Speaker 1: Welcome trillions.
Speaker 2: I'm Joel Whatever and I'm Eric Belchunas.
Speaker 1: Eric, maybe you've noticed the media tech landscapes are obsessed
Speaker 1: with artificial intelligence right now you think, yeah, yeah, you
Speaker 1: used GPT yet.
Speaker 2: Indirectly, but I totally know about it. It's impressive, although
Speaker 2: you know, I'm still trying to make sense of it all.
Speaker 2: I will say that it does seem like every two
Speaker 2: years something just hits the zeitgeist with the Wall Street
Speaker 2: Hype Machine, blockchain, and then it was like ESG. I
Speaker 2: just feel like now AI is like front and center.
Speaker 2: This is the new new thing. Anything with that associated
Speaker 2: with it is going to have success. Is it a
Speaker 2: bubble maybe? Is it just something to satiate the neat
Speaker 2: marketers or is it truly the next one? Or is
Speaker 2: it truly the next big thing? I will say I
Speaker 2: was at the SEC's first ever Investment Division of Investment
Speaker 2: Management conference in DC two fridays ago. Gensler spoke at
Speaker 2: this conference and he said AI is going to be
Speaker 2: bigger than the Internet, and they're looking into how to
Speaker 2: regulate it and whatnot. So that was an eye opener
Speaker 2: because I do find sometimes you don't know at first
Speaker 2: whether something's just this huge hype marketing thing or it's
Speaker 2: really worthy of all that attention. I'm not sold totally,
Speaker 2: but certainly in the ETF world, there's a ton of
Speaker 2: attention that's coming about AI, and we're going to continue
Speaker 2: to see ETFs that have AI in the name doing
Speaker 2: a variety of things, and so we should cover it
Speaker 2: for sure.
Speaker 1: Yeah, and we didn't ready to talk about this for
Speaker 1: a second, but I think we've got two perfect guests
Speaker 1: to kind of walk us through it. One's going to
Speaker 1: be Rebecca Sen at Bloomberg Intelligence, who's been watching this
Speaker 1: space closely. And then we've got Dave masa chief strategy
Speaker 1: officer at round Hill Investments, which just launched an ETF
Speaker 1: called Chat this time on Trillions AI Mania. Dave, Rebecca,
Speaker 1: Welcome to Trillions.
Speaker 3: Thank you for having me.
Speaker 4: It's pleasure to be here.
Speaker 1: Rebecca. I want to start with you. You, like I said,
Speaker 1: you've been watching the space closely. There's there's two distinct
Speaker 1: ways that we can talk about this, so let's just
Speaker 1: be clear about that. How do you break it down?
Speaker 3: So if we look at all of the ETFs that
Speaker 3: haven't mention of AI Autonomous robotics, there's really two ways
Speaker 3: that we classified it. The first are ETFs that track
Speaker 3: AI companies, so that's the like of ourc roundhill ball
Speaker 3: there ETF that just launched that day we'll talk about.
Speaker 3: But then the second category are really ETFs that utilize AI.
Speaker 3: So these are ETFs that had an artificial intelligence that's
Speaker 3: telling them which stocks to buy and sell, when to
Speaker 3: buy and sell, and the likes of those would be fourth.
Speaker 3: In Korea, they have a core ETFs and they just
Speaker 3: launched one last week. But then the other one is
Speaker 3: also AI EQ, which is tracking the IBM supercomputer and
Speaker 3: they analyze thousands of data points all day long, twenty
Speaker 3: four to seven, and they say that they could do
Speaker 3: the work of a thousand research analysts. So there's really
Speaker 3: two categories that we found.
Speaker 1: So yeah, one is a thematic bet on the sector, right,
Speaker 1: and the other is AI is coming for all of
Speaker 1: our jobs and it's just going to take over in
Speaker 1: either mint money or drive it portfolios into the ground
Speaker 1: or somewhere between.
Speaker 2: Yeah, So let's just chew through the second version and
Speaker 2: then we'll get to Dave and the thematic play. The
Speaker 2: first version is AI powered ETF, So these are ETFs
Speaker 2: that use AI to invest. Now, I consider this just
Speaker 2: sort of like an evolution of smart beta smart beta
Speaker 2: because it's using algorithms and numbers and stats. It's crunching
Speaker 2: numbers to try to figure out a way to get alpha.
