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SpaceX Lockup Tests the Elon Trade · The Financial Exchange Show

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Speaker 1: Zada and Mike Armstrong.
1:13
Speaker 2: Chuck, Mike and Tucker with you here today? Nope, not talker.
1:17
Speaker 3: It's Ben. Hi, Ben, I love you. You have a
1:21
Speaker 3: microphone back there, you know. Now it's it's better if
1:24
Speaker 3: he's kind of mysterious.
1:25
Speaker 2: You know, it's kind of like, Uh, what was the
1:28
Speaker 2: who's the guy in home improvement where you can only
1:30
Speaker 2: see his eyes? Like that's like I can only see
1:33
Speaker 2: his eyes above the computer.
1:35
Speaker 3: What was the neighbors name? I can't remember? Ben?
1:40
Speaker 2: Ben probably does, but we can't hear him because you know,
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Speaker 2: he doesn't want his mic on. So in any case,
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Speaker 2: I hope everyone's having a lovely day.
1:48
Speaker 1: Uh.
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Speaker 2: SpaceX Uh, I obviously don't know how it's doing today.
1:51
Speaker 2: I haven't looked at up a little bit. It's up
1:53
Speaker 2: a little bit. And this is actually not entirely surprising
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Speaker 2: to me because today is the day that the first
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Speaker 2: tranch of SpaceX's lock up expires, and you have some
2:07
Speaker 2: investors that are able to sell an additional nine hundred
2:10
Speaker 2: million shares that are now free and on the market.
2:16
Speaker 3: So let's talk a little bit about what lockups are. First.
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Speaker 2: Yeah, if you invest in a not invest if you
2:24
Speaker 2: happen to be, you know, owning shares of a private
2:26
Speaker 2: company that goes public. You aren't allowed to sell those
2:30
Speaker 2: shares right away for very obvious reasons. There's like a
2:35
Speaker 2: long history of you know, companies that went public and
2:40
Speaker 2: insiders could sell shares and it was pump and dump
2:42
Speaker 2: and okay, like this is unseemly, and the SEC and
2:45
Speaker 2: other regulators were like, hey.
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Speaker 3: Maybe we shouldn't do that, do something about it.
2:50
Speaker 2: It kind of you know, diminishes the uh trust in
2:55
Speaker 2: equity markets. So you end up with these lock up periods.
3:00
Speaker 2: And the reason again most of them typically the way
3:05
Speaker 2: that a lot of them tend to work is Okay,
3:07
Speaker 2: you get to one hundred and twenty days or ninety
3:09
Speaker 2: days or one hundred and eighty and here's you know,
3:12
Speaker 2: a bunch of liquidity that is available, and that's great,
3:17
Speaker 2: and that's that's fine. But SpaceX built their lock up
3:20
Speaker 2: period differently where okay, we're going to kind of have
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Speaker 2: this rolling expiration where every month for like a year,
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Speaker 2: there's more shares that end up being put onto the market.
3:32
Speaker 3: Which honestly, I think is kind of a nice model,
3:35
Speaker 3: like of all the things that feelings either way, Yeah,
3:37
Speaker 3: I mean if you're looking for stability. I don't know.
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Speaker 3: I think it's actually a reasonable model to go with,
3:46
Speaker 3: and you know, tying investors gains your losses to a
3:51
Speaker 3: longer term view on the stock. I like the overall
3:54
Speaker 3: composition of this. I don't think you should be required
3:56
Speaker 3: by any stretch, but I think it's a I think
3:57
Speaker 3: it's a good model. Sure.
3:59
Speaker 2: So Brent Donnelly, who I've been quoting quite a bit
4:02
Speaker 2: on SpaceX, just because he's written about it the last
4:04
Speaker 2: couple of days, and I find his take interesting. He
4:08
Speaker 2: compared it to some other recent IPOs in the tech
4:15
Speaker 2: and specifically AI space and said, okay, like, show me
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Speaker 2: what you know these companies look like before and after
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Speaker 2: their lock up expires. And so he looked at core Weave,
4:31
Speaker 2: which I think we're all familiar with the iPod last year,
4:36
Speaker 2: Sarah Bros, which is or Cerebros, however you pronounce it.
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Speaker 3: I don't really know.
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Speaker 2: I'm not particularly I'm interested because I like to pronounce
4:44
Speaker 2: words the right way. But it's kind of ambiguous because
4:47
Speaker 2: it's a made up word anyways, even though all words
4:49
Speaker 2: are made up. But Cerebros another AI company mostly on
4:54
Speaker 2: the chip side for them and then he also looked
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Speaker 2: at Rubric, who is a.
5:00
Speaker 3: Cloud data management company.
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Speaker 2: And here's what he found is that when you look
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Speaker 2: at those three companies, and again he wanted to look
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Speaker 2: at companies from like the last couple of years in
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Speaker 2: a similar space, AI focused tech companies that have iPod recently.
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Speaker 2: And what he found was that for core Weave and Cerebros,
5:22
Speaker 2: heading into the lockup, you saw the share prices declining
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Speaker 2: pretty meaningfully. You didn't really see any kind of meaningful decline.
