Is AI Taking Money & Attention Away From Bitcoin?

[0:00] Remember like 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. You
[0:10] 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] Meanwhile, China at that point is like
[0:18] foot on the pedal going. That's the
[0:20] thing that to me that I worry about the
[0:23] most is the self-created PR problem.
[0:27] What's going on guys? Today we've got a
[0:28] great conversation with Dan Ies. 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
[0:40] 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 Ies. Dan, let's start with
[1:02] SpaceX. Obviously, everyone is
[1:03] anticipating this IPO. It's supposed to
[1:05] be the biggest IPO in history. How do
[1:07] you view the positives and negative
[1:08] impact of this company coming public?
[1:10] >> Look, I mean, this is really it's
[1:12] defining what's going to be a new
[1:14] 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, the business
[1:28] components. Not necessarily we're
[1:29] talking like joy rides in space for, you
[1:32] know, 20 seconds. And it's really going
[1:35] to be almost a convergence of tech and
[1:39] this new sort of, you know, what I view
[1:41] as like like a spatial revolution. It
[1:45] all starts with SpaceX. But look,
[1:46] there's so many names like Planet Labs,
[1:49] Rocket Labs, Voyager, whatever. And this
[1:52] is just the start, but it comes down
[1:54] like for Musk, it's it's a watershed
[1:56] moment, not just for him, but what I
[2:00] view is kind of for the market. And
[2:02] really, it's starting to now create a
[2:04] whole another category in terms of what
[2:07] this is going to mean. So the company
[2:08] started off as just rocket launches and
[2:10] trying to make reusable rockets and
[2:12] cheaper uh launches, but now it went
[2:14] into satellites and then there's almost
[2:15] this like big promise of the orbital
[2:17] data centers and it seems like that's
[2:19] coming right at the time where everyone
[2:20] on Earth is like hey we may not have
[2:22] enough space or power or data centers
[2:24] and so how much of this is evaluating
[2:26] the existing business versus people
[2:28] buying into the future vision of what it
[2:30] could be?
[2:31] >> 80% of it future.
[2:33] >> Interesting. If you look at it
[2:36] currently, are you would you at two
[2:38] trillion or trillion and a half would
[2:39] you? No. In other words, it goes back to
[2:41] like what will this become? But then it
[2:45] comes down to like if you bought Intel
[2:48] when you know us put it stake. It wasn't
[2:51] just on that. It was like can they
[2:53] become a player in AI? With Nvidia, it
[2:57] wasn't just about like going after AI.
[2:59] like what eventually will happen if
[3:01] they're able to not just monetize
[3:03] enterprise but create physical AI when
[3:05] it comes to chips. So I think that
[3:07] continues to really be the focus for
[3:10] SpaceX because it's Musk and then we've
[3:12] talked about like we view it we've said
[3:15] 80% 85 that SpaceX to merge eventually
[3:20] with Tesla in 2027.
[3:23] >> Yeah. So you think 80 85% of SpaceX
[3:26] Tesla merging in 2027 not like just some
[3:28] point in the future but literally by
[3:29] next year
[3:29] >> because I think it's important that ju
[3:33] so just take a step back like why is
[3:35] there a trial Musk Alman this despite
[3:37] like personal beef and just all the
[3:40] things that have happened there I mean a
[3:42] lot of it really comes down to anthropic
[3:46] open AI then down here it's like XAI or
[3:49] SpaceX AI
[3:52] >> so now it's 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 different like biggest
[4:09] IPO ever.
[4:11] >> This would really create from a data
[4:14] perspective.
[4:15] should now be unmatched that I believe
[4:17] would enable Musk to really narrow the
[4:21] gap from a model perspective versus an
[4:23] anthropic open AI. It's hard to tell how
[4:25] much this is like a master plan that he
[4:27] had versus he's just uh going building
[4:29] these companies identifying areas that
[4:31] need to be solved and then expanding
[4:32] into them. But let's say these two
[4:34] companies do come together. It's I don't
[4:35] know Musk Industries or whatever you
[4:37] want to call it. But basically he's able
[4:39] to launch at a very low cost into space.
[4:42] So he can get both satellites and data
[4:44] centers up there. He then is able to use
[4:47] all the solar capabilities from Tesla
[4:49] and Solar City and all of that uh in
[4:51] space, capture the energy of the sun,
[4:54] create the compute in space in those
[4:56] orbital data centers, then beam it down
[4:58] via the satellite technology he has with
[5:00] Starlink and then he goes all the way to
[5:02] the end consumer where he is literally
[5:04] talking about humanoid robots and
[5:06] self-driving cars
[5:07] >> and crazy and that also tech companies
[5:11] whether it's Google and Microsoft tech
[5:13] companies ultimately How else are you
[5:16] getting a space
[5:18] >> like the the the Palm spaceship? Like
[5:20] the point is like
[5:21] >> never know. I mean with the new studio,
[5:23] but the point is like
[5:25] >> it comes down to like that will start to
[5:27] be you saw like from a technology
[5:29] partnership perspective in terms of
[5:31] where SpaceX is ultimately going and
[5:34] that's why I view SpaceX or just that
[5:37] broader sector as almost like second,
[5:39] third, fourth derivative plays off AI
[5:42] revolution that's happened in tech. I
[5:43] don't view them as separate and I
[5:45] actually think when you think about a
[5:47] theme being 5 10 15 year theme
[5:51] >> now one of the things I find interesting
[5:53] is there's so much like anti-AI
[5:55] narrative out there uh there's both the
[5:57] data centers which people are worried
[5:58] about electricity cost water noise you
[6:01] know environmental impact um I also
[6:03] think that there's maybe some distrust
[6:05] of oh I've heard this before of you're
[6:07] going to create jobs or economic
[6:08] activity uh at the same time there is a
[6:11] lot of just plain anti-AI narrative,
[6:13] right? Not even the data center stuff,
[6:15] just like I don't think this is good or
[6:16] I think this is going to take my job,
[6:18] etc.
