E247: Why Wall Street Is Wrong About AI w/ Dan Ives

0:00Dan Ives:I've always viewed valuation more as you have to look out three, five, seven years to ultimately think where you think the market's going. Today's guest is one of the most influential tech analysts on the planet. Don Ives is the managing director and head of technology research at Wedbush Securities. And for the last 25 years, he's been the person the world turns to when they need to understand what's really happening in tech. I remember in late 2022, meeting with a ton of engineers, just part of the work that we do, talking about AI and where everything's headed. They have to say what, we 22, yelling into an empty forest, right?

0:46Dan Ives:But I was convinced this was going to be the beginning in terms of everything NVIDIA was doing of the AI revolution. Microsoft does the open AI investment for$10 billion. And I think we put a note out where the AI revolution's begun. My whole view is like, it's not just about big tech. That was 23, 24. It's about who in software, who else in chips, the grid, infrastructure. Yeah, I've been excited to shout. Welcome to the How to Invest podcast. I'm so excited to be here and thanks for having me. So you're one of the most well-known Wall Street analysts. your famous fear calls on Microsoft, NVIDIA, Palantir, and perhaps most notably being early on Tesla.

1:31Let's start there. So why are you bullish on Tesla today?

1:36Dan Ives:Well, I mean, today it's because my view, along with NVIDIA, it's two of the best physical AI disruptive players in the world. Look, I've never viewed Tesla going back a decade as a car company. I always viewed everything Elon was doing was disruptive tech. And then today, what I think about the AI revolution, I don't think there's a better play outside NVIDIA. I'm thinking about the longer term AI vision, physical AI in terms of autonomous robotics than Tesla. And that's why I think it's$2 trillion and ultimately$3 trillion market.

2:15It may be a dumb question, but how is Tesla and AI playing? And maybe you could unpack that. Yeah, I mean, to me, when it comes to true AI technology,

2:26Dan Ives:I don't believe there's a better use case than autonomous. So I continue, it's my view that Tesla will dominate the autonomous world. And when I look out the next three, five, seven years, robots actually, I think, is just the start. But I think no one can master scale and scope. And I think when it comes to miles driven and ultimately really viewing Tesla as much more of an ecosystem, that's how I've always viewed the 10 million cars out there. I don't think there's a better AI use case than what I think about what Tesla is going to do over the coming years. And look, and I just say the last decade, you know, and I've covered tech, what, 25 years?

3:11Dan Ives:There's no more emotional bull bear story than Tesla. and now it's about Musk proving it out. You have kind of an art approach to your valuation as well as a science and you kind of marry these better than almost anyone. How do you go about figuring out the intrinsic value of something like a Tesla? Is it a DCF analysis 10 years from now or just walk me through kind of your methodology? I've always said, right? Like if you focus just on one year PE or one year valuation instead of a transformational tech stock the last 20 years, So there's no doubt, like I've always viewed valuation more as you have to look out three, five, seven years to ultimately think where you think the market's going.

3:56Dan Ives:So look, I mean, Tesla would be a good example. It's my view that like 20 % of automotive is going to be autonomous by the year 2030. So when you think about Tesla today, just forget deliveries quarter to quarter and what they're doing. I mean, I could argue that Tesla's revenue today will ultimately potentially be double when you look out over the next six, seven years relative to the opportunity. So when I look at EPS, can they do$12,$15,$20 of EPS power? Yeah. So I don't view it today as just a stock trading at XXX times next year earnings. It's my idea, what is robotics going to be? What is autonomous going to be?

4:49Dan Ives:Look, and Palantir has been a perfect example of that, right? Like the haters needed it at 12, the spies at 50, yelling from the mountaintops at 100. And I always say like, you know, the bears when they're in hibernation mode and the Peter Millars, and I like Peter Millar, but they can't see AI in spreadsheets. one of the thought experiments that you told me is that you think about kind of freezing time almost like private equity you make the investment in tesla today you wake up in five years what is it worth do you take kind of a private equity lens to it or how would you describe that yeah i think that's a great question i think it's much more of that approach that i've always taken even though like obviously a lot of investors you know over time have disagreed with it because it's my deal let's say let's say a company like palantir that's going from a government big data play transforming to a commercial ai play i don't think you could look at that in the next one two years you have to say okay their secret sauce what are they building out what's this going to look like in the next three, five, seven years.

