opportunities over the coming years. First, I'll play Dan Ives'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 two AI stocks to buy right now. Let's hear what Dan Ies has to say. >> For more, let's bring in Yorkville Ives partner Dan Ives and CBC contributor requisites Bin Talkington. Thank you both so much for being here. Um Dan, you think Alphabet is actually the best positioned of the hyperscalers and today is about proving it. Why do you think it's the best position and and what do you think it needs to do to actually prove it? I think it sets the tone for this tech earning season because when you think about what's happened on cloud call it mid60% growth this has really been a turnaround for the ages that you've seen alpha go back to a year ago I think it's showing that you're you're seeing the growth you're seeing the enterprise really start to go after the AI modernization and then of course what they've done on surge what they've really done across the board when it comes to Gemini despite the fact that it was delayed look a year ago New York City cab driver was bearish on Alphabet and I think now really for them it's showing that the capbacks and McKenzie talked about it likely over 300 billion next year that that's something that's now showing more and more monetization. It sets the tone for Microsoft for Amazon for ultimately down the road for for Meta and others in terms of what's happening going from this capex piece to modernization. >> Yeah, the cab driver may have been bearish but then Bergkshire Hathaway wasn't. So maybe that changed the game for them. Um, Bren, how are you thinking about the market appetite for raising capbacks in tonight's report if that happens in light of what we've seen so far with ROI? >> It seems like my bet is that Google is going to raise again. I mean, they're going to do what 117 billion in revenues. So, that's going to be a really strong number. And to kind of hit on, you know, um Dan's Dan's bullishness on Google, if you think about their vertical integration, I mean, from the AI side from the chips to YouTube, which is going to be they're going to be monetizing that advertising. So, well, I think uh GCP, the Google Cloud is going to continue to advance. I think probably 25% is the estimate of growth. And so, I think as AI accelerates, I think we're going to see the cloud business accelerate as well. And so really you have all of that. And so I think the market so far has been very willing to say you can spend. The stock's up about 10%. McKenzie said earlier obviously it's about 13% off off that almost 400 high. But I think the numbers will be strong. The market will allow them for capex just because they do have monetization not only with the chips but I do think the you know YouTube search Gemini etc in the cloud business which is growing very fast helps from the monetization. They're monetizing their current balance sheet very very well. >> Yeah. Cloud I think estimates are what mid60s in terms of percentage growth. Whisper number even higher than that. I mean is the bar too high that those are huge numbers. They're huge numbers, but I think when it comes down to probably the most important thing in this whole earning season, it's the hyperscalers what they show from a cloud growth perspective because that is at the end of that is showing the enterprise use cases even though there's capacity constraint in terms of what they're doing and what Curran's done there on Google Cloud. I think that continues to really almost be a poster child for what others want to do and that's what the street is so focused on. As Brenn talked about, this all comes down to capbacks, monetization, and I think it really starts tonight to really set the tone for what's going to be, I I continue to believe, very strong tech earning season. >> The interview actually begins with Dan Ies talking about his new chapter in his career. After spending more than 25 years on Wall Street as one of the most recognized technology analysts, he is now joining Yorkville Ives where he describes the firm as a modern merchant bank focused on AI, technology, infrastructure, and energy. That immediately tells you something important about how he sees the future. He is not simply analyzing technology anymore. He wants to build businesses around it. That is a major difference. When someone who has spent decades researching companies decides to move closer to building and financing companies in these industries, it usually signals a very high level of conviction about where the market is heading. He describes today's environment as the fourth industrial revolution. That phrase has been used frequently over the last several years, but hearing Dan Ies use it again reinforces just how transformational he believes artificial intelligence will become. Personally, I think that comparison is actually appropriate. When we look back throughout history, there have only been a handful of technological revolutions that completely reshaped economies. Electricity changed everything. The internet changed everything. Smartphones completely altered how we communicate and consume information. AI feels like it belongs in that same category because it has the potential to affect nearly every industry rather than just one specific sector. The conversation then quickly shifts toward one of the biggest concerns investors have today, and that is China. Recent developments coming out of China have raised questions about whether American companies are spending too much money on AI infrastructure while Chinese firms continue producing increasingly capable AI models at what appears to be a lower cost. Dan Ies calls this another white knuckle moment. I actually like that description because markets have experienced these kinds of moments several times already during the AI boom. Every few months, something happens that causes investors to panic. A new AI model gets released. A Chinese company announces a breakthrough. Someone claims AI costs are collapsing. Investors suddenly begin questioning whether hundreds of