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August 20, 2025 • 42 mins

Bloomberg’s Caroline Hyde discusses the tech sell-off as shares fall for a second day. Plus Bank of America’s new Chief Technology and Information Officer talks about the bank’s use of AI as a new report from MIT shows most enterprises see no return on investment from their AI spend. And analysts offer their take on Meta restructuring its AI team again.

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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is alive
from coast to coast with Caroline Hide in New York
and Edlow in Sentrancesco.

Speaker 2 (00:21):
This is Bloomberg Tech coming up. The tech sell of
accelerates as investors question valuations in the AI trade. This
is mit flag's concerns about enterprise AI adoption. We speak
but the return on tech investments, the Bank of America's
top technology officer, and what AI infused gadgets to expect
from Made by Google. Event that kicks off this afternoon.

(00:42):
But first we return to these markets that are having
another ugly day, two straight days of losses. We are
sinking significantly on the nastat one hundred, and they accelerate
off by more than three percentage points. Let's get into
some of the big points drags. We've got Netflix that's tumbling.
But I'm also looking at Palenteed. It is having its
worst two days in at least now four years. It's

(01:04):
twenty twenty two. We're seeing it sell off. We're off
by eight percent. Add that to the nine percent we
saw sell off yesterday. Those valuations that we were questioning
are actually coming down a fair bit in Video is
off by three point three percent after yesterday's about two
or three percent sell off as well. And Intel. It's
been outperforming the rest of the market previously, of course,
on the hopes of US investment coming from the government

(01:26):
and indeed two billion dollars coming from SoftBank, but today
even it succumbs to some of the anxiety. Let's stick
with a sell off. Let's get Ryan Rastellika's take. Go
really talk us through some of the worries in the market. Ryan,
what are we saying. We're having a questioning of AI valuations,
Is it macro concerns, is it August? And the fact
that we've got thin liquidity, what is it?

Speaker 3 (01:47):
You know, I've heard all of those sort of things.
I've heard that this is sort of a seasonal issue
that we've seen in past years. So there are some
people saying this looks like an attractive time to be buying.
The tech trade remains intact, but you do have a
number of these names sort of really come up this year.
You mentioned Palenteer, also companies like Core, We've Nvidia, a
lot of the MAGS seven names have been very strong

(02:08):
performance this year that has brought multiples and valuations, so
levels that are really kind of getting tougher to justify.
We are out of the earning season, We're in sort
of a slow news environment right now, and it just
seems like when you've seen moves like this, some kind
of consolidation or pullback.

Speaker 4 (02:24):
Is going to be expected.

Speaker 3 (02:26):
And when you have such high momentum names like Palenteer,
like core Weave, you start to see some of the
most aggressive selling in names like that.

Speaker 2 (02:33):
First Palenteers, who said worst two days set off in
three years, currently trading at one hundred and eighty times
future profit, but that's down from two hundred and forty
times street ship profits that it was current and previously
trading app but two days ago. Ryan is interesting. You'd
been digging into some of the valuations of the high
fliers that actually had only recently caught a bid. I
think of Intel and the fact that they'd added what

(02:55):
twenty four billion dollars in market capitalization in this month alone,
that's coming down today, and it did show this desire
to be getting into some AI related names.

Speaker 3 (03:05):
Yeah, so Intel's a bit of a special case. You
mentioned how there was reports of government wanting to take
a stake. You had soft Bait coming out and looking
to invest about two billion dollars into the company. You
did see a pull up there. I think the stock
rows twenty to thirty percent something like that. However, this
is the third twenty percent rally that Intel has seen
this year. We did see those previous rallies fade pretty quickly.

(03:27):
There still continues to be a lot of questions and
concerns about whether Intel will be able to re establish
itself as a major player within chip manufacturing but also
chip design. It is very much behind Nvidia and AMD
and AI chips. It's behind TSMC on the manufacturing side,
so there's still a lot of questions there. It's not
necessarily surprising to see the stock pull back after that

(03:49):
initial excitement, especially since you know, as we reported yesterday,
the multiple gotta levels last scene in the dot com era.

Speaker 2 (03:56):
And it's interesting that SoftBank's pulling back as well. It's
sun about seven percent, and in Asia trade we have
seen a bit of a global anxiety around tech by
doos lower as well after its results. Telling us a
little bit though about the next set of catalysts, because
at the moment we have been treading water more around
the macro concerns. We do get in Video's results next week,
that could be a key catalyst.

Speaker 5 (04:17):
Yeah.

Speaker 3 (04:17):
Absolutely, I think a lot of people are waiting to
see what is said there. I think there's a lot
of optimism about this report because we did just come
out of an earning season where all of its major
customers Microsoft, Meta, Alphabet, Amazon, they really affirmed their plans
to continue investing aggressively in AI, which is obviously going
to help Nvidia kind of first and foremost among the

(04:38):
infrastructure plays. Now, if they say anything about the outlook weakening,
or there's further skepticism about China or so on and
so forth, there is room for us to continue moving
down just because, like I said, we have seen really
strong gains in some of these stocks so far this year.
There is room for them to move down now. If
in Vidia is very strong, It's very possible that that

(04:58):
is a kind of sig people use to you know,
buy the step and maybe move back into tech.