6:01Dan Ives:And that's always how I've looked at, you know, especially disruptive technology plays. And given where we are, right, I mean, we're in the biggest disruption phase in the last 40, 50 years in terms of AI revolution. And it's my view, that's how you have to be able to look at these names. And easier said than done to kind of have this mental benchmark in your head of three to five years, very hard to kind of survive the turbulence. How do you deal with the turbulence and basically surviving the ups and downs of the public markets? I could go back to like my two worst years in 25 years, 08 and 2022, right?

6:42Dan Ives:In terms of like, you're just given the macro and then the re-environment. I think it's very easy as an analyst to just throw in the white towel. It's easier to kind of go with to pack, not fight sometimes the trends. Stocks are selling off against you. But look, I've traveled 3 million air miles 25 years. An advantage that we've had is that just being around the globe, you have such a sense in terms of like, what things look like in Taiwan, what customers are talking about in the Midwest, what are the technologies emerging. So it's my thesis that I've always built on is that like, I'm going to do the work.

7:26Dan Ives:And even if stocks might not be reacting at that time, favorably, or maybe even a quarter, right? Like we miss a quarter, like the company didn't crush numbers and maybe the stock, but our checks are telling us other lives. But if you think about the markets kind of gaslighting you, telling you that it's a bad stock and then your customers are telling you something else. So you have kind of almost this counterbalancing constant feedback. You're counterbalancing the market sentiment with kind of on the ground feedback. I'll give you like a really good example. Like I remember in late 2022 meeting with like a ton of engineers, you know, just part of the work that we do talking about AI and where everything's headed.

8:10Dan Ives:They don't see what we 22 yelling into an empty forest, right? But I was convinced like this was going to be the beginning in terms of everything NVIDIA was doing of the AI revolution. Microsoft does the open AI investment for 10 billion. Everyone's like, why would they do this? This is great. At that moment, we're like, and I think we put a note out, we're like, the AI revolution's begun. Then the emails that I got from institutional, but just I wouldn't repeat them here. What are you talking about? Create this. But that's a good example. Because I felt like the work that we did gave us confidence that we basically put a, you know, almost like, you know, a stamp or sort of pole on the ground saying like, this is it.

8:59Dan Ives:Things have changed. I think of mimetic and herd behavior. And I think of it as like different herds. There's like a Silicon Valley herd where certain things are accepted. Certain things are paradoxical. There's like a public markets herd. And for example, like the public markets are much more later adopters, right? It's just a different. So saying something when you're with your Silicon Valley friends could sound very different, could get you more isolated than with your public friends. Yeah. And then also I'd say like, it's also the role that retail has played in this market. I think the way a lot of people on the institutional side of like missed, you know, I think a lot of these stocks is that they've been caught up in their echo chambers from New York to San Fran to Connecticut and they've missed some of the underlying trends that are happening in needs and you know whether it's Robin Hood or Palantir some of the NVIDIA moves or whatever I think it's a good example where you have to have a good understanding of sentiment whether it's Singapore or meetings in Florida and also it's the work that we do in the field I remember Palantir was selling off like massive after a quarter.

10:16Dan Ives:Maybe I'm just from like$30 to like 23. I'm just giving an example. We're selling about around that. Everyone's like, that's it. Stories are like, I went from 12 to 30. This is it. But yet, like the work that we were doing at bootcamps for Palantir with customers, it was unlike anything I've seen, you know, relative to the demand. So that was a moment where everyone's like, is this it? People are downgrading the stock. You're like, no, this is, we might've like missed the quarter from a timing perspective. This is a table pound moment. When we last chatted, you said that your alpha are things that are not in the spreadsheets, which is very surprising for public companies.

10:59What exactly is not in the spreadsheet?

11:01Dan Ives:So let's say I'm talking to a customer and a year ago, they were, they thought AI was hype. they weren't allocating budget it's a cia and today after doing a bunch of demos that customer is like all in and now maybe it's a one or two priority in their budget that's one cut but but that's important data like that's showing what's happening in technology intelligent so like if mongo db misses a quarter in the stocks of disaster but i'm hearing from customers and i'm in the work that we're doing at user conferences or realize that they have a unique mousetrap well why would that not be just the opportunity rather than throwing the towel and i'm saying like on the i think as an analyst in the sell side it's easier to just stay with the herd.

