Is AI Taking Money & Attention Away From Bitcoin?

[0:00] Remember, what Anthropic's done is
[0:02] unbelievable, but you start that type of
[0:05] fear, that's the thing. Then all of a
[0:07] sudden, data centers don't get built.
[0:09] You have politicians get more focused on
[0:11] regulation of models. You start to go
[0:14] closer to Europe from a data privacy
[0:16] perspective. Meanwhile, China at that
[0:17] point is like foot on the pedal going
[0:19] That's the thing that to me that I worry
[0:22] about the most is the [music]
[0:24] self-created PR problem.
[0:27] What's going on, guys? Today, we've got
[0:28] a great conversation with Dan Ives. He's
[0:30] the head of tech research at Wedbush,
[0:31] and in this conversation, we dive deep
[0:33] into the AI trade. He explains what he's
[0:35] excited about, what he's worried about.
[0:37] He shows you where there is actual
[0:39] capital flowing, and then he takes us
[0:41] around the world as he goes on a trip
[0:43] and he tries to understand what's
[0:44] happening on the ground. We also talk
[0:46] about the impact from the macro
[0:47] environment, what's going on with
[0:48] Bitcoin and crypto, and then Dan zooms
[0:50] out and explains what needs to change in
[0:52] order for AI to become more adopted
[0:54] globally and actually usher in the age
[0:56] of abundance that everyone's so excited
[0:58] about. Here's my latest conversation
[1:00] with Dan Ives.
[1:01] Dan, let's start with SpaceX. Obviously,
[1:03] everyone is anticipating this IPO. It's
[1:04] supposed to be the biggest IPO in
[1:06] history. How do you view the positives
[1:08] and negative impact of this company
[1:09] coming public? Look, I mean, this is
[1:11] really it's defining what's going to be
[1:13] a new sector, no different than tech or
[1:17] retail, it's space. And I think there's
[1:20] misnomers because to me, SpaceX is going
[1:22] to be about defining space in terms of
[1:25] data centers in space.
[1:27] The business components, not necessarily
[1:29] we're talking like joyrides in space
[1:31] for, you know, 20 seconds. And it's
[1:34] really going to be almost a convergence
[1:37] of tech
[1:38] and this new sort of, you know, what I
[1:41] view is like a like a spatial
[1:43] revolution. It all starts with SpaceX.
[1:46] Look, there's so many names like Planet
[1:48] Labs, Rocket Labs, Voyager, whatever,
[1:51] and this is just the start, but it comes
[1:53] down like from Musk, it's it's a
[1:56] watershed moment, not just for him,
[1:59] but what I view is kind of for the
[2:01] market and really it's starting to now
[2:03] create a whole 'nother category in terms
[2:06] of what this is going to mean. So, the
[2:08] company started off as just rocket
[2:10] launches and trying to make reusable
[2:11] rockets and cheaper uh launches, but now
[2:13] it went into satellites and then there's
[2:15] almost this like big promise of the
[2:17] orbital data centers. And it seems like
[2:19] that's coming right at the time where
[2:20] everyone on Earth is like, "Hey, we may
[2:21] not have enough space or power or data
[2:23] centers." And so, how much of this is
[2:25] evaluating the existing business versus
[2:28] people buying into the future vision of
[2:29] what it could be? 80% of it, future.
[2:33] Interesting.
[2:34] If you look at it currently, are you
[2:37] would you at $2 trillion or $1.5
[2:39] trillion? Would you? No. In other words,
[2:40] it goes back to like what will this
[2:43] become?
[2:44] >> [clears throat]
[2:44] >> But then it comes down to like if you
[2:46] bought Intel when you know, you as put
[2:50] its stake, it wasn't just on that. It
[2:52] was like, "Can they become a player in
[2:54] AI?"
[2:55] With Nvidia, it wasn't just about like
[2:58] going after AI. It's like, "What
[2:59] eventually will happen if they're able
[3:01] to not just monetize enterprise, but
[3:03] create physical AI when it comes to
[3:05] chips?" So, I think that continues to
[3:07] really be the focus for SpaceX because
[3:10] it's Musk. And then we've talked about
[3:13] like we view it, we've said 80% 85
[3:17] that SpaceX to merge eventually with
[3:21] Tesla in 2027. Yeah, so you think 80-85%
[3:25] of SpaceX Tesla merging in 2027. Not
[3:27] like just some point in the future, but
[3:28] literally by next year. Because I think
[3:30] it's important that to just take a step
[3:33] back. Like, why is there a trial
[3:35] Musk-Altman? This despite like personal
[3:38] beef and just all the things that have
[3:40] happened there. I mean, a lot of it
[3:42] really comes down to
[3:44] Anthropic
[3:46] OpenAI
[3:47] then it will down here. It's like xAI or
[3:49] SpaceX
[3:51] AI.
[3:52] So, now it's like, "How are you going to
[3:54] converge?" No different what has Google
[3:56] done with Gemini?
[3:58] Data.
[3:59] Data is the new oil and gold.
[4:01] You converge, merge SpaceX and Tesla
[4:06] from a data perspective, forget all the
[4:08] hyperboles and everything like biggest
[4:09] IPO ever.
[4:11] This would really create from a data
[4:13] perspective
[4:15] so that will be unmatched that I believe
[4:17] will enable Musk to really narrow the
[4:20] gap from a model perspective versus an
[4:23] Anthropic Open AI. It's hard to tell how
[4:25] much of this is like a master plan that
[4:26] he had versus he's just going building
[4:29] these companies identifying areas that
[4:30] need to be solved and then expanding
[4:32] into them. But let's say these two
[4:33] companies do come together and it's I
[4:35] don't know Musk Industries or what
[4:37] whatever you want to call it. But
[4:38] basically he's able to launch at a very
[4:41] low cost into space. So, he can get both
[4:43] satellites and data centers up there. He
[4:45] then is able to use all the solar
[4:47] capabilities from Tesla and SolarCity
[4:49] and all of that in space, capture the
[4:52] energy of the sun, create the compute in
[4:55] space and those orbital data centers,
[4:57] then beam it down via the satellite
[4:59] technology he has with Starlink, and
[5:01] then he goes all the way to the end
[5:03] consumer where he is literally talking
[5:04] about humanoid robots and self-driving
[5:06] cars. And crazy. And that also tech
[5:10] companies, whether it's Google,
[5:12] Microsoft
[5:13] tech companies ultimately, how else are
[5:16] you getting into space? Like the the the
[5:18] palm spaceship? Like the [clears throat]
[5:20] point is like
[5:21] Never know. I mean within the studio.
[5:23] But the point is like it comes down to
[5:25] like that will start to be. You saw it
[5:28] like with from a technology partnership
[5:30] perspective in terms of where SpaceX is
[5:32] ultimately going. And that's why I view
[5:35] SpaceX or just that broader sector as
[5:38] almost like second, third, fourth
[5:40] derivative plays off AI revolution
[5:42] that's happening in tech. I don't view
[5:43] them as separate. And I actually think
[5:46] when you think about a theme being 5,
[5:49] 10, 15 year theme.