Speaker 5 (05:04):
Ran plus SELCA as always, we thank you.

Speaker 2 (05:07):
Let's get you some breaking news now actually revolving around
a big tech player and China.

Speaker 5 (05:11):
Microsoft is on the move.

Speaker 2 (05:12):
The company says it has curtailed Chinese companies access to
advance notifications about cybersecurity vulnerabilities in its own technology. That,
of course, is after investigating whether a leak led to
a series of hacks exploiting flaws in its share points software. Now,
the announcement from Microsoft follows a campaign of cyber attacks
that Microsoft blamed on state sponsored hackers in China who

(05:35):
targeted security weaknesses in its SharePoint servers. We're off by
just seven tens percent. It's not as bad as the
rest of the market, but still trading lower. Let's get
you full context on this market. Anna Rathbunners with US
CEO founder of wealth management firm Grenandilla Advisory, And I mean,
what a difference a couple of days makes. What do
you make about this sudden AI valuation anxiety?

Speaker 6 (05:58):
Yeah, good morning. In some ways it's expected, right, you
can't expect everything to go up all the time. I
do think that there is something to be said about
the month of August being you know, special in a
seasonal way. But the other thing is there are people
who are taking gains. There's also when there's fear that
comes into the markets. Usually the ones that are casualties

(06:20):
first are the ones with the highest valuations and those
are in the big techniques. So you know, this, this
I think is temporary. I don't think this is a
start of anything that will become a trend, but certainly
it's part of being an investor.

Speaker 2 (06:33):
Part of being an investor, and how do you protect
what have been profits made? Is this actually just a
profit taking moment and people are locking in really big
wins that they've seen run up this summer.

Speaker 6 (06:47):
You know, it would be prudent to certainly lock in
some of those gains, But I don't think you can
be out of it because AI is where all the growth.

Speaker 4 (06:56):
And investment is going into it.

Speaker 6 (06:57):
I mean, you saw, you know, about a month ago
Trump administration coming out and basically pledging its support behind
AI and data centers and all the infrastructure and hardware.

Speaker 4 (07:07):
That's a part of it.

Speaker 6 (07:10):
And certainly I think this move into taking an equity
stake in Intel is a part of that story and
also part of the story of bringing manufacturing back into
the United States.

Speaker 4 (07:20):
So there's a lot of momentum here.

Speaker 6 (07:22):
Now, government being a part of a private company is
a double edged sword, but if we're to take a
look at the upside, there's a lot of support around
AI and text, So I don't think investors can really
ignore it.

Speaker 2 (07:33):
And to that point, I mean, when you get Intel
suddenly prior to today running up valuation sword to well
the most expensive it's been since the dot com era,
should you be putting that much credence in government backing
and in the ability for them to secure long term
demand for future chip innovations.

Speaker 4 (07:54):
Yeah.

Speaker 6 (07:54):
I don't think this is just about the government, because
we also had softwarek coming in and committing to or
talking about committing two billion dollars in terms of investment.
So I don't think this is the end of it.
And also I know the Trump administraturs said that they're
not going to be taking a governance role in this,
but you know, if you're the US government and you're

(08:17):
one of the largest shareholders, you can definitely influence through tweet.
And if the government has skin in the game, is
it really going to sit to the sidelines and look
at you know, Intel maybe not following through with the
Ohio foundry. I could see a scenario, there's a speculation,
but I could see a scenario in which the government
can help to garner those customers for those chips. I

(08:41):
don't think this is we'll take an equity steck and
be done with it.

Speaker 4 (08:45):
I don't think that's that.

Speaker 2 (08:46):
It's interesting SoftBank came on board many fitting that with
the help of ARM we could start to see real competition,
maybe even to in video in the longer term. Had
been some of the analysis written Anna, let's think about
in video for a moment. It's two down over the
last couple of days. We anticipate its earnings. Look more broadly,
of the tech tail wins. The AI trade still on.

Speaker 4 (09:07):
I think it's still on.

Speaker 6 (09:08):
I mean, you know, Meta just came out, and I
mean there I think there are issues there with the
management and the team structure and everything, and I don't
think it's necessarily good news for Meta.

Speaker 2 (09:19):
But you know this hiring s Sorry. Why why is
the restructuring of the AI department Alexander Wang leading when
it comes to LMS and the breakdown of these four
different areas of focus. Why is that perhaps not good
news for Meta?

Speaker 4 (09:34):
Well, it's not good news.

Speaker 6 (09:35):
Good news in a sense that in the last two
months we've seen a lot of restructuring.

Speaker 4 (09:40):
This is the type of stuff.

Speaker 6 (09:41):
That makes investors nervous in terms of effective management. You know,
you can hire the smartest people at high price tag and.

Speaker 4 (09:50):
Put them in a room.

Speaker 6 (09:51):
If they can't work together, and if they can't like
produce a product, then you don't really have anything.

Speaker 4 (09:57):
You don't have an ROI on that right.

Speaker 6 (09:58):
So this is a type of stuff that makes investors nervous.
So I think that's a very meta specific problem.

Speaker 2 (10:04):
I love that you have that idea of ROAI because
that is what many are looking at this MIT report about.
At the moment, we're blaming and it's in an unnuanced manner.
This particular report out at MIT is saying, look, ninety
five percent of the work done by company is to
integrate AI hasn't returned money or productivity. What did you
make of the report?