11:59Dan Ives:Don't go against the grand. I've never dressed like that. I've never analyzed stocks like that. And I think that's been, look, I think that's been part of our framework, right? Like part of our DNA. And also like, I've learned like the most from our failures too. Like maybe like there have been stocks like over time like we were too early and then maybe lacked the confidence but yet at that time that was a huge momentous move opportunity and I think I learned a lot of that like being so bullish and like like what's it when the Della came to Microsoft you know if you go back at the time everyone's like oh my they should have gotten like an outsider like michael dellum's giving examples like you know chambers whoever it was and della i always viewed as the yoda like he understood a hyun's at the time cloud better than anyone but if you go back when he took over 14 it was like okay like it didn't at first hit and there were maybe moments in there where we're like okay we're fully confident in our vision but maybe we're not going to pound the table and and that actually was the time to pound the table you mentioned kind of how you dress and being outside of the herd is the dress a way for you to separate from the herd or are since you're separated from the herd you dress differently what is driving what it's kind of like i've always dressed funky so that's always i've been there but i do think like my it's like a little symbolism too like because i'm not gonna like i'm not gonna like go to the beat of like a typical drone like i'll dress different i could cower others think but it's just like the way that i call stocks investors that have like followed me for decades understand who I, they understand the way that we analyze, like just like our ETF, right?

14:12Dan Ives:They understand like how we pick stocks, why we pick stocks. And some could disagree, but I think over the years, like we've proven out our success. I had Mike Maple's famous venture capitalist. And one of the things he really focuses on, especially early on, is kind of finding your true believers and finding your early believers and not focusing on the people that don't believe in you. How do you operationalize? You seem to have operationalized this really good. How do you avoid the noise? How do you avoid conformity? And how do you find your early adopters? I guess it's two different questions.

14:49Dan Ives:Yeah. I mean, look, it's like I found that on the institutional side, right? There's a lot of people that believed in me early, like, you know, that were very influential, you know, on the institutional side. And that, in those early days, gave me, like, a lot of confidence. And then I think ultimately I started to realize, like, haters hate and to some extent understand the opposite side, like, understand the bear argument. Like, that sounds like it's very important to me to engage in the opposite side, to understand the differing view. Because actually it's helped me a lot. And I think obviously with social and retail, it's one where it's kind of like, I'm an open book.

15:41Dan Ives:People love it, people hate it. But the way that we do things has been very clear in terms of our view of stocks, in terms of staying long and strong, in terms of our view of just this basically 20-year tech bull market, my view of AI. So I just don't get caught up in noise because it's also confidence in the work that we do. How do you know when you're wrong? You know when you're wrong more from when the thesis changes, like when all of a sudden like let's like like i'll give you example it's like adobe like as being very bullish on adobe over the like i was a believer that adobe was going to be able to like pivot and ai was actually going to be like a talent for him and then basically like after like six nine months a year started to realize more and more from like customers and partners like that wasn't right.

16:49Dan Ives:It was actually the opposite. AI was going from a tailwind to actually a headwind. So that's a good example of recognizing we are wrong, maybe right, obviously, on the call, but on the AI piece wrong, admitting we are wrong, and then ultimately taken out of our core AI index. Essentially, a customer says something that breaks your frame of mind and then you start to build consensus on the bear case. You start to double click on the bear case. And also it's like not being, I think it's easy to wear like, let's say if you have a kid and your kid does something wrong, it's easy as a parent be like, oh, it's not my kid, it's the other kid, it's the parent, it's the coach.

17:36Dan Ives:So then you have to be like, okay, like, yeah, like it's my kid. Like you got the ownership. And I think it's very easy with stocks. you can kind of like not listen to things that maybe go against your thesis and rationalize them and i think that's how they i've gotten like a lot better over the years to understanding like that input and being like hey i gotta like this could be a red flag let me do more digging like I think Oracle is an example. About two years ago, stocks going to a really rough spot. I spent two days basically just at user conferences, talking to customers. It was one just to solidify that my broader thesis was right at the foundation, even though the execution could be off with time and perspective.

18:36I like the Andreessen Horowitz, strong convictions loosely held. So it's this idea of having very strongly rooted theories, but being willing to very quickly change it. And sometimes it just things change. A new CEO comes in, they change their strategy. It's not that you were quote unquote wrong. You were right at the time, but the thesis has changed.

