October 3, 2024 • 42 mins
Bloomberg's Caroline Hyde and Ed Ludlow break down OpenAI's historic funding round and its new loan agreement securing $10B in total liquidity. Plus, PitchBook data shows AI is dominating VC deals in the third quarter, and Nvidia insiders cash in on the AI hype by selling $1.8 billion of shares this year alone.
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Speaker 1 (00:01):
From Marhard where Innovation of Money and Power colle in
Silicon Valley, NBN. This is Bloomberg Technology with Caroline Hyde
and Ed lud Love.
Speaker 2 (00:25):
Live from New York and San Francisco. This is Bloomberg Technology.
Coming up, open.
Speaker 3 (00:29):
AI's historic funding round. We discussed one of the largest
ever private investments and its new loan agreement securing ten
billion dollars in total liquidity.
Speaker 4 (00:39):
And AI dominates VC deals.
Speaker 5 (00:41):
We have the latest data for venture funding in the
third quarter and in.
Speaker 3 (00:44):
Video insiders cash in on the AI height, selling one
point eight billion dollars of shares this year alone. That
and so much more coming uphead.
Speaker 4 (00:53):
Yeah, straight to our top story.
Speaker 5 (00:54):
Open ai said it has completed a deal to raise
six point six billion dollars in new giving the AI
company a one hundred and fifty seven billion dollar valuation
and bolstering its efforts to build the world's leading generative
AI technology. In the last hour, the startups also announced
a four billion dollar credit line from banks around the world,
(01:16):
giving access to a more than ten billion dollar war chest.
Blion both Rachel Metz joins us on set in San Francisco,
and we've been tracking this for weeks and months and
it's finally done. But the important point is they need
the money because the cutting edge model requires the money
to train and build.
Speaker 6 (01:36):
Yes, they are in a very expensive business. If you
want to build a cutting edge large language model, any
kind of cutting edge AI model, at this point, you're
looking at potentially spending up to hundreds of millions of dollars.
So if you think about multiplying that out over a
couple of billion dollars, I mean it's like, well, you
can train a couple models there, and what if you
train one and you're like, you know what, I'm not
(01:57):
that happy with this. I mean a lot of money. Also,
they need you know, chips, they have staff, they have
all kinds of expenses there. They are bringing in revenue
of course, but it's still costs quite a bit to
do what they're doing.
Speaker 3 (02:09):
It is the future revenue growth, the future profitability. That
means standout names from VC like Thrive Capital, like Coast
a Ventures back the round, but numerous big substantial banks
back the credit facility. We're looking at Goldman, Sachs, JP
Morgan santunder Wells Fargo to name but a few. What
(02:29):
is the future growth model that they're all building one
hundred and fifty seven billion dollar valuation on.
Speaker 6 (02:35):
Rachel, I mean they're looking at businesses using their products
going forward. They're hoping that businesses will increasingly do things
like fine tune the models. They recently made it so
that businesses can do that and use them in different
parts of their workflow and find it useful enough that
they will keep paying for it, and they are starting
(02:57):
to see uptake. They have quite a number of both
individual and business users at this point. They recently passed
the one million business user mark for business users of
chat GBT in particular, But they still have a long
ways to go if they want to get to this
level that this valuation is showing them going to at
some point.
Speaker 5 (03:17):
There's two points I want to make really quick with
my sort of finance coverage on this is a pre
EBITDAR private company or a pre positive EBITDAR private company,
so that it could go to banks and get four
billion dollars in credit is remarkable. And also the eagle
eyed audience will say some of those banks are in Europe.
Speaker 4 (03:36):
That is also remarkable, Rachel.
Speaker 5 (03:38):
When they announced the closing of the equity round, they
also gave us data on how they're doing not necessarily
financial metrics, but like how many people are using open Ai.
Do we know anything about like the scale of this
company in the real world.
Speaker 2 (03:53):
Yes, we do.