5:29
Speaker 2: For Rubric, it was just kind of flat. And then
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Speaker 2: for all three of them, they all saw, you know,
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Speaker 2: some rebounds in the you know, ten to fifty day
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Speaker 2: period after the lockup expired. And the thesis that Brent
5:45
Speaker 2: lays out that I think is reasonable here because everyone
5:48
Speaker 2: says like, oh, when these lockups expire, like that's when
5:53
Speaker 2: the stock's gonna get hit, because there's gonna be so
5:55
Speaker 2: many more people who want to sell. And in fact,
6:00
Speaker 2: what you end up seeing here is the opposite. And
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Speaker 2: the question is, okay, like why is this the case?
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Speaker 2: And there's two things. The first is everybody knows when
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Speaker 2: the lock up period expires. It's not a mystery, it's
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Speaker 2: a verified piece of data that you have on which
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Speaker 2: to trade.
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Speaker 3: Yeah, before the IPO even happens, you generally generally know this, correct.
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Speaker 2: You know all of that information, and so the big
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Speaker 2: thing that you that you look at when you think
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Speaker 2: about this is Okay, if you know that there is
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Speaker 2: going to be the potential for people coming onto the
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Speaker 2: market to sell something in the future, what do you
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Speaker 2: try to do? You want to sell first, and that's
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Speaker 2: why you tend to see sell offs on IPOs heading
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Speaker 2: into the lock up expery.
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Speaker 3: Which guess what we've seen. The thing got up to
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Speaker 3: over two hundred dollars to share. It's now training it
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Speaker 3: one blow, one ten correct.
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Speaker 2: In particular, Let's say that you are a hedge fund
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Speaker 2: or a mutual fund that owns this. Your the big
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Speaker 2: institutional investor that got allocated the IPO, or maybe you
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Speaker 2: owned it, you know, pre IPO. You say, hey, I'm
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Speaker 2: going to exercise you know, some liquidity on the shares
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Speaker 2: that I have available to me, and I want to
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Speaker 2: sell those because I'm able to get higher prices now. Likewise,
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Speaker 2: then you have the post lock up period and those
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Speaker 2: same institutional investors who might have been selling for the
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Speaker 2: last you know, thirty forty days. They then say, hey,
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Speaker 2: you know what we sold high, it's cheaper. Now we
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Speaker 2: want to own that. Let's go buy it back. And
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Speaker 2: so this is why you know, when you have these
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Speaker 2: lockup expirations, the period that's right around them, right after
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Speaker 2: the lockup expiration is not often the most bearished period
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Speaker 2: for recent IPOs because it's a well known fact that
7:48
Speaker 2: the expiration is the lockup is expiring, and investors take
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Speaker 2: advantage of that by saying, Okay, people are gonna want
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Speaker 2: to sell in the future, great, I'll sell first, and
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Speaker 2: then I can buy back cheaper. There are you know,
8:00
Speaker 2: if you get past the immediate you know, four to
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Speaker 2: eight week period surrounding the lock up expiration, this you
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Speaker 2: know no longer matters, and so you know, that short
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Speaker 2: term factor can end up you know, muff you know,
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Speaker 2: kind of muffling the message there, and then afterwards you
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Speaker 2: can see further sell offs that happen. But Brent's point
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Speaker 2: was basically, look, if everyone knows an expiration is happening
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Speaker 2: for a lockup, then you don't typically see the major
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Speaker 2: sell off after the lock up expiration. You see it before,
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Speaker 2: and then you get a little bit of cushion for
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Speaker 2: like a four to eight week period before regular market
8:40
Speaker 2: forces take over again.
8:41
Speaker 3: Other dynamics here, just you know, to think through with SpaceX.
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Speaker 3: So when they went public, we talked about, you know,
8:49
Speaker 3: of the reasons they weren't being included in major indices.
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Speaker 3: One of them was the public float, meaning how much
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Speaker 3: of these shares are actually going to be tradable on
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Speaker 3: public markets. It was less than five percent at IPO
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Speaker 3: according to sources. With this new tranch going available, that's
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Speaker 3: going to bring that up to about twelve percent. Yep. Still,
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Speaker 3: I don't know what the average is for the S
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Speaker 3: and P five hundred. I'm guessing quite a bit more
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Speaker 3: than twelve percent, but it does more than double the
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Speaker 3: available shares on public markets with this newest tranch going open. Now.
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Speaker 2: So that's where things stand for SpaceX right now. Let's
9:21
Speaker 2: take a quick break, and when we return, we'll talk
9:24
Speaker 2: a little bit about the dangers of thinking you're a
9:28
Speaker 2: pre IPO investor in SpaceX. When you were, but maybe
9:35
Speaker 2: not the way you thought you were.
9:37
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10:18
Speaker 2: Mike, would you say that SpaceX has been the most
10:21
Speaker 2: hyped IPO since Facebook?
10:25
Speaker 3: Yeah? I hesitated to come up with another one.
10:27
Speaker 2: Yeah, it's tough to find one in that, you know,
10:29
Speaker 2: in the middle of that fifteen year period, because I
10:31
Speaker 2: think Facebook was either like twenty eleven or twenty twelve
10:34
Speaker 2: if I recall correctly, maybe twenty ten, But in any case,
10:39
Speaker 2: ton of interest. And so you add all kinds of
10:42
Speaker 2: investors that were, you know, climbing over each other trying
10:44
Speaker 2: to get access to shares before at iPod, people you
10:48
Speaker 2: know were like, okay, Like what can I do in
10:50
Speaker 2: order to get this? And The Wall Street Journal has
10:54
Speaker 2: an investigative report that was published late yesterday yesterday evening,
10:59
Speaker 2: and it covers the story of a man by the
11:02
Speaker 2: name of rom Ruparetti who back in twenty twenty had
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Speaker 2: a friend tell him Hey, I've got, you know, this
11:12
Speaker 2: investment firm that I'm working with that has, you know,
11:15
Speaker 2: the ability to invest in shares in SpaceX and other
11:19
Speaker 2: privately held companies.
