October 28, 2025 • 38 mins
Mike Armstrong and Paul Lane discuss the ongoing issues in the private-credit sector. Martha Gimbel (Yale Budget Lab - Executive Director) joins the show to chat about AI's impact on the labor market. PayPal reaches deal to put digital wallet into OpenAI's ChatGPT. This is how the AI stock boom plays out. Google and NextEra to revive major Iowa nuclear facility.
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Episode Transcript
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Speaker 1 (00:00):
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(01:06):
and Paul.
Speaker 2 (01:06):
Lane, Good morning, Welcome back to the Financial Exchange. It's Mike,
Paul and Tucker with you on a Tuesday, ahead of
a big earnings week. Here Tomorrow, after the bell, we
are going to be hearing from Microsoft, hold up, Microsoft,
(01:27):
Alphabet and Meta themselves reporting let's see four seven nearly
nine trillion dollars worth of market capitalization. That's ahead of
Thursday's big report will be where we will hear from
both Apple and Amazon, who combined will be reporting more
than six trillion dollars worth of market cap, so big
(01:49):
ability to move markets that equates to a round a
fifth or a quarter of total market cap of the
S and P five hundred. We've got announcements from the
likes of UPS as well as Amazon, both of which
have announced that they are making job cuts. In some cases,
UPS already have made significant job cuts on the UPS side,
it's in the thirty plus thousand range. Amazon immediately planning
(02:12):
some fourteen thousand job cuts, with the potential for up
to thirty thousand. The two companies, I know, all of
us kind of think of the two as linked in
some ways, right. They are, you know, shipping companies in
a lot of ways, and we interact with them on
a daily basis. They're cutting different areas. You know, Ups
is purely that logistics company. They're cutting drivers, they're cutting
in store retail locations. Amazon holding on to their logistics
(02:35):
part of their business and really focusing on that corporate
workforce that they are reducing here. But again, big announcement
potential from all of these companies coming up this week
with big earnings. We also have a FED meeting that
is already underway. We expect that they will be cutting
rates tomorrow during their announcements at two pm press conference
(02:55):
at two thirty. The press conference itself, honestly, it will
be interesting, justin so far as I don't know what
you ask the FED right now, because they don't know
the state of the labor market. They have some semblance
of the state of inflation, but mainly I think they're
going to be asked questions like what will you do
if the government doesn't open for another thirty days? Which
is interesting, but I don't know how impactful it is, right,
(03:19):
there's no answer to it. What do you do if
in thirty days the government's still closed? Well, we guess
there's the answer, right Like that that's what we do,
and so they will have some answer on that front.
But again, I think the FED meeting is likely to
not give us a whole lot of new information, nor
should it, because the FED is flying blind a little bit.
(03:40):
Anything else catching your eye in markets or just big
financial news that I missed this morning, Paul.
Speaker 3 (03:46):
No, I think we hit on most of them here.
Speaker 2 (03:48):
So I am interested in this next piece from the
Wall Street Journal. It is from the opinion section of
the Wall Street Journal. It's from an individual named Dan Wertman,
who I had never heard of before. He's the CEO
of Nohedica market intelligence AI software company. Okay, got it.
There's a lot of these different companies. He's the CEO
of this one, and he writes about private credit and
(04:10):
the winter that is coming. So take us step back, Paul,
talk to us about private credit and the prevalence in
today's markets before we get into why it's heading for
a winter.
Speaker 4 (04:20):
So private credit has exploded over the course of the
last ten years. And when we're speaking about private credit,
there is the public credit markets that if your Intel
or Walmart.
Speaker 2 (04:31):
Or at and t issue can issue bonds.
Speaker 4 (04:33):
That someone at any you know, retail investment firm or
any type of major custodia out there could purchase the
debt that that company is issued. Private obviously implies that
you and I, Mike and Tucker and Paul wouldn't have
access to this funding. They're typically sourcing out funding from
non public markets. So that could be private equity firms,
(04:54):
it could be endowment, hedge funds, pensions.
Speaker 2 (04:57):
Family offices. Largely bigger investors though, who are going to
grab up a lot more than ten thousand dollars worth
of a bond.
Speaker 4 (05:04):
And it really jolted up when you had a period
of time or interest rates were extremely low and you
were looking for creative ways to be able to get
a better interest.
Speaker 3 (05:13):
From a debt perspective, think.
Speaker 2 (05:14):
About so the investors were looking for that, right and
the borrowers, I think, we're looking for a new source
because their neighborhood bank that used to issue debt stopped
doing so after the Great Financial Crisis.
Speaker 4 (05:27):
Exactly, if you look at sectors like the auto lending market,
if you look at the biggest banks out there, Goldman Sachs, JP, Morgan,
Bank of America, not a lot of lending in that space.
Speaker 3 (05:38):
They don't really make a huge focus on it.
Speaker 4 (05:40):
So as a result of that, there was liquidity that
needed to be taken up or debt issuance, and that
was sort of absorbed by the private credit market and
it's been a tremendous run where there's been a lot
of investment in that space. And what often happens in
financial markets is there is enthusiasm and growth that outpaces
the regulatory environment, and as a result, you have situations
(06:04):
occurring like we've seen with Tricolor and First Brands, where
the growth led to probably some unsavory business practices or
fraudulent business practices. We don't know the exact specifics yet,
but certainly it outpaced where the regulatory framework was, where
there just wasn't enough visibility onto some of these loopholes
(06:25):
that some of these companies, it seems exploited.
Speaker 2 (06:28):
Yeah, here are the pieces that there's a bunch that
we don't know right, like how big all this is,
where does it all lie? Is it concentrated in any
number of banks or insurance companies that would be really
upset if this stuff started to blow up. What we
do seem to know is that with the failure of
Tricolor and then First brands. The private credit industry seemed
(06:51):
a bit blindsided. They were not aware of all of
the different loans that were out there. The mechanisms that
they used to try and control risk did not work
quite as well in private markets where there's less transparency
than in public markets, and it just grew so at
(07:11):
least according to the author, the private credit industry has
grown so fast that the verification audit frameworks quote haven't
kept up with the lending. And so what the author
points out is that since twenty twenty three, but really
in the last quarter alone, there has been a good
hard look at these loans on behalf of the lenders,
and they're trying to in a number of different ways,
(07:36):
find the liabilities that are risky and close off the
risk in some way, shape or form to prevent contagion.
And so he points out, you know, I'm going to
quote right from here, since twenty twenty three, lenders have
started to close off liability management loopholes that make pandemic
era financing so risky. What those specific loopholes are, I mean,
I think it allows you to shift debt from one
(07:57):
organization to another without the lender being able to recapture
some of.
Speaker 4 (08:01):
That and move assets too. That's backing behind some of
the debt. But important to note that, you know, like
you mentioned, you hit the main point there where the
lenders are kind of reclassifying some of those turns basically
to make sure that they can get paid if there's
a result of a bankruptcy, making sure that they're high
on that list of creditors who need to be paid back,
(08:23):
and also that they need to have a say in
sort of this bankruptcy process before any other companies kind
of jump the ship here.
Speaker 2 (08:31):
So by the very nature of private credit, it's right
in the word, it's pretty private. We don't get a
lot of visibility into what these lenders are doing underneath
the hood, and what the banks and insurance companies and
endowments and everybody else that's buying this stuff are doing
underneath the hood. But this is one of the first
reports that I've seen that points to some specific numbers.