Speaker 6 (10:23):
Ana, Well, I mean what would you expect? I mean,
this is such new technology, you know. I think you
have to expect a lot of these efforts to fail
in the beginning. You have to have a lot of
failures before you can have the wins. That's why I
look at the AI efforts by these mag seven names
as incubation. I mean to look at ROI and expect

(10:45):
ROI within a year or two of them actually really
embarking and investing in it. I think it's too soon.
I think this is more of a long term play,
and so that report was sort of expected in my mind.

Speaker 5 (10:57):
Anna Rathbund, it's great to have you back on. Thank you.

Speaker 2 (10:59):
Brenna del Advisory now coming up and pleased to say
we're going to be digging into the return on AI
investment with Harry go Pel Krishnan is the chief Technology
and Information Officer for Bank of America. All about where
they've been focusing in on artificial intelligence and tech more broadly.
Let's get tech more broadly for a moment. So we
are in the eye the storm of a bit of
a sell off today. We're off by one and a

(11:21):
half percent on the Nasdaq one hundred, coming off of
our lows, the socks though Semiconductor Index, or by two
and a half percent. In Video off by two point
eight percent, Pallenteer having its worst couple of days in
three years. This is the Bloomberg Tech Oracle's cloud infrastructure unit. Well,

(11:41):
it's helped to propel CEO Larry Ellison to become the
second richest person in the world at one point. With
the AI boom, the company saw huge demand for its
computing and storage over the Internet, gaining foothold among key customers.
TikTok Open Ai for more. Bloomberg's Brodie Ford, who covers Oracle,
joins us now and many point in history, Oracle almost

(12:02):
pushed against this trend, and now they are well and
truly into it.

Speaker 7 (12:05):
Two thousand and eight, Larry Ellison gave the speech people
love citing. He said, this cloud is gibberish. And I mean,
they were making so much money and continue on old
school database software. But in the last couple of years
they've managed to really reinvent themselves from a legacy company
to one that's at the center of the AI boom.

(12:26):
And yeah, I mean there's no better example in their
work with open ai and stargate. Right we have the
details that on one new data center in West Texas
they're going to be spending over one billion per year
just to power the thing with gas. I mean that's
before construction, that's before all the chips. The scale of
the cloud build out happening for AI right now is

(12:48):
just it's a comical scale that we haven't seen before,
and Oracle has found itself at the center of it.

Speaker 2 (12:54):
Let's just talk about who's driven this because the CEO
is it called suffracats. How much has she been the
pinpointing of this growth area. How much has Larry Alison
really been playing a key role? What do you make
of the internal work and so good this business.

Speaker 7 (13:07):
We spoke with a lot of folks that are close
to this business, and you know, the CEO. Everybody wants
money from you, And for a long time, Saphra said, no,
we are not giving you all the money that it
takes to build these data centers. Right, I mean she
was skeptical the business for a long time, and then
these big deals started hitting. I mean, TikTok around twenty
twenty two was making so much money that it was

(13:29):
bigger than the entire rest of Oracle's Cloud all put together.
And so she saw deals like that, she saw deals
like open Ai, and that's when it became clear that
this isn't just part of Oracle's business. This is going
to be the business. Wall Street expects that by twenty
twenty nine that cloud Infra will actually be the largest
share of Oracle's revenue. And so this is a true

(13:51):
reinvention of the company for good and potentially for bad. Right,
I mean it's a much lower margin business. There's more
risk to it. But clearly for now the sentiment is
good and something is working well for them and the.

Speaker 2 (14:04):
Breadth of customer here, Brodie, because we think of TikTok
and we know they're a key strutch player for them,
we know the relationship with Stargate and therefore open Ai.

Speaker 7 (14:13):
But how broad is this getting It is a bit
of a whale business right now. It's a bit concentrated,
right The majority of their backlog is AI deals, largely training.
There are questions out there around how long does the
training boom last? What are the margins of it. It's
a very impressive customer list for sure, right. I mean,

(14:33):
as you said, we got open Ai, we got TikTok,
we got Elon Musk's Xai, we have Meta, we have
a kind of cadre of you know, all the AI
names that we all know, and so they've signed all
the right people. But the real test I'm going forward
is can you sell these folks more than just GPUs
and what can.

Speaker 2 (14:52):
They do with them? Punning Meg's Brodie Ford, fantastic to
have you, thank you. Let's talk about what you can
do with all of this GPU, this compute and how
it ultimately brings productivity to study from MIT saying that actually,
despite the billions enterprises have spent on general to AI,
perhaps only ninety five percent of organizations, well they say
they're actually getting a zero return. Thus far, only five

(15:14):
percent have got any return. This is really true. Harry
gopel Chrishnan is with us. He is the new Chief
Technology and Information officer over at Bank of America, but
he leads the bank's global technology approach. You've been at
Bank of America for fourteen years, but you've very recently
taken on this real global helm job. And there is
more nuance to that MIT report than the market has
given credence to. Basically, it's saying, look, if you just

(15:36):
tried to make it up and perhaps build some CHATCHBT
like products yourself, it didn't always work. But what have
you been doing internally to make things work for Bank
of America? Yeah?

