May 15, 2024 • 22 mins
Prepare to peer into the crystal ball of technology's future as Clem Miller and Steve Davenport, dissect Alphabet's latest developer conference bombshell, the generative AI phenomenon Gemini. This episode reveals how Alphabet's AI brainchild is shaping up to be core to the evolution of Google Search, Android, and other Alphabet products, giving OpenAI a run for its money. We'll navigate the intricate dance of AI and hardware, examining Alphabet's budding alliance with NVIDIA and their homegrown Tensor Trillium chips. Stick with us to understand why these strategic moves by Alphabet could usher in an era where AI's reach is vast and unbounded, as we speculate on how this could redefine the competitive tech landscape.
Then, we pivot to dissect the shockwaves that a TikTok ban in the U.S. could send through the digital ecosystem, possibly catapulting YouTube Shorts and Meta's Facebook Reels into the spotlight. Clem and I scrutinize the contrasting tech competition philosophies of the U.S. and EU, offering our take on the EU's use of its competition policy to defend small businesses. We'll also break down Alphabet's current market stronghold, diving into its financial vigor and the audacious 'reach projects' that could redraw the boundaries of tech innovation. Get ready for a riveting evaluation of how Alphabet's integration of AI into personal tech could solidify its avant-garde status, and why this juggernaut remains an unshakeable presence in our investment portfolios.
Straight Talk for All - Nonsense for None
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Steve Davenport (00:02):
Hello and welcome to Skeptic's Guide to
Investing with Glenn Miller andmyself, Steve Ebenholt.
In this episode, we're going totalk about Alphabet, still
often called Google.
Yesterday, Alphabet had aconference for its certified
software developers.
Alphabet rolled out a series ofnew products and product
(00:23):
improvements.
Glenn, can you share with uswhat was unveiled at the
developers conference?
Clem Miller (00:30):
Okay, so Google, that is, Alphabet has a product
called Gemini and that is theirAI product.
Think of it as being like themore famous open AI, which is
affiliated now with Microsoftinto the entire product line of
Alphabet and also trying tocreate the capabilities
(01:12):
technologically that allowGemini to operate, so in terms
of chips as well as data centertechnologies.
So that's what they're doing,that's what the that's what the
presentation was yesterday.
The presentation was wasabsolutely awesome in terms of
(01:35):
the ability of the uh, ofessentially a new type of Google
search search generativeexperience is what they call it
which will provide all sorts ofinformation on a multimedia
basis and actually anticipatethe questions that you want
(01:57):
answered.
So it's kind of, you know, takeopen AI but make it more sort
of search focused, and that'swhat you get with the search
generative experience of the newGemini powered Google.
That's interesting.
Steve Davenport (02:14):
Imagine this Gemini model and many of its
specific versions would requirea huge expansion in computer
power.
Has anybody thought about howready the market is for any of
these ideas, because it feels tome like we're going to shortage
in terms of the chips we needfor this type of technology.
Clem Miller (02:37):
Okay.
So, steve, there are really twotypes of chips that are useful
in this area.
One are the graphicalprocessing units, the GPUs, that
are used basically to supportthe NVIDIA computer stack, and
(03:00):
we've all heard about the GPUs.
We've done some of thesepodcasts, or at least one
podcast on NVIDIA and its GPUs,and what Alphabet is doing is
they have a partnership withNVIDIA, like some of the other
magnificent seven companies have.
They also have partnershipswith NVIDIA, but the real thing,
(03:26):
the real big thing anddifferent thing that Google is
doing, that Alphabet's doing, isthey have been developing their
own chips and they call it theTensor line of chips.
There's a they call it thetensor line of chips, and the
last iteration of this, thesixth generation, is called
(03:49):
Trillium, and and I think that'sa play on trillions, because
they want to be able to processtrillions of of transactions, of
information transactions, atany one point in time.
So it's the Trillium chips andthose are CPU chips and they are
(04:11):
used in the data centers toproduce, as I said, trillions of
calculations, to support theGoogle Gemini model.
Steve Davenport (04:34):
It feels like we're looking for a whole new
level of adjectives to describethis world of CPUs and
transactions per second anddecisions.