[5:51] >> Mhm. Now, one of the things I find
[5:52] interesting is there's so much like
[5:54] anti-AI narrative out there. There's
[5:56] both the data centers which people are
[5:58] worried about electricity cost, water,
[6:00] noise, you know, environmental impact. I
[6:03] also think that there's maybe some
[6:04] distrust of oh, I've heard this before
[6:06] of you're going to create jobs or
[6:08] economic activity. At the same time,
[6:10] there is a lot of just plain anti-AI
[6:13] narrative, right? Not even the data
[6:14] center stuff, just like I don't think
[6:16] this is good or I think this is going to
[6:17] take my job, etc. How do you think that
[6:20] we overcome that, right? Well, first of,
[6:23] I think a lot of it is actually
[6:25] self-created by the industry.
[6:27] When you have Dario from Anthropic
[6:29] saying 20, 30% job loss, Mustafa from
[6:32] Microsoft saying like we're going to all
[6:35] white collar you know, white collar sort
[6:37] of jobs are ultimately going to be, you
[6:39] know, done relative to AI in the next 18
[6:42] months. Guess what? You do that,
[6:45] that's where you continue to go further
[6:48] and further down the tone of pole when
[6:49] it comes to survey data. Because it
[6:51] comes down to the average US consumer.
[6:55] What's in it for me? Am I going to lose
[6:57] my job? My electricity bill is going to
[6:58] be higher? Huge PR issues. And guess
[7:01] what? When you create that,
[7:03] you have a lot of issues in the beltway.
[7:05] Regulatory.
[7:06] Then you got to get build the data
[7:08] centers. Locally has to get approved.
[7:11] You continue to do this, data centers
[7:13] don't get built. So, Now, you're not
[7:16] talking about like
[7:17] in our lifetime you go back multiple
[7:19] lifetimes. Like the only mean is polio,
[7:22] right? Can you cure cancer, dementia,
[7:25] Parkinson's with AI? That's obviously
[7:27] huge positive. There's going to be more
[7:28] data centers, you know, that are built
[7:31] today than active data centers. The
[7:32] jobs, the ripple effect, the
[7:34] restaurants, so many towns throughout
[7:36] the US.
[7:37] But that's not being talked about. A lot
[7:40] of it is PR issues that you can and I've
[7:45] told some of these companies like
[7:47] that can never talk externally because
[7:51] that is a negative for the industry and
[7:53] I think that a lot of this is
[7:55] self-created. There's fear AI fear and
[7:58] that's why you saw it with the Schmidt
[8:00] like the commencement speech and the
[8:02] booing. Yeah, of course, if you're a
[8:04] I speak in many colleges around the
[8:06] country. I would tell people like
[8:08] there's going to be more jobs over the
[8:09] coming years created but right now it is
[8:13] a huge issue. What's fascinating to me
[8:15] is I saw Iron, you know, the data center
[8:17] provider and and power generation
[8:19] company. They just bought a marketing
[8:21] and kind of branding studio and I've got
[8:24] to imagine that is specifically because
[8:26] they realized that a huge part of the
[8:28] future success of their business is
[8:29] going to come down to how do they
[8:30] communicate to local communities or
[8:32] local politicians about what they're
[8:34] trying to do? 100% and then also it's
[8:36] like let's say pump in the streets,
[8:39] okay?
[8:40] Company all of a sudden like get
[8:43] everyone together in all hands meeting.
[8:44] We're we're we're going to launch quad
[8:47] as a test trial run.
[8:49] What does the average consumer or the
[8:52] average person in that company think?
[8:54] Does that mean my job's at risk? No, see
[8:57] that's part of the problem. You need
[8:58] companies be like efficiency
[9:00] monetization. How are we going to be
[9:02] able to do it? That's a huge part of the
[9:04] issue that I hear not just but it's from
[9:07] investors as well and you need this to
[9:10] be something that's viewed as like it's
[9:12] an arms race US versus China and we said
[9:15] first time in 30 years US is ahead, you
[9:18] know, when it comes to tech versus
[9:19] China.
[9:20] But they need they need to get their act
[9:22] together broader tech in terms of the
[9:24] communication. Ironically like when you
[9:27] look at like what's going on I think a
[9:29] lot of that
[9:31] 78% of that is self-created and you
[9:35] create the narrative. You don't go on 60
[9:38] minutes to, you know,
[9:40] you know, talk about a cartoon, right?
[9:43] Like the point is like when you go on
[9:44] there and you scare people like Dario
[9:46] did, that's that's part of the issue.
[9:47] Yeah. It's so fascinating because one of
[9:49] the things that I'm very focused on is
[9:50] showing people how do you connect the
[9:52] adoption of artificial intelligence
[9:53] product to you making more money. And my
[9:56] whole theory has been if everyone is
[9:58] telling you you're going to lose your
[10:00] job, there's all these negative impact,
[10:01] then you have to look at AI as a tool.
[10:03] And so it's it can hurt some people, but
[10:06] those who adopt it and use it correctly
[10:07] are actually going to be able to
[10:08] benefit. And so we were talking
[10:09] beforehand, you know, this product
[10:11] Silvia that we built, it people go to
[10:13] cfosilvia.com, they attach their
[10:15] portfolio, and they start talking to an
[10:17] artificial intelligence model that is
[10:18] personalized to their portfolio. And we
[10:20] see in the data, the more they talk to
[10:22] it, the faster their net worth grows.
[10:23] 70% is And I was giving it 70% of the
[10:27] use cases that we see on enterprise are
[10:29] monetization, revenue enhance. They're
[10:32] not cost car
[10:34] They look, there's going to be a lot of
[10:35] companies that use it as kind of like to
[10:37] whitewash, right? Or they're going to be
[10:39] like, "We're going to Do you believe the
[10:41] CEOs who are saying they're firing
[10:42] people because of AI?"
[10:43] 20% of it.
[10:44] >> 20%. So 80% of the CEOs who say they're
[10:46] firing someone because of AI is actually
[10:49] just over hiring or mismanagement
[10:50] previously.
[10:51] >> Whatever. It's like the point is like
[10:52] But guess what? Like if it eventually
[10:54] models become commoditized, Mhm. if
[10:57] company A has the same models company B,
[10:59] C, D, what differentiates it? It's what
[11:01] goes up and down the elevator every day.
[11:03] It's the engineering talent, it's the
[11:04] product. So the point is like you're
[11:06] going to see a lot of companies that
[11:08] went way over. And we're not talking
[11:09] about big tech where these companies
[11:11] essentially hired cities
[11:14] over the course of the last four or five
[11:16] years. But that's why like you know, me
[11:18] and you have talked, you know, for years
[11:19] about like you got to separate like
[11:20] reality versus, you know, fiction.
[11:24] The point is like this is something from
[11:25] a productivity perspective, to
[11:28] monetization, to the jobs ultimately
[11:30] that will be created from data centers,
[11:32] from build out, from new companies. You
[11:34] could be a 23-year-old right now. You
[11:36] don't need 20, 30 million in seed
[11:37] capital. You got quality of an engineer
[11:40] or two. Who knows what you could build.
[11:42] Democratization has happened across the
[11:43] board. And for the first time in 30
[11:45] years, US is ahead of China when it
[11:48] comes to tech, which is very, very
[11:49] important in terms of what this all
[11:52] means.