billions of dollars in spending are justified. Technology stocks sell off. Then, after a few weeks, investors usually remember why the spending was happening in the first place. Dan compares this to the earlier Deep Seek scare, suggesting that while headlines create temporary panic, they do not necessarily change the long-term investment thesis. His core argument is actually very simple. He believes people are focusing far too much on the AI models themselves. Instead, he says the real opportunity lies in everything surrounding those models. He expects the world to have 10 times more AI models over the next 5 to seven years. Some will be industry specific, some will be country specific, some will be specialized for healthare, others will be built for finance, manufacturing, education, robotics, and every other industry imaginable. If that happens, then AI models themselves gradually become less unique. In other words, they become commodities. That is an important distinction because commodities rarely generate the largest long-term profits. Think about electricity. generating electricity became important, but many of the companies that created the biggest fortunes were those that built businesses powered by electricity rather than electricity itself. Dan argues that AI models may eventually follow a similar path. He specifically mentions OpenAI, Anthropic, and Google's Gemini. These companies are competing aggressively today, but he believes competition among models will continue increasing as more players enter the market. That naturally leads into his biggest point. He says the real spending is not happening on the models. It is happening on the data. It is happening inside data centers. It is happening through massive capital expenditures. It is happening through AI infrastructure. And ultimately, it will happen through what he calls physical AI. This is probably the single biggest takeaway from the interview. When most people hear artificial intelligence, they immediately think about chat GPT or Gemini answering questions. Dan Ies is thinking much further ahead. He is imagining AI powering autonomous factories, autonomous robots, self-driving systems, healthcare automation, industrial automation, smart manufacturing, smart cities, entire physical industries enhanced by artificial intelligence that requires an enormous amount of infrastructure, servers, networking equipment, advanced semiconductors, power generation, electric grids, cooling systems, storage, fiber, cloud infrastructure. The AI chatbot you interact with every day is really just the visible layer sitting on top of an incredibly massive technological foundation. And honestly, I completely agree with that way of thinking. Sometimes investors become obsessed with whichever AI chatbot has the best benchmark score this month. Meanwhile, companies supplying the picks and shovels are quietly generating billions of dollars in revenue regardless of which model wins. History has shown us that infrastructure providers often become some of the biggest beneficiaries during technological revolutions. The interview then moves into another important question. If infrastructure spending continues growing, where will investors ultimately make the most money? Will it be infrastructure or will it be applications? Dan answers that he believes the application infrastructure layer becomes the heart and lungs of the AI revolution. He gives a really useful analogy. Imagine building a massive automobile factory. Constructing the factory alone does not create value. Eventually, you need production lines, workers, operations, products moving through the system. AI infrastructure works the same way. Building data centers is only the beginning. Eventually, companies need software, enterprise applications, industry solutions, business workflows, customer service automation, healthcare tools, financial software, productivity platforms. All of those become revenue generating businesses sitting on top of AI infrastructure. That is where he believes significant value creation will happen. I actually think this is where many investors should pay close attention. For the past couple of years, almost everyone's attention has been focused on chipmakers. That makes sense because GPUs became the bottleneck of AI, but eventually the market broadens. History suggests technological revolutions rarely reward only one category of companies. The internet did not only create winners in networking hardware. It created software giants, e-commerce leaders, streaming companies, cloud businesses, digital advertising platforms, cyber security companies, payments companies, entire industries emerged because the infrastructure already existed. AI could easily follow the same path. The interviewer then asks an interesting question. Could the application layer eventually become commoditized as well? Dan says he is becoming less worried about that possibility. The reason is because more businesses are deploying AI into real world operations. As adoption grows, different companies will build unique solutions that create competitive advantages. Some companies will absolutely fail, others will dominate. That is exactly how every technological cycle unfolds. Personally, I think investors should remember that point. Not every AI company automatically becomes a winner. Some businesses will spend billions chasing AI and never generate meaningful returns. Others will execute exceptionally well and become industry leaders. Separating those two groups will probably become one of the biggest investing challenges over the next decade. One of Dan Ives's most famous statements makes another appearance during this interview. He says, "We are still only in the third inning of the AI revolution. That is significant because earlier he often described the industry as being in the second inning. Now he believes progress has advanced slightly further. But even calling it the third inning still implies the majority of this transformation remains ahead. If baseball has nine innings, then according to Dan