Is Alphabet, meta, microsoft,and I saw recently that Tesla
(04:59):
has a deal now with Oracle forusing databases to try to help
them with some of this decisionmaking and servers and networks.
Do you think that there is aclear leader coming out of this,
or has somebody figured out thepath forward ahead of the
(05:19):
others?
Or is this simply everyone isscattering in their own way to
try to come up with theirsolution, but nobody really
knows whether any of thesolutions are particularly
better or worse than the others.
Clem Miller (05:34):
Well, I think Steve , I think we're in the first or
second innings for generative AIin terms of what it can do, and
, to quote Mao Zedong, let athousand flowers bloom.
Right, I think that or was thatDeng Xiaoping?
(05:54):
I forget but anyway, let athousand flowers bloom, the idea
being that you're going to haveall sorts of variations on
generative AI that are beingdeveloped by all sorts of
companies, and not justMagnificent 7 companies, but by
(06:15):
a whole series of smallercompanies as well.
It's just, we hear a lot aboutthe big companies, the big tech
companies, but I think we'regoing to see a lot of those
smaller companies develop veryviable products and then perhaps
be scooped up by the big techcompany.
I think, though, it's earlyinnings.
(06:39):
I think, right now, we'reseeing somewhat different use
cases for generative AI at thedifferent big firms, and I think
that, over time, really it'shard to say whether those use
cases will harden into differentpaths for each of the companies
(07:00):
, or whether there will be somemore convergence of technologies
and thus greater competition.
Steve Davenport (07:11):
It feels to me like we had this same thing when
we talked about operatingsystems.
When we had operating systems,we had a bifurcation right there
was the Microsoft operatingsystem and there was the Apple
system, and then we had the cellphones and we had the iOS of
Apple and we have Samsung andothers.
(07:33):
It feels like there's going tobe an A and a B.
When I look at this.
I love your analogy to theinnings, because to me everybody
knows what a nine inning gameis and when you know you're near
the end of it and you know whenyou're kind of in the beginning
of it.
But when I look at this termartificial intelligence it kind
(07:56):
of bothers me a little bit,because when you think about
artificiality it means it's notreal and in some ways we've been
doing artificial intelligencefor a while.
Look at your tax returns.
You look at some of theQuickBooks, your tax returns.
(08:17):
You look at some of theQuickBooks.
You look at some of the waysthat we take information and
information is assimilated forus using a set of algorithms or
rules and the difference betweenthat and generative AI.
I agree there's a difference,but I also think that what we're
really seeing here is just acontinuation and so to go a
little bit off track here, I'mhaving an artificial hip put in
(08:40):
in the beginning of June, and soI said to myself gee, is this
like a?
When did this really start?
The first artificial hip wasput in in 1891.
And we've had various forms ofmetal and metal, metal and
plastic, ceramic all types ofdifferent materials used in this
procedure for 100 years.
(09:00):
And I look at it and say to methis is new, this is something
that I need to understand, it'suncertain.
And then I look at doctors andsay they've been doing this for
years, they've been doing thisprocedure.
And so are we a little bitnaive to say that artificial
(09:21):
intelligence is really justarriving now, because it really
feels like we've been findingways to artificially supplement
our lives, whether it's physicalprosthetics or whether it's in
trying to use software to solvereal problems.
Clem Miller (09:39):
Yeah, so, Steve, you're the bionic, or you will
be the bionic man soon.
I will.
Steve Davenport (09:48):
I'm just trying to figure out if they can maybe
put a chip in me and I'd startto become much more agreeable
and easygoing and it wouldimprove my investment results.
Clem Miller (10:01):
Well, I mean, speaking of that, you had this
experiment recently that Muskhad with his company Neuralink
you probably may have seen thatwhere they had to pull out the
chip, but they put a chip in aguy's brain to allow this guy to
(10:24):
move objects around on a screenjust by thinking about it,
which I think is kind of a crazything and, uh, I'm not sure I
would want a chip ever put intointo my brain, but it's uh, I
imagine some people might, um,and of course it has some
utility, or disabled people withprosthetics, and there's,
(10:47):
there's people now who are ableto help these people by
perceiving the end of theirfingers and be able to think
about and and and achieve asense of feeling from this
artificial limb which, if we'regetting to that point, does
(11:08):
artificial, you know.