(08:52):
For instance, terms requiring a unanimous lender consent before any
lean subordination jumps twenty three percentage points in the third
quarter and now appear eighty four percent of all credit deals. Again,
we have no way of verifying this, which is kind
of the concerning part other than you know, hearing it
from the major originators and lenders themselves. But this, to
(09:13):
me is the first piece of reporting that I've been
kind of keeping my eyes out for to confirm what
I suspected, which is the lenders seem nervous.
Speaker 3 (09:21):
M hm. He makes the parallel.
Speaker 4 (09:23):
Not to be clear, this isn't the size of scale
of the housing market back in seven, but similar behaviors
where you saw loan documents sort of loosening before months
before some of the defaults picked up.
Speaker 2 (09:36):
So again, how that will play out, over what timeframe
play will play out, and whether or not it blows
up in anybody's face, open questions. Nobody has an answer
to this stuff, but I don't think anybody's out of
the woods yet when it comes to this entire market.
We've got to take a quick break. When we come back,
we're going to be joined by Martha Gimble. She's in
(09:57):
the Budget Lab at Yale and they're doing a study
on AI impact on the labor market. We're gonna be
talking with Martha next on The Financial Exchange.
Speaker 1 (10:05):
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Speaker 5 (10:41):
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Speaker 2 (11:10):
The budget labb at Yale earlier this year was I
would have to say, the most cited source for research
on the impact of tariffs in this economy, and it
really was the front runner and anybody putting together measurements there.
The Budget labb at Yale is now taking a look
at the AI impact on the labor market. We're joined
by Martha Gimble from the Budget Lab at Yale to
(11:32):
talk about the I guess, the kickoff of their research
and what they've been able to measure so far. Martha,
thanks for joining us, appreciate it.
Speaker 6 (11:39):
Thank you so much for having me.
Speaker 2 (11:41):
So what sort of methodology I guess do you try
to apply to a question like how is artificial intelligence
affecting the labor market? It seems to be the express
goal of AI, but I'm just curious about how you
can even go about measuring something like this.
Speaker 6 (11:56):
Yeah, I mean to pic clear, that is the million
billion trillia depending on where you think AI is going,
I guess question right. You know, we tried to really
take this back to first principles and think about what
would you expect to see if and when AI starts
(12:16):
really affecting the labor market. And so what we did
was take existing labor market data, you know, the labor
market data that underpins a lot of statistic that many
of you are probably used to hearing about the labor
market like the unemployment rate, and used that to look
(12:36):
at how fast things are changing in the labor market,
but also whether or not you're seeing changes and who
is unemployed, who is employed, what that kind of looks like,
and the sort of spoiler is you are not. You
are not seeing big changes here yet, you know. I
think it sort of speaks to how fast this conversation
(13:02):
is moving that people expect to already be seeing employment
impacts from AI. Technological change takes time, and I think
our papers are an important reminder of that.
Speaker 2 (13:13):
So I guess provided some context. The biggest comparison point
that I can make would be the Internet. Now I've
said publicly that I think that this might be the
biggest technical technological innovation since the Internet. Do you have
some measurement of how long that technology took to affect
the labor market and what we in fact saw in
terms of the impacts.
Speaker 6 (13:35):
I mean, the Internet took time, and also it was gradual.
It was not a major shock. And one of the
things that happened because it was gradual was yes, people
lost their jobs, Yes, different skill sets became obsolete, but
it happened in such a way that it was easy
for people. I shouldn't say easy. It was easier for
(13:56):
people to retrain and new people coming into the labor market,
we're able to move into occupations that we're going to
have kind of long run options for them. I think
the Internet is the version that a lot of people
in AI are really hoping for, but they would say bigger.
(14:20):
I think the version of this that scares people is
the first industrial revolution, where you had a lot of
beavers suddenly out of business. Now there are changes, there
are things that are different now. Obviously that are different
about eighteen twenty two to state the obvious, But I
think part of what people are still trying to figure
out is one how long this is going to take,
(14:41):
how big it may or may not be, and who
it will affect.
Speaker 2 (14:47):
Martha when we talk about AI, obviously, you know companies
like IBM have been touting artificial intelligence for quite a
long time. When's the beginning point according to the budget
Labbid deal for this, I mean it feels like it's
definitely been dominating news stories for the last two to
three years. When's the beginning of your measurement? I guess
if we're going to try and guess at the impact
of this.
Speaker 6 (15:07):
This is such a good question. So we looked at
specifically the launch of generative AI, particularly chat GBT. You know,
obviously when we talk about AI, there's a lot of
things that are kind of swept into that definition, and
for your point, we are often a little bit sloppy
(15:29):
and how we talk about this, and we put many
different things under that heading. But we are specifically talking
about generative AI, which is the release that I think
caused a lot of people to start thinking, wait a minute,
can AI do my job? Can I do my employee's jobs?
Are we going to start seeing some big labor market
(15:49):
shifts here? And just to you know, kind of go
back to the point at the beginning, not yet right,
really clear and looking at our data, and we're not
the only ones who have found this that there are
not yet major impacts of AI on the local market.
Speaker 2 (16:06):
One of the places that this has been written about
quite a bit is recent college grads. It's been written
about the difficult labor market that they are facing as
they are graduating. You know, changes in what employers are
looking for. Is that measurable? I guess in this moment
that recent college grads are in fact facing a tougher
labor market, and if not, if not to be blamed
(16:27):
on AI, is there another thing that it can be
looked at to blame the struggle that recent college grads
are facing.
Speaker 6 (16:34):
So I think there's a couple of things that are
happening at once. One is, there are simply more people
graduating from college than ever before. And so if you
think about the competition for hiring college graduates, it's just
not as competitive as it used to be because there
are more college graduates. Right, It's a pure supply demand issue.
(16:57):
If you look at some of the worsening outcomes for
college graduates, and I should emphasize, you know, this is
all relative. You are still seeing much more positive economic
outcomes for college graduates relative people who don't have a
college degree on average. A lot of that predates this conversation.
(17:19):
I mean, we're talking about things starting in like twenty fourteen.
There's another aspect of this, which is, you know, I
have joked repeatedly that I will never forgive Sam Altman
for releasing chat GBT in the middle all of a
Federal Reserve hiking cycle. But I'm sort of not joking.
It makes it really hard to figure out how much
(17:42):
of any changes are about technological change versus these sort
of macroeconomic cyclical changes. Twenty twenty two was the middle
of a federal reserve hiking cycle. We would expect the
labor market to slow down. We would expect things to down,
particularly for younger workers who are just coming out of school,
(18:05):
because if people stop hiring, that is going to most
impact people who are trying to find a job for
the first time. And so a lot of what we're
seeing is almost certainly about the macroeconomic cycle rather than
technological change.
Speaker 2 (18:20):
Martha Gimble is the executive director and co founder of
the Budget Lab at Yale, and the most recent analysis
they're undertaking is valuing the impact of artificial intelligence on
the labor market, and the good news there is it's
going to apparently take some time to measure. Martha, really
appreciate you coming on and would love to chat with
you again as you release more stuff. So thank you,
thank you for having me. Yeah, she's right. This is
(18:44):
the trillion plus dollar question, maybe ten trillion dollar question
is will there actually be a measurable impact? And to me,
this echoes what we were just talking about with the
MIT study. Which is to this point, it's too early
to tell, right. It's not to say there won't be
an effect. It's not to say that you know it
won't be this, that and the other. But I especially
take her point that we are seeing this happen at
(19:06):
the same time that the FED is trying to control
the growth in the economy via interest rates, and so
very difficult to measure whether or not. Hey, is that
an AI effect or is the economy just slowing and
therefore the unemployment increasing.