Speaker 2: That's smart beta is sort of what that is already,
Speaker 2: and there's been AI for a couple of years. It's
Speaker 2: not totally brand new. AIEQ, as Rebecca mentioned, was the
Speaker 2: one that was using IBM's Watson supercomputer. We recently looked
Speaker 2: at this one. The returns aren't great. It's lagging the
Speaker 2: S and P by quite a bit. I dug into why,
Speaker 2: and my conclusion was it's just trades too much. It's
Speaker 2: turnover is really high. It's going through stocks left and right.
Speaker 2: And this brings up the bigger problem with AI powered ETFs,
Speaker 2: which is you can't really solve the problem that regular
Speaker 2: managers have, which is costs impeding onto your return. So
Speaker 2: AI is gonna, in my opinion, have to figure out
Speaker 2: a way to maybe limit costs, limit trading, and limit
Speaker 2: the fee in order to have outperformance. So it's not
Speaker 2: like AI is like somehow discovered some holy grail. It's
Speaker 2: gonna face the same challenges that regular managers have and
Speaker 2: that smart beta has, both of which have learned to
Speaker 2: get cheap and limit turnover, and they've started to succeed
Speaker 2: because they've done that. So I think AI is early
Speaker 2: a lot of ETFs that have come out using AI
Speaker 2: or pretty high fees, the turnovers high. I think over
Speaker 2: time we might see one or two succeed if they
Speaker 2: can get some performance. But I'm a little more bearish
Speaker 2: on this side of the fence versus the thematic place.
Speaker 1: But Rebecca, how could this version of AI powered ETFs?
Speaker 1: How could this evolve more going forward?
Speaker 3: So I think going to air points. If we look
Speaker 3: at all of the AI powered etf from a performance standpoint,
Speaker 3: just looking at year to date, they actually LaGG the
Speaker 3: S and P five hundred. So looking at all of
Speaker 3: the ETFs, the AI powered ETF on average return three
Speaker 3: percent versus the ETFs that track AI companies return twenty percent.
Speaker 3: And they're also more expensive. So we found that on
Speaker 3: average they cost roughly seventy five basis points versus fifty
Speaker 3: basis points. And so in terms of where the growth is,
Speaker 3: I think with the AI powered ETF, you really need
Speaker 3: to find the right fund managers, as Eric was saying,
Speaker 3: a lot of this, A lot of them churt, so
Speaker 3: they have a higher training cost. And so even though
Speaker 3: a lot of these funds are powered by a supercomputer
Speaker 3: an AI, there's still someone tweaking the model. There's still
Speaker 3: someone tweaking the code. So I think that also impacts
Speaker 3: the performance of the fund.
Speaker 1: Okay, but the big phenomenon that we're seeing with the
Speaker 1: chat gbts of the world, generative AI is sort of
Speaker 1: what this is called, right, how much generative AI is
Speaker 1: even in these AI powered ETFs or is there yet
Speaker 1: another chapter to what this investment future could look like.
Speaker 3: I think this is where round Hill differentiates themselves with
Speaker 3: their new ETF, because they really are in that generative space.
Speaker 3: I think a lot of the ETFs that were launched
Speaker 3: previously are a little bit more traditional. They are quantitative based,
Speaker 3: but there is still someone in the background that's tweaking
Speaker 3: the model, that's changing it. And so I think in
Speaker 3: terms of where the future goes there as we adopt
Speaker 3: AI more and more. And I think chat GPT is
Speaker 3: a perfect example. Since chat gbt launched in November, they
Speaker 3: got more than one hundred million users in less than
Speaker 3: two months. So to put that in context, how many
Speaker 3: users do you think it took Uber to How long
Speaker 3: do you think it took Uber to get one hundred
Speaker 3: million users a year?
Speaker 1: Two years, three years, six years, six years, okay.
Speaker 3: Six years. So Instagram took two years and Spotify took
Speaker 3: four years, and so chat GBT got one hundred millionars
Speaker 3: million users in just two months. And so this really
Speaker 3: shows that not only is there a hype into this,
Speaker 3: but people are really invested and interested in this. And
Speaker 3: I think as you get more and more data in
Speaker 3: the AI space, that is only going to improve and grow.
Speaker 3: So I think if we look at specifically at ETFs,
Speaker 3: the ETFs that are powered by AI, they don't have
Speaker 3: enough data points and a lot of the technology when
Speaker 3: they first launched. I think AIEQ eric that launched a
Speaker 3: while ago, and looking at all of the robotics ETF,
Speaker 3: I think the first ETIF that launched was in two
Speaker 3: thousand and six, and so if we look at where
Speaker 3: technology is now versus in two thousand and six, it's
Speaker 3: improved a lot and it's only going to grow exponentially.