11:20
Speaker 3: Yep.
11:21
Speaker 2: And so he took him up on that for not
11:24
Speaker 2: just SpaceX, but Sofi, the fintech company that went public
11:28
Speaker 2: a couple of years.
11:28
Speaker 3: Ago, Impossible Foods, the fake meat company.
11:32
Speaker 2: Yes, well the real fake meat company. It was not
11:35
Speaker 2: a fake meat company. It was a company that made
11:39
Speaker 2: fake meat. Real company making fake meat. Yeah, yeah, there
11:42
Speaker 2: you go. Yeah, So, in any case, he basically went
11:48
Speaker 2: in and said, Okay, I'm going to send about seventeen
11:51
Speaker 2: thousand dollars to this special purpose vehicle that this company
11:55
Speaker 2: had set up. That this is a pretty common thing.
11:58
Speaker 2: The estimates of that there's like a thousand pvs that
12:00
Speaker 2: hold SpaceX shares in order to you know, facilitate these
12:04
Speaker 2: kinds of transactions. And okay, he sent seventeen thousand dollars
12:09
Speaker 2: to buy shares.
12:10
Speaker 3: In the company. Undoubtedly signed a bunch of paperwork, Yeah,
12:14
Speaker 3: disclosing all sorts.
12:16
Speaker 2: Of journals saw a bunch of paperwork. They saw financial
12:19
Speaker 2: statements and uh butt into the company and received multiple
12:25
Speaker 2: documents from the the SPV saying, hey, you've got you know,
12:29
Speaker 2: five hundred shares of SpaceX stock. So SpaceX then went
12:35
Speaker 2: through a five to one stock split as a privately
12:38
Speaker 2: held company, and so he thought he had twenty five
12:40
Speaker 2: hundred shares that based on the IPO price, he said, Okay,
12:44
Speaker 2: it's gonna be like three hundred grand I can cover
12:46
Speaker 2: college for my kids. Like, this is gonna be great.
12:49
Speaker 2: And then what ended up happening is it's unclear exactly
12:56
Speaker 2: where the problem came up because there's different timeline in
13:00
Speaker 2: different statements from different parties. But somewhere in the mix,
13:06
Speaker 2: it turns out that the SPV that he was using,
13:09
Speaker 2: that he had invested in, sold his shares well before
13:13
Speaker 2: the IPO. There's some discussion about the exact date and
13:17
Speaker 2: before the stock split, and so he didn't own as
13:23
Speaker 2: many shares as he thought, didn't own them heading into
13:27
Speaker 2: the IPO, and instead had about forty five thousand dollars
13:31
Speaker 2: in cash inside his account in the SPV, but clearly
13:36
Speaker 2: not three hundred thousand.
13:37
Speaker 3: So things we don't know about this one would be
13:41
Speaker 3: SPV might have be well within their rights to sell
13:44
Speaker 3: everyone's shares of whatever company they could have very much
13:46
Speaker 3: discretion on how the SPV is operated. It could operate
13:50
Speaker 3: like a fund that buys and sells things at their
13:52
Speaker 3: own discretion.
13:53
Speaker 2: So we have not seen any paperwork about how it operates,
13:56
Speaker 2: and so it could all be on the up and up.
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Speaker 3: From that perspective, is definitely true. The allegation from the
14:04
Speaker 3: client is that based on the holding shown in his
14:06
Speaker 3: investment portal as of May twenty twenty six and on
14:09
Speaker 3: his twenty twenty five tax document, it contradicts what the
14:12
Speaker 3: firm is saying there. And the Wall Street Journal also
14:15
Speaker 3: say that they reviewed that. So, you know, some allegations
14:18
Speaker 3: here of fraud that nobody's really certain of. But so
14:23
Speaker 3: we didn't really talk about these types of vehicles much
14:26
Speaker 3: in twenty twenty from what I can recall, but I
14:28
Speaker 3: remember talking about them a lot this year when everybody
14:31
Speaker 3: was clamoring for the privately held sharees ahead of the
14:34
Speaker 3: IPO or trying to get into the IPO. And you know,
14:38
Speaker 3: part of the stuff we kind of paved over, right.
14:40
Speaker 3: He was introduced to this sales manager at late stage.
14:43
Speaker 3: They spoke on the phone, and then mostly the company
14:46
Speaker 3: that ran the SPV correct, sorry for paving over that.
14:49
Speaker 3: Spoke over the phone, mostly messaged back and forth on WhatsApp,
14:53
Speaker 3: never met with anyone in the firm in person. And
14:58
Speaker 3: I know it's a brave new world. I know we
15:00
Speaker 3: are much more comfortable these days operating or at least
15:04
Speaker 3: a certain generation is much more comfortable operating over the
15:08
Speaker 3: Internet and via text message than over the phone via
15:12
Speaker 3: zoom or in person. But a few of these things
15:14
Speaker 3: are red flags for any sort of investment, even those
15:18
Speaker 3: on the most cutting edge, such as communicating exclusively via
15:22
Speaker 3: WhatsApp message or primarily via WhatsApp message. I don't want
15:27
Speaker 3: to blame the individual who put the money in here.