Speaker 8 (15:46):
Great, thanks for having me. And look, we get to
serve seventy million clients every single day and AI is
not new to us.

Speaker 4 (15:52):
It's been part of our journey.

Speaker 8 (15:53):
So if I could offer you some soundbites of what
we've seen in the last five years, ninety nine percent
of our customers and clients today interact with us digitally
fully self serviced. Ninety nine percent of interactions in the
consumer business our self service digital. We have sixty five
percent of our account opening is digitally done. Ten years
ago zero percent. Our client satisfaction number, which we care
a lot about, has gone from the high seventies to

(16:15):
eighty nine point one. And yes we're counting, and so
you think about it, better client satisfaction. Shift to more
self service channels and more automation always yields great results.
And AI has been part of that.

Speaker 4 (16:26):
Journey for us.

Speaker 2 (16:27):
And I think of as the client. The customer perspective
is Erica. But your client and your other stakeholders, you
can your own employee base. How have they been adopting
general TODAI? Have them am using assistance?

Speaker 4 (16:38):
Yeah?

Speaker 8 (16:39):
And maybe if you just ruround the clock a bit right.
Our first journey into AI started with things like fraud
models and fraud algorithms. We have fourteen hundred plus patents
and two hundred and fifteen models in production with things
like AI models, and what we realized seventy eight years
ago is humans wanted to interact with machines in a
more humanistic fashion. And long before the large language models
came along, we thought about things like Erica, which allows

(17:00):
a customer to simply say a few words and for
us to figure out what they want rather than them
trying to figure out what our systems actually did. And
that's where we've now seen significant adoption. So this morning
we had a press release that we now had three
billion transactions that have been conducted on an aircut and
that continues to grow at.

Speaker 4 (17:15):
An exponential pace.

Speaker 8 (17:17):
So that's our clients and customers saying we actually like.

Speaker 4 (17:19):
To engage with you in this way.

Speaker 8 (17:21):
When you then pivot to our employee base, they're like, well,
why can't we use the same capability. So we've taken
this platform and broadened it use. So today a high
network advisor can actually look to Erica to say, look,
I need to hear about some complex trust policy in Delaware.
Can you summarize it for me and tell me how
I should talk to the client about it. And one
of the more recent implementation has been is I'm about
to meet a client, how do I prepare for that meeting?

(17:44):
Before a junior banker would take days to prepare a
docier for that. Now we can actually use Generati VI
models to create the first version of a draft that
saves hours and minutes, if not time, which then drops
to the bottom line.

Speaker 2 (17:55):
Harry, I know in many ways this is your secret source.
But I'm reading that you've got what seven eight hundred
patents of your own. How much are you having to
depend on purpose built general to AI. How much are
you looking to an open AI for the enterprise offering
or are you going to build it yourself?

Speaker 8 (18:12):
Well, I think we have a multi level approach to this, right,
We're not you know, we have enough reality to know
that we're not going to go build foundation models. We
want to build upon all the investments that are happening
in the industry. But the reason they're called foundation models
is they let you do a lot of things on
top of them. So we have a level of the
stack where we absolutely will embrace.

Speaker 2 (18:29):
Commodity, which ones I don't interest.

Speaker 8 (18:31):
Well, I think a little bit of everything. Right, We
are looking at it, and we intentionally want to be madalagnostic. Right,
We intentionally do not want to be wedded to any
one single solution, but then built upon it. When it
comes to our complex workflows. When you think about our
business processes, if it was just as simple as buy
something off the shelf, every one of us would be done.
The reality is you have to take these models in
and back to your productivity question, the way you unleash

(18:51):
productivities applying these to your business process. Understanding how your
current process work. Don't just try to replicate it, figure
out where you can eliminate parts of it, simplify it,
and then use AI to go after it.

Speaker 4 (19:03):
And what we've seen is it's yield a tremendous results
for us.

Speaker 2 (19:05):
I mean you said, and we're counting. How are you
measuring that productivity gain apart from the sheer scale of
interactions and numbers that you're seeing?

Speaker 8 (19:13):
Yea, I'll give you an example of it.

Speaker 1 (19:14):
Right.

Speaker 8 (19:14):
We now have seventeen thousand developers in my own team
that use coding agents to help their day to day activities.
Within that, we actually measure things like cost per story point,
defect density. There's a set of metrics productivity metrics that
we look at and we look at it before and
after we expect to do similar things on a business
process by business process basis. To actually understand the metrics

(19:35):
when we went into the problem how we deploy these
capabilities because they're not cheap, so we need to make
sure there's an ROI component to it. But coming out
of it, be able to see what comes out and
fail fast if it seems like a given process doesn't
lend itself appropriately.

Speaker 2 (19:48):
So I go to the sensitive question of those employees
that are embracing these coding agents.

Speaker 5 (19:52):
Yeah, to have a few of them.

Speaker 2 (19:54):
How are they feeling about being augmented or replaced?

Speaker 8 (19:57):
Well, I would say it actually allows us to get
to a backlog we could never get to. There's always
more work than you can get to. There's always things
that you could modernize, There's always more things to do.
And I actually tell you that our first reaction from
our teammates is been this frees them to do more
innovative work rather than the mundane work that was consuming
their time and resources. And I think we're going to
see that pattern play itself out over time.