Speaker 6 (03:54):
We know that there are I think it's two hundred
and fifty million weekly users of Chat GBT as we
previously reported. They also recently passed more than one million
business users for chat GPT, and that spans a couple
of different products related both to an educational product, they
have a smaller business product like for smaller companies, and
(04:15):
then also like a larger, more enterprise y product. So
they're definitely trying to hit out a lot of different
people in a lot of different areas, and they are
doing it. They are they are certainly bringing in revenue,
and they are seeing users. Uh. I think what remains
to be seen is how well this will all work
over time? What kind of you know, investors have to
be willing to wait. They have to be very patient.
Speaker 4 (04:37):
Right.
Speaker 2 (04:37):
This is not like your.
Speaker 6 (04:38):
Average startup where it's like, well, y, you know, you
might get a short term return and then maybe you'll
get a long term return. This is like, well, you're
gonna have to wait and see what we.
Speaker 2 (04:46):
Come up with. Over time. Rachel Metz, we thank you
so much.
Speaker 3 (04:50):
Meanwhile, Coast and Adventures participated in the Open AI round.
As we mentioned, tune in tomorrow our interview with Vinode
Coast and on this and of course AI's future impact.
Now we tend to another key story. US prosecutors are
broadening a probe of potential price fixing by German software
maker SAP and tech reseller Carasoft, seeking to examine the
company's work with almost one hundred government agencies.
Speaker 2 (05:12):
It's according to a new court record. Imers Jake Bleiberg
is here with more.
Speaker 3 (05:16):
You've been sifting through these court documents, remind us what
is being investigated, if not accused quite yet.
Speaker 7 (05:23):
Absolutely, the investigation is looking at the companies you mentioned, SAP, Kerosoft,
and then some other companies, the identities of which we
don't all know, for a potential scheme. And I should
stress that it's potential, not proven, to fix the prices,
to inflate the prices in sales of SAP technology to
(05:46):
the US government.
Speaker 5 (05:49):
Jake, you joined us the other day to discuss your
original reporting. What I'm trying to do is understand what's
new here. One hundred agencies is more than the agencies
you outline the other day. That's new, But is there
an expansion in the scope of what they're looking at.
Have they discovered more information that prompted more agencies to
say we better get on board with this.
Speaker 7 (06:10):
Absolutely, it's difficult to say what the prosecutors have discovered
at this point.
Speaker 4 (06:16):
And something we do.
Speaker 7 (06:17):
Know is that they say they've been having difficulty getting
information from the company. Sort of at the heart of
this Kerasoft. But as you point to, what has happened
is they went from an investigation primarily focused on sales
to the Department of Defense and then just as of July,
(06:37):
broaden this out pretty dramatically to look at sales to
ninety four or as many as ninety four civilian government
agencies as well.
Speaker 3 (06:48):
We're looking now at the statements coming from the company's
SAP saying it follows the rules around disclosing legal risks
are based on the current circumstances. There was still no
requirement to report on the individual cases. Karasoft also gave
us a statement. But ultimately, how are they going to
be interacting with these hundreds of agencies?
Speaker 2 (07:05):
What role do they now play in this?
Speaker 4 (07:08):
It's a great question.
Speaker 7 (07:09):
The sort of historic role that both of these companies
have played is by putting out a product. SAP makes
all sorts of workforce software, time cards, HR software, and
the complicated process of selling that sort of software to
the US government is sort of handled by Carasoft, which
(07:33):
stands in the middle and does a lot of the
difficult work of helping the software manufacturer navigate.
Speaker 4 (07:39):
These regulatory hurdles.
Speaker 7 (07:41):
So what those relationships will look like going forward in
the middle of this investigation is a big open question.
Speaker 5 (07:48):
Bloomberg's Jake Blybag, who broke the original story and continues
across the developing story, Thank you very much. Now coming
up here on this show, is job displacement caused by
AI something to brace for or is this just all hype?
We discussed with MIT economist Darren Smoglu, who gives us
his more skeptical view on what's really happening with AI
(08:12):
in the jobs market.
Speaker 4 (08:13):
This is Bloomberg Technology.
Speaker 3 (08:24):
Softbag founder Asoshi's son has sketched out one of the
most aggressive timelines for the adoption of AI yet, envisioning
a near future where the technology would run entire households
from monitoring the health of family members to grocery shopping now.