15:29
Speaker 3: That is not where I'm going with this. But unfortunately,
15:36
Speaker 3: you know, the financial world as a whole is full
15:40
Speaker 3: of potential scams that you need to constantly be on
15:44
Speaker 3: the lookout for, and speaking with a salesperson almost exclusively
15:50
Speaker 3: via WhatsApp is one of those red flags that needs
15:52
Speaker 3: to go up. I'm not sure.
15:56
Speaker 2: And when I say I'm not sure, twenty years ago
16:00
Speaker 2: people would have said, Hey, speaking with you know, someone
16:02
Speaker 2: purely over email would have been a red flag. Yep.
16:06
Speaker 2: And now that's the main way that people do business.
16:08
Speaker 3: Yep.
16:09
Speaker 2: So I'm not willing to say that, and I don't know. Again,
16:15
Speaker 2: it's it's really hard to tell what actually happened here, Okay,
16:20
Speaker 2: So I think for me, especially when you're talking about
16:24
Speaker 2: private investments, there's very often a gap between the understanding
16:31
Speaker 2: of the individual investor on what they own, what the
16:36
Speaker 2: liquidity is, and what the process is, and the understanding
16:39
Speaker 2: from the institution selling them that private investment. And I
16:45
Speaker 2: don't know who is to blame here, but something went
16:50
Speaker 2: wrong in this process that caused a misunderstanding to the
16:54
Speaker 2: tune of two hundred and fifty thousand dollars, and we're
16:57
Speaker 2: going to end up finding out what that's something is,
17:01
Speaker 2: It doesn't.
17:02
Speaker 3: Maybe it could be all privately settled, but probably not
17:07
Speaker 3: once the SEC is involved. That's usually now what happens,
17:09
Speaker 3: we don't know.
17:10
Speaker 2: Like again the SEC is saying like we can't confirm
17:13
Speaker 2: or deny, so like we don't know what's you know,
17:15
Speaker 2: what exactly is going on here. But this is another
17:20
Speaker 2: thing that you have to be aware of when you're
17:21
Speaker 2: talking about private investments, is hey understand that unlike something
17:26
Speaker 2: that trades on an exchange where you have the ability
17:29
Speaker 2: to see it every day and trade it and know
17:31
Speaker 2: exactly what you own. There are different rules of the
17:35
Speaker 2: road that can be changed, just like that when it
17:38
Speaker 2: comes to liquidity, either not allowing you liquidity, as we've
17:42
Speaker 2: seen with some private credit funds recently, or potentially forced
17:46
Speaker 2: liquidation if the manager says no, we're going to be
17:49
Speaker 2: selling all or part of this asset. Those things can
17:53
Speaker 2: happen as well. We see that quite a bit in
17:56
Speaker 2: like the privately held real estate world, where you know,
17:59
Speaker 2: someone might I'd say, okay, invested in this company, and
18:01
Speaker 2: oh they decided to sell the property, and so now
18:03
Speaker 2: I have, you know, liquidity event that I wasn't planning for.
18:07
Speaker 2: So I think that it's hard to understand who is
18:12
Speaker 2: at fault here and exactly what happened. But it's clear
18:17
Speaker 2: there was a miscommunication on something and there's some stink here.
18:24
Speaker 2: But I just don't know exactly what the problem was.
18:26
Speaker 3: I agreed, there's not enough information to tell. Maybe the
18:31
Speaker 3: lesson is purely understand what it is you are investing
18:35
Speaker 3: in and what it is you own. But then again,
18:39
Speaker 3: this guy thought he understood what it was he was
18:41
Speaker 3: investing in and what he owned right at the time,
18:45
Speaker 3: Like if you had asked him back in twenty twenty one,
18:47
Speaker 3: he would tell you, yeah, I own assets in a
18:50
Speaker 3: privately held vehicle that owns SpaceX shares, amongst other things.
18:54
Speaker 3: He might have been wrong about that, but he thought
18:57
Speaker 3: that he understood it. Yeah.
18:58
Speaker 2: So again, this is all a just another way of saying, like, look,
19:05
Speaker 2: when you're investing your money into something, realize that you
19:11
Speaker 2: spent oftentimes like years saving that money and doing a
19:17
Speaker 2: little bit of additional due diligence to make sure you
19:21
Speaker 2: know what you're getting into worth doing. Quick break here,
19:25
Speaker 2: We've got Wall Street Watch next.
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20:00
Speaker 4: Well, markets are mixed at this hour. The down Jones
20:02
Speaker 4: is off two tenths of a percent. The S and
20:04
Speaker 4: P five hundred, on the other hand, is up just
20:06
Speaker 4: barely a point zero eight percent. The Nasdaq is up
20:11
Speaker 4: four tenths of a percent. Oil prices are up a
20:14
Speaker 4: little over a dollar one point four to two percent.
20:16
Speaker 4: Print Crew to up a dollar fifty or one point
20:19
Speaker 4: nine percent. Gold is up four tenths of percent, while
20:23
Speaker 4: silver is down eight tenths of a percent. Meanwhile, Peloton
20:27
Speaker 4: shares sank nearly twelve percent effort after its fourth quarter results.