18:53Dan Ives:stocks don't lie sometimes it's like okay like stocks telling you something what is it telling you and it's like looking and i'll be the first one's like our if there was like a like almost kind of like a great way to like sort of simplify like our career it would be like greed at taking this inflection point great at riding it but probably like our fault is like not calling the top right like it was like staying on too long and i think that was maybe like the thesis like you know there's many times on names where like we've kind of gone like this stay on okay then eventually like you're right but like it's hard when you're like on this part where it's It's almost like you're like, okay, I should have gotten more cautious.

19:53Dan Ives:And I think that's something where it's always hard to see that, that inflection. And that's something that we spend a lot more time trying to find that, to make sure that we're not missing something and staying on stores too long. You've been doing this for decades. Have you ever had a situation where the company became more profitable, more intrinsically valuable, and the market just never caught up to it? Yeah, I mean, I think there are, and there are like a lot of, but I think a lot of those examples were companies that ultimately ended up getting acquired by like private equity. Like, oh, like SalePoint or.

20:34They may not have intrinsic value in public markets, but they still have intrinsic value.

20:37Dan Ives:Most of those examples were coming as like they got bought and it was almost like the public market never recognized it, whether it was like the managing team or the consistent execution or whatever. And then a lot of those companies ended up like getting acquired, either private equity or strategic. I think that's usually how that's played out. There have been some, like, I think Oracle is a good example where, like, that was happening, I feel like, a year ago. But it took the market time to catch up. Like, Oracle would be a good example where those dynamics were happening a year ago, nine months ago.

21:25Dan Ives:but only in this last six months is it truly caught up like another good example would be like google like look i'm of you like anytime someone says like this lawsuit this antitrust this breakup i'll always take like if we were betting i always take like the over like i always bet i always bet like this is gonna be a lot better than the fear so google is a good example i was like search it's gonna kill you know ai done with search the doj it's gonna get broken up like new york city cab drivers barris in the stock but that was an example i see what's happening in terms like google cloud I see everything Korean's doing.

22:16Dan Ives:I see salespeople going from company X and Y. So that was one where it was like, dang, okay, we're not right. We're not right. Stock's telling you something. Like sales force, investors, like, you're wrong. You're wrong. And it happened. There's a famous John Maynard Keynes quote, markets can remain irrational longer than you can remain solvent. And for somebody trying to operationalize being bullish on a single stock, what would your advice be to him or her in terms of the sizing because if you do size it too much it becomes difficult to execute so any guidance on sizing and how do you build the portfolio of these positions yeah i feel like it's almost like let's say if conviction levels scale 110 and let's say by definition of your bullish you're always going to be a conviction level like 8 to 10 when you're like an 8 8.5 you're scaling it's still like toe in the water toe in the water but when it inflects from like an 8.5 to like in the nines that's where you scale up like it's almost like because i do think you're exactly right like it's so it's easy where you can be like right but your timing was wrong and that and three bucks gets your coffee so it's almost like trying to figure out like when it inflex and just that's like there's those are the moments to me where like the conviction level it's i think that's where you and the conviction and inflex not the stock exactly almost separate from the stock it's like you're not trying to and you're not saying that you could pick inflection points in the stock.

24:00You're saying you know how to position yourself so that when there's a, I guess, catalystic...

24:06Dan Ives:That's exactly... And now you might be like, when that happens at first, like, stock might go the wrong way. But I'm fine with it because, like, you have conviction now. Now, that conviction could be from, like, the... Like, you're seeing more companies go for, like, the stack that the company, that the software company is selling. or people are lining up for chip demand that maybe hasn't been reflected so much in numbers. That would be a good example of NVIDIA in late 22, early 23. Sometimes it's very easy. The stock could go against you based on macro, whatever it may be. But if your work tells you, that's where it's like you.