[11:53] >> You You said that twice, that the United
[11:54] States is ahead of China now when it
[11:56] comes to artificial intelligence. How do
[11:57] you measure that? I mean, a lot of it
[11:59] comes down to what There's one chip in
[12:01] the world fueling the AI revolution.
[12:02] It's Godfather of AI engines, Nvidia. A
[12:05] third-rate Nvidia chip is a year and a
[12:07] half, 2 years ahead of Huawei. Like an
[12:09] H200.
[12:11] When you think about
[12:12] Anthropic, the hyperscalers, the
[12:15] software, Palantir among others.
[12:18] You look when you go go to China,
[12:20] robotics, they're leading. Mhm.
[12:23] Power, because of nuclear, they're
[12:25] leading.
[12:27] That's where it kind of stops.
[12:29] >> think that China is leading when it
[12:30] comes to the hardware and application of
[12:33] AI for robotics. And then you think
[12:34] they're leading when it comes to power
[12:35] generation, but you think that the
[12:37] United States is winning in terms of the
[12:38] models and the software.
[12:40] >> the software, the chips. That's also why
[12:42] like when Trump and Xi meet, they
[12:44] recognize I need you, you need me. Cuz
[12:47] guess what? Middle East, India, you
[12:49] know, obviously everyone's trying to
[12:51] think who's going to be the number three
[12:53] player.
[12:54] This is third inning, one out
[12:57] in a nine-inning game. The point is like
[13:00] that's where we are relative to AI, and
[13:01] it speaks to my overall like bull
[13:03] thesis. And we've talked about it is
[13:06] that
[13:07] you're going to go through these,
[13:09] whether it's liberation day, Iran,
[13:12] 10-year wars coming in,
[13:15] whatever. But the reality is like we
[13:18] This is a multi-year bull market
[13:20] relative to what's happening in tech,
[13:22] but also it's the derivatives, cuz that
[13:24] will go across financials, health care.
[13:28] companies. You like, what? They're
[13:29] trading at this? Because now all of a
[13:31] sudden some of these are utility
[13:32] companies are the derivative AI
[13:34] multiples going to increase across the
[13:36] board. Dude, these companies that don't
[13:38] embrace it, dude typewriters, they're
[13:40] epic. This computer thing's a joke. Dude
[13:43] that was doing horses back before my LT.
[13:46] Yo, this whole car thing's a joke. The
[13:47] point is like
[13:49] that will play itself out for those
[13:51] companies.
[13:52] >> [music]
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[15:03] Now let's talk about robotics because I
[15:05] think what's very interesting is in the
[15:06] United States we've seen the Figure
[15:07] AI's, the
[15:09] uh Apptronics, right? We we've seen some
[15:10] of these companies, obviously Tesla's
[15:12] got their humanoid robot. Um but also
[15:15] people kind of forget that there's an
[15:16] entire self-driving car revolution. And
[15:19] I've seen a ton of companies, whether
[15:21] they're building a net new car, whether
[15:22] they are trying to write software in an
[15:24] asset-light model, and then get it into
[15:26] the production of other people
[15:27] manufacturing cars, trucks. And then I'm
[15:29] even seeing a lot of these like semis
[15:31] and and kind of long-haul trucking
[15:33] self-driving cars. Is that the first
[15:35] area where the average American is going
[15:37] to interact with like robotics? Is
[15:40] actually in self-driving cars? Yeah,
[15:41] [clears throat] so and even take a step
[15:43] further back like the average consumer,
[15:46] okay, you've played around with ChatGPT
[15:49] and tropic different models. But where
[15:52] it all will start like when Apple
[15:53] ultimately releases the Gemini in terms
[15:56] of the model that that will be on, you
[15:58] know,
[15:58] at WWDC, that will be the start of
[16:01] what's going to happen like eventually
[16:03] miles will be on the phone, Mhm.
[16:05] storage, applications are going to get
[16:07] built, AI-driven applications,
[16:10] healthcare, financials, fitness across
[16:12] the board.
[16:14] So that's where you're going to see more
[16:15] and more used from a consumer
[16:16] perspective. But when it comes to
[16:18] physical AI, it's autonomous. I mean,
[16:21] that will be the first true interaction
[16:25] with a And there's some obviously have
[16:26] done Waymos in different cities, but
[16:29] that's why Tesla and robotaxis are so
[16:31] important. But then also it comes down
[16:33] to like regulatory.
[16:35] Cuz regulatory right now it's state.
[16:38] Mhm.
[16:38] You need federal. You need executive
[16:41] order from Trump to make this on the
[16:44] federal side. And I think that's a
[16:46] That's a huge missing piece versus what
[16:48] we see in China. One of the things
[16:50] people are excited about at the federal
[16:51] government level, but also there's a lot
[16:52] of critiques about are there a lot of
[16:54] technologists and private sector
[16:56] individuals who have gone into the
[16:57] federal government. And so I think that
[16:59] the people who are excited about this
[17:00] would argue hey these people understand
[17:01] the technology, they understand kind of
[17:03] how important private industry is, and
[17:05] they are trying to streamline, get rid
[17:07] of waste, and accelerate a lot of the
[17:09] innovation industries. On the other
[17:11] hand, I think that the critiques are hey
[17:13] there's as much people who are going in
[17:14] they're investors in a lot of companies,
[17:16] they've got a lot of connections and
[17:17] friends and there's all these, you know,
[17:18] kind of complexities of them being
[17:21] involved. Given that Trump now has just
[17:23] about 2 years left in office, is this a
[17:25] thing where if we have a pro-innovation,
[17:28] pro-technology administration, they
[17:30] should accelerate and get as much of
[17:31] this done as they possibly can from a
[17:33] regulation standpoint because there's a
[17:34] worry that maybe the next administration
[17:36] won't be as friendly or do you think
[17:38] that this has now reached a point where
[17:40] it doesn't matter, you know, red or
[17:42] blue's in office, it's going to be
[17:44] people embracing technology? Look, I
[17:46] think people are going to embrace
[17:48] technology, but it does it is very
[17:50] political Mhm. you know, sort of
[17:53] navigation is very important because
[17:56] it goes back to like you need a
[17:58] pro-innovation
[18:00] administration. And that's why like when
[18:03] you see Jensen and Cook and Musk and
[18:05] obviously the other CEOs in the China
[18:07] trip, I view that as bullish. They
[18:09] understand technology as well as that
[18:10] best person in the world.
[18:12] If you start to put, Mhm.
[18:15] >> in the gears and slow it down,
[18:18] look at Europe.
[18:19] They're building blockbuster videos
[18:20] there
[18:22] because of regulatory,
[18:24] because of, you know, just worry about
[18:26] data private and I see the frustration
[18:28] first hand in Europe because like if
[18:30] you're an innovator,
[18:32] entrepreneur,
[18:33] what in Europe is like you have to move
[18:35] to Middle East, US, Mhm. you know, Asia.
[18:40] So, it's very important, it's foot on
[18:43] the pedal
[18:44] on AI. Guess what? Cuz look at China.
[18:48] And you fall behind, but then a key part
[18:50] of that is data centers. That's why it
[18:53] all kind of goes where we start start
[18:55] talk about is like when you go like
[18:57] anti-data center because of PR, protest
[19:01] demonstrations, I love AI I love data
[19:04] centers is not in my backyard.
