AI Stocks Are Falling. Dan Ives Says It's Just Getting Started.

This is still early in terms of where AI has had. He's the biggest expert in tech for nearly a decade. Technology always gets ahead of regulation. And today, we are going to dive into absolutely all things AI. We're still less than 15% through the amount of spending that's going to happen in terms of AI. Whether you're interested in the up and coming stocks, who could be the next crouch right, the next pound here? Or what to do with some of the mag seven? I believe there's over 80% chance Tesla and SpaceX merged by the M220 summit. Dan Ives will cover it all for us today. You're going to have a lot of winners and a lot of losers. We have a very special edition of Market Beats today. We are partnering with Matt Weinstein from Top Stocks. So glad to be with you here today with our incredible guest, Dan Ives. We are going to cover so much ground today. I think we will talk about dozens of stocks in the AI field, for sure. But I think the most important place to start with Dan today is where is AI right now? Where are we at in that AI grow story? Is the bull run over or is it just starting? Look, our view is like this AI party started about 9.30 p.m. It's now about 11.30 p.m. If you look, more companies are getting led into the club. It's not just Nvidia and Jens on their AMD pound here, Snowflake. And we think like this party goes about 4 a.m. The bears, they'll continue to watch this party through the glass windows. They'll go up to their hotel room, read a book. The bulls and the bears meet up at 6 a.m. Bulls how out, bear night and the bears. Yeah, like you said, there's still a line out the door. There's new companies coming in. There's new companies trying to find out what their role in this party is and it's going to go on for a long time. And I think that's how I think investors continue to underestimate the scaling scope of the AI revolution. I think, look, we're going to continue to have sort of white knuckle moments whether it's macro, geopolitical, circular financing, catbacks, whatever it may be. But I mean, it's just my view like this is so still early in terms of where AI has had. Well, we talk about the party analogy again. We're still early. We're at that 1130 time frame. But it feels like the parents have come in and said, hey, it's too loud. Let's turn down the music a little bit. So let's talk about that safety parts a little bit. And what we're starting to hear about potential regulation. Are we getting too fast of tech development here? And if you think that that could slow down what's happening with AI? There's a technology always gets ahead of regulation. Now, there will be guard rails put in self-regulation, which is essentially what I believe is sort of happening right now. But look, you don't want government officials that are still using flip phones and blackberries dictating innovation in this country. And for the first time in 30 years, the US has had a China when it comes to tech. Now, in terms like the safety issue with Dario and you know why the sort of buzz that we've seen since then. Look, I just think if we slow down China wins, China is not slowing down. And I think that is part of what's happened right now is that it's getting the industry on the same page. Because like Jensen and Dela, they have, I think, much more wevel-headed views in terms of where this is heading. If they do have a pause, like if you knew they were going to collaborate and say, okay, we have to slow things down. Would that be, you think negative for most of these AI stocks in the short term? Like, would that cause a dip or in another view that would allow them to reduce their spending, their spending more against each other? And they could actually save some money from a model builder perspective. >> Yeah, and I think investors are not focused. Investors are focused on who's going to build the best models? Who's going to build ultimately the best use cases? But I would argue that if they slow down, that's why meta will accelerate. And I could argue that's why meta stock is done when it has since that came out. Because it also, you can slow down and then all of a sudden you're like, okay, wait, we're at the top of the top four. Now we're going to pull the elevator and stop it or we're going to pull the ladder up. While others are, so there's almost like a regulatory capture that's going on too. So I think it's very important to understand like some of the game of poker that's going on too. >> Yeah, I want to talk about whether this could also be an opportunity. So we talked about is this a risk, could it hurt the market in some way? But could there be an opportunity here if we do lean into safety a little bit? I mean, Jensen just came out saying, hey, we're going to have our own version of safety. Is there a growth opportunity in the AI story for more companies to lean into safety? >> Well, we'll get cyber security. I mean, cyber security stocks have had a huge run. But like that's a good example in terms of like safety. Look, you need safety in there. Guard rails need to get put in. But I'm not taking the view like mankind's at risk and if you tell me an anthropic engineer that was there less than six weeks, you should have to six weeks. You don't even know where the cappuccino maker is. If he and six weeks was able to see that then, you know, I'm playing the NBA. So the point is, I'm just trying to explain like there's political narratives going on. There's a lot of, so you just have to be careful sometimes in terms of some like the narratives and what it actually means. >> One other stack and the opportunity I wanted to talk about with the AI safety story, you are known for being a volunteer bull. I know a lot of our viewers absolutely love volunteer. We could talk this whole time about that. But I wondered if this AI safety discussion is kind of a boost for volunteer and what they're talking about with, you know, protecting your information. Make sure that your AI is secure. That sort of thing. That sovereign AI factor for