24:52Dan Ives:And look, you're betting on yourself at the end of the day. You travel the world. you talk to many of the buyers are you ever having the buyers actually point you to a new stock that you might have never heard of all the time like it would be like there's been a lot of companies where maybe like they weren't even on my radar but they're coming up like in beak-offs i'm like what they're coming like yeah oh like there's an example let's say like like InnoData small cap best software company in New Jersey stocks like no one cares but then all of a sudden like in a lot of these AI I'm hearing about them a lot like in a lot of these AI deployments no one cared about it that was a good example we started covering the stock and that's been one of our core probably one of our best calls over the last whatever six months i think that's also where like talking to so many people as investors customers partners and traveling a lot i think that helps you it's very easy to like be in your own like echo chamber and i think that's that sometimes like i think there could be like a big negative there's this weird psychological phenomenon where you learn something and blows your mind and then your brain convinces you that now you know everything about the topic so you're just constantly getting getting updates to your brain in ways that are very kind of non non-linear and then you still think that now you know everything so there's this bias that human beings have that they know you don't know what you don't know like i always view myself as like i never have like hubris like i i just i'm always trying to like learn right so it's like Like, to me, that is, I think that's one of the keys too.

26:53And it's just trying to learn about different things that maybe would just increase your ability to better understand the markets one way or another. Last time we chatted, you said that you make yourself a conduit of information. What does that mean?

27:10Dan Ives:As a cognitive information, we view ourselves as almost like very intertwined globally with investor feedback. And I think that's a big part of our value, right? Like when I'm marketing, no matter where it is, investors like, what's the sentiment on stock X? Why? Do you think a lot of people are bullish into year end? What about valuation? What are people talking about? And I think kind of information is like a big, it's a big role you play as an analyst. I kind of look at it as information bartering. We have conversations every day, three to four LPs, GBs. They're telling us information all the time.

27:53We're telling them market information. And it's kind of like this positive sum. As long as you have information to give and as long as you're giving kind of at the margin more, people will start feeding you information. Now you have more information to give to the market.

28:05Dan Ives:And also part of it is like that. And also like I'm very active and social, right? In terms of social media, speak at a lot of conferences, just by traveling. I feel like you have a lot. You're meeting new people all the time, different perspectives. And I think that's helped us. mark andresen recently said that the top public investors they knows look at public stocks as having power law type aspects so power law is when you're entire you have a portfolio of 10 one of them returns more than everybody combined to an order of magnitude that was a little surprising to me but if you look at amazon's returns since ipos and the thousands of x's and google microsoft are there still power law returns in the public markets today or is this kind of a thing of the 90s and 2000s more today because of what's happened with the ai revolution and i think how a lot of investors are maybe not even seeing the second third fourth derivatives that are happening i mean i go that's a whole part of like our etf like my whole view is like it's not just about big tech that was 23 24 it's about who in software who else in ships the grid infrastructure and a lot of times like i'm looking for names being like okay could this stock outperform and then there's there's the rare names where you're like okay like no one cares about this and i think this thing could be a four bagger a five like i feel like sometimes you know when you feel like you uncover some of those and what i love is like when sentiment is like so negative and you feel like you know you feel like you've like stumbled on to something it's quite common especially smart or among smart people to think of second order effects so you have you now need ai so now you need to build these data centers few investors actually think of third level third order effects and kind of even just it's only two derivations out but for whatever reason investors don't think about that or it's not commonplace But it's even like G.

30:39Dan Ives:Vinova as a power play, okay? Like that's in our like IBS AI-30. Like Nebesis, which is an infrastructure play, there. Like Aqua, which is a nuclear play, there. But David, these are the example. Okay, it's like I'm not talking about football, not the cookie cutter first 15 scripted players. what are those like moonshot plays and it's trying to sometimes see where the market is going that maybe at the time investors don't see like maybe even like if we're in a market now everyone's like nvidia open ai like is this a bubble like does this remind you of thinking you have froth like maybe risk off in the near term whatever so i do it differently for me it's like if somebody covered tech stocks in the 90s, I compare it dramatically different relative to the use cases, the spending and everything I see.

31:42Dan Ives:And I view times like when there's like sell-offs as maybe just times to just further my conviction in tech names that I think are mispriced. My reputation's been built not when stocks go from here to here. In that, my shih tzu or terrier could be the genius. It's when stocks are going like this and everyone's jumping ship and you're like, these are the opportunities. Do you judge yourself kind of as a venture capitalist would based on your big outliers or are you kind of looking at your hit rate? It's a combo. it's my hit rate but also a lot of times it's like my outliers like my moonshots like was i right like and i take it very personally in terms of what i'm doing like when i'm in an airport and some random person comes up to me and they're like thank you so much because you invest in this or if i'm in europe and someone's like my grandpa invests in it see i do it much more like personally This is not like quiet and just numbers and whatever money you make, whatever.

33:03I take it much more personally because people are putting their confidence in me.