[19:06] That's a huge piece because guess what?
[19:09] The way this is all works,
[19:11] data center without data centers, it's
[19:13] the hearts and lungs of AI. Mhm. So, it
[19:15] just it all kind of factors into what's
[19:18] going on here. It'll be a a big thing in
[19:21] terms of midterms.
[19:23] And of course, you know, when we go into
[19:25] like, you know, presidential election,
[19:26] but this is like a key time cuz I just
[19:29] keep going back to like so much of my
[19:31] life.
[19:33] Spent time like in Asia.
[19:35] You know, you're in Taiwan. You see the
[19:37] fabs. You see the efficiency. You see
[19:41] You know, and then you come back here.
[19:44] Like I was like land in New York
[19:45] airport, go to Dunkin' Donuts, and
[19:47] there's like a fist fight at Dunkin'
[19:49] Donuts, and then you wonder why we're
[19:50] 17th in math. So, the point is like now
[19:53] for the first time
[19:55] we're ahead. Now, when we think about um
[19:57] so much of this industry accelerating,
[20:00] that's great to talk about the
[20:01] fundamentals and the trends and the
[20:02] adoption, but people ultimately want to
[20:04] know how do I make money? And so, if we
[20:06] go and we look in the public market,
[20:07] there seems to be uh you know, kind of
[20:09] the hyperscalers, there's some very
[20:10] large tech companies, but now most of
[20:13] the conversation is about going and
[20:14] finding which companies can be the
[20:16] release valve for various shortage
[20:17] pressure. So, whether it's memories or
[20:19] chips or you know, etc. Just walk
[20:21] through maybe when you look at the
[20:23] public market, how do you break down the
[20:25] different uh sectors or verticals of how
[20:27] someone can invest in the AI trade, and
[20:29] then where are you more excited than
[20:31] maybe other areas?
[20:32] >> Yeah.
[20:33] And then and then I look what's happened
[20:34] with software. So, to me it all starts
[20:37] with like chips.
[20:40] At the epicenter, of course, has been
[20:41] Nvidia, but then you have to think This
[20:44] is almost like walking you through it.
[20:45] It's like
[20:46] Okay, like
[20:47] Meta, for every 10 chips they need,
[20:49] Nvidia's going to give them three cuz of
[20:51] supply. Where do they get the others? Is
[20:54] it Google?
[20:55] What about AMD?
[20:57] What about Intel? What about where
[20:59] Micron plays? Sandisk, the memory, the
[21:02] components. You have to think about like
[21:04] it's all it's all a puzzle. Mhm.
[21:06] And all the work we do is what is
[21:09] demand's pie look like in memory.
[21:11] And then it's a super cycle. Are there
[21:13] multiples that are high relative to
[21:15] historical? Yeah, but street
[21:17] underestimates the growth, okay? In
[21:20] terms of what that's going to look like.
[21:22] Then you start to view whether it's like
[21:24] a deep renewal or an iron, like where
[21:26] who are the ultimate players and maybe
[21:29] investors aren't seeing.
[21:31] But then there are trades when it comes
[21:33] to like
[21:34] the street gets wrong, but there are
[21:36] opportunities. I always give an example
[21:38] like
[21:40] we're at RSA conference in March, you
[21:43] know, in San Francisco.
[21:44] That's where like Anthropic mythos comes
[21:48] out to view like Anthropic's going to
[21:50] eat cybersecurity, going to eat
[21:52] software.
[21:54] But that that was a narrative that if
[21:56] you talked to customers, you know it's
[21:59] wrong.
[22:00] Look at CrowdStrike stock today versus
[22:03] where it was in March. Look at Palo
[22:05] Alto.
[22:06] It's a good example of like narratives
[22:09] create opportunities if you do the work.
[22:12] You go back a year ago, New York City
[22:14] cab drivers bearish on Alphabet. DOJ's
[22:17] going to break it up. AI's going to
[22:18] crush search. Gemini's nowhere. Now
[22:21] look, victory parties. I'm just trying
[22:24] to explain in this market
[22:27] it
[22:28] it's a multi-year bull market. We're in
[22:31] year three of a 10-year build out of AI.
[22:34] And it's very important to like try to
[22:37] pick who the winners are, do the work,
[22:40] cuz I think that's how you're able to
[22:42] ultimately make money
[22:43] in these markets. What do you look at
[22:45] like a Bill Ackman buying Microsoft and
[22:47] basically saying, "Look, we still think
[22:49] this is an amazing company that's just
[22:50] dislocated from price and value, and
[22:52] therefore we're going to go and put a
[22:53] position on." Couldn't agree more,
[22:55] because that's it because then it comes
[22:57] down to like Microsoft
[22:59] basically every enterprise in the world
[23:01] runs on Microsoft.
[23:03] As they move to AI as they move to Azure
[23:05] as I believe Nadella one of the best
[23:08] CEOs out there. Copilot has been under
[23:11] you know, underwhelming? Yeah. Are they
[23:14] training wheels of the open AI? Yeah. Is
[23:16] there a lot of noise? Yeah. But I like
[23:18] we've talked about like stock closer to
[23:20] 400. I think it's worth closer to 550 or
[23:23] 600 and like but that's a good example
[23:25] of like you have to be able to see
[23:29] around corners in this market. And then
[23:32] whether it's liberation day, Iran, oil,
[23:36] wars coming in 30 or hitting a certain
[23:39] level, yen that whatever. You have to be
[23:41] able sometimes to like I get the the
[23:44] worries there but tune that out to
[23:46] understand where are the opportunities
[23:49] in front of you. One of the hardest
[23:50] parts I think about investing in these,
[23:52] you know, accelerated bull markets is
[23:54] when you look at a certain stock, you
[23:55] may look at the last 6 months or 12
[23:57] months performance be like wow, it's up
[23:58] a lot already. And so give you some
[24:00] examples. Micron's up 6, 7, 800%. Uh
[24:03] company like Marvell is up 100% in 6
[24:06] months. And so I hear people talking
[24:07] about I'm interested in this company. I
[24:09] think they solve part of the problem for
[24:13] XYZ, you know, part of the industry or a
[24:14] shortage. I'm just really nervous at
[24:16] buying in at 100% higher than it was 6
[24:18] months ago. And then the fear is like
[24:20] it's a musical chairs you don't have a
[24:22] chair.
[24:23] Everyone heads for the elevators. You're
[24:25] waiting a year that so it's like that
[24:27] fear definitely is there but then I give
[24:31] you like on the other side, you have it
[24:32] on the whiteboard you didn't own it.
[24:35] Stock gets hit.
[24:37] Falling knife. Stock gets hit again. Oh,
[24:39] it's done. Negative sentiment whatever.
[24:43] It's very easy to miss
[24:45] the The dry house. But go back to March
[24:49] in terms of like where did Nvidia go?
[24:52] And I ran with I remember like being in
[24:55] Miami early March. I'm speaking at a
[24:57] conference.
[24:59] And
[25:00] you know, sentiment [snorts] so negative
[25:03] because like the Iran thing, oils
[25:06] trade
[25:07] And I remember like people like taking
[25:09] pictures in South Beach being like, "Oh,
[25:11] I can't wait. People they don't realize
[25:13] the longer." I'm like, "Yeah, I've done
[25:16] this since like late night. You start to
[25:18] go down that path, you'll miss and every
[25:20] geopolitical, you'll miss every sort of
[25:23] opportunity."