volunteer. Is this an opportunity for that company? >> Because it's sovereign AI and that's what carbon volunteer talk about. It's like, it's not necessarily just giving your data to the model players. So I would argue like that's also why like Carp, Jensen and Vity have done the same thing in terms like sovereign AI. I think it's very important because you can't just look at some of the things that are going on and be like, "Oh, it's so negative for the set." Because look, now like someone's loss will be someone's gain. And also companies are getting smarter about what's happening. Speaking of handing over your data, Meta's muse is the big hit of the last few weeks. And you know, people are signing up for it. Some people say you have to give it a lot of access. But what does having an AI assistant do for Meta's business? Right? How can they leverage that? Why is that important to them? >> Look, they have three and a half billion users. So if you monetize 10 percent of them, 15 percent through ultimately AI or advertising or other sort of cross, you know, cross sort of selling revenues, think about what that's going to do to the business model. I'd say muse is sort of definitely going to game changer relative to what we've seen play out because I think also there was a view in Meta like they're spending all this money, you're not seeing it. But it keeps coming down to like install basis, Apple install base, like you could go to Dell install it, Cisco install, the hyperscalers install it. So I think it's just very important to like understand that the opportunities that could be there, a lot of it, you could be wait but within install base, that's the ability to monetize. >> And so prior generations of technology have always been cheaper, right? It's a cheaper way to do things, AI is an expensive project to undertake, in most cases. So when you have this install base and you have these free cash flows, that's why it's such an advantage for these large incumbents. Even the building at the data centers, GPU capacity, but also remember it's like if you go back to like TVs, like a few years or whatever, five years, a TV, you go to CES or whatever that thing would cost like $45,000, okay? Then all of a sudden you forget about three months later, it costs $3,500, six months later, I'm just saying like tokenization, the cost will come down. On this initial build out, it's super expensive, but it's just important to understand, like it's a life cycle of a technology. >> I think so many investors though, because of that cost, are so afraid that this is ever going to really pay off and that's speaking to the bears a little bit who are saying that these companies, even though the hyperscalers who already have plenty of money in the bank, they're still worried about how much spend is happening, how long of a runway do you think it is before that spend really pays off before it does start your costs less? >> Yeah, it's a great point, but also I think in this last quarter, you started to see the monetization from the hyperscalers. You saw a monetization, Microsoft, Google, Amazon. So then that's like an important inflection point that we're starting to see. Look, it's a bouncing eye because the problem is that if these companies, what say come is like we're going to spend less on catbacks, and free cash will is going to be 30% above where the street thought it would be. Stocks down, in my opinion. Because in those arms race, it goes back to like, you're building the Vegas strip, 1955. There's one strip. You have to make sure it's tech company that you got your spot in the strip. Otherwise, you could spend less, and then you're in Reno. Right. Well, I mean, speaking of smaller cities and smaller things, I want to talk, you talk so much about the hyperscalers and those giant tech companies. I want to know your thoughts on these smaller, maybe call them neoclowns, the applied digitals and the iron and nebius is another one, where they're building out this space and spending tons of money just like the hyperscalers. How well do you think those kinds of stocks are going to do? I think they're a key part of this whole trade. Like if you look at nebius, we've been a huge fan of, if you look at what's happening, core weave and others, I think they're going to play, I would argue that they're going to play an increasingly more important role in terms of the AI build out, in terms of what we see from theirs. But look, it's going to take a lot of money. It's going to take patience. I think what you saw, especially those last quarter nebius core weave, I know there's like inflection type quarters. So when you talk about patience, it makes me think of how every company is saying, we're using AI, you know, and their grocery company is everything. How do you break down like what's a real company that's using AI and it's going to help them? And what's one that's behind the boat when you try and look at the landscape? Is there an indicator that you can suss out which one's doing it well? Yeah, I think right now like a lot of the true use cases, they're happening in like financial services. We're seeing a lot in like government military. And then you're starting to see a bunch in healthcare. A lot of it comes down to like, we're taking retail. Like you could argue a retail has been maybe like behind when it comes to AI. Maybe like a Walmart has been slightly ahead relative to competitors. So the use cases are just starting to happen on the enterprise, but they're real. And Palantir may be in the first, now you saw a snowflake. And then you'll see what I believe will be service now. So like others will are going to participate. But it's going to take time for the use cases to play out. And for these companies, they're going to have to spend a lot of money. But it's bored at ethics because if you don't spend, it might feel good at the time. I think you get you get left behind. The use cases for AI too. This is a little bit off course, but talking about sovereign AI and data. I'm so curious if you think that the monetization of data