[6:19] >> How do you think that we overcome that,
[6:22] right? Well, first off, I think a lot of
[6:24] it is actually self-created by the
[6:26] industry. When you have Daario from
[6:29] Anthropic saying 20 30% job loss,
[6:32] Mustafa from Microsoft saying like we're
[6:34] going to all white collar, you know,
[6:36] white collar sort of jobs are ultimately
[6:38] going to be, you know, done relative to
[6:41] AI in the next 18 months. Guess what?
[6:44] You do that, that's where you continue
[6:47] to go further and further down tonal
[6:49] pole when it comes to survey data
[6:50] because it comes down to the average US
[6:54] consumer.
[6:55] >> What's in it for me?
[6:56] >> I'm going to lose my job. My electricity
[6:58] bill is going to be higher. Huge PR
[7:00] issues. And guess what? When you create
[7:02] 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. You
[7:11] continue to do this. their hairs don't
[7:13] get built. So now you're not talking
[7:16] about like in our lifetime, you go back
[7:19] multiple lifetimes, like the only mean
[7:21] is polio, right? Can you cure cancer,
[7:24] dementia, Parkinson's with AI? That's
[7:26] obviously a huge positive. There's going
[7:28] to be more data centers, you know, that
[7:30] are built today than active data
[7:32] centers. The jobs, the ripple effect,
[7:34] the restaurants, so many towns
[7:36] throughout the US, but that's not being
[7:39] talked about. A lot of it is PR issues
[7:44] that you can and I've told some of these
[7:46] companies like that can never talk
[7:50] externally because that is a negative
[7:52] for the industry and I think that a lot
[7:54] of it is self-grade there's fear AI fear
[7:58] and that's why you saw like with the
[8:00] Schmidt like the commencement speech and
[8:02] the booing yeah of course if you're a co
[8:04] I speak in many colleges around the
[8:06] country I would tell people like there's
[8:08] going to be more jobs over the coming
[8:10] years created but right now it is a huge
[8:13] issue.
[8:14] >> What's fascinating to me is I saw iron
[8:16] you know the data center provider and
[8:18] power generation company they just
[8:20] bought a marketing and uh kind of
[8:22] branding studio and I've got to imagine
[8:25] that is specifically because they
[8:26] realize that a huge part of the future
[8:28] success of their business is going to
[8:30] come down to how do they communicate to
[8:31] local communities or local uh
[8:33] politicians about what they're trying to
[8:34] do
[8:35] >> 100%. And then also it's like let's say
[8:38] Pop Industries. Okay, company all of a
[8:42] sudden like get everyone together in all
[8:44] hands meeting. We're we're we're going
[8:46] to launch Claude as a test trial run.
[8:50] What does the average consumer or the
[8:52] average person at that company think?
[8:55] Does that mean my job's at risk? No.
[8:56] See, that's part of the problem. You
[8:58] need companies be like efficiency,
[9:01] monetization, how we're going to be able
[9:02] to do it. That's a huge part of the
[9:05] 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 China
[9:20] but they need they need to get their act
[9:22] together broader tech in terms of the
[9:25] communication ironically like when you
[9:27] look at like what's going on I think a
[9:30] lot of that
[9:32] 78% of that is selfcreated and you
[9:35] create the narrative. You don't go on 60
[9:38] Minutes to, you know, you know, talk
[9:42] about a cartoon, right? Like the point
[9:43] is like when you go on there and you
[9:45] scare people like Daario did, that's
[9:46] that's part of the issue.
[9:48] >> Yeah. It's so fascinating because one of
[9:49] the things that I'm very focused on is
[9:51] showing people how do you connect the
[9:52] adoption of artificial intelligence
[9:54] product to you making more money. And my
[9:56] whole theory has been if everyone is
[9:59] telling you you're going to lose your
[10:00] job, there's all these negative impact,
[10:02] 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] Sylvia that we built it. People go to
[10:13] cfosilia.com, they attach their
[10:15] portfolio, they start talking to an
[10:17] artificial intelligence model that is
[10:19] personalized to their portfolio. And we
[10:21] see in the data, the more they talk to
[10:22] it, the faster their net worth grows.
[10:24] 70% is and I was giving 70% of the use
[10:27] cases that we see on enterprise are
[10:30] monetization revenue enhance they're not
[10:32] cost cut the now look there's going to
[10:35] be a lot of companies they use it as
[10:37] kind of like to whitewash right be like
[10:39] we're going to
[10:40] >> do you believe the CEOs who are saying
[10:42] they're firing people because AI
[10:44] >> 20% of it
[10:45] >> 20% so 80% of the CEOs who say they're
[10:47] firing someone because of AI is actually
[10:49] just overhiring or mismanagement
[10:50] previously
[10:51] >> whatever it's like the point is like but
[10:52] guess what Like if eventually models
[10:55] become commoditized.
[10:56] >> Mhm.
[10:57] >> If company A has the same model as
[10:58] company B, C, D, what differentiates it?
[11:01] It's what goes up and down the elevator
[11:03] every day. It's the engineering town.
[11:04] It's the product. So the point is like
[11:06] you're going to see a lot of companies
[11:07] that went way over. And we're not
[11:09] talking about big tech where these
[11:11] companies 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
[11:21] reality versus you know fiction. The
[11:24] point is like this is something from a
[11:26] productivity perspective to monetization
[11:29] to the jobs ultimately that will be
[11:31] created from data centers from buildout
[11:33] from new companies. You could be a 23
[11:35] year old right now you don't need 20 30
[11:37] million of seed capital you got quad you
[11:39] have an engineer or two who knows what
[11:41] you could build. democratization that's
[11:43] happening across the board and for the
[11:45] first time in 30 years US is ahead of
[11:47] China when it comes to tech which is
[11:49] very very important in terms of what
[11:52] this all 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
[11:58] >> I mean a lot of it comes down to what
[12:00] there's one chip in the world fueling
[12:01] the AI revolution it's godfather of AI
[12:04] genvidia a third rate Nvidia chip is a
[12:07] year and a half two years ahead of
[12:08] Huawei like an H200
[12:11] when you Think about anthropic, the
[12:14] hyperscalers, the software, palenteer
[12:17] among you look when you go to China,
[12:20] robotics, they're leading.