Speaker 4 (19:18):
So much work to be done there, but it is
the fundamental question, and it's great that companies are trying
to tackle some research on it.
Speaker 2 (19:25):
Quick Break when we come back, Wall Street Watch plus
Trivia's next.
Speaker 1 (19:38):
Bringing the latest financial news straight to your radio. Every day,
It's the Financial Exchange on the Financial Exchange Radio Network.
Time now for Wall Street Watch. A complete look at
what's moving markets so far today right here on the
Financial Exchange Radio Network.
Speaker 5 (19:58):
Well, markets are exting games from yesterday's rally. Is the
FED kicks off its two day meeting followed by a
rate decision on Wednesday. Traders are also writing for a
big batch of big tech earnings and a potential China
trade deal later this week. Right now, the Dow is
up by four tenths of one percent or one hundred
and eighty three points. SMP five hundred flat at the moment.
(20:21):
NASDAC up about a quarter percent or fifty five points.
Rusted two thousands down two cents one percent, Tenure treasureel
is down one basis point at three point nine to
seventy nine percent, and crude oil down two percent today,
trading right around sixty dollars a barrel. Amazon announced that
it will lay off about fourteen thousand corporate jobs, marking
(20:43):
the largest round of corporate job cuts in the company's history.
Reports indicated Amazon's layoffs are expected to effect as many
as thirty thousand corporate jobs. Amazon is up slightly meanwhile,
ups rallying eight percent after the delivery Giant posted better
than a expected third quarter revenue and raised its fourth
quarter guidance. The company also said it has reduced its
(21:05):
management workforce by about fourteen thousand positions so far this year,
in its operational workforce by thirty four thousand positions elsewhere.
Microsoft and open Ai finalize a new agreement where Microsoft
will get a twenty seven percent ownership stake in open Ai,
worth about one hundred and thirty five billion dollars. Microsoft
(21:26):
is up about two percent today and has surpassed four
trillion dollars in market cap. Apple also crossing that mark today.
PayPal shares a climbing about eleven percent after the digital
payments company beat third quarter earnings and announced a new
e commerce partnership with open Ai. Wayfair surging twenty two
percent after the online furniture retailer posted stronger than expected
(21:48):
third quarter earnings, and after today's closing bell, Visa will
report its third quarter results. I'm Tucker Silva and that
is Wall Street Watch, and we haven't done trivia yet,
so let's get to it on this day. In twenty
twenty one, Mark Zuckerberg announced Facebook will change its corporate
name to Meta amid increased public scrutiny over leaked internal documents.
(22:12):
So our trivia question today, what year did Mark Zuckerberg
launch Facebook? Once again? What year did Mark Zuckerberg launch Facebook?
Be the fifth person today to text us at six one,
seven thirty six, two thirteen eighty five with the correct answer,
and you win a Financial Exchange show t shirt once again.
The fifth correct response to textas to the number six one, seven, three, six, two,
(22:35):
thirteen eighty five will win that T shirt. See complete
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Speaker 2 (22:42):
The whatever you want to call it, the Halo effect
or the Midas touch in the AI sector is at
least continuing to play out today. I know Tucker mentioned
a couple of these, but I just have to highlight
this for a moment. PayPal announces a deal to be
the payment processor for open Ai. Stock jumps eleven percent.
Nothing's been realized, they haven't implemented it, they haven't gained
(23:03):
any revenue, but stock's jumping eleven percent. Microsoft is announcing
that there's some clarity in terms of their ownership structure
of OpenAI. Stocks jumping two percent on a four trillion
dollar company, Nokia, as we just talked about some partnership
with Nvidia. It's going to be some sort of equity
investment into Nokia buying Vidia stocks jumping what was it,
(23:23):
fourteen percent on the news. Again, not to say that
any of these are completely out of line, but my
read on this is everyone is being treated as a
winner in the AI space. There are no losers right now.
If you have a business that is interacting with one
of these major players, and one thing we know is
(23:47):
that that's usually not the case. Usually not everyone is
a winner, unless you're a millennial playing soccer in the
nineteen nineties.
Speaker 4 (23:55):
But other than that, I'm sure that probably still continues today.
Speaker 3 (23:58):
I would imagine.
Speaker 4 (23:59):
I'm early in soccer coaching career, but I think it's
gonna trend that direction.
Speaker 2 (24:02):
Everybody gets a reped and.
Speaker 4 (24:04):
Not that I wanted to, but and also all against
the backdrop mic of a company who is not public.
You know, isn't it like that is they are public drink.
They're at the forefront of this revolution. I mean in
videos right there with them, and they are other players too.
But the seminal product on AI is chat GPT from
(24:24):
a company that is not public. It's it's fascinating the
tentacles of open AI and the fact that it has
grown so big and is still not a publicly traded
company yet.
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Speaker 6 (25:34):
Uh.
Speaker 2 (25:35):
There's a piece from Justin Fox and Bloomberg about how
the AI stock boom plays out. Unfortunately for all of
us out there, he does not have any insight into
when it plays out or what happens to the stock
market as a whole. In terms of pricing. But he
puts together basically a pretty convincing argument to me, which is,
(25:56):
as the economic significance of artificial intelligence becomes clear, or
the valuations of those companies, price to earnings, price to book,
price to all of these things will fall. And it's
because when you are dealing with something that is so
new and emerging, you don't honestly know how productive it
(26:16):
will make the economy, and so what you have is speculation.
You have some people betting, well, this is going to
make this company ten percent more productive, and therefore I'm
going to even if there's plenty of people they're saying, no,
it's only going to make them one percent more productive.
You take the averages there and you're saying, oh, yeah,
this company is going to become that more productive and
that more profitable. The answer is that we don't have
(26:39):
a real firm idea of how all this is going
to work. And so his point is, as it becomes clear,
valuations fall. Now, valuations can fall in two ways. Price
can come down, stock prices can come down, or these
companies are so productive that their earnings go up, and
in either case the valuation in those cases does fall
(27:03):
and he's not coming out and saying I know which
one's going to happen here. But it is a interesting
take on all this and why we do focus on
that piece quite a bit to say, oh, yeah, we
are in the ninety ninth percentile. Ever, in terms of
stock valuations, we are in a moment right now where
the only time that stock valuations have been pricier was
(27:23):
in the late nineties leading up to the dot com bubble.
It is because of that mere fact that, hey, there
is just so much unknown about this emerging new thing
that everyone is so excited about that there are speculators
all over there, all over the place trying to determine
and trying to bet on who's going to be the
winner and how big of a winner they are going
(27:44):
to be. And naturally, as you learn more, there will
be less speculation, because that's inherent in the idea of speculation,
is you're betting on something that you can't possibly know exactly.
Speaker 4 (27:54):
I thought it was a great framework to sort of
lay out the case where basically, with this next technological innovation,
the range of earnings growth that could be promised from
it is so wide. I mean, it could be minimal
into which his point, valuations will have to come crashing
down if you don't see a significant amount ofroductivity hancements
(28:15):
and earnings growth. But you could see on the other
end where you see tremendous earnings growth, and it's much
harder to make a clear determination from evaluation perspective where
some of these companies should fall because you just don't
know with this technology what the earnings growth rate is
going to be. It is much easier, for example, to
look at a real estate deal where you have a
(28:36):
multifamily building and you know how many tenants you have,
and you know how much rent and vacancy that you
could have. The variables are much more controllable of to
These are the amount of people I can fit in
this building, and this is the rent I will charge them.
Where you're talking about this, the earnings growth that you
can have is just far more variable and harder to assess.