Steve Davenport (11:11):
Is it replacement?
Is it right?
Let's get back to Google.
Clem Miller (11:15):
Well, let's let me just say something first.
I think generative AI is acategory of the broader
artificial intelligence.
I know sometimes people justuse the expression AI to refer
to generative AI, but the pointyou're making, which I totally
(11:35):
agree with, is that artificialintelligence AI, robotics just
goes way beyond what we'reseeing here with open AI and
Google and the others in termsof this.
Generative AI experience Goesway beyond that.
It goes to the self-drivingcars and so on.
Steve Davenport (11:58):
So let's talk about Alphabet's Waymo project.
What do you think about howWaymo and the cabs will
influence or?
Are they a leader?
Are they a follower?
Is Tesla still Uber?
Who is going to win in thisspace, and does it matter to?
Clem Miller (12:20):
us win in this space and does it matter to us?
So, for those of you who maynot know, waymo is the
autonomous car company orautonomous car vehicle that
Google has developed and it isnow driving around the streets
of a couple of US cities in acab formation, taxi formation,
(12:44):
and I would say it's still inkind of beta testing.
It's had some accidents,although it would be very
interesting to see datacomparing Waymo's accident rate
to the accident rates ofbasically human beings driving
(13:05):
around those cities.
We might be surprised to learnthat Waymo is actually pretty
good.
But I would say to yourquestion, steve, about Waymo
versus Tesla, I think Waymo andTesla appeal to different kinds
of consumers.
I think there are people,especially in the big cities,
(13:26):
who just don't like driving, whodon't like being in the
driver's seat.
They want to be ferried aroundas if they were in a bus or a
taxi, and that's what Waymo does.
For those folks, waymo has agreat utility as a taxi.
On the other hand, you've gotfolks who like to be in the
(13:50):
driver's seat and they like tobe assisted in their driving.
They may or may not want tohave something close to full
self-driving, but at the veryleast they want to be in the
driver's seat to monitor, uh,what's going on, uh, on screens
(14:15):
and that's what.
Uh, that's what tesla givesthem.
Um, I've had the opportunity totest drive a full self-driving
Tesla and it was quite aninteresting experience.
I got to tell you that, interms of weaving it out of crazy
traffic, I thought I was goingto die.
But a lot of people in thefront seats of those vehicles
(14:40):
sort of like what they'reexperiencing, and so I basically
see Waymo and Tesla as twodifferent user cases, two
different groups of consumers.
Steve Davenport (14:54):
You didn't mention YouTube.
Obviously, this is the mostsuccessful video platform,
except maybe for TikToksuccessful video platform,
except maybe for TikTok.
Clem Miller (15:17):
Yeah, I mean, I would say that one of the things
that we have to look at is thiseffort, already passed by
Congress, to perhaps get rid ofTikTok, at least in the United
States, for what I would say tobe geopolitical reasons more so
than anything else.
And you're going to have twobeneficiaries to that.
One is YouTube Shorts and theother one is Meta, that is,
(15:37):
facebook Reels.
But I think that YouTube Shortsis going to be the winner in
that kind of competition ifTikTok is forced to withdraw
from the market.
Steve Davenport (15:53):
I mean, who knows, against the US, big tech
has started to happen.
And where do you think MetaMicrosoft and where do you think
Meta Microsoft and Alphabetstack up in terms of having a
problem with the governmentactions?
Clem Miller (16:14):
Will one be more effective than the other in
Europe with the EU, is much more, I think, troubling for the big
tech companies than what we'reseeing in the United States, and
that comes from the nature, thedifferent nature of EU
(16:37):
competition and digital marketspolicies, digital markets being
a relatively new rule in the EU,and what that difference is is
that in the US there's a focuson horizontal competition.
By that I mean the US doesn'twant to see big competitors
(17:03):
buying each other and creatingmarket concentration and there's
less of a focus on bigcompanies gobbling up smaller
companies.
In Europe it's the oppositesituation where, yeah, I mean
there's some concern about bigcompanies gobbling each other up
.
I mean there's some concernabout big companies gobbling
each other up, but the biggerissue is bigger companies
(17:25):
gobbling up smaller companies,making it difficult for smaller
companies to do business andthen ultimately absorbing them.