[12:22] >> Mhm.
[12:23] >> Power because of nuclear, they're
[12:26] leading.
[12:27] That's where it kind of stops. So you
[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
[12:36] generation, but you think that the
[12:37] United States is winning in terms of the
[12:38] models and the software,
[12:39] >> the models, the software and the chips.
[12:42] That's also why like when Trump and she
[12:44] meet, they recognize I need you, you
[12:46] need me. Cuz guess what? Middle East,
[12:49] India, you know, obviously everyone's
[12:51] trying to think who's going to be the
[12:52] number three player. This is third
[12:55] 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
[13:02] it speaks to my overall like bull thesis
[13:04] and we've talked about it is that you're
[13:07] going to go through these whether it's
[13:09] liberation day Iran 10year wars coming
[13:14] in
[13:15] >> whatever but the reality is like we this
[13:18] is a multi-year bull market relative to
[13:21] what's happening in tax but also it's
[13:23] the derivatives cuz that will go across
[13:26] financials healthcare utility companies
[13:29] like what they're trading at this
[13:30] because now all of a sudden it's not
[13:32] necessarily a utility company. It's a
[13:33] derivative of AI multiple is going to
[13:35] increase across the board. Those
[13:37] companies that don't embrace it, dude.
[13:39] Typewriters, they're epic. This computer
[13:42] thing is a joke. Dude, that was doing
[13:44] horses back before Mile T. Yo, this
[13:46] whole car thing is a joke. The point is
[13:48] like that will play itself out for those
[13:51] companies.
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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 AI,
[15:08] the uh electronics, right? We we've seen
[15:10] some of these companies, obviously
[15:12] Tesla's got their humanoid robot. Um but
[15:14] also people kind of forget that there's
[15:16] an entire self-driving car revolution.
[15:18] And 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 semiis
[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
[15:38] to interact with like robotics is
[15:40] actually in self-driving cars?
[15:41] >> Yeah. So, and even take a step further
[15:43] back like the average consumer. Okay.
[15:46] you've played around with Chow GBT
[15:49] anthropic different models but where it
[15:52] all will start like when Apple
[15:54] ultimately releases the Gemini in terms
[15:56] of the model that that will be on you
[15:58] know um at WWDC that'll be the start of
[16:01] what's going to happen like eventually
[16:03] miles will be on the phone
[16:05] >> storage applications are going to get
[16:07] built AI driven applications healthcare
[16:10] financials fitness across the board so
[16:14] that's where you're going to see more
[16:15] and more use from consumer perspective
[16:17] but when it comes to physical AI it's
[16:19] autonomous I mean that will be the first
[16:24] true interaction with a and there some
[16:26] obviously have done wayos and different
[16:28] cities but that's why Tesla and robo tax
[16:30] is so important but then also it comes
[16:33] down to like regulatory because
[16:35] regulatory right now it's state
[16:39] >> 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 that's
[16:46] a huge missing piece versus what we see
[16:48] in China.
[16:49] >> One of the things people are excited
[16:50] about at the federal government level,
[16:52] but also there's a lot of critiques
[16:53] about are there are a lot of
[16:54] technologist and private sector
[16:56] individuals who have gone into the
[16:58] federal government. And so I think that
[16:59] the people who are excited about this
[17:00] would argue, hey, these people
[17:01] understand the technology. They
[17:03] understand kind of how important private
[17:04] industry is and they are trying to
[17:06] streamline, get rid of waste and
[17:08] accelerate a lot of the innovation
[17:10] industries. On the other hand, I think
[17:12] that the critiques are, hey, there's a
[17:13] bunch of 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
[17:18] know, kind of uh complexities of them
[17:20] being involved. Given that Trump now has
[17:23] just about two years left in office, is
[17:25] this a thing where if we have a pro-
[17:27] innovation, pro technology
[17:29] administration, they should accelerate
[17:31] and get as much of this done as they
[17:32] possibly can from a regulation
[17:33] standpoint because there's a worry that
[17:35] maybe the next administration won't be
[17:37] as friendly or do you think that this
[17:38] has now reached a point where it doesn't
[17:40] matter, you know, red or uh blue's in
[17:43] office, it's going to be people
[17:45] embracing technology. Look, I think
[17:47] people are going to embrace technology,
[17:49] but it is ve political,
[17:52] >> you know, sort of navigation is very
[17:54] important because
[17:56] it goes back to like you need a
[17:58] pro-inovation
[18:01] administration
[18:02] >> and that's why like when you see Jensen
[18:04] and Cook and Musk and obviously the
[18:06] other CEOs in the China trip, I view
[18:08] that as bullish. They understand
[18:09] technology as well best perch in the
[18:11] world. If you start to put, you know,
[18:15] sand in the gears and slow it down, look
[18:18] at Europe. They're building blockbuster
[18:20] videos there because of regulatory,
[18:24] because of, you know, just worry about
[18:26] data private. And I see the frustration
[18:28] firsthand in Europe because like if
[18:30] you're an innovator, entrepreneur
[18:33] a lot in Europe, it's like do you have
[18:35] to move to Middle East, US,
[18:38] >> Mhm.
[18:38] >> you know, Asia. So it's very important.
[18:41] it's foot on the pedal on AI. Guess
[18:46] what? Cuz look at China and you fall
[18:49] behind. But then a key part of that is
[18:51] data centers. That's why it all kind of
[18:54] goes what we start started to talk about
[18:56] is like when you go like anti-data
[18:58] center because of PR protest
[19:02] demonstrations. I love a I love data
[19:04] centers just not in my backyard.