20:31
Speaker 4: Its earnings of thirteen cents per share was in line
20:33
Speaker 4: with estimates, while its revenue top to expectations. Pelton also
20:37
Speaker 4: reported its active paying subscribers fell eight point eight percent
20:41
Speaker 4: year over year. The Food and Drug Administration approved Maderna's
20:45
Speaker 4: mRNA flu vaccine m Fluciva for adults fifty years or older.
20:50
Speaker 4: Despite the news, shares are down one percent. Sand Disk
20:53
Speaker 4: has slid four and a half percent as revenue guidance
20:56
Speaker 4: appeared to disappoint traders. SanDisk set it set it's he's
21:00
Speaker 4: first quarter revenue in a range of ten point three
21:02
Speaker 4: billion to ten point eight billion, while the consensus sought
21:05
Speaker 4: ten point four to seven billion. Fourth quarter results beat expectations.
21:10
Speaker 3: On the top and bottom lines.
21:12
Speaker 4: Door Dash added three percent after its quarterly revenue of
21:14
Speaker 4: four point four to five billion beat the consensus of
21:16
Speaker 4: four point three to four billion. Its earnings of forty
21:19
Speaker 4: six cents a share came in line with expectations, and
21:22
Speaker 4: finally Zillow slid more than twelve percent after expanded after
21:26
Speaker 4: it expanded chief financial officer Jeremy Hoffman's role, giving him
21:30
Speaker 4: the additional title of Chief Operating Officer. The company also
21:34
Speaker 4: reported a solid quarter after the bell, with adjusted earnings
21:37
Speaker 4: per share of fifty two cents, topping estimates of forty
21:40
Speaker 4: five cents and seven hundred and seventy two million dollars
21:43
Speaker 4: in revenue, beating estimates of seven hundred and fifty eight million.
21:46
Speaker 4: A day earlier, the company announced it would let go
21:49
Speaker 4: of about five hundred employees. I am Ben Kitchen and
21:52
Speaker 4: that was Wall Street Watch.
21:54
Speaker 2: So yesterday, Google, or rather the parent company of Google alphabets,
22:02
Speaker 2: at noon, announced two changes to the staff of their
22:08
Speaker 2: AI unit, losing two pretty senior members.
22:11
Speaker 3: Of that staff.
22:13
Speaker 2: Now, oftentimes, you know you kind of look at, you know,
22:16
Speaker 2: changes in personnel where you know, okay, like CEO leaves
22:21
Speaker 2: or CFO leaves, or you know, you know, this person
22:24
Speaker 2: leaves from a company and you're like, huh, I wonder
22:26
Speaker 2: like you know exactly how that's going to affect, you know,
22:29
Speaker 2: how the company is viewed and valued, and you usually.
22:32
Speaker 3: Can't make any heads or tails of it.
22:34
Speaker 2: Sure in this case, we know exactly how the market
22:38
Speaker 2: feels about this because the minute that Google announced this
22:42
Speaker 2: at noon yesterday, these two departures, what we saw was
22:46
Speaker 2: around one hundred and seventy five billion dollar drop in
22:49
Speaker 2: Google's market cap in the subsequent two minutes.
22:52
Speaker 3: It's a lot.
22:53
Speaker 2: Again, most of the time you look at moves in
22:55
Speaker 2: markets and you're like, well, it's a combination of these
22:58
Speaker 2: factors and that no, no, no, no.
23:00
Speaker 3: This one is That's what happened here.
23:04
Speaker 2: And basically, from my understanding in reading up on these
23:09
Speaker 2: guys from people who know them better than I do,
23:13
Speaker 2: these two guys are basically the architect of Gemini and
23:16
Speaker 2: the architects of Gemini and Google's efforts to this point,
23:21
Speaker 2: and a lot of people in the space feel that
23:23
Speaker 2: their departure is going to be awfully hard for them
23:26
Speaker 2: to overcome.
23:28
Speaker 3: So would in terms of the model race, and Google
23:35
Speaker 3: again has the from investor's perspective, fortunate position of both
23:40
Speaker 3: designing models as well as building out data centers and
23:45
Speaker 3: kind of an integrated approach to AI as well as
23:48
Speaker 3: designing semiconductors for all of this, so you know, more
23:51
Speaker 3: integrated than some of the others, and so it's not
23:53
Speaker 3: all tied out to the model, but it would seem
23:56
Speaker 3: to me that Gemini three months ago was in the
24:00
Speaker 3: conversation with Chat, GPT and Claude and has since fallen
24:06
Speaker 3: pretty far behind Anthropic and open AI. I recognize how
24:10
Speaker 3: quickly these companies can leap frog each other, but Gemini,
24:13
Speaker 3: for instance, has not been in the conversation of, you know,
24:18
Speaker 3: models that are capable of you know, big cybersecurity things.
24:22
Speaker 3: They have not been heavily in the conversation of models
24:25
Speaker 3: that are really good at coding. And that's where the
24:27
Speaker 3: frontier seems to have been going over the course of
24:30
Speaker 3: the last couple of months. And so I recognize the
24:34
Speaker 3: departure of basically the architects of your leading AI model
24:39
Speaker 3: is not exactly a good indication, But I just do
24:43
Speaker 3: openly wonder, you know, hey, is this shift necessary anyway
24:49
Speaker 3: based on how much ground they've lost recently?
24:53
Speaker 2: I don't know.
24:53
Speaker 3: It's again, these things can change so quickly.
24:56
Speaker 2: You know, a year ago, everyone was all about well
25:00
Speaker 2: AI and Chat GPT or you know that the clear leaders,
25:02
Speaker 2: and now it's.