[25:24] And look at where those stocks traded
[25:26] for its week or two of March. Mhm. And
[25:30] it's May. Like you we're not talking
[25:32] like 10 years ago.
[25:33] >> Mhm. One of the other things I find
[25:35] interesting um is how global this
[25:37] phenomenon is. And so for example, we
[25:39] saw Roundhill go and launch the uh DRAM
[25:42] or the memory ETF. Uh they had a $10
[25:44] billion get added in like 2 months. Um
[25:46] and a huge part of that was just they
[25:48] gave access to American investors to
[25:49] certain companies that they couldn't
[25:51] otherwise do. And so uh how do does that
[25:53] play out? Do we just get consolidation
[25:55] where you're going to see more and more
[25:56] ADRs or ETFs with swaps and things where
[25:59] American investors are going to be able
[26:00] to really invest globally, but it's
[26:02] going to be through American vehicles?
[26:04] Look,
[26:05] you it's a democratization
[26:07] of investing, democratization of
[26:09] information flow.
[26:11] People want access to how they could
[26:15] play certain themes. Mhm. And
[26:17] [clears throat] that's what that does,
[26:18] right? And obviously there's the active
[26:20] manage piece as well, you know, in terms
[26:22] of like you know, depending on who it
[26:23] is, you know, where where they play that
[26:25] well. But I think we're going to see
[26:27] more and more of this, right? In terms
[26:29] of just like
[26:31] it's a globalization. I just see it
[26:33] traveling the world like
[26:35] my conversations with people in Europe,
[26:37] Asia, Australia, Africa, whatever,
[26:40] Middle East are very similar a lot of
[26:42] times to like, you know, somewhere in
[26:44] Midtown Manhattan. Mhm. So that's the
[26:47] opportunity where investors want to play
[26:49] a lot of the global theme.
[26:51] >> Mhm. Now, how do you think about the
[26:53] experienced investors take the Stanley
[26:55] Druckenmillers, kind of the legends of
[26:56] Wall Street? They seem to be all over
[26:58] this trend, rightfully so. Uh Paul Tudor
[27:00] Jones was on CNBC recently saying, "Hey,
[27:01] I bought a bunch more AI stocks." But
[27:03] then there are people like Leopold and
[27:05] others who frankly have no experience as
[27:07] investors, but they seem to be young,
[27:09] very in tune with what's happening. They
[27:11] have access to a lot of information from
[27:12] the private market that's informing
[27:14] their investment decisions. And so it
[27:15] doesn't feel like you can put anyone in
[27:17] a box where experience is a liability or
[27:20] an advantage.
[27:21] >> But also a Druckenmiller at one point
[27:22] was like in his 20s. Like Buffett at one
[27:25] point was in his 20s. Like you I don't
[27:27] think you could just look at things like
[27:29] this is good, this is bad, experience is
[27:31] good. I think a lot of it's based on
[27:33] like the individual. Look, experience, I
[27:36] believe
[27:38] there's so much value with experience
[27:40] that I think investors
[27:43] poo-poo sometimes. But then on the other
[27:45] hand, there's different ways of
[27:47] understanding this market where you can
[27:50] discount
[27:51] newer investors that have had huge track
[27:53] record. Cuz I could go back my whole
[27:55] career
[27:57] and investors being like, you know,
[27:59] who's this hedge fund or Tiger or
[28:01] whatever. Now look at Tiger. Like you
[28:03] could go back to like, you know, the
[28:05] legend, whether it's Cohen or others,
[28:08] and and what they did, but at one point
[28:11] they had to prove it. And I just think
[28:13] in a market like this,
[28:15] you have to digest all the information.
[28:18] And it's ultimately it's ones that you
[28:21] think from an invest from a PM
[28:23] perspective or an investor perspective,
[28:26] you take that into your process to help
[28:29] you,
[28:31] you know, pick ultimately the winners,
[28:33] good or bad. So we know that the AI
[28:35] trade has been working, investors very
[28:37] excited about it. Um the rest of
[28:39] software has been struggling a little
[28:40] bit, and I think that the broader market
[28:42] generally has been lagging um kind of
[28:44] the AI trade. Now, one of the concerns
[28:46] is as the Iran war continues and we see
[28:48] oil spike energy prices go up, you get
[28:52] this kind of persistent inflation risk.
[28:54] And we have a new Fed chairman that's
[28:55] coming in. And now people are saying,
[28:57] "Hey, maybe 6 months ago we were all
[29:00] advocating for a rate cuts and we really
[29:02] thought that kind of true QE was
[29:04] coming." Now there's more talk actually
[29:06] of rate hikes instead. And so how do you
[29:08] think of the relationship between
[29:09] monetary policy and maybe the AI trade
[29:11] and how investors should think about it?
[29:12] >> Yeah, and like if you look at the number
[29:14] and Tommy he talks about like the first
[29:16] like three or six months when a new Fed
[29:17] chair comes in like stock market's down
[29:20] like in first three or six months X
[29:22] percent. So it's like, you know, it
[29:24] tends to be like a readjustment for the
[29:26] market. Look, he's coming in at such a
[29:29] complex time because of where the
[29:30] 10-year, what we see up in Japan, what
[29:33] you know, obviously what we see in in
[29:35] terms of the UK and then because of oil
[29:38] and this sort of like,
[29:40] you know, impasse relative to Iran, what
[29:42] we're what we're seeing here.
[29:45] I just think
[29:47] it's going to be a volatile period and
[29:50] we could have sell-offs based on
[29:52] what war says, getting used to him and
[29:55] his sort of wording and is there a sort
[29:57] of tightening. But I do believe like
[30:00] this will be ultimately a temporary
[30:04] sit relative to oil
[30:06] and then he'll have more flexibility on
[30:08] the other side to cut. And I just think
[30:11] as a Trump appointee, I just cannot
[30:14] believe war is coming in as some hawk.
[30:16] That's sort of like my view, but look,
[30:19] but the market's going to adjust to it.
[30:20] But as the market adjust to geopolitical
[30:24] and Fed
[30:26] and other issues that happen from a
[30:27] macro perspective, you cannot lose sight
[30:31] of what's happening in terms of the in
[30:34] terms of the tech trade. Now, one of the
[30:36] other areas I find very fascinating is I
[30:38] look at artificial intelligence,
[30:39] Bitcoin, robotics, you know, all this
[30:41] stuff is just really the age of
[30:43] automation. We are essentially
[30:44] automating a bunch of parts of the
[30:45] economy. We're squeezing inefficiencies
[30:47] out. And I feel like there's a group of
[30:50] companies that maybe I'll use Figure
[30:52] Technologies. And I know it intimately
[30:53] cuz I was an investor from the private
[30:54] market, but they basically said, "Look,
[30:56] how do we automate a huge part of the
[30:58] HELOC market and then the secondary
[31:00] trading of these assets and the
[31:01] securitization, etc." It feels like now
[31:04] Wall Street has woken up. And whether
[31:06] they call it crypto or they call it, you
[31:08] know, AI or they call it automation,
[31:10] there is this like software is going to
[31:12] eat finance game going on. And so, how
[31:15] do you look at that bucket of companies
[31:17] which they may not actually fall in the
[31:18] pure AI trade and they may not fall in
[31:20] the pure like crypto trade, either.
