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Markets Wrap: Trouble Ahead For The AI Money Machine? · Merryn Talks Money

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Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.
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Speaker 2: Welcome to the merriland Talks Money Market Wrap, where we
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Speaker 2: talk about the biggest moves and markets this week and
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Speaker 2: what's been driving them. I'm Join Stewick, senior reporter and
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Speaker 2: author of the Money Distilled newsletter, and then joining me
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Speaker 2: in the studio today is Bloomberg's Private Companies Managing Editor
0:32
Speaker 2: Neil Callanan. Neil covers hedge funds, asset management, and real
0:36
Speaker 2: estate in EMIA. So in today's show, I basically wanted
0:40
Speaker 2: to talk about the AI industry. Wanted to give us
0:44
Speaker 2: structure out of what it's actually about, lay it out
0:46
Speaker 2: so that you can understand it better. They kind of
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Speaker 2: who's producing the chips and who's producing the models, and
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Speaker 2: then wanted to look at how that's funded and why.
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Speaker 2: There are some concerns about perhaps the circularity of some
1:03
Speaker 2: of the deals in the industry, and Neil has written
1:05
Speaker 2: a lot about that. Thanks very much for being with
1:08
Speaker 2: us today, Neil. I was great to have you on
1:11
Speaker 2: the show, having not at all so but recording this
1:17
Speaker 2: on Wednesday. And probably the biggest story so far this
1:22
Speaker 2: week has been the route in the South Korean Cosby
1:26
Speaker 2: Index and Basically this is driven by the fact that
1:30
Speaker 2: Cosby is half of it is comprised of two stocks
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Speaker 2: that are related to the AI boom, and that's skh
1:38
Speaker 2: Nix and Samsung. And also there is an element of
1:44
Speaker 2: retail investors getting in over their heads because they've been
1:47
Speaker 2: able to buy all these leveraged ETFs and so the
1:50
Speaker 2: costby went up a lot and then down a lot.
1:52
Speaker 2: I mean, one of the stats that really jumped out
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Speaker 2: at me is that it's actually still up thirty five
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Speaker 2: percent on the year, but in the last month it's
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Speaker 2: fallen slightly formal set So yeah, okay, that's a proper
2:04
Speaker 2: roll off course at the moment. But does this tale
2:08
Speaker 2: is boy, does this suggest is about the overarching AI
2:14
Speaker 2: story because it's not just about Korean leverage. There's other
2:17
Speaker 2: stuff going on too, Isn't that absolutely?
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Speaker 1: And Korea in a way is a special case because
2:22
Speaker 1: Korea has almost gamified the finance industry and the stock market.
2:27
Speaker 1: And you mentioned the lever gts, but they've been big
2:30
Speaker 1: on crypto and heather and things like that, stable coins
2:33
Speaker 1: for a long time and and you know those a
2:37
Speaker 1: lot of those investors in retail have grown up very
2:40
Speaker 1: accepting of those levels of risk and in many cases
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Speaker 1: it has paid off. So, as you said, the COSPY
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Speaker 1: is still up this year despite the route in recent weeks.
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Speaker 1: But while it is driving a lot of the change
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Speaker 1: at the moment is the fear that China is catching up.
2:53
Speaker 1: And China's emergence in AI, which was always going to
2:58
Speaker 1: happen but perhaps faster than people, is really concentrating minds
3:02
Speaker 1: at the moment. And we have seen in the past
3:03
Speaker 1: when Deep Sea came out of nowhere and released its
3:06
Speaker 1: models at the market disruption that that cause. And now
3:09
Speaker 1: we're going to a kind of second bout of that
3:11
Speaker 1: where in the space of just over a week you've
3:14
Speaker 1: seen massive progress in terms of memory chips, in terms
3:17
Speaker 1: of language models, and so China is definitely emerging. And
3:21
Speaker 1: one of the things around all is spending that we're
3:23
Speaker 1: seeing in AI is the assumption is that people are
3:25
Speaker 1: willing to pay for it and won't pay a lot
3:28
Speaker 1: for it going forward. And then suddenly if you have
3:30
Speaker 1: these cheaper models coming out of China and people start
3:33
Speaker 1: switching to that, then what happens with the names we're
3:35
Speaker 1: all familiar like with like open AI and Anthropic and
3:41
Speaker 1: so you know, there's definitely fears in the market about
3:45
Speaker 1: that at the moment, and I think people are definitely
3:49
Speaker 1: taking pots globally as a result of that. At the
3:52
Speaker 1: same time, a lot of this money is going to
3:54
Speaker 1: be spent. There is an investment case for it. It's
3:59
Speaker 1: whether it's getting ahead of itself at the moment. In
4:01
Speaker 1: certainly in terms of graduations, it did seem to be
4:03
Speaker 1: getting steamy at one point this year.