And that's what the EU is veryconcerned about with respect to
US big tech.
They don't want US big tech tointerfere in the normal,
(17:45):
historical, traditional runningof those economies, which, in
Europe, has been focused more onsmall and medium-sized business
.
So, clem, let's look at ourmailbag and then, when you look
at the quantitative, screensthat I use and I'm not going to
(18:25):
go into all the numbers here,but I look at growth and revenue
growth.
Earnings growth has been strong.
Profitability and cashflowgeneration very strong.
Lots of cash buybacks using thefree cashflow generation very
strong.
Lots of cash buybacks using thefree cashflow generation.
Very strong.
Valuation actually not thatexpensive.
(18:49):
So I think that's a good thing.
It's not crazy expensive likeTesla is or Nvidia can be at
times, so relatively inexpensive.
In terms of how short sellerslook at the market look at
(19:11):
Google, I think that.
Look at Alphabet.
I should say short sellers havevery little short interest in
Alphabet, so that's good.
And lastly, one of the things Ilook at are Glassdoor ratings
for companies in order todetermine employee satisfaction
(19:34):
as a sort of a proxy forcorporate quality, and the
Glassdoor rating for Alphabet isactually pretty good.
So employees are very satisfiedwith the company.
So really across the board,it's really strong and I would
(19:54):
say, if it has sometimes someweaker performance, I think you
can expect that weakerperformance to be turned around
into stronger performance.
So it's really a core buy andhold stock for me, yep.
Steve Davenport (20:13):
I agree with almost all the aspects that you
said.
I think that the question hasbeen why has it kind of lagged?
I think that the question hasbeen why has it kind of lagged?
I think that for a while itfelt like it wasn't
participating in the MagnificentSeven, and it has recently come
back and started to performbetter.
(20:35):
But I believe that it's anintegral part of the economy.
I think it's an integral partof the economy.
I think it's an integral partof technology and I think it's
got good management in place todeliver on the project area that
it has.
And it also has some projectsthat are, I think, a little bit
of what I like to see and callreach projects, where they're
(20:56):
going down a path that couldhave huge potential, but they're
one of the few people who coulddo that because they have the
resources.
So I like Google as aninvestment.
It's been in our portfolios.
It's in the space ofcommunication services.
I'd say it's probably ournumber one name.
(21:18):
I think that when we look atthis stock, we see something
that has daily usage ofindividuals, and it feels to me
like they're going to be one ofthe people who get into that
first.
Integration of AI forindividuals not for businesses,
(21:39):
but for individuals.
I think they start to do thingswhich will impact people's
lives.
Thanks everybody for listeningto the podcast today.
Stay tuned for another episodeof Skeptic's Guide to Investing.
We're doing other episodes onmeme, stocks and the Fed, so
(22:00):
please check us out and pleaselet us know what you like and
what you don't like, and we'lltry to continue to get better.
Hello and welcome to Skeptic's Guide to
Investing with Glenn Miller andmyself, Steve Ebenholt.
In this episode, we're going totalk about Alphabet, still
often called Google.
Yesterday, Alphabet had aconference for its certified
software developers.
Alphabet rolled out a series ofnew products and product
(00:23):
improvements.
Glenn, can you share with uswhat was unveiled at the
developers conference?
Clem Miller (00:30):
Okay, so Google, that is, Alphabet has a product
called Gemini and that is theirAI product.
Think of it as being like themore famous open AI, which is
affiliated now with Microsoftinto the entire product line of
Alphabet and also trying tocreate the capabilities
(01:12):
technologically that allowGemini to operate, so in terms
of chips as well as data centertechnologies.
So that's what they're doing,that's what the that's what the
presentation was yesterday.
The presentation was wasabsolutely awesome in terms of
(01:35):
the ability of the uh, ofessentially a new type of Google
search search generativeexperience is what they call it
which will provide all sorts ofinformation on a multimedia
basis and actually anticipatethe questions that you want
(01:57):
answered.
So it's kind of, you know, takeopen AI but make it more sort
of search focused, and that'swhat you get with the search
generative experience of the newGemini powered Google.
That's interesting.
Steve Davenport (02:14):
Imagine this Gemini model and many of its
specific versions would requirea huge expansion in computer
power.