Speaker 2 (20:18):
Sunny One, what a few weeks into the leading job.
It's wonderful to speak with you, Harry. Harry go for
Christian who's the chief technology and information officer over Bank
of America. Time now for talking tech and first up,
Shaomi says it's looking to sell its first EVS in

(20:39):
Europe by twenty twenty seven, taking on the likes of
Tesla and byd Now. The company announced its strategy after
posting a thirty one percent rise in quarterly revenue, boosted
by the launch of its second EV Now. According to
the Shaomi president, the company is doing research and preparation,
has no specific product plan yet, plus shares a by
do where they're lower today. The company posting second revenue

(21:00):
that slips slightly as it faces an economic downturn in
China and our AI rivals and difficulties in net growth areas.
In particular, China's Internet search is looking to Genai to
drive future growth, but it is struggling as open source
models like Deep Sea gain traction and startup. Game Science
has unveiled its working on a successor to one of
last year's best selling RPG titles now at games Con

(21:24):
conference it was over in Germany, the company showed off
a teaser trailer to Black Myth chron Qui, a sequel
to twenty twenty fours Black Myth Wukong.

Speaker 4 (21:32):
Now.

Speaker 2 (21:32):
According to game Science back at tencent, the project is
quote little more than an empty folder at its current stage,
coming up Meta making those restructuring moves of its AI group.
They have the details. Next, at first, that's check in
on these markets. We are down, and we're down significantly.
Then a's that one hundred really accelerating yesterday's losses. We

(21:55):
bounce off our lowers, but still we're seeing some of
the worst sell off that we've seen in a few months.
Are also saying names like Palenteer really eroding some of
that valuation that we've seen, having its worst couple of
days in three years, Other names such as Apple and
contributing to the points perspective. This is the Blombg Tech.

(22:17):
Welcome back to Bloomberg Tech. Let's take a look at
these markets. We're in sell off mode. We are bouncing
off our lows. Nevertheless, we're off by two point four
percent in the last two days, worst sell off since
about April. In fact, we have some deep anxiety surrounding valuations,
particularly in the AI trade, whether it's macro concerns as
we anticipate. J. Powell and an awful lot of FED
talk what rates mean, but also more broadly, what these

(22:40):
valuations have got to extreme levels really mean. When you've
got perhaps Enterprise not fully adopting in the productivity means
that some anticipated that MIT research report causing some girations.
Let's move on to the individual movers that we keep
an eye on. Look, I'm off by overall in the
last few days, well five and a half percent for Palenteer,
but worst couple of days set off in a few years.

(23:01):
Intel is off by more than six percent, wiping out
a lot of yesterday's gains. After we were enthusiasmor and
soft Bank investing in this company, and indeed talk of
the US government taking at least a ten percent stake.
But we pull back on Intel as people really lock
in profits. On Meta as well, we're off by one
point four percent. It's down the three straight trading days,
having lost five point six percent in the course of

(23:22):
those three days. Let's just stick with Meta more broadly.
In the company announcing yesterday yet another restructuring of its
AI group, pursuing superintelligence. Now it will be splitting its
AI team into four distinct teams and move. The company says,
we'll allow it to better capitalize on its recently acquired talent.
Bloomberg's tech reporter Riley Griffin is here to break it
all down. You're in San Francisco really digesting what seems

(23:45):
to be a focus on llms, still on the frontier research,
but then there's the application of this research and the infrastructure.
Of course, no doubt.

Speaker 9 (23:56):
Yesterday we were able to obtain a memo that was
shared by Alan are Weighing, the new chief of Metasuperintelligence Labs,
and he's really laying out the new structure for this
organization after weeks and weeks of an incredible effort to
hire talent. As you might remember, Caroline, this is hundreds
of millions of dollars sometimes nearing billion dollars in total

(24:19):
compensation for individual AI researchers, and now they are finding
their home within META, within these four teams.

Speaker 2 (24:25):
Yeah, and the home how are you seeing the perhaps
what some have reported by the scenes of some jostling
or discomfort with what had been suddenly incredibly expensive talent
coming in and a reorientation of where the focus is.
Does this help better align that talent and actually push forward?
And ultimately is it open large language models for example?

(24:46):
Are they going to delve into closed ones? Potentially?

Speaker 9 (24:50):
That is a really a burning question for all of us.
What we do know is that one team will continue
to be dedicated to large language models, the Lama product
that under pins metas AI efforts broadly.

Speaker 2 (25:04):
And the one team that I.

Speaker 9 (25:06):
Really am keeping an eye on is the infrastructure team.
Mark Zuckerberg has pledged to spend hundreds of billions of
dollars specifically on AI infrastructure, and now we are seeing
talent from within the company go and lead that specific effort.
We expect more capital to be deployed there this year
and then certainly next some.

Speaker 2 (25:25):
Great reporting Ridley Griffin, we so appreciate it. Let's get
some of the investor and analysis take now. Rohit kol
Con is with this managing director and scene analyst covering
Internet and capital markets research at Growth Capital Partners. And
that commitment to infrastructure that Riley articulates there, that money
is it proving out?