Ies, we have not even reached halftime. That is an incredibly bullish message. He believes today's excitement represents the beginning rather than the end. He also connects this to physical AI. Again, this reinforces the idea that today's chatbot race is just one phase. The larger opportunity arrives when AI begins interacting directly with the physical world. Factories, robots, vehicles, industrial systems, healthcare devices, warehouses, infrastructure. Those markets are significantly larger than simply generating text responses on a computer screen. He also brings Apple into the discussion. According to Dan, Apple is helping launch the consumer AI revolution. He refers to Apple as becoming a toll booth on the AI highway. That is actually a clever analogy. Apple owns one of the largest consumer ecosystems on Earth. If AI becomes deeply integrated into hundreds of millions or even billions of devices, Apple potentially collects value every step of the way through its ecosystem. Whether Apple ends up leading AI innovation itself almost becomes a secondary question. Owning the customer relationship is incredibly valuable. The interviewer then asks about Alphabet and Gemini. There has been a lot of criticism over the past couple of years suggesting Google fell behind OpenAI. Dan admits Alphabet did trail initially. However, he believes Google has narrowed the gap much faster than many investors expected. That is something worth remembering. Markets often overreact during periods of disruption. When Chat GPT first exploded onto the scene, many investors assumed Google's dominance in search was ending almost immediately. Today, the conversation looks very different. Google still possesses enormous advantages. Its cloud business continues growing. Gemini continues improving. Search remains incredibly powerful. The company has one of the deepest AI research organizations in the world. Dan seems to believe investors underestimated Google's ability to respond. Personally, I think this highlights one of the biggest mistakes investors can make during technological transitions. People often assume incumbents cannot adapt. Sometimes they cannot, but sometimes they absolutely can. Companies with massive engineering talent, enormous cash flows, and billions of users should never be counted out too quickly. That does not guarantee Alphabet wins, but it certainly means the competitive landscape remains much more balanced than many predicted a year or two ago. Toward the end of the interview, the conversation becomes much lighter. Dan jokes about New York City taxi drivers. Years ago, he used them as a humorous market sentiment indicator. If taxi drivers became extremely bullish on a stock, it often suggested retail excitement had reached extraordinary levels. This time, however, the interviewer pushes back. He jokes that New York City cab drivers have actually become surprisingly good investors over the years. Dan laughs and says many of them are probably driving Bentleys now because of how well technology stocks have performed. It is obviously meant as humor, but there is an interesting investing lesson hidden inside the joke. Sometimes conventional wisdom tells us retail investors always arrive late. That is not always true. Tesla is actually a great example. Many professional investors spent years dismissing the stock because traditional valuation metrics looked extreme. Meanwhile, countless individual investors simply believed in the company's long-term vision and were rewarded with enormous gains. That does not mean every popular stock deserves a premium valuation. Far from it. But it does remind us that markets are driven by future expectations, not just today's financial statements. Overall, I think Dan Ies delivered a message that was remarkably consistent with everything he has been saying over the past several years. His conviction has not changed. He still believes AI spending remains justified. He still believes infrastructure will become one of the biggest investment opportunities. He still believes enterprise AI adoption is only beginning. He still believes physical AI represents the next major phase. And perhaps most importantly, he still believes investors are much earlier in this transformation than many people appreciate. Now, whether every one of those predictions proves correct remains to be seen. Markets never move in straight lines. There will almost certainly be corrections. There will be disappointments. Some AI companies will fail. Some technologies will never live up to expectations. Competition from China will continue increasing. Costs will continue changing. Regulation will evolve. Those risks are real. But if Dan Ies is even partially right about AI becoming the defining technological revolution of this generation, then today's volatility may eventually look like nothing more than temporary noise during the early chapters of a much bigger story. For me, the biggest lesson from this interview is that investors should avoid getting distracted by every headline about which chatbot is slightly better this week. The companies creating lasting value may ultimately be the ones building the infrastructure, powering enterprise adoption, and enabling AI to move beyond software into the physical economy. If that happens, then we really may still be only in the third inning of one of the biggest technological investment cycles we have ever witnessed. Now, let's dive in and break down the two AI stocks that could reward patient investors over the next decade. Let's begin with the first company. Palunteer Technologies, ticker symbol PLTR, has become one of the most fascinating AI companies in the market today. What makes Palunteer so interesting is that it isn't trying to build the next chatbot or compete for consumer attention. Instead, it has built something far more valuable. It has created an operating system that allows governments and businesses to organize massive amounts of data, make faster decisions, and increasingly deploy artificial intelligence across their entire organizations. That