25:04
Speaker 3: Finny to think about like who had even no there
25:06
Speaker 3: was not even even talking about no one was paying about.
25:09
Speaker 2: No one was paying attention to Anthropic Like last spring
25:11
Speaker 2: and summer it was all open AI and Anthropic was
25:14
Speaker 2: kind of viewed as like this distant competitive not a
25:17
Speaker 2: real you know, competition for them. So I think in
25:22
Speaker 2: a world where these models are increasingly becoming commoditized, the
25:27
Speaker 2: question really is like, hey, how much can you spend
25:30
Speaker 2: on developing and then you know, producing the the outputs
25:34
Speaker 2: from them given the increased competition that you have. Because
25:37
Speaker 2: when things become commoditized, we've talked about this, what happens
25:40
Speaker 2: to profits? They tend to go away. Like That's that's
25:43
Speaker 2: how commoditization works. That's like the very definition of a
25:45
Speaker 2: commodity is well, when when it doesn't matter who the
25:49
Speaker 2: provider is, you just buy the cheapest one. And that's
25:52
Speaker 2: kind of where we're going where so many of these
25:54
Speaker 2: are now clustered in like similar scores on different benchmarks.
25:59
Speaker 2: The other piece that I do think is interesting to
26:03
Speaker 2: talk about in this regard is when we talk about
26:07
Speaker 2: a lot of the benchmarking, a big chunk of it
26:10
Speaker 2: is on things like coding and math, because the reasons
26:15
Speaker 2: that you can have accurate benchmarks there are because there
26:19
Speaker 2: are clearly defined outputs that you can then test like
26:23
Speaker 2: does this work?
26:24
Speaker 3: Yes or no?
26:25
Speaker 2: Like does it accomplish this task? It's much harder to
26:29
Speaker 2: do that with other items when it comes to you know, hey,
26:35
Speaker 2: like how good is your essay? Like how good is
26:39
Speaker 2: the movie that you produced? How these things are more
26:43
Speaker 2: subjective and taste matters and personal preference matters and things
26:47
Speaker 2: along those lines. And so it's not surprising that when
26:50
Speaker 2: we talk about you know how, a lot of the
26:52
Speaker 2: benchmarks work, a lot of the scoring, and a lot
26:56
Speaker 2: of the places that people are using these are on
26:58
Speaker 2: coding and math oriented things simply because okay, you get
27:02
Speaker 2: results very quickly that you can check is this doing
27:05
Speaker 2: what it's supposed to do?
27:06
Speaker 1: Right?
27:07
Speaker 3: Jarck? Have you seen the chat GPT commercial recently with
27:11
Speaker 3: you know what looks like a woman over the age
27:12
Speaker 3: of seventy using chat gpt verbally? No? Okay, So for
27:18
Speaker 3: anybody that is listening, maybe you've seen it, but it's
27:20
Speaker 3: a woman talking to chat GPT, and it's an older
27:23
Speaker 3: woman who you know is probably exploring it for one
27:26
Speaker 3: of the first times, and she's talking to it. I know.
27:31
Speaker 3: We measure a lot of this stuff in terms of
27:33
Speaker 3: how well they are able to code. But and I
27:36
Speaker 3: don't know precisely the business model that chat GPT wants
27:39
Speaker 3: to go to, but it's been alluded to that they're
27:41
Speaker 3: going to effectively take the Facebook model of delivering a
27:44
Speaker 3: free product that sells a bunch of stuff to you.
27:47
Speaker 3: I wonder you talk about the commoditization of these different
27:51
Speaker 3: products and how you know, how we will all just
27:54
Speaker 3: switch to the cheapest and most efficient. I'm wondering how
27:58
Speaker 3: much that's true, right, you know? I think coders will
28:01
Speaker 3: switch to the cheapest and most efficient, but that's where
28:03
Speaker 3: the money is. Maybe, or maybe the money is to
28:07
Speaker 3: be made on selling ads to Grandma who's using chat gpt.
28:11
Speaker 2: There's not enough money there like that. The think of
28:15
Speaker 2: it this way. Companies have an AD budget, right, Like
28:19
Speaker 2: you have an AD budget where you say, hey, our
28:21
Speaker 2: marketing budget for this year.
28:22
Speaker 3: Is a million dollars.
28:25
Speaker 2: You know how much product like you can sell and
28:28
Speaker 2: how much you can produce. Yep, You're not going to
28:31
Speaker 2: double your marketing budget because chat GPT exists. You're going
28:36
Speaker 2: to say, no, we're going to redeploy that from somewhere else.
28:40
Speaker 2: Maybe we can increase it like five or ten percent. Sure,
28:42
Speaker 2: but there's only so much ad money to go around.
28:44
Speaker 2: It's why when Google, you know, took over Google and Facebook.
28:48
Speaker 2: The reason why local newspapers have died is because classified
28:51
Speaker 2: ads are no longer a thing like ad budgets got
28:55
Speaker 2: redirected elsewhere. And so I think that in that context,
29:00
Speaker 2: when you're talking about trying to spend four trillion dollars
29:04
Speaker 2: on data centers over the next three years, there's not
29:07
Speaker 2: enough ad money for that to make a difference.
29:09
Speaker 3: It's you.