[31:22] But there's a monetization that's
[31:24] happening, right? And I think like you
[31:27] see the world adjusting to these
[31:29] technologies. And I think it's something
[31:32] where it's going to make companies just
[31:34] that much more efficient. But also
[31:38] there's going to be software that comes
[31:41] in and it's wake-up calls for different
[31:42] companies that's going to create their
[31:44] own proprietary technology with their
[31:46] people. And that's going to make them
[31:49] that much better.
[31:50] So, I think
[31:51] it's an arms race that's playing going
[31:53] on between numerous
[31:56] new AI tech
[31:58] versus traditional. I think that's been
[32:00] from I think if there's any best example
[32:02] would be SaaS apocalypse, software,
[32:06] ServiceNow, Salesforce, Oracle, Workday,
[32:09] where do they sit?
[32:11] I I do believe that a lot of that is
[32:14] disconnected relative to how it's going
[32:16] to ultimately play out. But it's been a
[32:18] huge wake-up call for Benioff or
[32:20] Salesforce, like what they're going to
[32:21] have to do. But I think also the view
[32:24] that these models are broken or the new
[32:27] kid on the block is going to change, you
[32:30] know, whether it's Wall Street or
[32:32] whether it's Corporate America. Those
[32:34] are also easier said than done. And I
[32:36] think it's just it's all part of like
[32:38] who are the winners
[32:40] and trying to discount what's baked into
[32:43] the stocks at the end of the day. Now,
[32:45] as we see this all play out, another
[32:47] question that I think immediately people
[32:48] look at is something like Bitcoin. And
[32:50] we've seen Bitcoin actually operate I
[32:52] think a little bit differently than
[32:53] people thought it was going to. So,
[32:54] since the Iran war, it's up, not down.
[32:57] Uh over the last 90 days or so, it's up
[32:59] about 15%. It's up, you know, more than
[33:02] gold and S&P over the last 3 years, but
[33:04] it's also struggled over the last year.
[33:06] And so, kind of you can pick different
[33:07] time frames, and you can twist the data
[33:09] to tell different stories.
[33:12] One thing I think a lot of critics would
[33:13] argue is that there is a tension and
[33:15] capital that is being diverted from
[33:17] Bitcoin to the AI trade. And so, how do
[33:19] you look at the relationship between
[33:21] these
[33:22] >> I was literally going to I think that
[33:24] You think what? Exactly that. Like, I
[33:26] think risk assets,
[33:29] if you have a dollar,
[33:31] do you put it in this bucket,
[33:33] this bucket, or this bucket?
[33:35] >> Okay. And I think that
[33:37] is something that's playing out in the
[33:40] broader crypto market from an asset
[33:42] allocation perspective in terms of
[33:44] globally.
[33:46] Because
[33:47] when it comes to like the AI trade and
[33:49] what's happened, tech, and the level of
[33:51] disruption, it's
[33:54] we're talking like a one to like a
[33:56] 100-year type of cycle. Mhm. So, I think
[34:00] investors, whether it's FOMO, whatever,
[34:03] it's like, okay, do I want to
[34:05] invest here, where maybe I can make,
[34:08] whatever, this 15, 20%, or you know,
[34:11] what whatever wherever you think that
[34:12] goes.
[34:13] Whereas here, that's where some of the
[34:17] generational names. But, it's all
[34:20] relative.
[34:21] You could pick the wrong name here, Mhm.
[34:24] and then you're like, I should have
[34:26] stayed in crypto.
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[36:51] Do you think that this is just mere
[36:53] momentum and so, you know, kind of
[36:55] crypto or or Bitcoin in particular had
[36:57] momentum in 2020 through 2022, then
[37:00] people kind of rotated over to AI and it
[37:01] comes back? I think it's a pendulum. I
[37:04] think these things that I look, crypto's
[37:06] not going anywhere. Like it's going to
[37:08] continue to be I think among many like a
[37:10] part of their like portfolio.
[37:13] But I think you're going to go and you
[37:14] go in pendulum shifts. And I think as
[37:16] part of the pendulum shifts, it's very
[37:18] easy to get caught up in those
[37:20] narratives. I could say like a big
[37:23] pendulum shift for a while if you go
[37:24] back like in November is the is the tech
[37:26] trade done? Mhm. Is there rotation? Is
[37:29] it financials that are going to lead? Is
[37:31] it your traditional industrials? Look at
[37:34] like Walmart's multiple relative to
[37:36] Amazon. I'm just saying like that's
[37:38] another example of like
[37:40] think about that narrative. Mhm. So I
[37:42] think
[37:43] it's also you cannot get so caught up in
[37:46] narratives. You have to be able to
[37:50] whether it's individually or for, you
[37:51] know, whoever is investing to figure out
[37:54] what's the one that makes the most sense
[37:55] for them. You recently went on a couple
[37:57] of trips that I think are pretty
[37:58] interesting and maybe you can give us
[37:59] some like on the ground truth as to what
[38:00] you saw that maybe is different than the
[38:02] public narrative.
[38:03] >> Yeah. Um you went to Asia and spent a
[38:05] couple of weeks there. Uh talk a little
[38:06] bit maybe about going to the fabs in
[38:08] Taiwan and what you learned on this
[38:10] entire trip.
[38:10] >> I mean to me it's like that's how you're
[38:12] both that's how like we are
[38:15] so bullish on like memory and chips. And
[38:17] we knew this before earning season, but
[38:19] it's like it's why like a lot of times
[38:22] people would be like, "Oh, you're so
[38:23] bullish, bullish, no matter what." I'm
[38:25] like, "No, dude, like, cuz you're
[38:26] bearish sitting in your, you know, like,
[38:29] on Metro-North or in, you know, 35th
[38:32] floor in your your New York City office
[38:34] building,
[38:35] but you're just bearish based on
[38:37] narratives, people in your circle, and
[38:39] spreadsheets.
[38:41] If I see the demand in Asia, that's what
[38:44] makes me bullish. Mhm. Like, when when
[38:47] you say you see the demand, what do you
[38:48] see?
[38:48] >> demand. You see what's happening in
[38:50] terms of production. You see the the You
[38:52] see the supply You see the component
[38:53] issues. You have You have a better
[38:55] understanding what's happening in
[38:57] hardware, from Nvidia to memory to chips
[39:00] to other components.
[39:02] Then, you're able to kind of, like,
[39:04] triangulate that with what you're seeing
[39:07] from companies, what they're spending
[39:09] on, budgets, whether it's cybersecurity,
[39:11] whether it's software, whether it's
[39:12] broader tech infrastructure.
[39:15] That's why I think those trips are so
[39:17] important. Then, even, like, you know,
[39:19] been in Europe a few times on different
[39:21] trips, and like, I could tell you, like,
[39:24] just came back from Poland, like, the
[39:25] amount of spending around, like, defense
[39:28] spending, a lot of it coming out of
[39:29] Ukraine, but just, like, that you're
[39:32] seeing in Eastern Europe.
[39:35] AI really just starting to get started.