4:05
Speaker 2: Yeah, I mean, I thought we'd just kind of lay
4:08
Speaker 2: out roughly the AI industry and the business mode because
4:12
Speaker 2: I think a lot of the time, you know, we
4:14
Speaker 2: sort about AI and it's quite an amorphous kind of blob,
4:18
Speaker 2: and a lot of time we're thinking about chat GPT.
4:21
Speaker 2: I mean, the video is in there somewhere and all
4:23
Speaker 2: the rest of these things. But so always kind of
4:27
Speaker 2: looking at it. And that's what I was talking to
4:29
Speaker 2: you to AI about it and getting a sense of
4:32
Speaker 2: what the kind of value chain it. So you've got
4:34
Speaker 2: your you've got the machines that make them, So you've
4:38
Speaker 2: got the companies that make the machines that make the chips,
4:40
Speaker 2: and that's like your SML that makes the kind of
4:44
Speaker 2: lift up lithography machines and then you get the chip
4:47
Speaker 2: foundries themselves, and that's like the Taiwanese company t s MC.
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Speaker 2: You've got chip designers and that's the video. So they're
4:56
Speaker 2: they're the ones that basically do the kind of value
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Speaker 2: add element, isn't it. It's like they are they're making
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Speaker 2: the brains for these things. And then all of these
5:05
Speaker 2: chips go into big AI hotels, the kind of data centers,
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Speaker 2: and they're run by the same people that run what
5:11
Speaker 2: we used to call Internet hotels, the kind of data servers,
5:14
Speaker 2: like the Amazons and all the rest of this world.
5:17
Speaker 2: And then you've got the people who actually make the
5:19
Speaker 2: AI models and the AI models the brains of the
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Speaker 2: AI live on the data centers, and that's like your
5:27
Speaker 2: open AI. And then they're selling them companies either big
5:31
Speaker 2: enterprise providers who kind of like garnish their existing offerings
5:35
Speaker 2: with AI, orange users like me and you, are smaller companies.
5:41
Speaker 2: Is that about the size of it?
5:43
Speaker 1: Is that?
5:43
Speaker 2: Does that kind of sound about right in terms of
5:47
Speaker 2: what the EI value chain is and who all the
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Speaker 2: companies are involved in this?
5:52
Speaker 1: But like this is so massive now that encompasses everything
5:56
Speaker 1: else as well. So they need energy and so we're
5:59
Speaker 1: saying boom and energy, and people are talking about leading
6:02
Speaker 1: up to three hundred gigawatts of additional energy power by
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Speaker 1: twenty thirty. That's enough to power two hundred and twenty
6:09
Speaker 1: five million homes for a year just for data centers. Now,
6:13
Speaker 1: those things have to be built as well. You have
6:15
Speaker 1: to get people to build the data centers and build
6:17
Speaker 1: the energy infrastructure, et cetera. So construction firms are taking
6:21
Speaker 1: off as well. And so you know, in the US
6:23
Speaker 1: in particular, it's driving a lot of the economic growth,
6:26
Speaker 1: and any slowdown in this kind of spending will be
6:28
Speaker 1: negative for growth, not necessarily turn recessionary anything, but it
6:32
Speaker 1: would be negative for growth in the US. But this
6:36
Speaker 1: goes back your point about in the end. It comes
6:38
Speaker 1: back to the end users. Goes back to my point
6:40
Speaker 1: about China in a way, which is that you know,
6:43
Speaker 1: we need people at the end to be paying for
6:44
Speaker 1: these services in order to justify these investments. And when
6:48
Speaker 1: you look at the amount of money that are being
6:50
Speaker 1: spent by some of the hyperscalers in particular, which are
6:53
Speaker 1: these Internet hotels originally as you describe them, you know,
6:57
Speaker 1: if you look at alphabet th recent filing, it's forward
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Speaker 1: spending commitments rows five hundred billion dollars essentially in three
7:06
Speaker 1: months now. Revenue, the future revenue growth grew but not
7:11
Speaker 1: by anything close to that, and that goes back to
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Speaker 1: the fears people have about this entire ecosystem that is
7:16
Speaker 1: sucking up so much money and so much capital at
7:19
Speaker 1: the moment that people are kind of going, well, well,
7:22
Speaker 1: I don't know whether I want to have as much
7:24
Speaker 1: exposure as I could have to this. And you're starting
7:27