In a speech add an annual forum for enterprise clients
earlier today, Sun said that artificial general intelligence or AGI would.
Speaker 2 (08:46):
Arrive within the next two to three years.
Speaker 5 (08:49):
ED, but not everyone is so bullish on AI, at
least not when it comes to jobs. Darren Asmoglu, a
renowned professor at MIT, says that by his calculation, only
a small percent of all jobs round five percent is
right to be taken over at least heavily aided by
AI over the next decade. Darren Asamogli joins us now
(09:13):
and welcome to the program. This was one of the
most read stories on Bloomberg in the last twenty four hours.
There's no surprise about that. It has all of the
facets of a story that would you know, just engage
our audience on Bloomberg technology. Let's get specifics why only
five percent of jobs and which sectors in industries are
(09:34):
you basing your thesis on.
Speaker 8 (09:36):
Well, thanks, Ed, It's great to be on the program.
I think right now there is a lot of potential excitement,
perhaps hyper about AI, but if you look at its
current capabilities, you know we are very far from AI,
either general to AI or other types of AI performing
(09:59):
any of the tasks that involve a heavy level of
interaction with the physical world construction work, manufacturing work, carpentry.
Those perhaps one day will be much more feasible, for example,
if AI becomes so much more advanced, so much more reliable,
and can be integrated with so much better robots, for instance,
(10:22):
But it's not something that's going to happen in the
next five or ten years now. There's a lot of
other potential for future AI, perhaps to perform some social tasks,
but those are not going to be possible right now either.
You know you're not going to go to an AI
psychiatrist anytime soon, So if you stip out all of these,
(10:44):
you're not going to be left with much more than
five percent of the economy.
Speaker 5 (10:49):
Professor may I jump in and push back with a
point raised by our audience when I said you were
coming on, which is that AI technology is exponential, much
in the way that the invention of electricity with time
led to all sorts of breakthroughs. Right now, you're saying
five percent of jobs, But in two years or five
years from now, would you need to rethink your thesis
(11:13):
or redo your calculations.
Speaker 8 (11:15):
I should have prefaced this by saying there's a huge
amount of uncertainty in any forecast about AI, and apologies
that I didn't do that. I tried to do that
all the time. I was very excited. I just jumped
into it. There's a huge amount of uncertainty, and one
source of uncertainty is exactly what's gonna happen with AI
in the next several years. I don't think that the
(11:37):
most optimistic views in the industry, which sometimes people refer
to as scaling laws, actually will hold water when you
look at it within the next five years or ten years,
which say, you know, just double the amount of data,
double the amount of computer power, and then you're gonna
get double the amount of capabilities. Because to do that
(11:59):
we would actual need higher quality data. So if you
want AI to do the job of a carpenter, you
really need a completely different kettle of fish when it
comes to the kinds of data, and something like that
might be feasible with a different architecture of AI, but
right now all of the money is going into the
sort of the basic dominant architecture, which has its limitations
(12:22):
both in terms of reliability in terms of high level reasoning.
So that's the basis of my belief that, of course
generative AI and other types of AI will improve, but
we're not going to see a qualitative jump within the
next five to ten years.
Speaker 3 (12:37):
So as like your belief, what is exactly based on
what data, what historical norms are you looking back on
to drive and push forward on this five percent take?
Speaker 8 (12:47):
Yeah, I think this is why there is so much uncertainty.
There's nothing that's identical to generative AI in the past,
and that's part of the reason why people can hold
very different beliefs. But what I'm basing that on is,
first of all, other waves of digital technologies that promised
a lot of automation, sometimes a lot of productivity improvements,
(13:08):
sometimes a lot of changes in the way that we
would organize our offices and things like that, and at
the end, all of those changes have been very gradual.
And also what we have seen over the last two
and a half years, where you know, there have been advances,
but the advances haven't really been sort of qualitative in nature.
(13:29):
They haven't really exceeded the sort of the basic capabilities
of GPT three point five or three point GPT four.
So there will be advances, but I don't think any
of those advances will very quickly change the way that
we do various tasks in the economy. So, for example,
(13:50):
I do not believe that in five years time, when
we look at the labor market, we're going to see
certain occupations that will have completely disappeared.