[39:37] Who's going to be the European country
[39:39] that, like, pops out and is we I think
[39:42] Poland could actually be I mean, you
[39:43] could assume maybe even France,
[39:45] but that continent is not just a zero in
[39:49] terms of the opportunity At one point,
[39:51] when they wake up,
[39:53] and regulatory, whatever, pushes back,
[39:56] there's going to be massive
[39:57] opportunities. So, I think investors are
[39:59] trying to figure out, like, where the
[40:01] opportunities are, specifically when it
[40:03] comes either tech or defense tech.
[40:06] >> Mhm. What are the areas where you're
[40:07] concerned in the AI trade? Maybe where
[40:09] you think investors are allocating
[40:10] capital and and their uh maybe
[40:12] misplaced.
[40:13] >> My biggest concern goes back to how we
[40:15] started this.
[40:17] Is that tech companies, it's about them
[40:20] tripping over their own shoe lace,
[40:23] having the hubris, talking about job
[40:26] cuts like it's like not reading the
[40:28] room,
[40:29] saying that their technology is going
[40:31] to, you know, is going to wipe out
[40:33] whether it's lawyers, you know,
[40:35] different areas and in financials for
[40:37] young people that Dude, you do that. You
[40:41] just shot yourself in the foot.
[40:42] >> But but I think a lot of people hear you
[40:44] say this, right? And
[40:45] I think I've got a unique view as to
[40:47] I've got a lot of friends who they know
[40:48] nothing about finance, they know nothing
[40:50] about technology. These people work as
[40:52] about as average American, you know,
[40:54] lifestyle as you could imagine. They're
[40:55] very happy, right? Sometimes I think I'm
[40:57] even jealous of how how happy they are.
[41:00] But they would say, "Oh, Dan just
[41:02] doesn't want them to say what they
[41:03] actually think." On the other side,
[41:06] understanding what the data is showing
[41:07] us, that's what is a job growth is
[41:09] actually happening, etc.
[41:11] >> That's It's not what they think.
[41:14] It's what
[41:16] Talk about what AI is going to do to
[41:17] pharmaceutical in this country is more
[41:19] is brought into the US and the drug
[41:22] discovery that could happen with, you
[41:24] know, in when it comes to like pharma,
[41:26] biotech, and others. Talk about like how
[41:29] many town I've been all around the
[41:30] United States for 30 year. How many
[41:32] towns had 30,000 people now have 10,000
[41:36] because the factory left and it went to
[41:38] Mexico, Indonesia, wherever and now they
[41:40] have like education, drug issues,
[41:42] whatever in a lot of those towns about
[41:45] data centers,
[41:46] jobs,
[41:48] a renais- a retraining of the work for
[41:50] It's a renaissance in this in this
[41:51] country. So, that's why it's very like
[41:54] cool
[41:55] it's very like
[41:57] it's it's almost more not even as a
[41:59] stock perspective, but just as an
[42:00] American, I see the opportunity. Mhm.
[42:04] It's [clears throat] we're talking about
[42:05] like something that's generational
[42:08] that will I'm not talking about just
[42:09] like wealthy people making money on
[42:10] stock. I'm talking like this can do,
[42:12] democratization data. So, it's
[42:14] frustrating,
[42:16] more than frustrating, when I see these
[42:18] tech companies in these certain areas
[42:20] about job cuts and then guess what?
[42:23] Politics get involved, regulatory. You
[42:26] know how many politicians I saw at
[42:27] Milken?
[42:29] A lot. Okay? And what are they focused
[42:31] on? Regulatory, there's job
[42:33] They're not They're not just going to
[42:35] watch Mhm. this take place. That's why
[42:38] to me when the data centers have to get
[42:40] built, they're not built in the towns
[42:42] and approved,
[42:44] that's the thing that worries me the
[42:45] most.
[42:46] >> Is it fair to say that you think Dario
[42:47] is wrong when he says that all these
[42:49] jobs are going to get wiped out?
[42:50] >> 100%. Explain. Because the reality is is
[42:53] that like the view and you know, you
[42:57] could hear it from like major banks to
[42:59] marketing whatever, what's going to
[43:01] separate companies, the technology,
[43:03] there's massive efficiencies.
[43:05] But ultimately, the models over time are
[43:08] going to get more commoditized. You're
[43:09] going to have hundreds of models, LLMs,
[43:12] that will be across US, across the
[43:14] world. As that data set gets
[43:17] commoditized, what separates company A
[43:20] from B to C to D?
[43:21] It's the people. Surprise It's the
[43:23] engineering, it's the mark. So, the
[43:26] thing is to have that like dystopian
[43:28] type view, remember like what
[43:30] Anthropic's done is unbelievable.
[43:33] But you start that type of fear,
[43:38] that that's the thing they don't all of
[43:40] a sudden data centers don't get built.
[43:42] You have politicians get more focused on
[43:44] regulation of models. You start to go
[43:46] closer to Europe from a data privacy
[43:48] way. Meanwhile, China that point is like
[43:50] foot on the pedal going
[43:52] That's the thing that to me, that I
[43:55] worry about the most, is the
[43:57] self-created PR problem
[44:00] that a lot of big tech has done.
[44:03] And
[44:05] you know, I think that has to be course
[44:06] corrected. Otherwise, like that would be
[44:08] the thing that I fear the most. Data
[44:10] centers don't get built,
[44:12] then a lot of
[44:14] Yeah, we're we're in trouble. So,
[44:17] that to me is what I fear the most.
[44:19] >> Let's talk about Apple. I think Apple's
[44:21] one of those companies that people
[44:22] obviously respect as a big business that
[44:24] has been very successful. Tim Cook is
[44:26] stepping down, but I think a lot of
[44:27] people are looking at Apple saying,
[44:28] "Hey, what's your AI strategy? Are you
[44:30] guys behind?" How do you evaluate that
[44:32] business?
[44:32] >> Yeah, we behind, but I mean, 1.5 billion
[44:35] iPhones, 2.5 billion iOS devices. You
[44:38] don't have to be first when you have
[44:41] that. You could be late to the game cuz
[44:44] they they're almost uh
[44:47] they're thing about them, Mike, they're
[44:50] you know, on the highway, the US
[44:52] consumer highway, the global highway.
[44:55] They're basically a toll collector.
[44:57] They're going to get their share.
[44:59] The way 20% of the world is going to
[45:01] access AI through an Apple device.
[45:04] That's why WWDC in June is so important
[45:07] for them to launch that strategy with
[45:09] Gemini. Start to actually now make sure
[45:12] that they're not watching this game from
[45:15] the outside. And I think it's very
[45:17] important not get so caught up in
[45:20] narratives where these companies they're
[45:21] done. Google was done a year ago.
[45:24] Look at them now. So, I just think
[45:27] Apple's like a sleeping giant relative
[45:30] to where I believe they're going to be
[45:31] able to monetize in the consumer side.
[45:34] Cook was obviously surprised at the
[45:36] time, but when I look at Turnus, core
[45:39] Apple veteran and innovator, someone
[45:41] that I think would also double down
[45:43] services. So, it's a very important time
[45:45] for Apple, but watch that stock. I
[45:48] continue to think that that's probably
[45:50] the one as large cap, probably on large
[45:52] cap that probably the one that's like
[45:53] the most mispriced along with maybe
[45:56] Microsoft not being factored in. And so,
[45:58] I think the narrative for a while was
[46:00] like the big companies, they have
[46:01] distribution, they have data, they have
[46:03] you know, very large teams. They're
[46:04] going to get the bulk of the benefit
[46:06] from AI. Do you still believe that? I
[46:07] still believe that and I think that's
[46:09] why, but also those companies are
[46:11] shifting quickly.