And that's why you see the speculation and the build
(28:58):
up and the buy up of price to earnings valuations
here because so much, like you said, is hard to
gauge which side it's going to fall on.
Speaker 2 (29:05):
Let's take a quick break. When we come back, we'll
have the trivia winner and stack Roulette.
Speaker 1 (29:11):
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Speaker 3 (29:48):
Anks trivi.
Speaker 5 (29:49):
Your question today was what year did Mark Zuckerberg launch Facebook?
That would be two thousand and four. Mic from Lebanon,
New Hampshire is our winner today taking on Financial Exchange
Show t shirt. Congrats to Mike and we play trivia
every day here in the Financial Exchange. See complete contest
rules at Financial Exchange Show dot com.
Speaker 2 (30:10):
Time for a bit of Stacker. Let's hear Paul, what
do you have for us this morning?
Speaker 4 (30:15):
Next Era and Google are making an attempt to revive
a major nuclear facility in Iowa as an AI energy
demand serves. This is something that we talked about on
the show a lot. There is going to be a
tremendous amount of computing power and electrical power that has
required as part of the billions of dollars that these
(30:36):
major companies are spending to build these data centers across
our country. And as a result of that, nuclear energy
has become much more in vogue. And so this particular
plant was decommissioned back in twenty twenty, but they're now
setting it up to try and get it back online
in twenty twenty nine. And the one question that comes
to mind is, you know, we're in a huge competition
(30:59):
with China to become the leader in terms of AI
and the technology and how it evolves and hopefully become
the front runner in that space. And there's a huge
disparity in terms of the power generation that China has
versus the US in terms obviously there are some negatives
that comes with China and just how they can put
(31:21):
this power online without any regard for human life or
you know, the environment or anything like that. But we
got to wait four years, you know, three or four
years to get this thing online. There needs to be
a little bit more regulation. Regulation that is our legislation.
Maybe that's stripped back, and we need to be a
little faster with this.
Speaker 2 (31:42):
Yeah, I keep going back to this China US AI
race as a theme that's not really discussed or appreciated.
I think there's good reason for why it's not discussed,
because nobody truly knows. But on the energy side, it's measurable, right,
I have done it. But I'm sure somebody has measured
(32:03):
the current electricity capacity in China versus the United States,
and also measured the pace at which new stuff comes
online there compared to the US.
Speaker 4 (32:12):
They're doing more than ten times this year than we
are in terms of I think it's measured it. I've
read something that but like.
Speaker 2 (32:21):
That is measurable. What is not measurable is just how
far ahead US chip design is compared and you know
general of AI models, how far ahead that design is
compared to China. We have some sense that we are
far ahead. We know this by the fact that China
keeps trying to illegally import our latest and greatest semiconductors
(32:44):
and chips in order to design their own models. But
that part nobody can really measure. For me, Hey, are
we three x more efficient and more capable than China
when it comes to chip design? Are we one point?
Five x, because here's where the rubber hits the road, right, Like,
the reason that we are making and designing these latest
(33:08):
and greatest, faster and faster and more efficient chips is
to be able to implement them in the United States
where we don't have the same power generation. And if
it all, if a lot of that just comes down
to efficiency, how much power do you need to generate
the same level of artificial intelligence computing power, then I
(33:30):
think we're kind of screwed. And I'm not saying that
that is the case, but there does not seem like
any seeming willingness willingness in the United States to catch
up to China in terms of the pace at which
they can bring on energy infrastructure, no question, And so
I don't think that it all just comes down to efficiency.
(33:51):
I think it also comes down to speed and other
factors when it comes to these chip designs, as well
as the AI models themselves. And I hope that the
the American edge when it comes to tech innovation and
ingenuity and just that edge that we've always seemed to
have against other countries when it comes to designing this stuff.
(34:11):
And maybe it's because of institutions, maybe it's because of
more freedoms, and that stokes the creativeness. But if it all,
if all of it just comes down to who can
throw more power at the problem, China's gonna win.
Speaker 3 (34:25):
That game, definitely, definitely, but especially.
Speaker 2 (34:27):
At least anytime in the next decade, they will far
surpass us in that one game. So are we able
to innovate, innovate them faster, innovate and prevent them from
then they have? Yeah, it's a multi trillion dollar question. Uh,
let's see here, what do we want to talk about.
Let's talk about Airbnb. Airbnb wants to prevent Halloween parties
(34:53):
in the United States and Canada, and next they're canceling Christmas.
That's actually not being reported, but Airbnb does have a
real problem here where halloweens on a Friday, so you
know people are going to be extra sloppy. But really
the bigger problem is young people who want to throw
(35:16):
a massive party and do not have the space in
their four hundred square foot apartment to do So what
do you do. You get a bunch of people together
and throw a bunch of money at an Airbnb and
trash that place instead. So they're they're implementing some innovative
new ways to go about this. But they are taking
(35:36):
a look and blocking guests, you know, from booking certain
properties based on the timing of the booking, how far
away the booking is from their place that they're inquiring
about it. Right, So if I live in Boston and
I'm searching for a place to rent in I don't know,
Cape cod then they're they're taking a look at that
and saying, Okay, interesting, you're booking it for two nights
(35:59):
around Hall's. That's an interesting timing request here. So last year,
the companies said it prevented about thirty eight thousand people
in the United States and sixty three hundred in Canada
from making bookings during this time period.
Speaker 3 (36:14):
How you know what percentage were actually throwing a party. Yeah,
just beyond me. But maybe they have good enough data
where they're able to sort that out.
Speaker 2 (36:21):
Yeah. Look, I know that this is a serious problem
for them. I don't I don't really know how much
of this falls on Airbnb compared to the owner of
the property who's listing it and saying, hey, I'm comfortable
with you renting it out over Halloween, like I'm you know,
if I'm genuinely worried about this sort of thing. I'm
probably just saying, hey, I don't want my property to
(36:43):
be trashed, so I'm not going to rent it on
this Or.
Speaker 4 (36:45):
You extend the amount of nights, right, that would box
out someone who's trying to do this. You say, okay,
you can rent during the time period, but it's got
to be five nights. No college age or younger person
is going to commit to a five nights of a
rental rate just to throw one night party unless they
have a real big bankroll, I guess, but you think
that would sort of cut it off at the head.
Speaker 2 (37:05):
So my question then is why isn't Airbnb in the
business of having parties, having Halloween parties?
Speaker 3 (37:12):
Right?
Speaker 2 (37:12):
If they're going to prevent all of this stuff from happening,
they know there's demand. Talk about a business model. Okay,
you need to start renting out locations that you can
throw a party, not piss off all the neighbors, and
charge all these college kids a whole bunch of money.
Speaker 4 (37:27):
And I'm sure Airbnb executives could throw one hundred thousands
of lawsuits at us to explain why they don't want
to be in that game. From all of the issues
that they've dealt with over the years that I'm sure would.
Speaker 3 (37:39):
Make our heads spin.
Speaker 2 (37:41):
Yeah, yeah, I guess, just go look at it.
Speaker 5 (37:43):
I guess some of these listings have noise meters inside.
Speaker 3 (37:46):
Wow, like.
Speaker 2 (37:49):
Rent it to my family, Big quiet the noise meter,
My baby can't sleep. Markets are open and remain in
positive territory. SMP barely hanging on to gains here for
the day, but the Dow and NASDAC up a third
of a percent each. Big day tomorrow with Fed meeting
(38:11):
a two thirty plus big big earnings reports after the bell.
We'll be back at it tomorrow, folks. Have a great
rest of your day.