[19:06] That's a huge piece because guess what?
[19:09] the way this is all works it's data
[19:12] without data centers it's the hearts and
[19:14] lungs of AI
[19:15] >> so it just it all kind of factors into
[19:18] what's going on here it'll be a a big
[19:21] thing in terms of the midterms and of
[19:23] course you know when we go into like you
[19:25] know presidential election but this is
[19:27] like a key time because I just keep
[19:30] going back to like so much of my life
[19:33] spent time like in Asia you know you're
[19:36] in Taiwan you see the fabs you see the
[19:39] efficiency you see, you know, and then
[19:42] you come back here like I was like land
[19:45] in New York airport, go to Dunk and
[19:47] Donuts and there's like a fist fight at
[19:49] Dunk and Donuts and then you wonder why
[19:50] I was 17th in math. So the point is like
[19:53] now for the first time we're ahead. Now
[19:56] when we think about um so much of this
[19:59] industry accelerating that's great to
[20:01] talk about the fundamentals and the
[20:02] trends and the adoption, but people
[20:04] ultimately want to know how do I make
[20:05] money? And so if we go and we look in
[20:06] the public market, there seems to be um
[20:09] you know kind of the hyperscalers,
[20:10] there's some very large tech companies,
[20:12] but now most of the conversation is
[20:14] about going and finding which companies
[20:15] can be the release valve for various
[20:17] shortage pressure. So whether it's
[20:19] memories or chips or you know etc. Just
[20:21] walk 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. And then on the other hand, look
[20:34] what's happened with software. So to me,
[20:36] it all starts with like chips
[20:40] at the epicenter. Of course, it's been
[20:42] Nvidia, but then you have to think, so
[20:44] I'm just like walking you through. It's
[20:45] like, okay, like Meta for every 10 chips
[20:49] they need, Nvidia is going to give them
[20:51] three because of supply. Where are they
[20:53] get the others? Is it Google? What about
[20:56] AMD? What about Intel? What about where
[20:59] Micron plays? Sandis the memory the
[21:02] components you have to think about it
[21:04] like it's all p it's all a puzzle
[21:06] >> and all the work we do is what is the
[21:09] man's pie look like in memory then it's
[21:12] a super cycle are there multiples that
[21:14] are high relative to historical yeah but
[21:17] street 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 GOV an iron like where who are the
[21:27] ultimate players that maybe investors
[21:29] aren't seeing
[21:31] But then there are trades when it comes
[21:33] to like the street gets wrong but
[21:36] they're opportunities. I'll just give
[21:38] you example like
[21:40] we're at RSA conference in March you
[21:43] know in San Francisco that's where like
[21:45] anthropic mythos comes out the view like
[21:50] anthrop is going to eat cyber security
[21:52] going to eat software but that that was
[21:55] a narrative that if you talk to
[21:57] customers you know it's wrong look at
[22:01] crowd strike stock today versus where it
[22:03] was in March look at powa it's a good
[22:06] example of like narratives create
[22:10] opportunities if you do the work.
[22:12] >> You go back a year ago, New York City
[22:14] cab drivers bearish an alphabet. DOJ is
[22:17] going to break it up. AI is going to
[22:18] crush search. Gemini is nowhere. Now
[22:21] look, victory parties. I'm just trying
[22:24] to explain in this market,
[22:27] it it's a multi-year bull market. We're
[22:31] in year three of a 10-year buildout of
[22:33] AI. And it's very important to like try
[22:37] to pick who the winners are do the work
[22:40] because I think that's how you're able
[22:42] to ultimately make money in these
[22:44] markets.
[22:45] >> What do you look at like a Bill Aman
[22:46] buying Microsoft and basically saying
[22:48] look we still think this is an amazing
[22:50] company that's just dislocated from
[22:51] price and value and therefore we're
[22:53] going to go and put a position on.
[22:54] couldn't agree more because that's
[22:56] because then it comes down to like
[22:58] Microsoft basically every enterprise in
[23:01] the world runs on Microsoft as they move
[23:03] to AI as they move to Azure as I believe
[23:07] Nadella one of the best CEOs out there
[23:09] co-pilot has been under you know
[23:12] underwhelming yeah are they training
[23:14] wheels with open AI yeah is there a lot
[23:16] of noise yeah but I like we've talked
[23:19] about like stock closer to 400 I think
[23:21] it's worth closer to 550 to 600 and But
[23:24] that's a good example of like you have
[23:27] to be able to see around corners in this
[23:30] market. And then whether it's liberation
[23:33] day, I ran oil wars coming in 30 hitting
[23:38] a certain level, yen, what you have to
[23:41] be 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
[23:56] may look at the last 6 months or 12
[23:57] months performance, be like, "Wow, it's
[23:58] up a lot already." And so I'll give you
[24:00] some examples. Micron's up 67 800%. Uh
[24:04] company like Marll is up 100% in 6
[24:06] months. And so I hear people talking
[24:08] about I'm interested in this company. I
[24:10] think they solve part of the problem for
[24:13] XYZ, you know, part of the industry or a
[24:15] shortage. I'm just really nervous at
[24:16] buying in at 100% higher than it was six
[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. Everyone heads for the elevators.
[24:25] You're waiting like you're that. So it's
[24:27] like that fear definitely is there. But
[24:30] then I give you like on the other side
[24:32] you have it on the whiteboard. You
[24:34] didn't own it. Stock gets hit.
[24:37] Fall knife. Stock gets hit again. Ah
[24:40] it's done. Negative sentiment. Whatever.
[24:43] It's very easy to miss the
[24:47] >> but go back to March in terms of like
[24:51] where did Nvidia go in Iran look I
[24:54] remember like being in Miami early March
[24:57] I'm speaking at a conference and
[25:01] you know sentiment so negative because
[25:04] like the Iran thing oils
[25:07] tra and I remember like people like
[25:09] taking pictures in South Beach like oh I
[25:11] can't believe people They don't realize
[25:13] the longer. I'm like, "Yo, I've done
[25:16] this since like late night." You start
[25:18] to go down that path, you'll miss in
[25:20] every geopolitical, you'll miss every
[25:23] sort of opportunity.