Speaker 4 (25:44):
I hey, thanks for having me.

Speaker 10 (25:45):
I think so far, what we have seen looking backwards
last twelve perhaps fifteen months, Meta is probably the best
poster child in providing qualifiable returns on investment in AI
in ffrastructure. By that, what I mean is the company
has demonstrated accelerating revenues. The company has demonstrated upside to

(26:07):
industry growth and a lot of other belts and vestles
around AI investment. So looking backwards, yes, definitely is the
poster child of showing written on investment looking forward.

Speaker 4 (26:21):
That's the question mark in the stock today.

Speaker 2 (26:23):
Okay, so they've been able to make it work for
advertising in the business model, but now for superintelligence and
the race to be one what business model does that
align itself with?

Speaker 5 (26:33):
For Meta?

Speaker 2 (26:33):
How much are we going to see generative AI affect
the way in which we interact and communicate.

Speaker 10 (26:40):
I believe the problems that Meta is trying to solve
using AI and using superintelligence are just compounding with the
data that they're collecting and the possible business models that
they are exploring. Remember, they have invested a lot of
money in the augmented reality virtual reality glasses they are

(27:00):
They have been working on that over the last four years.
There has been a reset in that and now probably
we are not now looking at twenty twenty seven for
the actual launch, So there is a timetable to build
AI within those glasses. I believe that's going to take
up a lot of money. And second, integrating the three
apps that they have, and those are the three largest
mobile apps in the world with billions of people using

(27:23):
on a daily basis. To make those apps super intelligent
and to make them extremely sticky is probably a monumental
investment opportunity for them. So these two are orthogonal investment opportunities,
but I think both are probably going to be something
that Zuckerberg is going to be fully invested in.

Speaker 2 (27:43):
At one point eight seven trillion dollars, is that a
full valuation for this full investment theme.

Speaker 10 (27:50):
That you have ro head, I believe, like the layers
unpacking in the future, it's just going to be something
that we are going to be excited about.

Speaker 4 (28:00):
I feel we are.

Speaker 10 (28:02):
We have still not yet scratched the surface of the
potential of jen Ai on a very large, multi dimensional
platform like Meta, and I feel Zuckerberg has the founder
whip if you feel he's investing behind this as if
it's an existential, once in a lifetime opportunity, even bigger
than when iPhone was launched. So I feel the excitement

(28:26):
and the kind of attitude that they can disrupt the
Apple card while redoing something new is something that the
investors are willing to be patient around on Metasta, and
so are we.

Speaker 2 (28:39):
Your patient is still got a buy rating. Compare and
contrast to some of the other key companies that you
do analyze. When I'm thinking that, you're looking at Alphabet
and Amazon and they as bigger winners. Have they been
as bigger winners in the capex? They've already spent and
do they have as good a road map as you
currently articulate for Meta?

Speaker 4 (28:58):
So far, I think Meta is the clear winner.

Speaker 10 (29:01):
Amazon is so far probably a number three, and Google
is a number two player, number two winner as far
as demonstrating returns on GENEI investments. Having said that, I
think the complex problems that each of these very large,
massive companies are solving or trying to solve using AI

(29:23):
are essentially compounding with every day, and that is leading
to more investment and more investment needed to solve those problems.
Think of the multi dimensional e commerce, cloud, advertising, prime video,
same day delivery.

Speaker 4 (29:38):
All of these elements.

Speaker 10 (29:40):
Can be optimized using AI, and at any given time,
probably Amazon.

Speaker 4 (29:44):
Is focused on maybe one or two of those.

Speaker 10 (29:46):
So I feel over the longer arc, the bigger winner
is probably going to be a company like Amazon.

Speaker 4 (29:53):
Given the surface area of improvement.

Speaker 10 (29:55):
They have the potential, but in the near term probably
a one pony like a Facebook, has executed better in
the last eighteen months, and they are demonstrating better returns today.

Speaker 2 (30:07):
I hate to talk about the near term because I
know you're a man who likes to give longer term
projections and price targets. But when you're seeing a sell
off like we've had after the last couple of days,
a lot of it tied up with worries about ROAI
and the report coming out of MIT, the GENAI divide,
and the state of AI and business. Do you give
credence to that? Do you think there's a lack of
nuance or do you think actually we should be worried

(30:29):
about how much we're investing in the returns on it.

Speaker 4 (30:33):
I think there are two ways to.

Speaker 10 (30:36):
Interpret miit and just the overall questions that are being
raised that hey, by the way we applied Genni algorithms llms,
we invested so much, but we are not getting the
returns as much as we wanted. I think these large
companies are trying to solve really large problems. The efficiency
gains that they will provide over the next twelve months

(30:57):
are something that we are very confident on whether that
translates into revenue uplift that remains to be seen only
a company like Meta has demonstrated that other guys are
kind of TVD. That's why from AI winner standpoint, Meta
is the one to buy on this weakness today.