Speaker 2 (13:59):
Think you would say that they would be augmented.
Speaker 3 (14:03):
The idea is, perhaps the optimist view is we will
not lose lots of people from the labor force, but
their productivity will be scaled.
Speaker 8 (14:10):
Where you think that's a yes, I think that's a
very very interesting and important point. I am not an
AI denier or an AI pessimist. I actually believe AI
has a lot of potential, And in fact, the real
potential is exactly what you said, Caroline, which is that
AI becomes a tool for workers to boost their productivity.
(14:32):
And again we're seeing some of that happening. You know,
Microsoft has a lot of co pilots. You know, some
of them work and they give some productivity improvements. There
are a few areas where we're seeing really phenomenal improvements, like,
for example, if you want to write simple subroutines in
one of the common programming languages. You know, GPT four
(14:52):
is great. Before then getthub copilot was pretty good. So
there are some things in which that sort of help
to decision makers as possible. But again, when you look
at the whole economy, that means helping carpenters, electricians, plumbers,
blue collar workers, construction workers, transport workers, people who are
doing teaching, people who are doing journalism. Those are things
(15:16):
that could be achieved perhaps at some point, but the
reliability and the reasoning of the models is not up
to the task yet.
Speaker 5 (15:24):
Do you see specific job creation in specific industries from AI.
Speaker 8 (15:31):
Well, there is one class of jobs where AI is
leading a big boost, which is people who have AI fluency,
either people who are AI programmers, AI integrators, or other
AI related service activities. But in my research, albeit from
a previous wave of AI in the late twenty tens,
(15:54):
we didn't see any other job category get a boost
in terms of hiring. And there are some other jobs
that I think there will be some retrenchment. So if
you're in IT security and you're doing so routine end
of IT security, there will be declines and job vacancies
in that area because some of these AI tools can
actually perform that quite well.
Speaker 3 (16:14):
When you see the headline that open ai is worth
one hundred and fifty seven billion dollars, when you see
that in Video is now worth almost three trillion, what
do you make of that in terms of how truly
the capital markets are analyzing the growth here.
Speaker 8 (16:30):
Well, I think there's a difference between Nvidia and open Ai.
Nvidia is riding a wave which is based on the
belief that those chips are going to become more valuable
because generative AI and other types of AI are going
to continue to boom, but they are generating revenues. Open ai,
on the other hand, I think does hasn't found a
(16:51):
revenue model that could justify the types of valuations we
are seeing at the moment now. It may well be
that in the future suddenly their API is going to
be so valuable and other firms are going to start
building on it, but it doesn't seem like there are
the kinds of applications that can have deep impact on
(17:13):
the productivity of workers or the automation of firms that
are going to be sold within the next five years
ten years. So I'm a little bit skeptical. But on
the other hand, open ai is also emerging as the
market leader, and the current ecosystem in the digital world
is right firms that take over the market and they
can use all of the data. They can you know,
(17:35):
interact with the consumers or the programmers directly. Those have
become very valuable because of venture capital or other deep
pocketed funders.
Speaker 3 (17:43):
Can't wait to see the response to this interview. I'm
sure someone has some thoughts. It economics professor drown Asmlgloo.
We appreciate your time, Aura. It's just world a new
flagship device with the Ring four of dating its popular
smart rings with new sensors, but a battery life and
(18:05):
about an algorithm. This is competition is really heating up.
Samsung of course, debuting its own Galaxy Ring for more
or a CEO Tom Hale joins us, So, how does
this make me distinct from the crowd.
Speaker 9 (18:17):
Well, the thing about the or Ring four is that
it's slimmer, sleeker, thinner, better, of course, and the feel
of the ring is what matters to many people because
there's a lot of technology packed in here.
Speaker 4 (18:27):
You want it to be small and compact.
Speaker 9 (18:29):
Maybe more importantly, we've taken a big leap forward in
sensing with something we call smart sensing, and smart sensing
adjusts dynamically to your body because not everyone's the same.