Speaker 1: to see that in the credit markets as well, where
7:29
Speaker 1: people are becoming much more discriminating about the deals they
7:32
Speaker 1: invest in and the price they're wanting to pay. And
7:34
Speaker 1: they're also hedging a bit more so this week Core
7:37
Speaker 1: Weaves CDs, which is the form of hedging against the
7:42
Speaker 1: fault risk that's risen't almost a record. The core Weave
7:45
Speaker 1: is one of these companies that is like a wee
7:48
Speaker 1: work of the GPU world, which is the chips, and
7:51
Speaker 1: they basically rent out other people what they're doing. And
7:55
Speaker 1: you know, people have become much more cynical in the
7:58
Speaker 1: last few weeks about deals, partly because they know so
8:01
Speaker 1: much of this stuff is coming to the credit markets
8:03
Speaker 1: that they don't have to buy everything and The question
8:06
Speaker 1: is whether people in the AI industry as a wider
8:11
Speaker 1: thing have become too complaisent about the idea that the
8:14
Speaker 1: credit markets will be there and be supportive of them,
8:17
Speaker 1: and that's not necessarily always going to be the case.
8:19
Speaker 2: Well, I mean, I think that this is it is
8:21
Speaker 2: fascinating from that point of view, and that there really
8:24
Speaker 2: has been a wug bond issue and hasn't. And I
8:28
Speaker 2: mean we're talking about by some measures now the hyperscalers
8:33
Speaker 2: are the biggest issues of corporate investment grade debt, and
8:37
Speaker 2: you're used to being the banks and the other point
8:40
Speaker 2: but hyperscalers is that before all this they were they
8:44
Speaker 2: were basically running on their own cash generation. They were
8:48
Speaker 2: deemed as being essentially impregnable balance sheets. And while it's
8:53
Speaker 2: not negative that they've started, you know, recent or not started,
8:56
Speaker 2: they've now got a lot of debt. And for example,
8:59
Speaker 2: our for bet It's latest quarter was its first negative
9:02
Speaker 2: free cash flow quarter ever since it lest date. It's
9:07
Speaker 2: just a sort of sign of how much is out
9:10
Speaker 2: there and how these these businesses are kind of fundamentally
9:14
Speaker 2: being changed by this. And then you throw in China
9:18
Speaker 2: maybe turning around and doing it all much much cheaper,
9:21
Speaker 2: and suddenly you're kind of oh, your onions are going
9:23
Speaker 2: to be crushed, or so the Indians that we're hoping
9:27
Speaker 2: that you get might get crushed by this. And the
9:30
Speaker 2: one thing I thought was really interesting, going back to
9:32
Speaker 2: the debt point, as you involved in putting together this
9:36
Speaker 2: very complicated and now famous in a sort of local
9:41
Speaker 2: way chart about how this is all being financed. And
9:46
Speaker 2: one of the big things that's I think slightly worrying
9:49
Speaker 2: people as well is that a lot of the money
9:52
Speaker 2: seems to be coming from the people who raise the
9:56
Speaker 2: money in the first place, so like almost like a
10:00
Speaker 2: form of vendor financing. You've got companies that kind of
10:04
Speaker 2: make the chips, paying the people who buy the chips
10:07
Speaker 2: or who are going to rent the data centers that
10:09
Speaker 2: use the chips. Can you talk to us a bit
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Speaker 2: more about about that and how that's kind of panning out.
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Speaker 1: Yeah, what happened late last year was I was sitting
10:20
Speaker 1: there reading story after story about these deals where companies
10:24
Speaker 1: were doing deals with other companies in the universe, and
10:27
Speaker 1: video has always been at the center of this, but
10:30
Speaker 1: the likes of Google, Ananthropic and open Ai were doing
10:32
Speaker 1: all these as well. And I literally couldn't keep up,
10:35
Speaker 1: and so we just had the idea and maybe we
10:38
Speaker 1: need to do a visual here and kind of show
10:40
Speaker 1: the levels of circular deals that are happening. And you know,
10:45
Speaker 1: this became something of a bad word in the nineteen
10:48
Speaker 1: nineties with fiber optic and when there was a big
10:50
Speaker 1: rollout of that, lots of spending and there was vendor financing,
10:53
Speaker 1: and there was capacity sharing and various other things, and
10:57
Speaker 1: then a lot of those companies went bus when the
10:59
Speaker 1: demand was in there at the end having invested in
11:01
Speaker 1: all that money. And of course the irony, of course
11:03
Speaker 1: is that long term the economy benefit and massively from
11:08
Speaker 1: that level of spending. It's just the companies involved. But
11:11
Speaker 1: noways so many of them ended up going bankrupt.