Has anybody thought about howready the market is for any of
these ideas, because it feels tome like we're going to shortage
in terms of the chips we needfor this type of technology.
Clem Miller (02:37):
Okay.
So, steve, there are really twotypes of chips that are useful
in this area.
One are the graphicalprocessing units, the GPUs, that
are used basically to supportthe NVIDIA computer stack, and
(03:00):
we've all heard about the GPUs.
We've done some of thesepodcasts, or at least one
podcast on NVIDIA and its GPUs,and what Alphabet is doing is
they have a partnership withNVIDIA, like some of the other
magnificent seven companies have.
They also have partnershipswith NVIDIA, but the real thing,
(03:26):
the real big thing anddifferent thing that Google is
doing, that Alphabet's doing, isthey have been developing their
own chips and they call it theTensor line of chips.
There's a they call it thetensor line of chips, and the
last iteration of this, thesixth generation, is called
(03:49):
Trillium, and and I think that'sa play on trillions, because
they want to be able to processtrillions of of transactions, of
information transactions, atany one point in time.
So it's the Trillium chips andthose are CPU chips and they are
(04:11):
used in the data centers toproduce, as I said, trillions of
calculations, to support theGoogle Gemini model.
Steve Davenport (04:34):
It feels like we're looking for a whole new
level of adjectives to describethis world of CPUs and
transactions per second anddecisions.
Is Alphabet, meta, microsoft,and I saw recently that Tesla
(04:59):
has a deal now with Oracle forusing databases to try to help
them with some of this decisionmaking and servers and networks.
Do you think that there is aclear leader coming out of this,
or has somebody figured out thepath forward ahead of the
(05:19):
others?
Or is this simply everyone isscattering in their own way to
try to come up with theirsolution, but nobody really
knows whether any of thesolutions are particularly
better or worse than the others.
Clem Miller (05:34):
Well, I think Steve , I think we're in the first or
second innings for generative AIin terms of what it can do, and
, to quote Mao Zedong, let athousand flowers bloom.
Right, I think that or was thatDeng Xiaoping?
(05:54):
I forget but anyway, let athousand flowers bloom, the idea
being that you're going to haveall sorts of variations on
generative AI that are beingdeveloped by all sorts of
companies, and not justMagnificent 7 companies, but by
(06:15):
a whole series of smallercompanies as well.
It's just, we hear a lot aboutthe big companies, the big tech
companies, but I think we'regoing to see a lot of those
smaller companies develop veryviable products and then perhaps
be scooped up by the big techcompany.
I think, though, it's earlyinnings.
(06:39):
I think, right now, we'reseeing somewhat different use
cases for generative AI at thedifferent big firms, and I think
that, over time, really it'shard to say whether those use
cases will harden into differentpaths for each of the companies
(07:00):
, or whether there will be somemore convergence of technologies
and thus greater competition.
Steve Davenport (07:11):
It feels to me like we had this same thing when
we talked about operatingsystems.
When we had operating systems,we had a bifurcation right there
was the Microsoft operatingsystem and there was the Apple
system, and then we had the cellphones and we had the iOS of
Apple and we have Samsung andothers.
(07:33):
It feels like there's going tobe an A and a B.
When I look at this.
I love your analogy to theinnings, because to me everybody
knows what a nine inning gameis and when you know you're near
the end of it and you know whenyou're kind of in the beginning
of it.
But when I look at this termartificial intelligence it kind
(07:56):
of bothers me a little bit,because when you think about
artificiality it means it's notreal and in some ways we've been
doing artificial intelligencefor a while.
Look at your tax returns.
You look at some of theQuickBooks, your tax returns.
(08:17):
You look at some of theQuickBooks.
You look at some of the waysthat we take information and
information is assimilated forus using a set of algorithms or
rules and the difference betweenthat and generative AI.
I agree there's a difference,but I also think that what we're
really seeing here is just acontinuation and so to go a
little bit off track here, I'mhaving an artificial hip put in
(08:40):
in the beginning of June, and soI said to myself gee, is this
like a?
When did this really start?
The first artificial hip wasput in in 1891.
And we've had various forms ofmetal and metal, metal and
plastic, ceramic all types ofdifferent materials used in this
procedure for 100 years.
(09:00):
And I look at it and say to methis is new, this is something
that I need to understand, it'suncertain.