and like actually paying AI models to get your data is going to be an actual part of the market in the future. Right now, there's several companies out there, very small companies that are trying to do that. Do you think that that idea has potential of monetizing information for AI models? I think it's actually a big debate point in terms of the models versus sovereign AI. Because if you think about the last few years, companies are just. We need AI, it's kind of like drinking out of firehose. Now they're starting to understand our data. We want control of our data. The model players, they obviously want access to that data. But that's also why Amazon shut down use in terms of that. Because Amazon is like, "Hey, they don't. Who knows where their initiatives are going to be in the future." So there's going to be a lot that's going on. Speaking of AI company SpaceX is really an AI company. I know you have a pretty strong opinion of what's going to happen with SpaceX and Tesla in the future. And I want to hear what you think about that. My view is the value is all going to be about the data. So when it comes to like Musk, it's building the ecosystem. I believe there's over an 80% chance that Tesla and SpaceX merged by the end of 2027. Because it's a data play. And I think that's really the golden vision for Musk is to have that all under one hood. And the data, you mean the data that Tesla has from self-driving? And you want to get that over to XAI? Well, because even the cross-pollination that happens, the algorithms, the. The level of data, if you think about anthropic and open AI are here, the only way that Groc or Narrow's gap is data. I mean, it's a data race. I just think for Musk, when you do that space, space at one point is really going to be more. It's going to be about a data play. So when it comes to SpaceX for investors, I think what they want to know is where are we at in that timeline? So SpaceX just launched the price of the stock spin all over the place. But if you're looking at investing in SpaceX today, what kind of timeline for actually paying off for investors? For the transformational names. Especially as they go through like lockups and all that, you can just look at them over the course of like three months, six months. I mean, to me, SpaceX, it's really important in terms of what's happening. And not just on the one child, but what's happening on Starlink. It's very important that you start seeing monetization from a data perspective. And I think, look, I think SpaceX is one like now that you like just given IP of that size, you've gone through the lockup. Now it's really executing and it's hitting targets. But look, it's someone that's been such a big believer in Tesla. If you just focused, you know, let's say 2017, 2018, you would have thought the Tesla story was dead. But it was actually just beginning. I think SpaceX, you're going to have a lot of sort of ebbs and flows. But I think it's going to take a few years for them to like, to really prove out that this is. I think that execution piece, I wanted to just go back to Tesla because you've been bullish for so long on them. Do you have any concerns about the execution of optimists for Tesla? Well, they're almost like caught between two worlds as a disruptive car maker to robotaxi, optimist, autonomous. And I think that's why the stocks kind of been stuck in the mud because the robotaxi ramp has been slower than expected. They're spending, but as opposed to maybe meta where you actually see the monetization of Tesla, you haven't seen it. It's like a six to nine month prove it that they're going to need to ultimately show a special when it comes like robotaxi launch, the autonomous vision playing out. It's going to be a super important period, but I'm optimistic that they're going to be able to do that. Speaking of these sort of new products that get in customer's hands, Apple's kind of doing a bit of a pivot, new products, new CEO, product focus CEO. But they're taking a very different approach to AI than anyone else. Like where does Apple fit in this new ecosystem? Look, I think Apple, they definitely went into like a few years of like trial and error that didn't work, you know, relatively either build their own or some of the partnerships. They finally have a viable AI strategy that's actually happened. But for Apple, like with 1.5 billion iPhones, 2.5 billion iOS devices, you could be wait, but within install base like that, that's the ability to monitor. So I just think now from a device perspective, like look, foldable. That's not the same move the need. I think it's obviously it's innovative. But the big thing for Apple is going to be like 20th anniversary iPhone 2027 in AI enabled device. This turn is being a hardware guy, what that innovation ultimately will say from a hardware perspective, but turn is will be judged on how successful they are with AI. Yeah, that's a lot for Apple for sure. I was in on your presentation here at this conference. And I know you apples, one of your top 10 stocks to buy another one was Microsoft. And I'm so curious what you think about how they are doing on implementing AI. And what you think of co pilot, this had actually moved the needle for Microsoft or is there other things? Yeah, I think co pilot was probably like a bit of a black eye moment, I knew relative to like losing share. I think they've curtailed some of that. The biggest thing for them is really about Azure. It's about like on the enterprise, that's their backyard. that surprises me. to AI, Microsoft's going to be a huge beneficiary, but it's not going to be a straight line. They're going to go through periods, and I think they've gone through them, but eyes continue to believe like they're still in their early days of monetization. What do you think? So, AI is disruption, and as many AI winners that we had, there's been these waves of different AI losers, software stocks, healthcare at times. What do you, when you look at a company, a software company, how do you start the winners from the losers? And also, you have to, you