11:13
Speaker 2: Well, that's that's the infrastructure story, isn't it. The always
11:17
Speaker 2: are still hearing we still have trained a lot of
11:19
Speaker 2: the companies about them went bused and seeing me dot
11:22
Speaker 2: com and.
11:23
Speaker 1: That happens with most new technologies. And again that goes
11:25
Speaker 1: back to why investors are being somewhat skeptical at the
11:29
Speaker 1: moment about that. But these circlear deals, they can create
11:31
Speaker 1: misaligned incentives around things like are you making the decision
11:37
Speaker 1: for the in the best interests of the company. Are
11:39
Speaker 1: you making it in the best interest of the company
11:41
Speaker 1: that invested in you and is one of your biggest customers, etcetera.
11:45
Speaker 1: And does that mean you're not the voting resources to
11:48
Speaker 1: something else when perhaps you should be. It also raises
11:51
Speaker 1: the question of whether there might be misaligned values. So, yeah,
11:54
Speaker 1: the deal has been done out let's just say seven
11:57
Speaker 1: billion valuation, but if that is with somebody else might
12:01
Speaker 1: have been a four billion. Yeah, you're also creating customers
12:05
Speaker 1: for you who are beholding by those contracts. And then
12:09
Speaker 1: that like essentially creates regulatory risk as well. But regulators
12:12
Speaker 1: may come alongo, actually we don't like that, and we're
12:15
Speaker 1: not sure whether that's the best deal for the consumer.
12:18
Speaker 1: And so, you know, all these risks are immerging up
12:21
Speaker 1: perhaps we didn't have before. But the biggest one, probably
12:24
Speaker 1: of all, is that these circular deals can create a
12:27
Speaker 1: false impression of demand. And you may think that all
12:31
Speaker 1: these companies are generating massive revenues, but if it's all
12:33
Speaker 1: just moving around and slashing around, then if something falls
12:36
Speaker 1: out of bed, then there could be wider implications and
12:39
Speaker 1: that could become systemic.
12:52
Speaker 2: The other thing I thought was interested in this week
12:54
Speaker 2: is that athough cost we's fallen out of bed the
12:58
Speaker 2: nasdyke to cup a bump, but not a big one.
13:02
Speaker 2: It so far seems to be restricted largely to the
13:06
Speaker 2: AI and the tech sector. And actually plenty of other
13:10
Speaker 2: stocks are doing fine. They equal weighted S and P
13:14
Speaker 2: is doing fine as there's in that's the S and
13:16
Speaker 2: P that's not wholly invested in the tech sector. And
13:20
Speaker 2: also the FOOTS one hundred is almost back at a
13:23
Speaker 2: record high, the kind of laggard of the global stock markets.
13:28
Speaker 2: But is this issue of how much does this spread
13:32
Speaker 2: or could it spread beyond the tech sector? So who
13:36
Speaker 2: else is involved in lending to these companies and if
13:40
Speaker 2: something did break down there sort of where are the
13:43
Speaker 2: contagion sort of vectors.
13:49
Speaker 1: The demand means that the AI industry has had to
13:52
Speaker 1: go to pretty much every corner of the credit market
13:54
Speaker 1: and hand out the ball and kind of say, give
13:56
Speaker 1: us a few quid what we need going for. And
14:00
Speaker 1: so you're seeing everything from direct lending, which is a
14:04
Speaker 1: private credit usually for infrastructure, so like just to build
14:07
Speaker 1: a data center, and you're seeing investment grade. You're also
14:10
Speaker 1: seeing these neo clouds like core Weave who I mentioned to,
14:14
Speaker 1: are sub investment grade. Sometimes not all of them, but
14:17
Speaker 1: some of them are sub investment grades. So that's the
14:19
Speaker 1: high year market. The junk bonds that people might know
14:23
Speaker 1: they're in the structured credit markets that are you know,
14:27
Speaker 1: these are basically taking bond payments that are gue and
14:31
Speaker 1: slicing them up by risk and selling them off to people.