Speaker 2 (31:16):
Right here, Kolk Carney, Managing director and Senior analyst at
Growth Capital Partners, it's great to catch up with you.
This is Bloomberg Tech and you're looking at a live
shot of the principal room. Bloomberg is live at Jackson
Hole this week. Tune in a continuing coverage leading up
to a special episode of Bloomberg Surveilience on Friday. This
is Bloomberg. Elisei, which ultimates complex healthcare housing systems, has

(31:45):
just announced a two hundred and fifty million dollars Series
E round led by Andrews and Horowitz. The startup, which
was founded back in twenty seventeen, off is Conversational AI,
a platform for users. And I'm pleased to say that
the CEO and founder and Lisa Mina Song is here
with me. You're based in New York and just how
was it raising these funds? How quickly are you able
to raise such an enormous amount of money?

Speaker 11 (32:07):
Thank you for having me.

Speaker 12 (32:09):
It was pretty quick actually to raise the round of funding.
I think investors are incredibly excited about investing in vertical AI,
which is AI that solves specific problems for specific industries,
which is exactly what we do, particularly focused in the
housing and healthcare industries.

Speaker 2 (32:26):
And why those particular industries. Was it just the pain
points were just so obvious and glaring to you.

Speaker 12 (32:31):
I think so it's pretty obvious to all of us
how inefficient and how limited the technology is when we
interact with these industries. But the core mission of the
company has always been to develop advanced technology for industries
that serve fundamental human needs.

Speaker 11 (32:47):
So housing and healthcare are some of the.

Speaker 12 (32:48):
Most important decisions we make and the important, most basic
needs that we have as humans.

Speaker 2 (32:53):
So the way in which the business works is you're
selling your conversational AI in a B to B manner,
but then it's me that ends up experience it as
a consumer. How have you seen healthcare institutions, housing institutions
willingness to just these sorts of products thus far?

Speaker 12 (33:10):
Yeah, they're extremely excited to use it. So we serve
on the housing side, One in every eight apartments in
the US today are using our AI software and they
we're using AI to automate manual processes to make operations
more efficient and to make them more cost effective. And
these inefficiencies really affect all of us. When an industry

(33:30):
is inefficient, then those that drives up costs for owners,
which ultimately trickles down to renters, which is really important
and really affects all of our lives. So there's a
lot of excitement about AI.

Speaker 2 (33:43):
Okay, And so with the money you do want.

Speaker 12 (33:46):
A significant amount of the funds are going to be
going to expanding our teams, so a lot of engineering
team members, product team members, research operations and more. We're
expanding our offices in New York City, San Francisco, Chicago,
in Boston. So we're looking for people who want to
have real world impact and solve really important problems that
impact millions of people's lives.

Speaker 2 (34:07):
We've talked a lot about talent wars and how expensive
certain researches have become. Is it the mission that therefore
attracts them or have you got to up the paycheck significantly?
And indeed, the.

Speaker 12 (34:18):
Reward of equity absolutely the mission. I think people who
want to apply these great advancements in artificial intelligence, but
want to see that that has real world impact and
that it can affect all of us is what attracts
people to working at alys Ai.

Speaker 2 (34:34):
How do you tend to offer when you think about packages.
Are people coming on board wanting to see a roadmap
for you to go public? I mean you're already a
series stage.

Speaker 12 (34:43):
We're focused on building a generational company. That's what's really
important to us. We want to change the face of
housing and healthcare and want people to look back on
it and say, I can't imagine what it was like
back when all of these services were so expensive expensive?

Speaker 11 (35:00):
Were they like that?

Speaker 12 (35:00):
And people who are joining want to be part of
making that change happen.

Speaker 2 (35:04):
How do you calm any anxiety that you're not going
to do a wind surf, You're not going to do
suddenly a big purchase where you, as the founder get
lifted Alexander Wang style but leave others behind. How do
you ensure that this idea that you take the team
with you remains resilient.

Speaker 12 (35:20):
I think we've been through and through dedicated to the
mission of the company, and there's so much more that
we all want to be a part of. To make
this happen and it's a really exciting journey to be on.

Speaker 2 (35:31):
We have no plans to do that well. Thus far,
it seems as though the clients have loved you and
speak very highly about the impact that your technology is
having serving people in healthcare, people in housing. Mina Song,
founder and CEO of Elise AI.

Speaker 5 (35:43):
On that fundraise, we can gractually done.

Speaker 2 (35:45):
Meanwhile, soaring valuations are coming from the likes also of
the major foundational models think open Ai, think Anthropic, but
also data bricks. They've also been boosting, but they're creating
perhaps a bit of a full sense of strength among
the VC markets. In reality, only the top one percent
of companies are pulling in the majority of capital, and
now more investors are beginning to worry about the health

(36:05):
of the young Silicon Valley startups who most k Clark
joins us for more And really you've been uncovering, as
you always do within tech and venture capital. That's some
of the trends. So these big whopping valuations cover up
a dark side.

Speaker 11 (36:19):
Yeah, there's a tale of two markets and venture capital.

Speaker 13 (36:21):
Right now.

Speaker 11 (36:21):
You have the AI mega companies Open ai Andthropic, Deta
Bricks raising rounds in what feels like in a monthly cadence.
And then you have all of the other startups and
many of them are actually struggling or even raising down rounds.

Speaker 2 (36:36):
So who are those types of startups because we just
had a lease AI on these very two hundred and
fifty million, relatively young startup and actually managing to well raise.
But who are those who have been left behind, particularly
those peraps who did well in twenty twenty one and
don't really want to admit that they're going to have
to face a downroute.