may not sound exciting at first, but think about it this way. Artificial intelligence is only as useful as the data feeding it. If a company has information scattered across dozens of disconnected databases, spreadsheets, cloud services, and internal systems, even the most advanced AI model will struggle to deliver meaningful insights. Palunteer solves that problem. Its software connects fragmented data into one unified platform, allowing organizations to ask complex questions, automate workflows, and make decisions in real time that creates a very powerful competitive advantage. Once an organization integrates its operations into Palunteer's ecosystem, replacing it becomes extremely difficult. The software becomes deeply embedded in daily operations, creating high switching costs and long-asting customer relationships. I believe this is one of the reasons investors continue paying close attention to the company despite its premium valuation. The market often rewards businesses that become missionritical. When your software helps governments protect national security or enables large corporations to make billiondoll decisions faster and more accurately, customers are much less likely to cancel their contracts. That creates recurring revenue, pricing power, and long-term growth opportunities. What's particularly impressive is that Palunteer is no longer just a government contractor. Over the past few years, the commercial side of the business has accelerated dramatically. Its artificial intelligence platform has allowed companies to integrate large language models directly into their operations while maintaining security, governance, and control over sensitive information. That combination has become increasingly attractive as businesses move beyond experimenting with AI and begin deploying it across real world operations. The financial results clearly reflect this momentum. During the first quarter of fiscal 2026, Palanteer generated revenue of approximately 1.63 billion, representing an extraordinary 84.7% increase compared to the same period last year. Even more impressive was the strength of its United States commercial business, where revenue surged 133% to $595 million. Adjusted earnings per share came in at 33 cents, comfortably ahead of Wall Street expectations of 28. Those are not the numbers of a company experiencing slowing demand. Those are the numbers of a company benefiting from a massive shift in enterprise spending toward artificial intelligence. Management clearly sees that momentum continuing. Following those results, the company raised its fiscal 2026 revenue guidance to between 7.65 billion and $7.66 $66 billion. Whenever management raises guidance while already delivering exceptional growth, investors usually pay attention because it signals confidence that demand remains strong. CEO Alex Karp highlighted just how unusual the company's performance has become. He pointed to Palunteer's rule of 40 score reaching an astonishing 145% while emphasizing that the company achieved its highest year-over-year growth rate in history. For anyone unfamiliar with the rule of 40, it combines revenue growth with profit margins to measure the overall health of a software company. Generally speaking, anything above 40% is considered excellent. Palunteer reaching 145% is remarkable and demonstrates that the company is balancing rapid expansion with improving profitability. One development that also caught investors attention recently was Palanteer's sovereign AI partnership announced earlier this month. Governments around the world are increasingly viewing artificial intelligence as a matter of national competitiveness and security. Instead of relying entirely on foreign AI infrastructure, many countries want their own secure AI capabilities built around domestic regulations and protected data. That trend could create another long runway for Palunteer's government business over the coming years. Analysts have also begun recognizing the improving outlook. A recent upgrade from DAD Davidson included a buy rating and a price target of $175. While overall analyst consensus sits around $183 with roughly 63% of analysts maintaining bullish ratings. Now while all of this sounds extremely positive, I think it's important to discuss the biggest concern surrounding Palanteer valuation. Even after the stock has declined roughly 20% this year, Palanteer still trades at approximately 89 times forward earnings. That is not cheap by any traditional valuation measure. In fact, it means investors are already pricing in years of exceptional growth. When expectations become that high, the company has very little room for disappointment. One weaker earnings report, one slowdown in commercial growth, one guidance reduction. Any of those could create meaningful volatility in the share price. That doesn't necessarily mean the business is weak. It simply means expectations have become extremely demanding. Personally, I always remind myself that a great company and a great stock are not always the same thing at every point in time. A wonderful business purchased at an unrealistic valuation can still produce disappointing investment returns over shorter periods. Fortunately for long-term investors, Palunteer's recent pullback has started bringing valuation back toward more reasonable levels compared to where the stock traded earlier. Another issue investors continue monitoring is stockbased compensation. During the first quarter, Palanteer reported approximately $21.6 million in stock-based compensation. While this helps attract talented employees, issuing additional shares over time can dilute existing shareholders, that remains something investors should continue watching in future earnings reports. Even with those concerns, I believe the overall investment case remains compelling. Artificial intelligence is moving from experimentation toward full deployment inside enterprises. That transition plays directly into Palunteer's strengths. The company already possesses trusted relationships, proven software, and