14:36
Speaker 2: It's didn't something like that hal in the mortgage market,
14:40
Speaker 2: was it twenty years ago?
14:42
Speaker 1: We haven't got the kind of the CDO level or
14:44
Speaker 1: CDO squared level. But like where I would be concerned
14:52
Speaker 1: around that. Lending in particular is around what in real
14:55
Speaker 1: estate is called speculative lending, which means something else too
14:58
Speaker 1: many people. But in real estate it's basically building the
15:01
Speaker 1: stuff before you have a tenant, and if you can
15:04
Speaker 1: get finance, and that from a bank or from a
15:07
Speaker 1: private credit lender, that says something about bubble territory because
15:10
Speaker 1: they are taking a complete risk that you are building
15:13
Speaker 1: this thing over the course of five years and you
15:15
Speaker 1: will find somebody to occupy it. If not, or if
15:18
Speaker 1: the industry moves on and technology moves on, you can
15:20
Speaker 1: end up with a very expensive elephant at the end,
15:24
Speaker 1: which may not have much residual value for people.
15:27
Speaker 2: If you build it, they will come only walks in
15:29
Speaker 2: the field of dreams done that.
15:32
Speaker 1: I mean, there can be a first moving thing where
15:34
Speaker 1: you can get away with it. But if you're spending
15:36
Speaker 1: five billion credits building a data center, I would want
15:40
Speaker 1: to be more certain of that. But we are beginning
15:42
Speaker 1: to see elements of that, and we're also beginning to
15:45
Speaker 1: see terms being pushed within those deals for lending that
15:54
Speaker 1: maybe are too generous to the hyperscouts. That is the
15:57
Speaker 1: point of view of the credit markets. So you're starting
16:00
Speaker 1: to hear things like after a certain amount of time,
16:03
Speaker 1: if the project is delayed, then the hyperscat to come
16:05
Speaker 1: back out. Now, if you've invested five years and spent
16:09
Speaker 1: as I say, five billion dollars in billiing a data
16:11
Speaker 1: center and it gets a bit delayed because let's just
16:13
Speaker 1: say something got stuck in the straits of her moves
16:16
Speaker 1: at the moment, that's a very big risk. And so
16:19
Speaker 1: again that's part of what's happening with the credit markets
16:21
Speaker 1: and the pullback. They're kind of reconsidering some of the
16:25
Speaker 1: levels of risk that they're accepting at the moment.
16:28
Speaker 2: I mean from that point of view, this arguably, as
16:31
Speaker 2: long as it's not already going too far, maybe a
16:33
Speaker 2: good thing, and then maybe it gets a arein end
16:36
Speaker 2: of horns a bit before it does go properly payer shaped.
16:42
Speaker 1: Yeah, and I think it was always going to happen.
16:45
Speaker 1: And to be fair, like you look at something like
16:46
Speaker 1: the Cosby and it's still up. You know, many of
16:49
Speaker 1: the companies in are still up over one hundred percent
16:51
Speaker 1: here today in some cases with AIA adjacent companies are
16:55
Speaker 1: up three hundred percent for the year, so that you know,
16:58
Speaker 1: and there was an act moment for a pause anyway.
17:02
Speaker 1: And while we are seeing in terms of the Chinese evolution,
17:08
Speaker 1: is that that was always going to happen as well.
17:10
Speaker 1: And China's big advantages. It has cheap electricity, so the
17:14
Speaker 1: tokenization is cheaper. So if you're a company that's also
17:18
Speaker 1: been spending loads of money and AI and your staff,
17:21
Speaker 1: it turns out are using it to convert excel files
17:24
Speaker 1: into PDFs rather than actually, you know, using a much
17:27
Speaker 1: cheaper technology for that, you're going to be scatting around
17:29
Speaker 1: for cheaper prices. And so you know, China and the
17:33
Speaker 1: Chinese LM's become a natural kind of success story from that,
17:37
Speaker 1: and you know that was all to be expected, I
17:43
Speaker 1: think when a certain reason, and it's just all happened
17:47
Speaker 1: very quickly and all at once, as it does these
17:48
Speaker 1: days and markets, and there's a bit of panic in
17:51
Speaker 1: certain areas, particularly when it comes to retail money. You
17:54
Speaker 1: and I have spent years writing about retail money being
17:57
Speaker 1: hot money and how people can panic, and to be fair,
18:00
Speaker 1: if I had leveraged several times, I've been looking at
18:02
Speaker 1: that and kind of gone, oh my god. So it's
18:04
Speaker 1: understandable in a way, but you know, if people are
18:06
Speaker 1: sensible about how the investors still major opportunities there.