Speaker 2: That also the biggest challenge, and what nobody can get around,
Speaker 2: is that nobody really knows the future. It's just hard
Speaker 2: to predict the future and robot Ai Smart Beta Active Manager,
Speaker 2: it's just very difficult. My guess is one of these
Speaker 2: breaks out the pressro goes with like robots Win, that
Speaker 2: gets some money, but then it underperforms and maybe sees
Speaker 2: some outflows.
Speaker 1: And you've said you're saying that you've seen this movie before.
Speaker 1: I've seen this movie before.
Speaker 2: So now what Rebecca talked about Chat GPT and the
Speaker 2: frenzy to get on there, I think that speaks more
Speaker 2: to thematic play. In other words, let me buy some
Speaker 2: stocks that are going to benefit from this and let
Speaker 2: me get a piece of that action. That is where
Speaker 2: the thematic side comes from. Bringing Dave, now, I think
Speaker 2: that's a perfect intro. Dave, you've launched a new ETF
Speaker 2: called Chat. You're the chief strategy officer at Roundhill. What
Speaker 2: was the thought behind this and how long have you
Speaker 2: been working on it?
Speaker 4: Well, I think Rebecca hit the nail on the head,
Speaker 4: which was exciting for us when thinking about AI is
Speaker 4: not really just AI itself. This has been around for
Speaker 4: some time, but AI's been waiting for the killer app,
Speaker 4: and the killer app with Chat gibt and that made
Speaker 4: it so that because of its use and you biquitous nature.
Speaker 4: All you need is computer access or a smartphone and
Speaker 4: you can use Genera of AI in your daily life.
Speaker 4: That it opened up our eyes that this is not
Speaker 4: necessarily a theme or a fad that's happening ten fifteen
Speaker 4: years in the future. This can happen today and now
Speaker 4: we're seeing CEOs or as you noted, Gary Genzer, discussing AI,
Speaker 4: general AI and material ways because that's really where the
Speaker 4: productivity goes. I think it's exciting and everyone can be
Speaker 4: focused on humanoids and robots and thinking that's AI, and
Speaker 4: it is. But the ability to do so on sort
Speaker 4: of a micro level is what Genera of AI is doing,
Speaker 4: and that's really the idea behind creating an ETF just
Speaker 4: for that space, and chat provides exposure around thirty companies
Speaker 4: that are at the forefront of general AI, whether it's
Speaker 4: the picks and shovels of a company like Navidia, or
Speaker 4: companies that are exposed to it directly through ownership about
Speaker 4: OpenAI like Microsoft, or a handful of other names that
Speaker 4: folks may not is familiar with who are involved in
Speaker 4: the space.
Speaker 1: How quickly were you able to move on this.
Speaker 4: We launched the EUTF color I should say a couple
Speaker 4: of weeks ago, and so we moved really quickly, and
Speaker 4: this is an idea that we were using it. We
Speaker 4: started looking at chat EBT using it again either in
Speaker 4: our workflows or just to have fun and realize, say,
Speaker 4: there's something here. Can we do some research to identify
Speaker 4: other companies that may be exposed to it because it
Speaker 4: is a very nascent space, And it turns out once
Speaker 4: you do that peel back the onion, even just one layer,
Speaker 4: you can see that companies sort of have been poised
Speaker 4: to do this, and now that the intention is there,
Speaker 4: we're really beginning to see more and more folks latch
Speaker 4: onto it.
Speaker 1: So how do you figure out who's a real deal
Speaker 1: player here that has unique exposure? Like an Nvidia comes
Speaker 1: to mind, right, where you've got a chip maker who
Speaker 1: is all about the creating the chip four AI applications,
Speaker 1: and Microsoft, which is a backro of chat GPT right,
Speaker 1: But then like there's a kind of a falloff. I mean,
Speaker 1: I'll keep Google sort of in that camp or Alphabet
Speaker 1: in that camp, maybe because we know that they'll have
Speaker 1: something significant with bard. But after that, like, how do
Speaker 1: you figure out who's legit versus just generating more hype
Speaker 1: from the hype machine.