Your anatomy is not the same, your physiology is not
the same, your skin color is not the same, and
we adjust dynamically even as you rotate the ring a
little bit, we actually are able to keep the most
accurate signal.
Speaker 5 (18:51):
Tom, who do you consider it to be the composition
for this ring? Is it other rings or is it
other form fact? As a device, I think a lot
about watches it the moment, particularly having just been at
Apples event in recent weeks.
Speaker 9 (19:06):
What's interesting to me is that amongst our users, almost
two thirds wear a second wearable, usually a smart watch.
On the smart watch great for daytime notifications, you're getting
alerts all the time, but has an achilles heel, which
is battery life.
Speaker 4 (19:20):
And the ring is.
Speaker 9 (19:21):
Something that doesn't ask for your attention, doesn't send you notifications.
It's just in the background, seamlessly fitting into your life,
capturing your physiology so that you don't have to pay.
Speaker 4 (19:32):
A ton of attention to it.
Speaker 9 (19:33):
And as a result, you have an eight day battery
life with the or four ring. And so what that's
really interesting to think about is that you just don't
have to worry about your health as much, and then
therefore the watch in the ring can be compatible. So
in many ways we find these things to be two
devices that can work together on one person's body.
Speaker 3 (19:51):
And what's interesting is you've been working with other companies
that make other devices. We understand from Mark German's reporting
that you've been working alongside Meta's Raband team, for example. Well,
how do you see integration with other businesses going.
Speaker 9 (20:03):
Well, we've got so many great partners that we work with.
We haven't announced anything formally with Meta, but you can
imagine this world where you have this cloud of devices
on your body that you're using in different contexts. Maybe
it's headphones, maybe it's glasses with an AI assistant, And
how does your busiological state and something that you've got
on your body all the time work, maybe as a controller,
(20:26):
maybe as a way to guide, maybe as a way
to provide input, maybe as a way to give you
your other wearables a sense of whether you're stressed or
whether you're well rested, whether you're ready. There's a lot
of really interesting opportunities to explore when you think about
a permanently worn device that's oriented around your health that's
on your body. Twenty four to seven.
Speaker 5 (20:44):
Tom, we've just shown your latest financials and the trajectory
of this company. Your focus this point has been technology
and innovation. But where do you see this company going
from here? The direction for the business.
Speaker 9 (21:00):
Yeah, I mean, I think there's a lot of headroom
for us to grow just simply in the ring category.
Rings are new. People are just learning about the benefits
of long term health tracking, learning about the benefits of
getting sleep, learning about the understanding of their body. So
you know, the way the ring works is it can
tell you when you're getting sick, it can tell you
when you're doing well.
Speaker 4 (21:20):
It gives you.
Speaker 9 (21:20):
Lots of information and lots of insights, even an AI
coach that helps you make behavior changes. And I think
there's a lot of headroom just in that category. But
as you look beyond that, not only is it interaction
with other devices, but it might be potentially other devices
that you might see, Like we've seen prototypes for a
locket that sits on your chest. We've seen prototypes for
things that look more like designer rings. We introduced a
(21:42):
product with Gucci a couple of years back where we
have something that looks much more like jewelry and much
more like you know, much less like a piece of technology,
and it really fits into your life. So I think
the future is very bright for Rings. Lots of headroom
for us to grow this business. But more importantly, I
think people being aware of their health and understanding how
to manage their health is just a really big opportunity.
(22:04):
Everybody on the planet should have one of these things.
Speaker 4 (22:07):
Tom Hale or a CEO, good to catch up, Thank you.
Speaker 2 (22:17):
Welcome back to read Technology.
Speaker 5 (22:18):
I'm Caroline Hid in New York and Amed Lovelow in
San Francisco. If you're just joining us this fine Thursday morning,
or waking up to financial markets as a technology investor,
this is what it looks like Now's that one hundred
is kind of flat. There's a modest outperformance in semiconductors,
with the modest gain on the socks. Bitcoins have been
under pressure throughout the US morning session. If you're an investor,
(22:39):
it's been about weighing an escalating conflict in the Middle East,
with some economic data, a lot of hype around AI,
but no strong movement in either direction apart from a
few single names.