The Financial Exchange is produced by Money Matters Radio and
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(01:06):
and Paul.
Speaker 2 (01:06):
Lane, Good morning, Welcome back to the Financial Exchange. It's Mike,
Paul and Tucker with you on a Tuesday, ahead of
a big earnings week. Here Tomorrow, after the bell, we
are going to be hearing from Microsoft, hold up, Microsoft,
(01:27):
Alphabet and Meta themselves reporting let's see four seven nearly
nine trillion dollars worth of market capitalization. That's ahead of
Thursday's big report will be where we will hear from
both Apple and Amazon, who combined will be reporting more
than six trillion dollars worth of market cap, so big
(01:49):
ability to move markets that equates to a round a
fifth or a quarter of total market cap of the
S and P five hundred. We've got announcements from the
likes of UPS as well as Amazon, both of which
have announced that they are making job cuts. In some cases,
UPS already have made significant job cuts on the UPS side,
it's in the thirty plus thousand range. Amazon immediately planning
(02:12):
some fourteen thousand job cuts, with the potential for up
to thirty thousand. The two companies, I know, all of
us kind of think of the two as linked in
some ways, right. They are, you know, shipping companies in
a lot of ways, and we interact with them on
a daily basis. They're cutting different areas. You know, Ups
is purely that logistics company. They're cutting drivers, they're cutting
in store retail locations. Amazon holding on to their logistics
(02:35):
part of their business and really focusing on that corporate
workforce that they are reducing here. But again, big announcement
potential from all of these companies coming up this week
with big earnings. We also have a FED meeting that
is already underway. We expect that they will be cutting
rates tomorrow during their announcements at two pm press conference
(02:55):
at two thirty. The press conference itself, honestly, it will
be interesting, justin so far as I don't know what
you ask the FED right now, because they don't know
the state of the labor market. They have some semblance
of the state of inflation, but mainly I think they're
going to be asked questions like what will you do
if the government doesn't open for another thirty days? Which
is interesting, but I don't know how impactful it is, right,
(03:19):
there's no answer to it. What do you do if
in thirty days the government's still closed? Well, we guess
there's the answer, right Like that that's what we do,
and so they will have some answer on that front.
But again, I think the FED meeting is likely to
not give us a whole lot of new information, nor
should it, because the FED is flying blind a little bit.
(03:40):
Anything else catching your eye in markets or just big
financial news that I missed this morning, Paul.
Speaker 3 (03:46):
No, I think we hit on most of them here.
Speaker 2 (03:48):
So I am interested in this next piece from the
Wall Street Journal. It is from the opinion section of
the Wall Street Journal. It's from an individual named Dan Wertman,
who I had never heard of before. He's the CEO
of Nohedica market intelligence AI software company. Okay, got it.
There's a lot of these different companies. He's the CEO
of this one, and he writes about private credit and
(04:10):
the winter that is coming. So take us step back, Paul,
talk to us about private credit and the prevalence in
today's markets before we get into why it's heading for
a winter.
Speaker 4 (04:20):
So private credit has exploded over the course of the
last ten years. And when we're speaking about private credit,
there is the public credit markets that if your Intel
or Walmart.
Speaker 2 (04:31):
Or at and t issue can issue bonds.
Speaker 4 (04:33):
That someone at any you know, retail investment firm or
any type of major custodia out there could purchase the
debt that that company is issued. Private obviously implies that
you and I, Mike and Tucker and Paul wouldn't have
access to this funding. They're typically sourcing out funding from
non public markets. So that could be private equity firms,
(04:54):
it could be endowment, hedge funds, pensions.
Speaker 2 (04:57):
Family offices. Largely bigger investors though, who are going to
grab up a lot more than ten thousand dollars worth
of a bond.
Speaker 4 (05:04):
And it really jolted up when you had a period
of time or interest rates were extremely low and you
were looking for creative ways to be able to get
a better interest.
Speaker 3 (05:13):
From a debt perspective, think.
Speaker 2 (05:14):
About so the investors were looking for that, right and
the borrowers, I think, we're looking for a new source
because their neighborhood bank that used to issue debt stopped
doing so after the Great Financial Crisis.
Speaker 4 (05:27):
Exactly, if you look at sectors like the auto lending market,
if you look at the biggest banks out there, Goldman Sachs, JP, Morgan,
Bank of America, not a lot of lending in that space.
Speaker 3 (05:38):
They don't really make a huge focus on it.
Speaker 4 (05:40):
So as a result of that, there was liquidity that
needed to be taken up or debt issuance, and that
was sort of absorbed by the private credit market and
it's been a tremendous run where there's been a lot
of investment in that space. And what often happens in
financial markets is there is enthusiasm and growth that outpaces
the regulatory environment, and as a result, you have situations
(06:04):
occurring like we've seen with Tricolor and First Brands, where
the growth led to probably some unsavory business practices or
fraudulent business practices. We don't know the exact specifics yet,
but certainly it outpaced where the regulatory framework was, where
there just wasn't enough visibility onto some of these loopholes
(06:25):
that some of these companies, it seems exploited.
Speaker 2 (06:28):
Yeah, here are the pieces that there's a bunch that
we don't know right, like how big all this is,
where does it all lie? Is it concentrated in any
number of banks or insurance companies that would be really
upset if this stuff started to blow up. What we
do seem to know is that with the failure of
Tricolor and then First brands. The private credit industry seemed
(06:51):
a bit blindsided. They were not aware of all of
the different loans that were out there. The mechanisms that
they used to try and control risk did not work
quite as well in private markets where there's less transparency
than in public markets, and it just grew so at
(07:11):
least according to the author, the private credit industry has
grown so fast that the verification audit frameworks quote haven't
kept up with the lending. And so what the author
points out is that since twenty twenty three, but really
in the last quarter alone, there has been a good
hard look at these loans on behalf of the lenders,
and they're trying to in a number of different ways,
(07:36):
find the liabilities that are risky and close off the
risk in some way, shape or form to prevent contagion.
And so he points out, you know, I'm going to
quote right from here, since twenty twenty three, lenders have
started to close off liability management loopholes that make pandemic
era financing so risky. What those specific loopholes are, I mean,
I think it allows you to shift debt from one
(07:57):
organization to another without the lender being able to recapture
some of.
Speaker 4 (08:01):
That and move assets too. That's backing behind some of
the debt. But important to note that, you know, like
you mentioned, you hit the main point there where the
lenders are kind of reclassifying some of those turns basically
to make sure that they can get paid if there's
a result of a bankruptcy, making sure that they're high
on that list of creditors who need to be paid back,
(08:23):
and also that they need to have a say in
sort of this bankruptcy process before any other companies kind
of jump the ship here.
Speaker 2 (08:31):
So by the very nature of private credit, it's right
in the word, it's pretty private. We don't get a
lot of visibility into what these lenders are doing underneath
the hood, and what the banks and insurance companies and
endowments and everybody else that's buying this stuff are doing
underneath the hood. But this is one of the first
reports that I've seen that points to some specific numbers.
(08:52):
For instance, terms requiring a unanimous lender consent before any
lean subordination jumps twenty three percentage points in the third
quarter and now appear eighty four percent of all credit deals. Again,
we have no way of verifying this, which is kind
of the concerning part other than you know, hearing it
from the major originators and lenders themselves. But this, to
(09:13):
me is the first piece of reporting that I've been
kind of keeping my eyes out for to confirm what
I suspected, which is the lenders seem nervous.
Speaker 3 (09:21):
M hm. He makes the parallel.