Speaker 4: Yeah, this is really important because I think what we're
Speaker 4: gonna find is, and we saw this with crypto and blockchain,
Speaker 4: there's got to be a handful of companies that perhaps
Speaker 4: changed their name we all know one from Long Island famously,
Speaker 4: or companies that are using it but not really exposed
Speaker 4: to it. Perhaps maybe some consumer names come to mind,
Speaker 4: a Wendy's or Pepsi. So what we're doing is two things,
Speaker 4: and I call it a kind of a talking to
Speaker 4: talk and walking the walk approach. You need both here
Speaker 4: to identify those companies that are truly exposed. So first
Speaker 4: and foremost we're transcript Score and so here we're looking
Speaker 4: at a proprietary keyword analysis of public documents, whether they
Speaker 4: are company filings, transcripts, presentations, or press releases to see
Speaker 4: if that company has references to various AI and related
Speaker 4: technology terms. And I you know, you'd imagine a company
Speaker 4: like Navidia jumps to the top of that list. But
Speaker 4: then importantly we also have what we call a sector score,
Speaker 4: and that's to do some real quantitative research to understand
Speaker 4: is a company actually spending or has direct revenue exposed
Speaker 4: to generate AI and the related technologies, and so companies
Speaker 4: that are doing more or have higher portion of revenue
Speaker 4: coming from that, or are spending on it for the
Speaker 4: future from a true R and D standpoint, are going
Speaker 4: to get higher score. So you pair those together, you know,
Speaker 4: subject to some standard market cap and liquidity requirements, you
Speaker 4: end up with a portfolio relatively concentrated in the grand
Speaker 4: scheme of things that has exposure to microcaps, small caps,
Speaker 4: mid caps, and of course some of the megacap names
Speaker 4: that are powering this forward. So investors can expect to
Speaker 4: see around twenty five to thirty securities going forward. It's
Speaker 4: a global portfolio, a lot of US exposure, but a
Speaker 4: lot of China exposure in the portfolio as well. And
Speaker 4: this is going to adapt through time, which is one
Speaker 4: of the reasons why we're excited that this is actually
Speaker 4: an active approach.
Speaker 1: How do you figure out the waitings?
Speaker 4: The waitings are really i'd say a derivation of both
Speaker 4: the transcript score and the sector score. So subject so
Speaker 4: companies that have are talking about it a lot and
Speaker 4: are actually spending on it, we're going to get higher rates.
Speaker 4: Hence the video being the top holding, and then and
Speaker 4: then so on. So if you look at our top
Speaker 4: ten holdings, uh, you know, it's names like Navidia, Microsoft,
Speaker 4: C three, AI, Alphabet and then AMD another semiconductor which
Speaker 4: is making some inroads with g GPUs and the chips needed.
Speaker 3: For general AI.
Speaker 1: It's interesting.
Speaker 2: I was at the inside ETFs conference and I looked
Speaker 2: at and I was on an AI panel, and I
Speaker 2: can't say I'm a total expert, but I looked at
Speaker 2: some of the ETFs and I brought shot up and
Speaker 2: my one critique of it. This is before Navidia's earnings.
Speaker 2: I looked at and I said, you know, I don't
Speaker 2: love theme ETFs that have big cap names at the
Speaker 2: top because I already own those in my low cost
Speaker 2: beta core. I don't need to be redundant. Then navidia
Speaker 2: earnings came out and I felt like maybe they were
Speaker 2: justified a little more because Navidia is the top holding,
Speaker 2: and they felt a lot of that juice. But typically
Speaker 2: I find DAVE in a fledgling area where the theme
Speaker 2: might not be totally ripe enough for a full ETF
Speaker 2: equal weighting or some kind of modified market cap waiting
Speaker 2: to give you more exposure to the small and mid
Speaker 2: cap space could be better because it helps differentiate the
Speaker 2: ETF more from BETA.
Speaker 1: Well, I think you.
Speaker 4: Raised a good point, and we could have this conversation
Speaker 4: about a variety of different ETF areas. It's whether it's
Speaker 4: factor based, smart, beta, ESG is a whole other can
Speaker 4: of worms and stomats.
Speaker 1: Right.