Speaker 4 (22:49):
One of them is in Nvidia.
Speaker 5 (22:51):
In an interview last night, Jensen Wang, the CEO, saying
that demand for Blackwell the latest GPU is insane. No
direct correlation, but the at one point trading its highest
level since August. Then ev go on track for its
biggest jump since twenty twenty one, trading its highest level
I think since May of twenty twenty three.
Speaker 4 (23:10):
It secured a one point.
Speaker 5 (23:11):
One billion dollar loan from the Department of Energy. Those
are two kind of movers. A lot going on, but
in video in particular, on a daily basis, it's still
the name that people are talking about character.
Speaker 3 (23:21):
Because it's worth more than three trillion dollars when you're
looking at its market capitalization and look insiders, they've been
cashing in.
Speaker 2 (23:28):
On what is a huge valuation jump.
Speaker 3 (23:30):
They've actually sold one is worth more than one point
eight billion dollars in shares so far this year. The
selling is it expected. Jess Menton is here to put
this into context. We often see insiders sell shares and
feels a lot when the market caps up so much.
Speaker 10 (23:45):
That's right, and this is in focus, and this is
a really the great story from Jeron Wodenstein and Crimin
Renicky on our equities team that put this together. And
whenever this happens, people want to question a company whether
or not there's growth concerns and things like that. But Jensen,
of course the CEO, this was pre planned and he
actually went through and did this from mid June until
mid of last month. That actually correlated with obviously the
(24:05):
drawdown that we saw with the stock because there was
such a huge run up. I mean, it's still up
close to like one hundred and fifty percent year to date,
but of course it's still down from that June peak
around nine percent, and still the S and P five
hundred has been able to rally even without one of
the biggest wings, but at a certain point it actually
eclipsed Microsoft and Apple and that market capitalization. But moving forward,
there's actually supposed to be additional sales, so in Vidia's
(24:26):
director is still supposed to sell about three million additional shares.
So that's kind of a question mark of whether or not,
well we still continue to see the stock held back
a little bit, even though we've seen it rally and
come back from some of those lows that we saw
earlier this summer, or will keep those gains in check,
but of course I was talking to you all about
this yesterday. But evercre actually made a call for chip
makers and is more optimistic that we would see a
rebound in the fourth quarter of this year.
Speaker 5 (24:48):
Suggests for so many people watching Bloombog technology, it will
be a familiar story. It is a classic in Silicon
Valley wealth creation from stock compensation. You sell shares over
time you get more money than you could ever have
dreamed of. But there is a paragraph in the story
that raises the question of whether or not the sales
inspire confidence in the stock.
Speaker 4 (25:10):
Do they inspire confidence or not?
Speaker 10 (25:13):
Well, there's someone too that when it comes to portfolio
managers that the reporters were speaking with, and Kim Mahoney
was actually one of them at for Mahony Asset Management,
and he was talking about sometimes you shouldn't read too
much into it, say, for instance, Jensen was already pre planned.
But a lot of times it's not just because of
reasons of growth concerns about the company. Obviously, you were
just mentioning earlier ed about how the CEO is talking
(25:34):
about this insane demand for the Blackwell chips. Of course,
there was a lot of scrutiny in recent weeks because
obviously the investors want the valuation of the company to
justify those future earnings and the growth. But still those
executive directors in the company, they sold about eleven million
shares so far in twenty twenty four, and so to
put that into context, that's the most since twenty twenty
when you are excluding, of course different stock splits like
(25:55):
earlier this year and in twenty twenty one. But you
do have some portfolio managers arguing it's not just because
of growth concerns.
Speaker 5 (26:01):
Ed Bloombergs just meant it brilliant as always, Thank you
very much. Now it's launched ay for the Roundhill China
Dragons ETF. It tracks an equal weighted basket of Chinese
tech companies under the ticker drag Bloombergs. Isabel A had
a story that hit the wire in the website in
the last couple of hours.
Speaker 4 (26:20):
What's the idea behind the CTF.