Speaker 4 (09:23):
Not to be clear, this isn't the size of scale
of the housing market back in seven, but similar behaviors
where you saw loan documents sort of loosening before months
before some of the defaults picked up.
Speaker 2 (09:36):
So again, how that will play out, over what timeframe
play will play out, and whether or not it blows
up in anybody's face, open questions. Nobody has an answer
to this stuff, but I don't think anybody's out of
the woods yet when it comes to this entire market.
We've got to take a quick break. When we come back,
we're going to be joined by Martha Gimble. She's in
(09:57):
the Budget Lab at Yale and they're doing a study
on AI impact on the labor market. We're gonna be
talking with Martha next on The Financial Exchange.
Speaker 1 (10:05):
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Speaker 5 (10:41):
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and you can visit DAV fivek dot Boston to make
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Speaker 2 (11:10):
The budget labb at Yale earlier this year was I
would have to say, the most cited source for research
on the impact of tariffs in this economy, and it
really was the front runner and anybody putting together measurements there.
The Budget labb at Yale is now taking a look
at the AI impact on the labor market. We're joined
by Martha Gimble from the Budget Lab at Yale to
(11:32):
talk about the I guess, the kickoff of their research
and what they've been able to measure so far. Martha,
thanks for joining us, appreciate it.
Speaker 6 (11:39):
Thank you so much for having me.
Speaker 2 (11:41):
So what sort of methodology I guess do you try
to apply to a question like how is artificial intelligence
affecting the labor market? It seems to be the express
goal of AI, but I'm just curious about how you
can even go about measuring something like this.
Speaker 6 (11:56):
Yeah, I mean to pic clear, that is the million
billion trillia depending on where you think AI is going,
I guess question right. You know, we tried to really
take this back to first principles and think about what
would you expect to see if and when AI starts
(12:16):
really affecting the labor market. And so what we did
was take existing labor market data, you know, the labor
market data that underpins a lot of statistic that many
of you are probably used to hearing about the labor
market like the unemployment rate, and used that to look
(12:36):
at how fast things are changing in the labor market,
but also whether or not you're seeing changes and who
is unemployed, who is employed, what that kind of looks like,
and the sort of spoiler is you are not. You
are not seeing big changes here yet, you know. I
think it sort of speaks to how fast this conversation
(13:02):
is moving that people expect to already be seeing employment
impacts from AI. Technological change takes time, and I think
our papers are an important reminder of that.
Speaker 2 (13:13):
So I guess provided some context. The biggest comparison point
that I can make would be the Internet. Now I've
said publicly that I think that this might be the
biggest technical technological innovation since the Internet. Do you have
some measurement of how long that technology took to affect
the labor market and what we in fact saw in
terms of the impacts.
Speaker 6 (13:35):
I mean, the Internet took time, and also it was gradual.
It was not a major shock. And one of the
things that happened because it was gradual was yes, people
lost their jobs, Yes, different skill sets became obsolete, but
it happened in such a way that it was easy
for people. I shouldn't say easy. It was easier for
(13:56):
people to retrain and new people coming into the labor market,
we're able to move into occupations that we're going to
have kind of long run options for them. I think
the Internet is the version that a lot of people
in AI are really hoping for, but they would say bigger.
(14:20):
I think the version of this that scares people is
the first industrial revolution, where you had a lot of
beavers suddenly out of business. Now there are changes, there
are things that are different now. Obviously that are different
about eighteen twenty two to state the obvious, But I
think part of what people are still trying to figure
out is one how long this is going to take,
(14:41):
how big it may or may not be, and who
it will affect.
Speaker 2 (14:47):
Martha when we talk about AI, obviously, you know companies
like IBM have been touting artificial intelligence for quite a
long time. When's the beginning point according to the budget
Labbid deal for this, I mean it feels like it's
definitely been dominating news stories for the last two to
three years. When's the beginning of your measurement? I guess
if we're going to try and guess at the impact
of this.
Speaker 6 (15:07):
This is such a good question. So we looked at
specifically the launch of generative AI, particularly chat GBT. You know,
obviously when we talk about AI, there's a lot of
things that are kind of swept into that definition, and
for your point, we are often a little bit sloppy
(15:29):
and how we talk about this, and we put many
different things under that heading. But we are specifically talking
about generative AI, which is the release that I think
caused a lot of people to start thinking, wait a minute,
can AI do my job? Can I do my employee's jobs?
Are we going to start seeing some big labor market
(15:49):
shifts here? And just to you know, kind of go
back to the point at the beginning, not yet right,
really clear and looking at our data, and we're not
the only ones who have found this that there are
not yet major impacts of AI on the local market.
Speaker 2 (16:06):
One of the places that this has been written about
quite a bit is recent college grads. It's been written
about the difficult labor market that they are facing as
they are graduating. You know, changes in what employers are
looking for. Is that measurable? I guess in this moment
that recent college grads are in fact facing a tougher
labor market, and if not, if not to be blamed
(16:27):
on AI, is there another thing that it can be
looked at to blame the struggle that recent college grads
are facing.
Speaker 6 (16:34):
So I think there's a couple of things that are
happening at once. One is, there are simply more people
graduating from college than ever before. And so if you
think about the competition for hiring college graduates, it's just
not as competitive as it used to be because there
are more college graduates. Right, It's a pure supply demand issue.
(16:57):
If you look at some of the worsening outcomes for
college graduates, and I should emphasize, you know, this is
all relative. You are still seeing much more positive economic
outcomes for college graduates relative people who don't have a
college degree on average. A lot of that predates this conversation.
(17:19):
I mean, we're talking about things starting in like twenty fourteen.
There's another aspect of this, which is, you know, I
have joked repeatedly that I will never forgive Sam Altman
for releasing chat GBT in the middle all of a
Federal Reserve hiking cycle. But I'm sort of not joking.
It makes it really hard to figure out how much
(17:42):
of any changes are about technological change versus these sort
of macroeconomic cyclical changes. Twenty twenty two was the middle
of a federal reserve hiking cycle. We would expect the
labor market to slow down. We would expect things to down,
particularly for younger workers who are just coming out of school,
(18:05):
because if people stop hiring, that is going to most
impact people who are trying to find a job for
the first time. And so a lot of what we're
seeing is almost certainly about the macroeconomic cycle rather than
technological change.
Speaker 2 (18:20):
Martha Gimble is the executive director and co founder of
the Budget Lab at Yale, and the most recent analysis
they're undertaking is valuing the impact of artificial intelligence on
the labor market, and the good news there is it's
going to apparently take some time to measure. Martha, really
appreciate you coming on and would love to chat with
you again as you release more stuff. So thank you,
thank you for having me. Yeah, she's right. This is
(18:44):
the trillion plus dollar question, maybe ten trillion dollar question
is will there actually be a measurable impact? And to me,
this echoes what we were just talking about with the
MIT study. Which is to this point, it's too early
to tell, right. It's not to say there won't be
an effect. It's not to say that you know it
won't be this, that and the other. But I especially
take her point that we are seeing this happen at
(19:06):
the same time that the FED is trying to control
the growth in the economy via interest rates, and so
very difficult to measure whether or not. Hey, is that
an AI effect or is the economy just slowing and
therefore the unemployment increasing.
Speaker 4 (19:18):
So much work to be done there, but it is
the fundamental question, and it's great that companies are trying
to tackle some research on it.
Speaker 2 (19:25):
Quick Break when we come back, Wall Street Watch plus
Trivia's next.