Speaker 4: The way I think about it for this space is
Speaker 4: it would be I think disingenuous not to have the
Speaker 4: exposure to a company like the Video or Microsoft or
Speaker 4: Alphabet in a material way in this portfolio, and because
Speaker 4: they're exposed to it, they get a higher weight. But
Speaker 4: you know, again in the top ten holding there's names
Speaker 4: like iFly Tech, since Time Group, even C three AI
Speaker 4: to some extent, a company like More you know, or
Speaker 4: a risk in networks that are not megacap growth. Right,
Speaker 4: So even among the thirty names, we have a wide
Speaker 4: representation of companies across the market cap spectrum. For US,
Speaker 4: it's really are you truly exposed to genera of AI
Speaker 4: or not? And that's what we're going to hang our
Speaker 4: hat on. And of course this market has been rewarding
Speaker 4: that that may not always be the case going forward.
Speaker 4: But if we can provide that exposure again in a
Speaker 4: concentrated way to companies truly exposed to jener of AI,
Speaker 4: then we feel like we're doing.
Speaker 1: Our job here.
Speaker 3: So I guess going off that Dave, there are seventy
Speaker 3: ETFs that has AI mentioned in their description and roughly
Speaker 3: sixteen billion in assets. We expect that by twenty thirty
Speaker 3: there's going to be one hundred and fifty ETFs with
Speaker 3: the mention of AI. Given how crazy and everyone's interest
Speaker 3: in this area with thirty five billion, what do you
Speaker 3: tell investors that say, you know, how do I pick
Speaker 3: which ETFs? A lot of them do have AI in
Speaker 3: their wording. There's a lot of hype in there. And
Speaker 3: to Eric's point, you know, just looking at NASDAQ one
Speaker 3: hundred and sm P five hundred, they have all the
Speaker 3: six names alphabet Navidia, Apple, Microsoft, and so what would
Speaker 3: you say to investors?
Speaker 4: Yeah, so it's funny. I did actually a research paper
Speaker 4: that was published at this point, probably ten years ago
Speaker 4: about givin ndtfs, and at the time it was crazy
Speaker 4: because it had first marked that there was one hundred
Speaker 4: divid endtfs. So now as you all know, there's hundreds more.
Speaker 4: And if you look at the performance dispersion of them.
Speaker 4: They were massive, right, and at the end of the day,
Speaker 4: a big difference was whether they give it in growth,
Speaker 4: which is more quality, or give it in yield there's
Speaker 4: more value. And I think the same can be said
Speaker 4: about the Mattos that when I in this market, it's
Speaker 4: very easy to put a buzzy name in an ETF
Speaker 4: name and see if that gets people's attention. I think,
Speaker 4: particularly post COVID experience and some of the selloff, investors
Speaker 4: have become more discriminating about the funds that they own
Speaker 4: and they understand that, you know, like our friend Todd
Speaker 4: Rosenblue says, you need to know what you own. And
Speaker 4: some people just want to buy either the largest or
Speaker 4: most well known, but it might not be the exposure
Speaker 4: you want. So I always advocate take a look at
Speaker 4: one what is the process to get the names in there?
Speaker 4: If it's an index process, take a quick look and
Speaker 4: understand the index methodology. You don't need to be an
Speaker 4: expert in any of this space, but can you understand
Speaker 4: what they're trying to do and then do the whole
Speaker 4: things generally reflect that? Right, So if we're in our
Speaker 4: case saying we're going to provide exposure to companies at
Speaker 4: the forefront of GENERATIVII, and a name like Navidia isn't
Speaker 4: a top holding, I'd probably question that. But also if
Speaker 4: there's names like sense Time Group, which is a leader
Speaker 4: in China in creating a computer focused AI marketplace, they
Speaker 4: have their own large language model, then that makes sense too.
Speaker 4: So this is going to be a space where I
Speaker 4: think there's there's, as noted, a ton of continued investor interest.
Speaker 4: There could be right or wrong reasons to buying any
Speaker 4: of these ETFs, but for us, when it comes to
Speaker 4: what is really focused on, generative AI chat stands alone.
Speaker 1: Okay, Dave, I'm curious. You've got this thematic option, You've
Speaker 1: laid out the case for it. At what point what
Speaker 1: would it take to put that engine that we talked
Speaker 1: about earlier in the show, the AI powered ETF engine,
Speaker 1: into the thematic thing, and then you have an AIM
Speaker 1: powered AI thematic ETF. What would that take? Yeah?