29:10
Speaker 2: You have to be replacing employees. Yeah, because the only
29:15
Speaker 2: way that you get to the numbers that you can
29:17
Speaker 2: get to that you want to get to on this
29:20
Speaker 2: is we're going to take something that was previously done
29:23
Speaker 2: by a sixty thousand dollars employee and get it for
29:26
Speaker 2: a twenty thousand dollars contract.
29:28
Speaker 3: And if we do that for a.
29:29
Speaker 2: Million employees, then okay, great, now we've been able. Now
29:35
Speaker 2: we've been able to realize twenty billion dollars in new revenue.
29:39
Speaker 3: Okay, that helps to do it?
29:41
Speaker 2: Not well, Hey, you know Meta's got you know, ad
29:44
Speaker 2: spend of what's what's Meta's revenue right now?
29:47
Speaker 3: Let me just pull it up just to get the number.
29:50
Speaker 2: Meta's revenue for the last year is two hundred and
29:52
Speaker 2: twenty eight billion dollars, almost all of which comes from
29:55
Speaker 2: almost all advertising. Well, okay, like so if doesn't get
29:59
Speaker 2: you there, if you know, Delta or McDonald says, hey,
30:04
Speaker 2: we're gonna redirect our because remember McDonald's isn't the thing
30:08
Speaker 2: that's limiting McDonald's isn't. Well, if we could just get
30:12
Speaker 2: better ads to more people, like more people would eat
30:14
Speaker 2: our sandwiches. It's there's a fixed pool of people that
30:19
Speaker 2: want to have McDonald's, and on the margin, advertising might
30:23
Speaker 2: add you know, a little bit to that pool on
30:26
Speaker 2: any given day or week. But it's not like by
30:29
Speaker 2: advertising an open AI, McDonald's can double their sales. It
30:33
Speaker 2: is something where okay, if IBM is able to replace
30:39
Speaker 2: two engineers for the cost of one using AI, that
30:43
Speaker 2: provides a meaningful change to what the revenue picture looks like.
30:47
Speaker 2: So I don't think the ad piece is enough and
30:49
Speaker 2: the other thing. AI has a ton of users, right,
30:54
Speaker 2: Like we know that there's like billions of people worldwide
30:56
Speaker 2: that are using different AI platforms. Sure do you or
31:01
Speaker 2: any question for both of you, do any of your
31:04
Speaker 2: friends talk about using AI agents? Yeah?
31:09
Speaker 4: No, never once mentioned.
31:11
Speaker 2: So I find that, like the average person is using
31:14
Speaker 2: AI pretty much as a glorified search engine or companion. Correct,
31:20
Speaker 2: there's no money in that to justify the build out
31:23
Speaker 2: for Capex, right, because all AI would be then is
31:26
Speaker 2: a more expensive search engine. It might be better, like
31:29
Speaker 2: I tend to for some things. I prefer it because
31:33
Speaker 2: I get a better answer with the link sited and
31:35
Speaker 2: clearly explained, as opposed to like having to like figure
31:38
Speaker 2: out which link works. But I just don't think there's
31:43
Speaker 2: enough money in that, And so it's gotta be the
31:46
Speaker 2: business cases that drive this, and that's where the proof
31:49
Speaker 2: is gonna have to be in the pudding. Take a
31:52
Speaker 2: quick break when we return. I can't do any more AI.
31:56
Speaker 3: I just.
32:00
Speaker 2: Can't do any more AI. I'm just I'm aied out.
32:04
Speaker 3: We can do that. I think at some point we
32:06
Speaker 3: should talk about the depreciation in data centers that we've
32:09
Speaker 3: been alluding to for a while, because there's being a
32:12
Speaker 3: piece written about it. But let's let's take a take
32:16
Speaker 3: a break and talk about anything else. Yeah, let's take
32:18
Speaker 3: a break and we'll talk about something else next.
32:21
Speaker 1: Smart financial talk. Whenever you want, find the financial Exchange
32:24
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32:27
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32:30
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32:41
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32:55
Speaker 2: Talk about a couple excuse me, let's talk about a
33:00
Speaker 2: couple of earnings that came out in the last couple
33:03
Speaker 2: of days. Restaurant Brands International, commonly known as RBI.
33:10
Speaker 3: Nope, nope, not okay.
33:13
Speaker 2: So Restaurant Brands International, the company that is the parent
33:20
Speaker 2: of Burger King, Popeye's, Tim Horton's, they're all under that umbrella. Now,
33:27
Speaker 2: they came out with earnings and Burger King so same
33:31
Speaker 2: store sales growth of eight and a half percent for
33:33
Speaker 2: the quarter. So it's what's the King doing that's got
33:36
Speaker 2: him back on top or back.
33:37
Speaker 3: Some just kind of getting back to basics and fundamentals,
33:41
Speaker 3: cleaning up their restaurants a little bit, making them look
33:43
Speaker 3: a little bit nicer, which was noticeable for anybody that
33:46
Speaker 3: had been inside a Burger King in the last two years.
33:50
Speaker 3: But for a point of comparison here, so Burger King's
33:52
Speaker 3: same store sales. Same store sales are stores that have
33:54
Speaker 3: been open for at least twelve months, so you get
33:56
Speaker 3: a real view of yep, hey, taking out the new
33:59
Speaker 3: stores that we open, what were the what was the
34:01
Speaker 3: sales growth? Eight and a half percent. McDonald's publishes the
34:03
Speaker 3: same metric zero point eight percent.
34:07
Speaker 2: So there's something going on at Burger King's executing wells work.