Speaker 1 (19:38):
Bringing the latest financial news straight to your radio. Every day,
It's the Financial Exchange on the Financial Exchange Radio Network.
Time now for Wall Street Watch. A complete look at
what's moving markets so far today right here on the
Financial Exchange Radio Network.
Speaker 5 (19:58):
Well, markets are exting games from yesterday's rally. Is the
FED kicks off its two day meeting followed by a
rate decision on Wednesday. Traders are also writing for a
big batch of big tech earnings and a potential China
trade deal later this week. Right now, the Dow is
up by four tenths of one percent or one hundred
and eighty three points. SMP five hundred flat at the moment.
(20:21):
NASDAC up about a quarter percent or fifty five points.
Rusted two thousands down two cents one percent, Tenure treasureel
is down one basis point at three point nine to
seventy nine percent, and crude oil down two percent today,
trading right around sixty dollars a barrel. Amazon announced that
it will lay off about fourteen thousand corporate jobs, marking
(20:43):
the largest round of corporate job cuts in the company's history.
Reports indicated Amazon's layoffs are expected to effect as many
as thirty thousand corporate jobs. Amazon is up slightly meanwhile,
ups rallying eight percent after the delivery Giant posted better
than a expected third quarter revenue and raised its fourth
quarter guidance. The company also said it has reduced its
(21:05):
management workforce by about fourteen thousand positions so far this year,
in its operational workforce by thirty four thousand positions elsewhere.
Microsoft and open Ai finalize a new agreement where Microsoft
will get a twenty seven percent ownership stake in open Ai,
worth about one hundred and thirty five billion dollars. Microsoft
(21:26):
is up about two percent today and has surpassed four
trillion dollars in market cap. Apple also crossing that mark today.
PayPal shares a climbing about eleven percent after the digital
payments company beat third quarter earnings and announced a new
e commerce partnership with open Ai. Wayfair surging twenty two
percent after the online furniture retailer posted stronger than expected
(21:48):
third quarter earnings, and after today's closing bell, Visa will
report its third quarter results. I'm Tucker Silva and that
is Wall Street Watch, and we haven't done trivia yet,
so let's get to it on this day. In twenty
twenty one, Mark Zuckerberg announced Facebook will change its corporate
name to Meta amid increased public scrutiny over leaked internal documents.
(22:12):
So our trivia question today, what year did Mark Zuckerberg
launch Facebook? Once again? What year did Mark Zuckerberg launch Facebook?
Be the fifth person today to text us at six one,
seven thirty six, two thirteen eighty five with the correct answer,
and you win a Financial Exchange show t shirt once again.
The fifth correct response to textas to the number six one, seven, three, six, two,
(22:35):
thirteen eighty five will win that T shirt. See complete
contest rules at Financial Exchange Show dot com.
Speaker 2 (22:42):
The whatever you want to call it, the Halo effect
or the Midas touch in the AI sector is at
least continuing to play out today. I know Tucker mentioned
a couple of these, but I just have to highlight
this for a moment. PayPal announces a deal to be
the payment processor for open Ai. Stock jumps eleven percent.
Nothing's been realized, they haven't implemented it, they haven't gained
(23:03):
any revenue, but stock's jumping eleven percent. Microsoft is announcing
that there's some clarity in terms of their ownership structure
of OpenAI. Stocks jumping two percent on a four trillion
dollar company, Nokia, as we just talked about some partnership
with Nvidia. It's going to be some sort of equity
investment into Nokia buying Vidia stocks jumping what was it,
(23:23):
fourteen percent on the news. Again, not to say that
any of these are completely out of line, but my
read on this is everyone is being treated as a
winner in the AI space. There are no losers right now.
If you have a business that is interacting with one
of these major players, and one thing we know is
(23:47):
that that's usually not the case. Usually not everyone is
a winner, unless you're a millennial playing soccer in the
nineteen nineties.
Speaker 4 (23:55):
But other than that, I'm sure that probably still continues today.
Speaker 3 (23:58):
I would imagine.
Speaker 4 (23:59):
I'm early in soccer coaching career, but I think it's
gonna trend that direction.
Speaker 2 (24:02):
Everybody gets a reped and.
Speaker 4 (24:04):
Not that I wanted to, but and also all against
the backdrop mic of a company who is not public.
You know, isn't it like that is they are public drink.
They're at the forefront of this revolution. I mean in
videos right there with them, and they are other players too.
But the seminal product on AI is chat GPT from
(24:24):
a company that is not public. It's it's fascinating the
tentacles of open AI and the fact that it has
grown so big and is still not a publicly traded
company yet.
Speaker 5 (24:36):
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Speaker 6 (25:34):
Uh.
Speaker 2 (25:35):
There's a piece from Justin Fox and Bloomberg about how
the AI stock boom plays out. Unfortunately for all of
us out there, he does not have any insight into
when it plays out or what happens to the stock
market as a whole. In terms of pricing. But he
puts together basically a pretty convincing argument to me, which is,
(25:56):
as the economic significance of artificial intelligence becomes clear, or
the valuations of those companies, price to earnings, price to book,
price to all of these things will fall. And it's
because when you are dealing with something that is so
new and emerging, you don't honestly know how productive it
(26:16):
will make the economy, and so what you have is speculation.
You have some people betting, well, this is going to
make this company ten percent more productive, and therefore I'm
going to even if there's plenty of people they're saying, no,
it's only going to make them one percent more productive.
You take the averages there and you're saying, oh, yeah,
this company is going to become that more productive and
that more profitable. The answer is that we don't have
(26:39):
a real firm idea of how all this is going
to work. And so his point is, as it becomes clear,
valuations fall. Now, valuations can fall in two ways. Price
can come down, stock prices can come down, or these
companies are so productive that their earnings go up, and
in either case the valuation in those cases does fall
(27:03):
and he's not coming out and saying I know which
one's going to happen here. But it is a interesting
take on all this and why we do focus on
that piece quite a bit to say, oh, yeah, we
are in the ninety ninth percentile. Ever, in terms of
stock valuations, we are in a moment right now where
the only time that stock valuations have been pricier was
(27:23):
in the late nineties leading up to the dot com bubble.
It is because of that mere fact that, hey, there
is just so much unknown about this emerging new thing
that everyone is so excited about that there are speculators
all over there, all over the place trying to determine
and trying to bet on who's going to be the
winner and how big of a winner they are going
(27:44):
to be. And naturally, as you learn more, there will
be less speculation, because that's inherent in the idea of speculation,
is you're betting on something that you can't possibly know exactly.
Speaker 4 (27:54):
I thought it was a great framework to sort of
lay out the case where basically, with this next technological innovation,
the range of earnings growth that could be promised from
it is so wide. I mean, it could be minimal
into which his point, valuations will have to come crashing
down if you don't see a significant amount ofroductivity hancements
(28:15):
and earnings growth. But you could see on the other
end where you see tremendous earnings growth, and it's much
harder to make a clear determination from evaluation perspective where
some of these companies should fall because you just don't
know with this technology what the earnings growth rate is
going to be. It is much easier, for example, to
look at a real estate deal where you have a
(28:36):
multifamily building and you know how many tenants you have,
and you know how much rent and vacancy that you
could have. The variables are much more controllable of to
These are the amount of people I can fit in
this building, and this is the rent I will charge them.
Where you're talking about this, the earnings growth that you
can have is just far more variable and harder to assess.
And that's why you see the speculation and the build
(28:58):
up and the buy up of price to earnings valuations
here because so much, like you said, is hard to
gauge which side it's going to fall on.