Speaker 4: So, look, look, we are huge believers in the transformation
Speaker 4: that jenerava I can bring both to everything from enterprise
Speaker 4: software where our director of research publisher report focused on
Speaker 4: an estimate of our tam of over one hundred and
Speaker 4: twenty billion in a ten years time, and also the
Speaker 4: consumer applications. But the idea that AI can be used
Speaker 4: to identify the company systematically at this point in time,
Speaker 4: I questioned that to me, I would agree at the
Speaker 4: intro to the show that this may just be the
Speaker 4: next evolution of quantitative investing. When I was a assistant
Speaker 4: quant portfolio manager in the mid two thousands, we had
Speaker 4: three components to our SoC selection model and we actually
Speaker 4: outperformed before the global financial crisis consistently, and one of
Speaker 4: those was priced book. It was so simple, but it worked,
Speaker 4: and then guess what happens? It gets arbitraged away. I
Speaker 4: think with AI, it's all dependent AI powered ets, AI
Speaker 4: powered investment processes. It all matters at this stage of
Speaker 4: development of is it being powered by humans appropriately?
Speaker 1: Now?
Speaker 4: Over time, as general of AI continues to improve, as
Speaker 4: large language models and other use cases begin to become
Speaker 4: more real time, we have to remember a lot of
Speaker 4: the genera of AI potential right now is still having
Speaker 4: that kind of backward looking learning. It's we are just
Speaker 4: at the cusp of it being applied across a wide
Speaker 4: range of industries. Then maybe I'd have more confidence in
Speaker 4: those particular approaches, But for now, our quantitative process, both
Speaker 4: sort of on the transcript side and then on the
Speaker 4: sector analysis side, gives me more confidence that will be
Speaker 4: identifying the names that will continue to be exposed to
Speaker 4: general of AI in the future.
Speaker 1: Is there any busy work that you can unleash AI
Speaker 1: on to improve your daily life?
Speaker 4: Dave, Uh, Well, one thing that you know, I think
Speaker 4: people are experimenting with, and we've heard some stories about
Speaker 4: about ai US is going right and also going wrong.
Speaker 4: You know, there's there's things that I use to help
Speaker 4: me craft uh to almost serve as an editor on
Speaker 4: a daily basis, for for whether it's a blog that
Speaker 4: I'm writing or just other research that I'm doing to
Speaker 4: power that. So we're using it. In fact, if you
Speaker 4: go on the research section of Roundhill Investments website, we
Speaker 4: will we will note where where articles are being helped
Speaker 4: to be written by chat GBT. Now, I think the
Speaker 4: generative text is where all the easy attention is being paid.
Speaker 4: But I think in the short term we're going to
Speaker 4: see people experimenting with image generation, uh, sound generation and
Speaker 4: things of that nature. So again we are just at
Speaker 4: the cusp of that. But yeah, busy work is something
Speaker 4: that we're looking to offload pretty frequently, uh to to
Speaker 4: help to help guide us and be that assistant for us.
Speaker 2: So this brings up a good point with ETF research.
Speaker 2: I always tell my team put as much as your
Speaker 2: voice in your writing as possible, get as much human
Speaker 2: in those words, because some of this stuff is going
Speaker 2: to be automated if you are dull, you know, And
Speaker 2: I do think of this one. You know, the Hollywood
Speaker 2: writers are on strike. There was this one billboard from
Speaker 2: this woman who who was at the strike and it
Speaker 2: said chat GPT never had childhood trauma. And I do
Speaker 2: think that nothing will replace the human at the end
Speaker 2: of the day for certain tasks. But again, dull, repetitive tasks,
Speaker 2: I just see just automated. We do it at Bloomberg
Speaker 2: on several types of data stories. There's a lot of
Speaker 2: automated stories already, but I think research and you're editing
Speaker 2: BusinessWeek over there, how much of your let's say, ten
Speaker 2: years from now, how much of the copies can.
Speaker 1: Be written by AI? No comment, no comment, I've stumped roll. Yeah, No,
Speaker 1: I mean, look like we have there's a long ways
Speaker 1: to go, Like is AI going to conduct interviews no,
Speaker 1: So I think there's a long way for a lot
Speaker 1: of it, and I think that you're right, there's a
Speaker 1: lot of things that are rote that can be disrupted.
Speaker 1: But I think, you know, the question for humans is
Speaker 1: like where you add value, and I think there's a
Speaker 1: lot of things that humans will still add value to.