[25:25] And look at where their stock traded
[25:27] first week or two of March.
[25:29] >> Mhm. And it's May. Again, we're not
[25:32] talking like 10 years ago.
[25:34] >> 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 Round Hill go and launch the uh DRAM
[25:42] or the memory ETF. Uh they had $10
[25:44] billion get added in like two months. Um
[25:47] and a huge part of that was just they
[25:48] gave access to American investors to
[25:50] certain companies that they couldn't
[25:51] otherwise do. And so, uh how do does
[25:53] that play out? Do we just get
[25:54] consolidation where you're going to see
[25:56] more and more ADRs or ETFs with swaps
[25:58] and things where American investors are
[26:00] going to be able to really invest
[26:01] globally, but it's going to be through
[26:03] American vehicles? Look, you it's a
[26:06] democratization of investing,
[26:08] democratization of information flow.
[26:12] People want access to how they could
[26:15] play certain themes.
[26:16] >> Mhm.
[26:17] >> And that's what that does, right? And
[26:19] obviously there's the active manage
[26:20] piece as well, you know, in terms of
[26:22] like, you know, depending on who it is,
[26:24] 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. And I just see it
[26:33] traveling the world like my
[26:35] conversations with people in Europe,
[26:38] Asia, Australia, Africa, whatever,
[26:40] Middle East are very similar a lot of
[26:43] times to like you know somewhere in
[26:45] Midtown Manhattan.
[26:46] >> So that's the opportunity where
[26:48] investors want to play a lot of the
[26:50] global theme.
[26:51] >> Mhm. Now, how do you think about the
[26:53] experienced investors take the Stanley
[26:55] Ducken Millers kind of the legends of
[26:56] Wall Street? They seem to be all over
[26:58] this trend rightfully so. Uh Paul Tudtor
[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
[27:16] 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 like drunk Miller at one point
[27:22] was like in his 20s. Like Buffett at one
[27:25] point was in his to like you I don't
[27:28] 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
[27:37] believe there's so much value with
[27:40] experience that I think investors
[27:43] poo poo sometimes. But then on the other
[27:46] hand, there's different ways of
[27:47] understanding this market where you can
[27:50] discount newer investors that have had
[27:53] huge track record because I could go
[27:55] back my whole career and investors being
[27:58] like, you know, who's this hedge fund or
[28:01] Tiger or whatever. Now I could like you
[28:04] could go back to like, you know, the
[28:05] legit whether it's Cohen or others and
[28:08] and what they did, but at one point they
[28:12] had to prove it. And I just think in a
[28:13] market like this, you have to digest all
[28:16] the information
[28:18] and it's ultimately it's ones that you
[28:21] think from an from a PM perspective or
[28:24] an investor perspective.
[28:26] You take that into your process to help
[28:30] you,
[28:31] you know, pick ultimately the winners,
[28:33] good or bad. So we know that the AI
[28:36] trade has been working. Investors are
[28:37] very 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
[28:49] oil spike, energy prices go up, uh you
[28:52] get this kind of persistent inflation
[28:53] risk and we have a new Fed chairman
[28:55] that's coming in and now people are
[28:57] saying, hey, maybe 6 months ago we were
[28:59] all advocating for rate cuts and we
[29:02] really 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 Tom Lee talks about like the first
[29:16] like 3 to 6 months when a new Fed chair
[29:18] comes in like stock markets down like
[29:20] the first 3 to 6 months x%. So it's like
[29:23] you know it tends to be like a
[29:25] readjustment for the market. Look, he's
[29:28] coming in at such a complex time because
[29:30] of where the 10year what we see happen
[29:32] in Japan, what you know, obviously what
[29:34] we see in terms of the UK and then
[29:37] because of oil and this sort of like you
[29:40] know impass relative to Iran and what
[29:42] we're what we're seeing here. I just
[29:45] think it's going to be a volatile period
[29:49] and we could have selloffs based on what
[29:53] War says getting used to him and his
[29:55] sort of wording and is there sort of
[29:57] tightening. But I do believe like this
[30:01] will be ultimately a temporary
[30:04] sit relative to oil and then he'll have
[30:07] more flexibility on the other side to
[30:10] cut. And I just think as a Trump
[30:12] appointee, I just cannot believe wars
[30:15] comes in as some hawk. That's sort of
[30:17] like my view. But look, but the market's
[30:20] going to adjust to it. But as the market
[30:22] adjusts, the geopolitical
[30:24] and Fed and other issues that happen
[30:27] from a macro perspective, you cannot
[30:30] lose sight of what's happening
[30:33] >> in terms of in terms of the tech trade.
[30:35] Now, one of the other areas I find very
[30:37] fascinating is I look at artificial
[30:39] intelligence, Bitcoin, robotics, you
[30:41] know, all this stuff is just really the
[30:42] age of 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] because I was an investor from the
[30:54] private market, but they basically said,
[30:56] look, how do we automate a huge part of
[30:58] the heliloc market and then the
[30:59] secondary trading of these assets and
[31:01] the securization, 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 do
[31:15] you look at that bucket of companies
[31:17] which they may not actually fall in the
[31:19] pure AI trade and they may not fall in
[31:20] the pure like crypto trade either but
[31:23] there's a modernization that's happening
[31:25] right and I think like you see the world
[31:28] adjusting to these technologies and I
[31:31] think it's something where it's going to
[31:34] make companies just that much more
[31:36] efficient but also there's going to be
[31:39] software that comes in and it's wakeup
[31:42] calls for different companies that's
[31:43] going to create their own proprietary
[31:45] technology with their people and that's
[31:48] going to make them that much better. So
[31:50] I think it's an arms race that's playing
[31:53] going on between Numa's new AI tech
[31:59] versus traditional. I think that's been
[32:00] from I think if there's an best example
[32:03] would be SAS apocalypse software service
[32:06] now Salesforce Oracle workday where they
[32:10] sit 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 wakeup call for Benny offer sales
[32:20] force like what they're going to have to
[32:22] do but I think also the view that these
[32:25] models are broken or the new kid on the
[32:28] block is going
[32:30] change, you know, whether it's Wall
[32:31] Street or whether it's corporate
[32:33] America, those are also easier said than
[32:36] done. And I think it's just it's all
[32:37] part of like who are the winners and
[32:41] trying to discount what's baked into the
[32:43] stocks at the end of the day.