Speaker 11 (36:50):
I mean, it's exactly companies like that. A lot of
the unicorns that were minted in twenty twenty one, a
lot of the companies that were founded before twenty twenty one.
The vcs like to call these sort of the non
A native companies that are maybe trying to catch up,
trying to incorporate AI, but really they were They were
born before chat GPT, born before CHATCHAPT.

Speaker 2 (37:09):
Some of them have made the pivot, like I think
of a Figma, for example, managed then IPO at evaluation
that they were previously going to be bought at, and
people have really managed to think of them as generative
AI business even though they've integrated it as they grew.
Where are some of the pitfalls? Where are the industry
exposures that we're not liking right now?

Speaker 11 (37:27):
I mean, I think you have to look at e commerce, fintech, cryptocurrency.
There are many areas in which investors are not as
excited because they don't see how generative AI can really
help that business. I think, though, the main point of
weakness are the companies that raise at extremely high valuations
during the last hype cycle, and investors now just don't
see a path to allowing them to raise money at
an even higher price. So those companies are kind of

(37:49):
becoming what again VCS call like zombie unicorns and are
just sort of slowly, slowly dying.

Speaker 2 (37:56):
Will they be allowed to die? Will they be forced
to consolidate?

Speaker 5 (37:59):
What happen?

Speaker 11 (38:00):
I think there'll be some consolidation, But I do think
you'll you'll sadly see a lot of just companies quietly
disappearing and slowly dying over time. But of course there'll
be M and A, and of course there will be winners.
There will be companies like Figma and many others that
were born pre CHATDPT and still find success.

Speaker 5 (38:18):
And you'll be there to document it. Okay, comeup, we
appreciate it.

Speaker 2 (38:26):
Google. Well, it's set to show off new Pixel hardware
later today and it's made by Google. Event just bringing
man leap Sing who has technearch of Bloomberg Intelligence and
talk about well, how important is the hardware for Alphabet
parent company of Google.

Speaker 13 (38:41):
I mean everyone realizes Google has an advantage on the
custom chip side because of their TPUs. I think that's
going to show up in repeatedly, like they release Pixel
every year, so you will see a much better Pixel
version that can run LLLMS natively. That's the one thing
everyone wants Apple to do. I think Google is already

(39:02):
doing that obviously on device l LAMS is not that
big off an opportunity right now. But look, whatever people
think in terms of AI agents, to me, AI agent
opportunity will come through on device l LAMS and yes
there will be apps that run AI. LLMS browser is

(39:23):
very important. I mean, in the case of Google, they
have the Chrome browser for now now and then layering
it on operating system I think gives them a unique
advantage along with the chips. So that's what I feel
they will emphasize at the event.

Speaker 2 (39:38):
This asset is incredibly useful to them and really only
useful to them and will wither and die on the
vine if sold to another. But compare and contrast how
important it is to show off it within their hardware.
That's to say, a Samsung which was also infused with
Gemini too.

Speaker 13 (39:53):
Yeah, and look, Android operating system is used by a
lot of other OEMs. So from that perspective, what Google
has done well is to showcase AI capabilities on all
kinds of hardware. I mean, even the earbuds that they
will showcase I expect at the event will have some
integration of AI into variables because that's what they want

(40:15):
to show. At the end of the day. Your llms
right now will be distilled into smaller versions that can
do intelligent tasks, whether it's scheduling or voice assistance. And
that's where Google has a unique advantage because it has
the chips, it has the LLM, it has all the data,
and it has the family of apps with you know,
over two billion plus users, and that is why it

(40:38):
knows so much that it can do personalized AI that
others can. So to my mind, they are in a
unique position. Obviously, they have a small market share when
it comes to smartphones, but they're doing enough to showcase
that embedded AI element which could potentially drive up their
share when it comes to the hardware side.

Speaker 2 (40:57):
Yeah, briefly, how much could they steal from a cluster
theory offering.

Speaker 13 (41:01):
Well, I mean, look, Apple has their problems. They have
to figure out a way to integrate llms, whether through
partnerships or through their own I think it will be
through partnerships. In the case of Google, they will use
all the OEMs, so really the advancements will be at
the operating system later, but they have to showcase that
in their own hardware first. So that's why this event

(41:22):
is quite important.

Speaker 2 (41:23):
So too is as we wait in anticipation of Judge
Metas ruling on whether or not they're able to keep
Chrome as well. Bloombig Intelligence man Deep saying we love
having him as always as we anticipate some of that
hardware coming out. But that does it for this edition
a Bloomberg Tech. One last check on these markets before
we leave, because it's been a volatile hour of trading
during the show. We're off by one and a quarter

(41:43):
percent on then astat one hundred socks is feeling the
pain and video is down significantly. We're off by two
percent on the Semiconductor Index scrypto though turning back into
the red. There is risk and anxiety building about some
of the valuations in the market. We see some profit taking.
Don't forget, though, to check out our podcast. You can
find it on the terminal as well as you do
online on Apple, Spotify, and iHeart from New York. This

(42:05):
is Boomberg Tech.

Speaker 6 (42:08):
Mm hmmm mm hmmmmmmmmmmmmmmmm
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