Speaker 11 (26:22):
So this tracks a basket that Roundhill made. So it's
five to ten Chinese companies that they can they qualified
as those that impress, those that exhibit great economies of scale,
competitive advantages, and really basically companies that they believe in.
So they're five to ten stocks and for another are nine.
These includes pdd Ali, Baba, may Twan, buid net Ease.
(26:42):
And what sets this apart from the other ets out
there that track Chinese linked stocks is that it's more targeted.
We have the biggest I shares one attracts some thirty.
We have k Webcrane shares attracts some thirty or fifty.
So this is just five to ten and that's what
they say. You don't want those little companies diluting you're
trying to exposure.
Speaker 3 (27:01):
These are megacap tech names, in particular Isabelle. And the
timing is kind of beautiful. It comes in line with
everyone getting over excited in a fomo feel around Chinese stocks.
Speaker 2 (27:13):
Was it always plans to come out. Now, that's the
thing with ETFs.
Speaker 11 (27:17):
You file for they filed earlier this year, you don't
really know when it will come out. So they said
that the timing couldn't have been better. But then they
said they also really just make products when they see
investor demand. And that actually is what caught my attention,
because even if we all hear these kind of negative
rhetoric around China, there are still investors who want China. Remember,
there are two ways to look at China. It's too cheap,
(27:37):
so let's buy it, or it's too cheap so let's
kind of stay away. And it's proving that the former
is still kind of that their echo calls are kind
of loud because for Roundhill to launch and ETF like
this just really showcases the demand of clients. But for
now it's trading today and it's really interesting. It's also
cheaper than some of its peers. It's only at fifty
nine basis points.
Speaker 5 (27:58):
I guess it's also for us like an interesting data
set here on the show, we often look at the
NASA Golden Dragon Index as like a barometer sentiment towards
China tech. How unique is this ets in the kind
of landscape of products where they first are there more
to come?
Speaker 11 (28:14):
It's unique in the sense that it's round here. Round
Hill's selection for now, they're only nine. They're only going
to limit it to five to ten, and they can
drop stocks that they think doesn't show economies of scale
or solid fundamentals or competitive advantages. So that is kind
of very interesting because if you look at the Bloomberg
Magnificent seven Index, it only really tracks those magnificent seven
(28:36):
stocks and a's that one hundred tracks all the big
tech stocks. So to an extent, some investors really just
want those targeted focus You don't want this broad based index.
You just want this little slice of the market.
Speaker 3 (28:49):
Being backs as well. LEI, thanks for bringing it to us.
Coming up, where is the bench money going? Funnily enough
if you'll probably guess given the open AI News got
the latest state to the pitch book analyst Carl Stamford,
and we also dig into it all with the VC
Dinis Shiker.
Speaker 2 (29:06):
This is Bloomberg.
Speaker 3 (29:17):
Poolside is a startup building AI software for programmers, who
just raised five hundred million dollars from investors ahead of
the company's plans to release an initial product.
Speaker 2 (29:25):
And the round was led by Bane.
Speaker 3 (29:26):
Capital Ventures and includes funds from DST Globals, Stepstone Groups,
City Ventures, and HSBC Ventures, Poolside said in a statement yesterday. Now,
as Bloomberg reported last month, the new financing gives a
startup foundation of three billion dollars.
Speaker 5 (29:40):
Venture deal making hobbled along at a slightly better pace
than a year ago in dollar terms, but investors are
getting more selective and cash went to just a handful
of companies. Open AI's latest funded raising bodes more of
the same to come for the current quarter and beyond.
Let's bring in Carl Stanford from Pitchbook, who's been crunched
that data, and I point out from the offset that
(30:03):
the data to date does not include that open Ai round.
We can get to it, but summarize the pitch book
data as of third quarter.
Speaker 1 (30:13):
Right it does not include that open aideal. But what
we've seen is that venture still continues to be a
really slow market. When you look at exits and you
look at fundraising, you can really see why that is.
There's nothing coming out of the market right now. And
some of the US during Q three there's about thirty
seven and a half billion invested, which is lower than
the quarter before, but that had a few large deals.
(30:33):
But there's nothing really exciting happening outside of AI in
terms of investments being made.