[32:45] >> Now, as we see this all play out,
[32:47] another question that I think
[32:48] immediately people look at is something
[32:49] like Bitcoin. And we've seen Bitcoin
[32:51] actually operate, I think, a little bit
[32:53] differently than people thought it was
[32:54] going to. So, since the Iran war, it's
[32:56] up, not down. uh over the last 90 days
[32:58] or so it's up about 15%. It's up, you
[33:01] know, at more than gold and S&P over the
[33:03] last three years, but it's also
[33:05] struggled over the last year. And so
[33:06] kind of you can pick different time
[33:08] frames and you can twist the data to
[33:10] tell different stories.
[33:12] >> One thing I think a lot of critics would
[33:13] argue is that there is a tension in
[33:15] capital that is being diverted from
[33:17] Bitcoin to the AI trade. And so how do
[33:20] you look at the relationship between
[33:21] >> that's a I was literally going to I
[33:23] think that's you think what
[33:25] >> exactly that like I think risk assets
[33:29] if you have a dollar do you put it in
[33:32] this bucket this bucket or this bucket
[33:35] and I think that
[33:38] 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 because when it comes to like
[33:48] the AI I trade and what's happened in
[33:50] TAC and the level of disruption it's
[33:54] we're talking like a once in like
[33:57] 100year type of cycle.
[34:00] >> Mhm. So I think investors whether it's
[34:02] FOMO whatever it's like okay do I want
[34:04] to
[34:06] invest here where maybe I can make
[34:08] whatever
[34:10] 15 20% or you know whatever wherever you
[34:12] think that goes whereas here that's
[34:15] where some of the
[34:18] generational names but it's all
[34:20] relative. You could pick the wrong name
[34:23] here
[34:24] >> and then you're like I should have
[34:26] stayed in crypto.
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[36:50] check them out today. Do you think that
[36:52] uh this is just mere momentum and so you
[36:54] know kind of crypto or or Bitcoin in
[36:56] particular had momentum in 2020 through
[36:58] 2022 then people kind of rotated over to
[37:01] AI and it comes back. I think it's a
[37:03] pendulum. I think these things like look
[37:06] crypto is not going anywhere like it's
[37:08] going to continue to be I think among
[37:09] many like a part of their like portfolio
[37:13] >> but I think you're going to go in you go
[37:15] in pendulum shifts and I think as part
[37:17] of the pendulum shifts it's very easy to
[37:19] get caught up in those narratives I
[37:21] could say like a big pendulum shift for
[37:24] a while if you go back like in November
[37:26] is a tech trade done
[37:28] >> is there a rotation is it financials
[37:30] that are going to lead is it you know
[37:32] traditional industrial Look at like
[37:34] Walmart's multiple relative to Amazon.
[37:37] I'm just saying like that's another
[37:38] example of like think about that
[37:41] narrative.
[37:41] >> Mhm.
[37:42] >> So I think it's also you cannot get so
[37:45] caught up in narratives. You have to be
[37:48] able to whether it's individually or for
[37:51] you know whoever is investing to figure
[37:54] out what's the one that makes 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
[38:01] you saw that maybe is different than the
[38:02] public narrative. Um you went to Asia
[38:04] and spent a couple of weeks there. Uh
[38:06] talk a little bit maybe about going to
[38:07] the fabs in Taiwan and what you learned
[38:09] on this entire trip.
[38:10] >> I mean to me it's like that's how you're
[38:12] b that's how like we are so bullish in
[38:15] like memory and chips and you know this
[38:18] is before earning season but it's like
[38:20] it's why like a lot of times people be
[38:22] like oh you're so bull bullish no matter
[38:24] what. I'm like, "No, dude." Like, cuz
[38:26] you're bearish sitting in your, you
[38:29] know, like on Metro North or in, you
[38:31] know, 35th floor in your New York City
[38:34] office building, but you're just bearish
[38:36] based on narratives, people in your
[38:39] circle and spreadsheets.
[38:41] >> If I see the demand in Asia, that's what
[38:44] makes me bullish. Mhm.
[38:46] >> Like when you say you see the demand
[38:48] >> because you see chip demand, you see
[38:49] what's happen in terms of production,
[38:51] you see the you see the supply, you see
[38:53] the component issues, you you have a
[38:55] better understand what's happening
[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 on
[39:09] budget, whether it's cyber security,
[39:11] whether it's software, whether it's
[39:13] broader tech infrastructure.
[39:15] That's why I think those trips are so
[39:17] important. Then even like you know been
[39:19] in Europe a few times and different
[39:21] trips and like I could tell you like
[39:24] just came back from Poland like the
[39:26] 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 seeing
[39:32] in Eastern Europe
[39:35] AI really just starting to get started.