Speaker 3: So we interviewed Kathy with and asked her thoughts on AI,
Speaker 3: and she said, it's going to add any It's going
Speaker 3: to be the area that adds the most value in
Speaker 3: the tech sector. And I think when we look at AA,
Speaker 3: there's really two areas that we can look at. Most
Speaker 3: people probably look at it from a software and hardware perspective,
Speaker 3: but her view is that if we take Tesla for instance,
Speaker 3: the autonomous driving of getting from point A to point
Speaker 3: B safely is another way that AI is going to
Speaker 3: have a huge influence in our daily lives. And so
Speaker 3: I think it's interesting as we look at a lot
Speaker 3: of these companies to see how they evolve. You know,
Speaker 3: we don't know what they're going to do in five, ten,
Speaker 3: twenty years time, and so there's a lot of growth potential.
Speaker 1: Dave, So if Kathy would has been there's nobody more
Speaker 1: bullishean tech in the future and AI than Kathy? Could
Speaker 1: you imagine a world where Chat invests in ARC or
Speaker 1: is that not enough of a pure play?
Speaker 4: Wow, that is an interesting way to think about it.
Speaker 4: I think my short answer would be never say never.
Speaker 4: But I don't think as of now, that's really the
Speaker 4: exposure that we're or intention that we're we're looking to
Speaker 4: have right is And also people I think are looking
Speaker 4: to Chat to serve that direct exposure to jenitor of
Speaker 4: AI and kind of for now having another fund look
Speaker 4: to do that, it may not make as much sense.
Speaker 2: Yeah, that's a little like just bad form if you're
Speaker 2: an ETF.
Speaker 1: It's funny.
Speaker 2: There was a cannabis mutual fund that used HMMJ for
Speaker 2: the longest time. It had like ten percent. There was
Speaker 2: an African mutual fund that used AFK. It's happened sometimes
Speaker 2: here and there, But I generally ETFs don't want to
Speaker 2: use other ETFs unless they're an ETF vtfs.
Speaker 1: Yeah, okay, okay, Dave, first time on trillions. Welcome by
Speaker 1: the way again. Uh, there's a question that we often
Speaker 1: ask first timers, and I'm gonna ask it of you
Speaker 1: now because you've got an epic ticker, Chat is a
Speaker 1: great one. What is your favorite ETF ticker other than
Speaker 1: your own?
Speaker 4: So Chat is a pretty good one. The Roundhell Investment
Speaker 4: team has a great number of.
Speaker 1: Storied history of great tickers.
Speaker 2: We'd don't forget about the twenty five million dollar bad
Speaker 2: Boy Meta's that's probably the greatest ticker of all time,
Speaker 2: simply because of the price tag.
Speaker 1: But you can't use any of those.
Speaker 4: Yeah, you'd have to keep me around all day because
Speaker 4: I could go to my time at Direction and some
Speaker 4: of the great tickers there. Gosh, drip, it's really hard
Speaker 4: to pick a few.
Speaker 3: Just pick one in Asia it's a random number exactly.
Speaker 2: By the way, Asia is so boring, Like in the
Speaker 2: China ETFs, the tickers are six numbers. It's like five
Speaker 2: five O three three one, And it's like, come on,
Speaker 2: the AI.
Speaker 3: Tells you what your ticker will be.
Speaker 4: I'm old school, and I'm so I'm gonna go with
Speaker 4: something like move, you know from from our friends over
Speaker 4: at van Ax. That was to me one of like
Speaker 4: the original cool tickers. I think it still plays a role.
Speaker 4: So I always have a soft spot.
Speaker 2: For that one wholesome, wholesome pick that's probably the most
Speaker 2: popular pick moo tan.
Speaker 1: You know it's funny. That's the thing I like about it.
Speaker 2: Like you know the other It's likable and so I
Speaker 2: like verbs. Yeah, that's why chat's good. Chat's also verban
Speaker 2: nown You got a two for there.
Speaker 4: Well, I'm trying to make it an adjective and an adverb,
Speaker 4: so give us, give us a few months.
Speaker 1: Yeah, all right, Dave Rebecca, thanks so much for joining
Speaker 1: us on rallians.
Speaker 5: Thank you, thanks for having us, Thanks for listening to Trillions.
Speaker 1: Until next time. You can find us on the Bloomberg terminal,
Speaker 1: Bloomberg dot com, Apple Podcasts, Spotify, or wherever else you'd
Speaker 1: like to listen. We'd love to hear from you. We're
Speaker 1: on Twitter, I'm at Joel Webber Show. He's at Eric Baltuna's.
Speaker 1: This episode of Trillions was produced by Magnus Hendrickson. Bye