And then I look at doctors andsay they've been doing this for
years, they've been doing thisprocedure.
And so are we a little bitnaive to say that artificial
(09:21):
intelligence is really justarriving now, because it really
feels like we've been findingways to artificially supplement
our lives, whether it's physicalprosthetics or whether it's in
trying to use software to solvereal problems.
Clem Miller (09:39):
Yeah, so, Steve, you're the bionic, or you will
be the bionic man soon.
I will.
Steve Davenport (09:48):
I'm just trying to figure out if they can maybe
put a chip in me and I'd startto become much more agreeable
and easygoing and it wouldimprove my investment results.
Clem Miller (10:01):
Well, I mean, speaking of that, you had this
experiment recently that Muskhad with his company Neuralink
you probably may have seen thatwhere they had to pull out the
chip, but they put a chip in aguy's brain to allow this guy to
(10:24):
move objects around on a screenjust by thinking about it,
which I think is kind of a crazything and, uh, I'm not sure I
would want a chip ever put intointo my brain, but it's uh, I
imagine some people might, um,and of course it has some
utility, or disabled people withprosthetics, and there's,
(10:47):
there's people now who are ableto help these people by
perceiving the end of theirfingers and be able to think
about and and and achieve asense of feeling from this
artificial limb which, if we'regetting to that point, does
(11:08):
artificial, you know.
Steve Davenport (11:11):
Is it replacement?
Is it right?
Let's get back to Google.
Clem Miller (11:15):
Well, let's let me just say something first.
I think generative AI is acategory of the broader
artificial intelligence.
I know sometimes people justuse the expression AI to refer
to generative AI, but the pointyou're making, which I totally
(11:35):
agree with, is that artificialintelligence AI, robotics just
goes way beyond what we'reseeing here with open AI and
Google and the others in termsof this.
Generative AI experience Goesway beyond that.
It goes to the self-drivingcars and so on.
Steve Davenport (11:58):
So let's talk about Alphabet's Waymo project.
What do you think about howWaymo and the cabs will
influence or?
Are they a leader?
Are they a follower?
Is Tesla still Uber?
Who is going to win in thisspace, and does it matter to?
Clem Miller (12:20):
us win in this space and does it matter to us?
So, for those of you who maynot know, waymo is the
autonomous car company orautonomous car vehicle that
Google has developed and it isnow driving around the streets
of a couple of US cities in acab formation, taxi formation,
(12:44):
and I would say it's still inkind of beta testing.
It's had some accidents,although it would be very
interesting to see datacomparing Waymo's accident rate
to the accident rates ofbasically human beings driving
(13:05):
around those cities.
We might be surprised to learnthat Waymo is actually pretty
good.
But I would say to yourquestion, steve, about Waymo
versus Tesla, I think Waymo andTesla appeal to different kinds
of consumers.
I think there are people,especially in the big cities,
(13:26):
who just don't like driving, whodon't like being in the
driver's seat.
They want to be ferried aroundas if they were in a bus or a
taxi, and that's what Waymo does.
For those folks, waymo has agreat utility as a taxi.
On the other hand, you've gotfolks who like to be in the
(13:50):
driver's seat and they like tobe assisted in their driving.
They may or may not want tohave something close to full
self-driving, but at the veryleast they want to be in the
driver's seat to monitor, uh,what's going on, uh, on screens
(14:15):
and that's what.
Uh, that's what tesla givesthem.
Um, I've had the opportunity totest drive a full self-driving
Tesla and it was quite aninteresting experience.
I got to tell you that, interms of weaving it out of crazy
traffic, I thought I was goingto die.
But a lot of people in thefront seats of those vehicles
(14:40):
sort of like what they'reexperiencing, and so I basically
see Waymo and Tesla as twodifferent user cases, two
different groups of consumers.
Steve Davenport (14:54):
You didn't mention YouTube.
Obviously, this is the mostsuccessful video platform,
except maybe for TikToksuccessful video platform,
except maybe for TikTok.
Clem Miller (15:17):
Yeah, I mean, I would say that one of the things
that we have to look at is thiseffort, already passed by
Congress, to perhaps get rid ofTikTok, at least in the United
States, for what I would say tobe geopolitical reasons more so
than anything else.