[46:13] If you look like what's happening at
[46:15] Meta,
[46:16] you look what's happening at Amazon,
[46:18] I think they're also going to have to
[46:20] significantly like not just partner with
[46:23] the Anthropic to open AI's, like they're
[46:24] essentially going to build their own
[46:26] vertical stacks.
[46:27] The power,
[46:29] the data It goes back to like the Circa
[46:30] financing fears. They got to plant their
[46:33] flags with those partners. They got to
[46:35] create their own ecosystem.
[46:37] >> Mhm.
[46:38] But, it's democratization of data.
[46:41] There's There will be companies that we
[46:44] have never heard of 2 years from now.
[46:46] Could they be the next Anthropic? I
[46:48] think that speaks to the opportunity now
[46:51] that we see in this world. Let's talk
[46:54] about the ETF that you have. Um talk a
[46:56] little bit about like the portfolio
[46:57] construction cuz I think a lot of people
[46:59] they're convinced of the AI trade. And
[47:00] what they're trying to think about is
[47:02] should I have, you know, three to five
[47:03] stocks? Should I be diversified across
[47:05] the individual sectors? How should I
[47:07] think about rotating my capital? And
[47:09] some of them frankly I think just say,
[47:11] "Well, I don't know." And so is there
[47:13] some sort of external party that I can
[47:15] go and I put my capital with? So talk a
[47:16] little bit as to how you guys
[47:17] >> Yeah, and that's all based on like our
[47:19] research and it's managed separately
[47:20] from from the Wedbush side. Um but it's
[47:24] it's the AIVS AI 30. It's our research
[47:26] It's basically it's putting out on all
[47:28] of our clients that we started doing a
[47:31] year ago.
[47:32] Who are the 30 names that are going to
[47:35] benefit in AI? Derivative. From chips to
[47:39] software to
[47:41] infrastructure to cybersecurity soft and
[47:45] that, you know, every quarter we switch
[47:47] that out relative to some of the names
[47:49] the 30 that come in, some come out based
[47:51] on all the the data and the research
[47:54] that we do.
[47:55] And what I've liked about the the I was
[47:58] AI 30 research as well as the I was AI
[48:01] 30 power um that that we've come out
[48:04] with, it's trying to just give a road
[48:06] map to our clients, our investors, is
[48:10] it's not just about these one, two
[48:12] names. It's about you have to be able to
[48:15] figure out who the second, third, fourth
[48:16] derivatives are. Mhm.
[48:19] When you look at um so many of these
[48:21] investors are now taking control of
[48:23] their own capital and they're saying I'm
[48:24] not going to go to RIAs or to financial
[48:26] advisors. I want to invest myself. How
[48:29] do you see them using the AI tools to
[48:31] actually become better investors? Are
[48:33] there things you guys are doing
[48:34] internally on the research side? Are
[48:35] there things that you're seeing in
[48:36] conversations with people?
[48:38] >> I would just say like just obviously
[48:40] been in so many of conferences, RIA. I
[48:42] mean, the value of RIAs are extremely
[48:45] important, you know, base for so many
[48:47] people. And I also think like there's so
[48:49] many people like everyone could look
[48:50] like a genius when stuff. Then all of a
[48:53] sudden like you know, you hit choppy and
[48:55] this that's also where
[48:56] you know, like it's very it's a
[48:59] dangerous time, too.
[49:01] Look, I think
[49:02] there's there's a flattening of data.
[49:05] There's more information out there.
[49:07] But I think it comes down to like for
[49:09] investors, it's also making sure I
[49:11] diversify portfolio, making sure you
[49:13] understand risk. Because a lot people
[49:15] like they think they This is where like
[49:17] when you go back to like the
[49:18] Druckenmiller and
[49:20] the Buffets and the Paul Tudor Jones and
[49:23] the other
[49:24] they understand See,
[49:27] they there might be like names that
[49:29] they're bullish on and that don't work
[49:31] with. The thing with a lot of them, what
[49:33] it makes them so elite,
[49:36] and Steve Cohen among others, is that
[49:38] they understand risk. Risk is the key
[49:42] piece. So, they and that's something
[49:44] from an individual perspective, a lot of
[49:45] investors like I think they
[49:48] undercalculate or miscalculate or
[49:50] something is risk. Mhm. And then what
[49:52] about like just the NASDAQ as a beta,
[49:55] you know, to the market, right? It It
[49:57] seems like if you go back for the last
[49:59] 10 years, that's been a pretty good bet
[50:00] because you should have just bought the
[50:02] index and maybe didn't even have to do
[50:03] any work. Yeah, I mean like look, people
[50:05] do that, right?
[50:08] but and and and and I get it because it
[50:11] plays the broader view and I think it
[50:13] just depends on like what themes you
[50:16] want to play and how you want to do it
[50:18] and
[50:19] I think more and more younger people
[50:22] investing.
[50:24] More and more of the population is
[50:26] invested in terms of the market and I
[50:28] think that's a it's a positive thing
[50:31] because also like you want to see wealth
[50:33] creation,
[50:35] you know, across the board. That's to me
[50:38] what makes me happy when I see like
[50:41] you know, like when you hear about
[50:43] investors that
[50:45] you know,
[50:45] they can pay off their college loans or
[50:48] they pay off their house or whatever it
[50:50] is by being on the right side of it. I
[50:52] think that's like
[50:54] those are the things that bring me joy
[50:55] when I hear about them.
[50:57] All right, where can we send people to
[50:58] find you on the internet? Yeah, so you
[51:00] know, I'm on X, um DIYs Tech, LinkedIn,
[51:04] you know, I mean you know how to contact
[51:06] me. And look, we just try to just be
[51:09] like one like we do the work
[51:12] and we try to communicate that to our
[51:15] clients and investors because there's a
[51:17] lot of haters out there.
[51:20] And it's very important in these sort of
[51:24] market to just sometimes like have a a
[51:29] light in a dark tunnel sometimes and I
[51:31] think that's very important especially
[51:33] in a market that's very confusing. Do
[51:35] you have a book suggestion for anybody?
[51:38] I mean look, I'm more like I'm more of a
[51:42] historian when it comes to but sorry,
[51:45] you know, I read a lot about like, you
[51:46] know, American history and then world
[51:48] history. And and I the one that I will
[51:51] say like a lot of times in books that
[51:53] investors like, oh, this is like a you
[51:55] know, Liar's Poker or whatever, you
[51:56] know, like the typical like walk. I
[51:58] actually think a lot of times like
[51:59] understanding like history, whether it's
[52:02] US history, America, it actually gives
[52:05] you good perspective when you even
[52:07] triangulate with the market in terms of
[52:10] just understanding like different
[52:12] generations and and what what happened
[52:14] especially over the last, you know, 150,
[52:16] 200 years. Yeah, I like it. All right,
[52:18] thank you so much for doing this.
[52:20] Awesome. Great.