[39:38] 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
[39:44] maybe even France but that continent is
[39:47] not just a zero in terms of opportunity
[39:51] at one point when they wake up and
[39:54] regulatory whatever pushes back there's
[39:57] going to be massive opportunities so I
[39:59] think investors trying to figure out
[40:00] like where the opportunities are
[40:03] specifically when it comes to either
[40:04] tech or defense tech
[40:06] >> 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 they're uh maybe
[40:12] misplaced. My biggest concern goes back
[40:15] to how we started this is that tech
[40:18] companies it's about them tripping over
[40:21] their own shoelace
[40:23] having the hubris talking about job cuts
[40:27] like it's like not reading the room
[40:29] saying that their technology is going to
[40:31] you know is going to wipe out whether
[40:33] it's lawyers you know different areas
[40:36] and financials for young people that
[40:39] dude you do that you just shot yourself
[40:42] in the But but I think a lot of people
[40:43] hear you say this, right? And um I think
[40:46] I've got a unique view as to I've got a
[40:48] lot of friends who they know nothing
[40:49] about finance. They know nothing about
[40:50] technology. These people work as about
[40:52] as average American, you know, lifestyle
[40:55] as you could imagine. They're very
[40:56] happy, right? Sometimes I think I'm even
[40:57] jealous of how how happy they are. But
[41:00] they would say, "Oh, Dan just doesn't
[41:02] want them to say what they actually
[41:04] think." On the other side, understanding
[41:06] what the data is showing us,
[41:08] >> that's what is that job growth is
[41:10] actually happening, etc. That's it's not
[41:12] what they think it's what talk about
[41:16] what AI is going to do to pharmaceutical
[41:18] in this country is more is brought into
[41:20] the US and the drug discovery that could
[41:23] happen with you know in when it comes to
[41:25] like pharma biotech and others talk
[41:28] about like how many towns I've been all
[41:30] around the United States for 30 years
[41:32] how many towns had 30,000 people now
[41:35] have 10,000 because the factory left and
[41:38] it went to Mexico Indonesia wherever and
[41:40] Now they have like education, drug
[41:42] issues, whatever in a lot of those
[41:43] towns, data centers, jobs, a ren a
[41:48] retraining of the workforce. It's a
[41:50] renaissance in this in this country. So
[41:53] that's why it's very like 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.
[42:03] >> Mhm. It's we're talking about like
[42:05] something that's generational that will
[42:08] I'm not talking about just like wealthy
[42:10] people making money on stocks. I'm
[42:11] talking like what this can do
[42:12] democratization data. So it's
[42:15] frustrating
[42:16] more than frustrating when I see these
[42:18] tech companies in these certain
[42:20] narratives about job cuts and guess what
[42:23] politics get involved regulatory. You
[42:26] know how many politicians I saw at
[42:28] Milin? A lot. Okay. And what do they
[42:31] focus on? Regulatory. this job grow.
[42:34] They're not they're not just going to
[42:35] watch
[42:36] >> this take place. That's why it's
[42:38] important and then data centers have to
[42:40] get built. If they're not built in the
[42:42] towns 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 Daario
[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 from like major banks to
[42:59] market to 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 commodized you're
[43:09] going to have hundreds of models LLMs
[43:12] that will be across US across the world
[43:15] as that data set gets commoditized what
[43:19] separates company A from B to P to D
[43:21] it's the people
[43:23] >> surprise it's engineering it's the mark
[43:25] so the thing is to have that like
[43:28] dystopian type view remember like what
[43:30] anthropics done is unbelievable
[43:33] but you start that type of fear
[43:38] then that's the thing then all of a
[43:40] sudden data centers don't get built you
[43:42] have politicians get more focused on
[43:44] regulation of models you start to go
[43:46] closer to Europe from a data privacy
[43:49] meanwhile China that point is like foot
[43:51] on the pedal going that's the thing that
[43:54] to me that I worry about the most is the
[43:57] self-created PR problem that a lot of
[44:01] big tech has done and you know I think
[44:05] that has to be course corrected
[44:07] otherwise like that would be the thing
[44:08] that I fear the most data centers don't
[44:10] get built
[44:12] >> then a lot of yeah we're we're in
[44:15] trouble so that to me is what I fear the
[44:19] most let's talk about Apple. I think
[44:20] Apple's one of those companies that
[44:22] people obviously respect as a big
[44:23] business that has been very successful.
[44:25] Uh Tim Cook is stepping down, but I
[44:27] think a lot of people are looking at
[44:28] Apple saying, "Hey, what's your AI
[44:29] strategy? Are you guys behind?" How do
[44:31] you evaluate that business?
[44:32] >> Yeah, way behind. But I mean, 1.5
[44:35] billion iPhones, 2.5 billion iOS
[44:37] devices. You don't have to be first when
[44:40] you have that. You could be late to the
[44:43] game cuz they they're almost
[44:47] they're think about them like 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. The
[44:59] way 20% of the world is going to access
[45:02] AI is through an Apple device. That's
[45:04] why WWDC in June is so important for
[45:07] 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 to not get so caught up in
[45:20] narratives where these companies they're
[45:22] done. Google was done a year ago.
[45:25] >> Look at them now. So I just think Apple
[45:27] is like a sleeping giant relative to
[45:30] where I believe they're going to be able
[45:32] to monetize in the consumer side. Cook
[45:34] it was obviously surprised at the time
[45:37] but when I look at turnis core Apple
[45:39] veteran an innovator someone that I
[45:42] think will also double down services. So
[45:44] it's a very important time for Apple but
[45:47] watch that stock. I continue to think
[45:49] that that's probably the one is large
[45:51] cap probably on large cap probably the
[45:53] one that's like the most mispriced along
[45:55] with maybe Microsoft not being factored
[45:58] in. And so I think the narrative for a
[45:59] while was like the big companies, they
[46:01] have distribution, they have data, they
[46:03] have, you know, very large teams,
[46:04] they're going to get the bulk of the
[46:05] benefit from AI. Do you still believe
[46:07] that?