34:10
Speaker 3: And now it may have just been that they were
34:12
Speaker 3: at a particularly low starting point. And either way, my
34:17
Speaker 3: perception of this is very micro. But I'm going to
34:19
Speaker 3: talk about my perception of Burger King because occasionally when
34:26
Speaker 3: I play Beer League Men's hockey, which you know happens
34:32
Speaker 3: during the winter time once a week. Yes, to relieve
34:36
Speaker 3: my wife a little bit, I'll take all three of
34:38
Speaker 3: my kids with me and they'll sit in the stands
34:40
Speaker 3: and watch. You know, they'll be the only fans at
34:41
Speaker 3: beer League hockey and watch me play hockey. And so
34:43
Speaker 3: the cheer for you were against you, uh four right now,
34:48
Speaker 3: But I see that changing it just in the future, yea.
34:50
Speaker 3: And to incentivize them, I will take them to either
34:53
Speaker 3: McDonald's or Burger King and go through the drive through
34:56
Speaker 3: lane and where I stopped. There's a McDonald's on one
34:59
Speaker 3: corner and the burger King right across. The McDonald's drive
35:02
Speaker 3: through line consistently ten vehicles, the burger King one empty,
35:06
Speaker 3: And so depending on how much of a rush I'm in,
35:09
Speaker 3: I will either choose the Burger King line or the
35:11
Speaker 3: McDonald's line because it is consistently shorter. It's been, you know,
35:15
Speaker 3: a little while since I've done this exercise, but that
35:19
Speaker 3: was my perception of Burger King, and frankly, the food is,
35:22
Speaker 3: you know, from my perspective, the same the little fidgets
35:27
Speaker 3: and dadgets that the kids will get in their happy
35:29
Speaker 3: meals are the same. But it was all that perceived
35:34
Speaker 3: niceness of not even just the inside, like I wasn't
35:36
Speaker 3: even going inside the store. It was even the perceived
35:38
Speaker 3: nicest of the drive through line.
35:41
Speaker 2: While we're on the topic of fast food, Luke Cowa,
35:44
Speaker 2: who we have on the show, occasionally found some data
35:48
Speaker 2: on Taco Bell.
35:50
Speaker 3: Uh huh.
35:51
Speaker 2: So Taco Bell has kind of been at the center
35:54
Speaker 2: of concern about this cyclospora outbreak. Yes, and on July
35:59
Speaker 2: twenty eighth, Taco Bell offered a one day only one
36:03
Speaker 2: dollar Mexican pizza promotion Taco Bell, foot traffic was up
36:08
Speaker 2: four percent year over year from you know, the prior
36:12
Speaker 2: year on that day. In the four days after Taco Bell,
36:17
Speaker 2: foot traffic was down anywhere from twelve to fifteen percent
36:21
Speaker 2: year over year.
36:22
Speaker 3: Wow.
36:22
Speaker 2: So the message that you can take from this is that,
36:27
Speaker 2: and this is how Luke phrased it, because I just
36:30
Speaker 2: think it's it's fantastic Mexican pizza cravings outweigh explosive diarrhea fears.
36:39
Speaker 3: This is so long as they cost basically nothing.
36:41
Speaker 2: There's a there's a twenty percent difference in foot traffic
36:45
Speaker 2: in Taco Bell from the day offering the one dollar
36:48
Speaker 2: Mexican pizza promotion to the days immediately before and after it. Yeah,
36:52
Speaker 2: and it can only be explained as, hey, when offered
36:55
Speaker 2: free Mexican pizza, even in a place where you have
36:59
Speaker 2: concerns about you know, explosive explosive diarrhea that has killed
37:03
Speaker 2: two people in Michigan, twenty percent of potential customers say
37:08
Speaker 2: let's give it a try. Yeah, which brings me back
37:12
Speaker 2: to that Boston Globe article that we covered a few
37:14
Speaker 2: weeks ago.
37:15
Speaker 3: There's struggling with there's nothing more American than this. Yeah,
37:20
Speaker 3: Like that there is nothing more American than this.
37:22
Speaker 2: Yeah, hey, dollar food, but might give you a real bad,
37:27
Speaker 2: you know, stomach issue. What's the worst that could happen? Well,
37:32
Speaker 2: we told you what. The worst that could happen is.
37:33
Speaker 2: It's all over the news.
37:35
Speaker 3: Yes, you used to pay full price for diarrhea.
37:37
Speaker 4: Now it's just a dollar.
37:38
Speaker 3: Speaking of which, now you saw the jlopenos, right, did
37:41
Speaker 3: we cover that yesterday?
37:42
Speaker 4: No?
37:43
Speaker 3: Yeah, the jalapenos are not cyclospora. They have salmonella. So
37:46
Speaker 3: Chipotle had to pull all their I crossed like thirteen states. Okay,
37:51
Speaker 3: this is good.
37:52
Speaker 2: Actually, because I had bought jalapenos, I was gonna make
37:55
Speaker 2: tacos on Tuesday.
37:56
Speaker 3: Yeah, double check the label. I uh.
37:58
Speaker 2: We decided to do turkey instead, And I'm thankful this
38:02
Speaker 2: morning that we went in that direction because I hadn't
38:05
Speaker 2: seen that alert. The produce is fighting back, Michael, Yep,
38:10
Speaker 2: the produce is fighting back. Let's take a quick break.
38:14
Speaker 2: We had hour two coming up in just a little bit.