And you're going to have twobeneficiaries to that.
One is YouTube Shorts and theother one is Meta, that is,
(15:37):
facebook Reels.
But I think that YouTube Shortsis going to be the winner in
that kind of competition ifTikTok is forced to withdraw
from the market.
Steve Davenport (15:53):
I mean, who knows, against the US, big tech
has started to happen.
And where do you think MetaMicrosoft and where do you think
Meta Microsoft and Alphabetstack up in terms of having a
problem with the governmentactions?
Clem Miller (16:14):
Will one be more effective than the other in
Europe with the EU, is much more, I think, troubling for the big
tech companies than what we'reseeing in the United States, and
that comes from the nature, thedifferent nature of EU
(16:37):
competition and digital marketspolicies, digital markets being
a relatively new rule in the EU,and what that difference is is
that in the US there's a focuson horizontal competition.
By that I mean the US doesn'twant to see big competitors
(17:03):
buying each other and creatingmarket concentration and there's
less of a focus on bigcompanies gobbling up smaller
companies.
In Europe it's the oppositesituation where, yeah, I mean
there's some concern about bigcompanies gobbling each other up
.
I mean there's some concernabout big companies gobbling
each other up, but the biggerissue is bigger companies
(17:25):
gobbling up smaller companies,making it difficult for smaller
companies to do business andthen ultimately absorbing them.
And that's what the EU is veryconcerned about with respect to
US big tech.
They don't want US big tech tointerfere in the normal,
(17:45):
historical, traditional runningof those economies, which, in
Europe, has been focused more onsmall and medium-sized business
.
So, clem, let's look at ourmailbag and then, when you look
at the quantitative, screensthat I use and I'm not going to
(18:25):
go into all the numbers here,but I look at growth and revenue
growth.
Earnings growth has been strong.
Profitability and cashflowgeneration very strong.
Lots of cash buybacks using thefree cashflow generation very
strong.
Lots of cash buybacks using thefree cashflow generation.
Very strong.
Valuation actually not thatexpensive.
(18:49):
So I think that's a good thing.
It's not crazy expensive likeTesla is or Nvidia can be at
times, so relatively inexpensive.
In terms of how short sellerslook at the market look at
(19:11):
Google, I think that.
Look at Alphabet.
I should say short sellers havevery little short interest in
Alphabet, so that's good.
And lastly, one of the things Ilook at are Glassdoor ratings
for companies in order todetermine employee satisfaction
(19:34):
as a sort of a proxy forcorporate quality, and the
Glassdoor rating for Alphabet isactually pretty good.
So employees are very satisfiedwith the company.
So really across the board,it's really strong and I would
(19:54):
say, if it has sometimes someweaker performance, I think you
can expect that weakerperformance to be turned around
into stronger performance.
So it's really a core buy andhold stock for me, yep.
Steve Davenport (20:13):
I agree with almost all the aspects that you
said.
I think that the question hasbeen why has it kind of lagged?
I think that the question hasbeen why has it kind of lagged?
I think that for a while itfelt like it wasn't
participating in the MagnificentSeven, and it has recently come
back and started to performbetter.
(20:35):
But I believe that it's anintegral part of the economy.
I think it's an integral partof the economy.
I think it's an integral partof technology and I think it's
got good management in place todeliver on the project area that
it has.
And it also has some projectsthat are, I think, a little bit
of what I like to see and callreach projects, where they're
(20:56):
going down a path that couldhave huge potential, but they're
one of the few people who coulddo that because they have the
resources.
So I like Google as aninvestment.
It's been in our portfolios.
It's in the space ofcommunication services.
I'd say it's probably ournumber one name.
(21:18):
I think that when we look atthis stock, we see something
that has daily usage ofindividuals, and it feels to me
like they're going to be one ofthe people who get into that
first.
Integration of AI forindividuals not for businesses,
(21:39):
but for individuals.
I think they start to do thingswhich will impact people's
lives.
Thanks everybody for listeningto the podcast today.
Stay tuned for another episodeof Skeptic's Guide to Investing.
We're doing other episodes onmeme, stocks and the Fed, so
(22:00):
please check us out and pleaselet us know what you like and
what you don't like, and we'lltry to continue to get better.
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