[46:07] >> I still believe that. And I think that's
[46:09] why, but also those companies are
[46:12] shifting quickly. If you look like
[46:14] what's happened at Meta, you look what's
[46:17] happened in Amazon, I think they're also
[46:19] going to have to significantly like not
[46:22] just partner with the anthropic open AI,
[46:24] like they're essentially going to build
[46:25] their own vertical stacks. the power the
[46:29] D it goes back to the circular financing
[46:31] fears they got to plant their flags with
[46:34] those part they got to create their own
[46:36] ecosystem
[46:38] >> but it's democratization of data there's
[46:42] there will be companies that we have
[46:44] never heard of two years from now could
[46:46] they be the next anthropic I think that
[46:49] speaks to the opportunity now that we
[46:52] see in this world let's talk about the
[46:54] ETF that you have um talk a little bit
[46:56] about like the portfolio construction
[46:58] because I think a lot of people they're
[46:59] convinced of the AI trade and what
[47:01] they're trying to think about is should
[47:02] I have you know three to five stocks
[47:04] should I be diversified across the
[47:06] individual sectors how should I think
[47:07] about rotating my capital and some of
[47:09] them frankly I think just say well I
[47:12] don't know and so is there some sort of
[47:14] external party that I can go and I put
[47:15] my capital with so talk a little bit as
[47:17] to how you guys
[47:17] >> Yeah and that's all based on like our
[47:19] research you know it's managed
[47:20] separately from from the Wedbush side um
[47:23] but it's it's the Ives AI30 it's our
[47:26] research It's basically it's putting out
[47:28] and all of our clients that we started
[47:31] do a year ago who are the 30 names that
[47:35] are going to benefit in AI derivative
[47:38] from chips to software to infrastructure
[47:43] to cyber security software and that you
[47:45] know every quarter we switch that out
[47:47] relative to some of the names 30 that
[47:49] come in some come out based on all the
[47:52] the data and the research that we do and
[47:55] what I've liked about the the Ives AI30
[47:59] research as well as the Ives AI30 power
[48:03] um that that we've come out with. It's
[48:05] trying to just give a road map to our
[48:08] clients, our investors is it's not just
[48:11] about these one two names. It's about
[48:13] you have to be able to figure out who
[48:15] the second, third, fourth derivatives
[48:17] are.
[48:18] >> Mhm. when you look at um so many of
[48:21] these investors are now taking control
[48:23] of their own capital and they're saying
[48:24] I'm not going to go to RAAS or to
[48:26] financial advisors I want to invest
[48:28] myself how do you see them using the AI
[48:31] tools to actually become better
[48:32] investors are there things you guys are
[48:34] doing internally on the research side
[48:35] are there things that you're seeing in
[48:37] conversations with people
[48:38] >> I mean I would just say like just
[48:39] obviously I've been in so many
[48:41] conferences ra I mean the value of raas
[48:44] are extremely important you know based
[48:46] for so many people and I also think Like
[48:48] there's so many people like everyone
[48:50] could look like a genius when stuff then
[48:53] all of a sudden like you know you hit
[48:54] choppiness that's also where you know
[48:57] like it's very it's a dangerous time
[49:00] too.
[49:01] Look, I think there's there's a
[49:04] flattening of data. there's more
[49:06] information out there, but I think it
[49:08] comes down to like for investors, it's
[49:10] also making sure like diversified
[49:12] portfolio, making sure you understand
[49:13] risk because a lot of people like they
[49:16] think they this is where like when you
[49:18] go back to like the drunken miller and
[49:20] the Buffetts and the Paul Tudtor Jones
[49:23] and other they
[49:26] see
[49:28] there might be like names that they're
[49:30] bullish on that don't work but the thing
[49:32] with a lot of them that makes them so
[49:34] elite
[49:36] and Steve Cohen among others is that
[49:38] they understand risk. Risk is the key
[49:42] piece.
[49:43] >> The thing and that's from an individual
[49:45] perspective. A lot of investors like I
[49:47] think they under calculate or
[49:49] miscalculate sometimes risk.
[49:51] >> Mhm. And then what about like just the
[49:53] NASDAQ as a beta, you know, to the
[49:56] market, right? It it seems like uh if
[49:58] you go back for the last 10 years,
[49:59] that's been a pretty good bet. You
[50:01] should have just bought the index and
[50:03] maybe didn't even have to do any work.
[50:04] Yeah. I mean, like, look, people do
[50:06] that, right? Um,
[50:08] but 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 I think more and more younger people
[50:22] investing,
[50:24] >> more and more of the population is
[50:27] invested in terms of the market. And I
[50:29] think that's a it's a positive thing
[50:31] because also like you want to see wealth
[50:34] creation, you know, across the board.
[50:36] That's to me what makes me happy when I
[50:40] see like, you know, like when you hear
[50:43] about investors that
[50:45] >> they could pay off their college loans
[50:48] or they pay off their house or whatever
[50:50] it is by being on the right side of it.
[50:52] I think that's like
[50:54] >> those are the things that bring me joy
[50:56] when I hear about them.
[50:57] >> Mhm. All right. All right. Where can we
[50:58] send people to find you on the internet?
[51:00] >> Yeah. So, uh, you know, I'm on X, um,
[51:02] Dives Tech, LinkedIn. You know, many
[51:06] know how to contact me. And look, we
[51:08] just try to just be like one like we do
[51:11] the work and we try to communicate that
[51:15] to our clients and investors because
[51:17] there's a lot of haters out there.
[51:20] And it's very important in these sort of
[51:24] markets to just sometimes like have a a
[51:29] light in a dark tunnel sometimes and I
[51:32] 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 books. So I
[51:45] you know I read a lot about like you
[51:46] know American history and world history
[51:49] and and I the one thing I will say like
[51:51] a lot of times in books the investors
[51:53] like oh this is like a you know liars
[51:56] poker what you know the typical like
[51:57] wall I actually think a lot of times
[51:59] like understanding like history
[52:02] >> whether it's US history America it
[52:04] actually gives you good perspective when
[52:06] you even triangulate with the market in
[52:09] terms of just understanding like
[52:11] different generations and and ultimately
[52:14] what happened especially over the last
[52:15] you know 150 200 years.
[52:17] >> Yeah, I like it. All right, thank you so
[52:19] much for doing this.
[52:19] >> Thank you so much.
[52:20] >> Awesome. Great.