18:09
Speaker 2: Yeah, I mean yeah. My heart goes out to the
18:12
Speaker 2: various kind of rookie retail investors in South Korea who
18:16
Speaker 2: are now looking at, you know, some really nasty losses.
18:20
Speaker 2: I'm hoping that they were all young enough to bounce
18:22
Speaker 2: back from it. The only thanks very much for this
18:25
Speaker 2: was really helpful. The one other thing I was asking
18:28
Speaker 2: about is on the debt side to flood, the kind
18:32
Speaker 2: of the debt market, if you like, And we have
18:35
Speaker 2: also seen a bit of equity issuings, and I suppose
18:39
Speaker 2: the other thing I'm wondering about, is how much can
18:42
Speaker 2: the market take whenever We've had decades of de equitization,
18:48
Speaker 2: so companies buying back order shares or getting bought off
18:52
Speaker 2: the market, and now we're going to get quite unusually
18:57
Speaker 2: kind of net equity issues quite possibly year. I mean,
19:01
Speaker 2: my design city about what might happen regarding the tightness
19:05
Speaker 2: of my overall as They're just not going to be
19:10
Speaker 2: enough to go around for all the hungry mouths.
19:12
Speaker 1: So I think investors would be discerning. I mean, you
19:15
Speaker 1: can tell, you can tell an equity story that people
19:18
Speaker 1: will follow. I mean, just thinking within AI, how many
19:22
Speaker 1: of these companies we had heard of three years ago?
19:24
Speaker 1: Very few of Annie and yeah you know that, and
19:27
Speaker 1: they may not have very much revenue, but people are
19:30
Speaker 1: wenting to bet on a deal. But there's also a
19:34
Speaker 1: thing of like it can go wrong quite quickly, and
19:37
Speaker 1: a SpaceX is probably a good example of that, and
19:39
Speaker 1: unless say, went wrong, but there was so much hype
19:42
Speaker 1: and now it's obviously down since its IPO price, which
19:45
Speaker 1: was ambitious in the first place. I looked recently and
19:49
Speaker 1: the short interests on the stock was at near forty percent,
19:52
Speaker 1: So people are being very bearish on the future for it,
19:55
Speaker 1: and that's probably the big question for investors at the moment,
19:59
Speaker 1: SpaceX being partially the NAI story with data centers in space,
20:02
Speaker 1: et cetera. Is has that and what happened to that
20:07
Speaker 1: stock closed the I P O window for a while,
20:11
Speaker 1: and in that sense, then the focus would shift back
20:15
Speaker 1: to the equity markets. I started to the credit markets
20:19
Speaker 1: and the credit markets, and Sculptor I think it was,
20:22
Speaker 1: put an investor letter out recently and they said they
20:25
Speaker 1: talked about how credit capacity is needed. It's great, it's
20:28
Speaker 1: the extent just as people are pulling back, and that's
20:32
Speaker 1: something you have to be a bit fearful of. I
20:33
Speaker 1: think now often we have taught these things in two
20:37
Speaker 1: weeks later, it's the market is that over sold and
20:40
Speaker 1: it's all right back up and often exceeding the previous
20:44
Speaker 1: size obviously, but at the moment, it's definitely a moment.
20:49
Speaker 1: It's just the length that that moment takes.
20:52
Speaker 2: Oay, well, look thanks a lot, Neil. I think that
20:55
Speaker 2: was really helpful.
20:56
Speaker 1: I hope.
20:58
Speaker 2: That the main point it was to try and explain
21:00
Speaker 2: to people what's going on, and I think you've done
21:02
Speaker 2: that excellently. And obviously the market can remain excitable for
21:06
Speaker 2: longer than anyone can remain solvent, especially if you're invested
21:10
Speaker 2: in a leverage VTF, so just be careful out there.
21:13
Speaker 2: Thanks again, Neil, Thank you, thanks for listening this week's
21:23
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21:38
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21:41
Speaker 2: Money at Bloomberg dot Net. Special thanks to Neil Callen.