Speaker 2 (29:05):
Let's take a quick break. When we come back, we'll
have the trivia winner and stack Roulette.
Speaker 1 (29:11):
Here the Financial Exchange every day from eleven to noon
non Serious XM's Business radio channel one thirty two. Keep
it here for the latest business and financial news and
the trends on Wall Street. The Financial Exchange is now
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(29:33):
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Speaker 3 (29:48):
Anks trivi.
Speaker 5 (29:49):
Your question today was what year did Mark Zuckerberg launch Facebook?
That would be two thousand and four. Mic from Lebanon,
New Hampshire is our winner today taking on Financial Exchange
Show t shirt. Congrats to Mike and we play trivia
every day here in the Financial Exchange. See complete contest
rules at Financial Exchange Show dot com.
Speaker 2 (30:10):
Time for a bit of Stacker. Let's hear Paul, what
do you have for us this morning?
Speaker 4 (30:15):
Next Era and Google are making an attempt to revive
a major nuclear facility in Iowa as an AI energy
demand serves. This is something that we talked about on
the show a lot. There is going to be a
tremendous amount of computing power and electrical power that has
required as part of the billions of dollars that these
(30:36):
major companies are spending to build these data centers across
our country. And as a result of that, nuclear energy
has become much more in vogue. And so this particular
plant was decommissioned back in twenty twenty, but they're now
setting it up to try and get it back online
in twenty twenty nine. And the one question that comes
to mind is, you know, we're in a huge competition
(30:59):
with China to become the leader in terms of AI
and the technology and how it evolves and hopefully become
the front runner in that space. And there's a huge
disparity in terms of the power generation that China has
versus the US in terms obviously there are some negatives
that comes with China and just how they can put
(31:21):
this power online without any regard for human life or
you know, the environment or anything like that. But we
got to wait four years, you know, three or four
years to get this thing online. There needs to be
a little bit more regulation. Regulation that is our legislation.
Maybe that's stripped back, and we need to be a
little faster with this.
Speaker 2 (31:42):
Yeah, I keep going back to this China US AI
race as a theme that's not really discussed or appreciated.
I think there's good reason for why it's not discussed,
because nobody truly knows. But on the energy side, it's measurable, right,
I have done it. But I'm sure somebody has measured
(32:03):
the current electricity capacity in China versus the United States,
and also measured the pace at which new stuff comes
online there compared to the US.
Speaker 4 (32:12):
They're doing more than ten times this year than we
are in terms of I think it's measured it. I've
read something that but like.
Speaker 2 (32:21):
That is measurable. What is not measurable is just how
far ahead US chip design is compared and you know
general of AI models, how far ahead that design is
compared to China. We have some sense that we are
far ahead. We know this by the fact that China
keeps trying to illegally import our latest and greatest semiconductors
(32:44):
and chips in order to design their own models. But
that part nobody can really measure. For me, Hey, are
we three x more efficient and more capable than China
when it comes to chip design? Are we one point?
Five x, because here's where the rubber hits the road, right, Like,
the reason that we are making and designing these latest
(33:08):
and greatest, faster and faster and more efficient chips is
to be able to implement them in the United States
where we don't have the same power generation. And if
it all, if a lot of that just comes down
to efficiency, how much power do you need to generate
the same level of artificial intelligence computing power, then I
(33:30):
think we're kind of screwed. And I'm not saying that
that is the case, but there does not seem like
any seeming willingness willingness in the United States to catch
up to China in terms of the pace at which
they can bring on energy infrastructure, no question, And so
I don't think that it all just comes down to efficiency.
(33:51):
I think it also comes down to speed and other
factors when it comes to these chip designs, as well
as the AI models themselves. And I hope that the
the American edge when it comes to tech innovation and
ingenuity and just that edge that we've always seemed to
have against other countries when it comes to designing this stuff.
(34:11):
And maybe it's because of institutions, maybe it's because of
more freedoms, and that stokes the creativeness. But if it all,
if all of it just comes down to who can
throw more power at the problem, China's gonna win.
Speaker 3 (34:25):
That game, definitely, definitely, but especially.
Speaker 2 (34:27):
At least anytime in the next decade, they will far
surpass us in that one game. So are we able
to innovate, innovate them faster, innovate and prevent them from
then they have? Yeah, it's a multi trillion dollar question. Uh,
let's see here, what do we want to talk about.
Let's talk about Airbnb. Airbnb wants to prevent Halloween parties
(34:53):
in the United States and Canada, and next they're canceling Christmas.
That's actually not being reported, but Airbnb does have a
real problem here where halloweens on a Friday, so you
know people are going to be extra sloppy. But really
the bigger problem is young people who want to throw
(35:16):
a massive party and do not have the space in
their four hundred square foot apartment to do So what
do you do. You get a bunch of people together
and throw a bunch of money at an Airbnb and
trash that place instead. So they're they're implementing some innovative
new ways to go about this. But they are taking
(35:36):
a look and blocking guests, you know, from booking certain
properties based on the timing of the booking, how far
away the booking is from their place that they're inquiring
about it. Right, So if I live in Boston and
I'm searching for a place to rent in I don't know,
Cape cod then they're they're taking a look at that
and saying, Okay, interesting, you're booking it for two nights
(35:59):
around Hall's. That's an interesting timing request here. So last year,
the companies said it prevented about thirty eight thousand people
in the United States and sixty three hundred in Canada
from making bookings during this time period.
Speaker 3 (36:14):
How you know what percentage were actually throwing a party. Yeah,
just beyond me. But maybe they have good enough data
where they're able to sort that out.
Speaker 2 (36:21):
Yeah. Look, I know that this is a serious problem
for them. I don't I don't really know how much
of this falls on Airbnb compared to the owner of
the property who's listing it and saying, hey, I'm comfortable
with you renting it out over Halloween, like I'm you know,
if I'm genuinely worried about this sort of thing. I'm
probably just saying, hey, I don't want my property to
(36:43):
be trashed, so I'm not going to rent it on
this Or.
Speaker 4 (36:45):
You extend the amount of nights, right, that would box
out someone who's trying to do this. You say, okay,
you can rent during the time period, but it's got
to be five nights. No college age or younger person
is going to commit to a five nights of a
rental rate just to throw one night party unless they
have a real big bankroll, I guess, but you think
that would sort of cut it off at the head.
Speaker 2 (37:05):
So my question then is why isn't Airbnb in the
business of having parties, having Halloween parties?
Speaker 3 (37:12):
Right?
Speaker 2 (37:12):
If they're going to prevent all of this stuff from happening,
they know there's demand. Talk about a business model. Okay,
you need to start renting out locations that you can
throw a party, not piss off all the neighbors, and
charge all these college kids a whole bunch of money.
Speaker 4 (37:27):
And I'm sure Airbnb executives could throw one hundred thousands
of lawsuits at us to explain why they don't want
to be in that game. From all of the issues
that they've dealt with over the years that I'm sure would.
Speaker 3 (37:39):
Make our heads spin.
Speaker 2 (37:41):
Yeah, yeah, I guess, just go look at it.
Speaker 5 (37:43):
I guess some of these listings have noise meters inside.
Speaker 3 (37:46):
Wow, like.
Speaker 2 (37:49):
Rent it to my family, Big quiet the noise meter,
My baby can't sleep. Markets are open and remain in
positive territory. SMP barely hanging on to gains here for
the day, but the Dow and NASDAC up a third
of a percent each. Big day tomorrow with Fed meeting
(38:11):
a two thirty plus big big earnings reports after the bell.
We'll be back at it tomorrow, folks. Have a great
rest of your day.
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