an expanding AI platform designed specifically for organizations handling complex and sensitive data. What excites me most is that Palunteer isn't simply selling software. It is becoming deeply integrated into how organizations operate. When software becomes essential to everyday decision-making, customer relationships often strengthen over time rather than weaken. That creates a durable competitive moat that can be very difficult for competitors to overcome. Looking ahead, investors should pay particularly close attention to the upcoming quarterly earnings report. One number I'll be watching carefully is United States commercial revenue. Management has already raised guidance. So continued acceleration in this segment would reinforce the idea that enterprise AI adoption remains very strong. If commercial growth continues expanding anywhere near its current pace, it would strengthen the long-term bullcase considerably. On the other hand, if that momentum begins slowing meaningfully, investors may start questioning whether today's premium valuation remains justified. Either way, the next earnings report could become an important catalyst for the stock. Overall, I think Palunteer represents one of the most unique opportunities in artificial intelligence today. It sits at the intersection of enterprise software, national security, and AI deployment. Its revenue growth is accelerating, customer demand continues expanding, management is raising guidance, and the company appears well positioned to benefit from one of the largest technology transformations of our generation. The biggest question isn't whether Palunteer has built an impressive business. The real question is whether it can continue executing well enough to justify the premium investors are still willing to pay. 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. Now, let's move on to the second company on the list. Astera Labs, ticker symbol ALAB, is probably the least recognized name in this video, but that may actually be one of the biggest reasons investors should pay attention to it. Whenever a new technology revolution begins, most investors naturally focus on the biggest household names. During the internet boom, everyone talked about websites. During the smartphone revolution, everyone talked about phones. And today during the AI boom, almost every conversation revolves around chat bots, AI models, and graphics processors. But there is an entire ecosystem sitting underneath those headlines. Artificial intelligence is no longer just about building faster chips. As AI systems become larger and more complex, companies also need technology that allows thousands of processors to communicate with one another at incredibly high speeds without creating bottlenecks. That is exactly where Asterolabs comes in. Its business focuses on what many people call the connectivity fabric of AI infrastructure. Think of an AI server rack as a massive team working together on one project. Every processor inside that rack has to constantly exchange enormous amounts of information with every other processor. If those connections become slow or inefficient, then even the most powerful chips cannot perform at their full potential. In other words, the processors are only as effective as the system connecting them. That is why I think Astera Labs occupies one of the most important positions within the AI infrastructure stack. Instead of competing directly in areas that already receive enormous investor attention, the company has carved out a niche that becomes increasingly valuable as AI clusters continue growing in size. Every new generation of AI models requires more computing power. More computing power requires larger server clusters. Larger server clusters require faster connectivity. and faster connectivity is exactly what Astera Labab specializes in that creates a very attractive long-term growth story. The company operates as a fab semiconductor business, meaning it designs advanced connectivity solutions while relying on manufacturing partners to produce the chips that allows management to focus on innovation without carrying the enormous capital costs associated with owning fabrication plants. As AI infrastructure spending accelerates worldwide, AsteroLabs has been benefiting directly from that demand. The numbers tell an impressive story. During the first quarter of fiscal 2026, the company generated revenue of approximately $38.4 million, representing year-over-year growth of 93.4%. That kind of growth is exceptional, especially for a company that already operates at this scale. Even more encouraging, non-GAAP earnings per share reached 61 cents, comfortably exceeding analyst expectations of 54. Operating income surged an incredible $448% year-over-year to $61.8 million. Those results demonstrate something very important. Revenue growth is not coming at the expense of profitability. The business is becoming increasingly efficient as demand continues expanding. Whenever I see both revenue and operating income accelerating together, it usually tells me that a company is executing extremely well. Another major catalyst arrived earlier this year when Aira Labs officially joined the NASDAQ 100 index. That may sound like a small administrative change, but it actually matters quite a bit. Many index funds and institutional investors automatically purchase shares of companies added to major indexes. that creates additional demand for the stock while also increasing visibility among professional investors who may not have previously followed the company. Inclusion in the NASDAQ 100 effectively introduces Aster Labs to an entirely new group of long-term shareholders. The second major catalyst came with the introduction of the company's Scorpio X series 320 lane smart fabric switch. This product targets what management believes could become a 20 billion merchant scaleup market by the year 2030. That is an enormous opportunity. As AI infrastructure becomes increasingly sophisticated, companies need solutions capable of managing communication across