have to be able to judge it from a time perspective because sometimes like, it could take time, and that's some of the investors don't like to hear. I think it's about the use cases, playing out, it's about customer reception, you know, sales force being a good example, like, strategies there, like, are you seeing reception, service now being another example. So, and then there's companies like Adobe, Intuit, queerly wear like, the business models, have like, major, major headwinds because of AI, and I think that look, it's a huge sort of gut-checked moment for software. Yeah, I mean, when you look at sales force to me at the start, people say, everyone's going to vibe code their own CRM, and I don't, I think that's far away, and I, in fact, I think people will go to sales force to say, come bring AI into our business, and it's been a roller coaster ride of whether that's been working for them or not, and if they're executing it. And Benioff definitely underestimated the impact to the model, like, they were way behind. So, I think it's been a huge warning lesson for them, but, look, they have, it's an important six to 12 months ahead for sales force to kind of prove themselves. I think some of these software companies, would you consider some of them really AI companies now because of how much they've integrated with this? Well, they go a pound-tier, snowflake, good examples, like, by MongoDB's and AI play, but Meta-based prector CEO to run a business unit, which, you know, it's obviously a bad work for them. But I think it also shows, like, the arms raised for town, and that's going to continue to play out. I want to talk a little bit more. We've talked about a lot of the huge names that are out there right now, the, the big hyperscalers, the Mag Seven. What's your take on these smaller companies? I know you just started your own business, investing in some of these startup companies. Are you also, as an investor, really interested in, what's that next AI story? What are some of these smaller companies, the next-palentier, that's going to be a huge player? Yeah. And so many of them, like, private and public, it's trying, because you're going to be trying to understand, like, who could be the next crowd, right, the next-palentier, the next, you know, hugging fate, whatever it may be. And that's like the opportunity and the challenge because competition is so stiff, there's a lot of money there funding these companies. So for us, is trying to figure out, like, they're trying to separate that out. And that, looking, that's what we're spending a lot of our time on. Yeah. I think the winners from the losers, this analogy is usual at the time, but you think about the dot com days. And there were a lot of losers that literally went to zero. And I think investors who are looking in the market right now feel that fear of, like, what if I'm investing all of this capital into this company that could eventually go to zero? Will this be one of the losers? And so what are you looking for at your company as you're looking to see who's a winner or a loser in this race because there's so many names entering the market. Like we said earlier, lots of people come into the party right now. A lot of it comes down to, like, kicking the tires and the technology. What do customers say? What do partners say? Who are the engineers of these companies? Who are their investors, if it's private, so I mean, that's why there's like a lot more that goes into it. Like, what are their opportunities, like, where's the competitive landscape look like? I think these are all the important things. And do you think this the second and third and fourth order effects of AI are still going strong? The energy demand, everything like that. That's the heart side of the bubble. That's just start. I mean, but it goes back to every dollar spent on Nvidia chip. There's the $8.10 multiplier across the rest of the tech. You talk a lot about Nvidia. What do you think about AMD? This has been the darling of the stock market really the last couple of months. And the huge fans of Lisa, Sue and AMD, like, look, Nvidia is obviously the golden child. They want their chip fuel in the AI revolution. But AMD is going to be a huge player. And I think as this all plays out, like, Lisa Sue is just further showing like how they're going to build things out. And it's not just Nvidia and AMD, like, even if you look at where Intel is today, like, no one would have seen that 18 months ago or two years ago. But in the money that's being spent, those are the opportunities. We haven't even talked about quantum yet. Are you somebody who's curious and interested in that quantum area because there's some other big companies that are getting a lot of investment, even from the federal government on this quantum computing? Yeah, I mean, like, look, we're big fans of quantum in terms of, like, that space. Krillik, some of the bigger players like IBM and others that are played there. I think it's almost like a third, fourth derivative of the AI revolution in terms of what's happened on quantum. And it just speaks like where we are today. Like, it's still so early days. And there's going to be a lot of offshoots of the spending. AI just has like everybody's head spinning. They don't know what their life's going to look like. They don't know what their portfolio is going to look like. If you could boil it down and just clarify it and you wake up in the morning and you go, what's going on with AI? Dan Ives needs to tell you what? I'd say first time in 30 years, US has added China when it comes to tech. It's really the driver of what I view as it's going to be two to three years more in this tech bull market. And I think you can't get caught up sometimes in a lot of the negative narratives from the bears that have called 10 of the last two downturns. Such a great interview today. I hope you learned a lot from Dan. If you want to learn more from some of the analysts we interviewed at that conference in Las Vegas, they are all on our channel. You can find that playlist right here.