thousands of interconnected processors. Products like Scorpio are designed specifically to solve that challenge. Chief Executive Officer Jatendra Mohan attributed the company's outstanding performance to robust demand for its PCIe6 portfolio. That statement reinforces the broader theme we continue hearing across the AI industry. Demand is not slowing. Instead, customers are investing heavily in next generation infrastructure designed to support increasingly powerful AI workloads. The market has certainly rewarded that execution. Over the past year, Astera Lab shares have climbed roughly 154%. That is a remarkable move. Normally, when investors see gains like that, the first question becomes whether all of the good news has already been priced into the stock. That is a fair concern. Several Wall Street analysts clearly believe there is still room for additional upside. Bank of America significantly increased its price target from $240 to $450. Stifel Nicolaus also raised its target from $260 to $460. Those are substantial revisions upward reflecting improving confidence in the company's long-term outlook. Personally, I think one of the biggest reasons Astera Labs remains attractive is because it offers something investors often struggle to find. It provides pure exposure to one specific part of AI infrastructure. Many larger technology companies participate in dozens of different markets simultaneously. Aster is almost entirely focused on solving one critical problem within AI data centers. Sometimes those focused businesses become major winners because they establish leadership in one highly specialized area. However, no investment is without risk and Astera Lab certainly has several investors should understand. The first is valuation. The company currently trades at a trailing price to earnings ratio approaching 296. That is an extraordinarily rich valuation. Whenever a stock reaches those levels, expectations become incredibly high. Investors are essentially assuming exceptional growth continues for many years. If growth slows even modestly, valuation multiples can contract very quickly. Another consideration is volatility. Astera Labs currently carries a beta of approximately 3.67. For investors unfamiliar with beta, that means the stock tends to move much more aggressively than the broader market. When markets are rising, that can create tremendous upside. But during corrections, those same stocks often experience much steeper declines. This is probably not the kind of investment suitable for someone who becomes uncomfortable every time the market experiences volatility. The company has also indicated that second quarter gross margins could moderate toward approximately 73%. While that remains a very healthy margin, investors will want to monitor whether this represents a temporary adjustment associated with product launches or the beginning of a longer trend. Margin compression can sometimes signal increasing competition or changing product mix. So, it deserves attention during upcoming earnings reports. One other topic that has generated discussion involves insider selling. Over the past three months, insiders sold approximately $460 million worth of stock. At first glance, that number may sound alarming, but context matters. Most of those transactions occurred under pre-arranged rule 10b51 trading plans. These plans allow executives to schedule stock sales well in advance, helping avoid concerns about trading based on material non-public information. In other words, insider selling does not automatically mean management has lost confidence in the business. Executives sell shares for many reasons, including diversification, taxes, estate planning, and personal financial decisions. That said, I still believe investors should always pay attention to insider activity. While it should never be viewed in isolation, it becomes one additional piece of information worth monitoring alongside earnings, guidance, customer demand, and product adoption. Looking ahead, one milestone stands above everything else. The market will be watching the roll out of Scorpio X volume shipments very closely. If management demonstrates strong customer adoption while maintaining gross margins above the guided 73% floor, investors will likely view that as confirmation that the next phase of growth remains firmly on track. That could become another meaningful catalyst over the coming quarters. When I step back and look at Astera Labs as a whole, what stands out most is its position within the AI ecosystem, this company is not trying to become the face of artificial intelligence. Instead, it is quietly building technology that allows the entire AI infrastructure to function more efficiently. Sometimes the businesses operating behind the scenes become some of the biggest long-term winners because demand continues growing regardless of which AI applications ultimately dominate the market. As AI clusters become larger, faster, and more complex, efficient connectivity becomes increasingly valuable. That is exactly the trend Aster Labs is positioned to benefit from. For investors seeking exposure beyond the obvious AI names, this is certainly one company worth watching closely over the next several years. 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. When I compare these two companies we've discussed today, something interesting stands out. None of them are trying to become the next consumer AI chatbot. Instead, each company operates one layer deeper inside the AI ecosystem. Palunteer focuses on organizing enterprise and government data so artificial intelligence can generate meaningful insights. Asterira Labs builds the connectivity technology allowing AI infrastructure to operate efficiently at enormous scale. To me, that is exactly why these businesses deserve attention. 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. Do not forget to like the video, share your thoughts in the comments, and subscribe so you do not miss the next important investing update. Thanks for watching and I will see you in the next