Speaker 3 (30:38):
Right now, Where is the excitement happening in AI?
Speaker 2 (30:41):
From a geographical perspective.
Speaker 1 (30:42):
Club right, it's happening in San Francisco, It's happening here
in the US.
Speaker 2 (30:47):
Right.
Speaker 1 (30:47):
If you look at open AI, I think the deal
that just close shows two things. One, it shows the
incredible amount of capital that AI needs and the cost
that these companies are incurring, and also shows the excitement
around own AI in the technology. Right, if you look
at who is in that Nvidia, Microsoft, They Thrive Capital,
soft Bank, you know, all of these all these investors
(31:08):
are looking at this deal and this company has something
that's going to be able to provide them huge returns
moving down down the road, right, And that's how you know,
many of these investors have looked at AI, you know,
up and down the venture life cycle, and so that
has definitely been the interest area of interest for investors,
you know, in the USN and globally up to this point.
Speaker 5 (31:28):
So if we got on the basis that the data
we're showing on the screen as of September thirtieth does
not include the open AI round, how does it change
the trajectory for twenty twenty four against prior years when
we do take that round into account.
Speaker 1 (31:46):
Yeah, right, I mean I think we can look at
it and say, yeah, and obviously it is going to
make twenty twenty four look much better. But if it's
only one deal, it's not really capital available for the
entire marketing. And I think something that something we've been
saying with past quarters rounds of core Weave, Toropic, these
are very exciting, interesting, you know, scaling companies, But that's
not what the rest of the market is seeing.
Speaker 3 (32:07):
Right.
Speaker 1 (32:07):
Valuations in AI are forty percent higher than in other verticals,
deal sizes are much larger. Obviously, six point six billion
dollars is not a typical deal that many of these
companies should expect anytime soon or ever. And so when
you talk about the trajectory of the dollar value dollars
going into the US world, the global venture market, I
think that really needs to be taken into account.
Speaker 2 (32:29):
What unplugs for the rest.
Speaker 3 (32:31):
If you're not AI native, but you're AI adopting and
you've got a decent run rate in terms of revenue,
do we need more exits to be able to see
the money come back in?
Speaker 4 (32:41):
Yeah?
Speaker 1 (32:42):
Right, I mean exits are still the kind of dam
of the of vanter activity. When we look at distributions
that are coming out of the market, we know that
there has been very very little for the past two years.
Even the IPOs of Q one and Q two did
not We're not able to sustain the venture market. And
so we take how large the AUM has grown for
(33:04):
VC in the past few years. Then just consider that
all of that is stuck private and LPs have no
way to use that cash for more investments or to
recycle it back into venture. You can really start to
see why there's such a slow market over the past
few quarters and something we should expect for the coming
quarters as well.
Speaker 3 (33:22):
Kyle Stanfa Pitchfoot, lead VC research on list.
Speaker 2 (33:24):
Me, thank you.
Speaker 3 (33:26):
Let's got some more analysis from the horse's mouth. Someone
who's in VC. Lux Capital general partner Diana Shacker, joins us. Now,
Dina does not feel what you're seeing a tone of
two hobs.
Speaker 12 (33:35):
Why now you know it has in many ways a
tale of two cities. But I don't think I would
agree with the sentence that there's nothing exciting outside of AI,
and at Lux we love to invest in the intersections.
In fact, we just had our AI summit here in
New York on Tuesday, and what you see is a
lot of AI, but AI intersecting intersecting with life sciences,
intersecting with physical intelligence, intersecting with health tech, even with
(33:59):
medic Caid care deliveries. So while I do think AI
is very exciting, it's an area we've been investing in
for quite some time. It's not necessarily the only area
that we're seeing exciting investments these days.
Speaker 5 (34:13):
That was the point when you launched a new fund, right,
I remember all the things that I get excited about robotics,
dare I say life sciences? But has it been an
easy environment to cut checks in because you sometimes have
to find willing partners who have the same level of
excitement that you do in those fields.
Speaker 12 (34:31):
Yes, these are all areas we are still excited in.
And I think one way in which it's a tale
of two cities is that you're seeing these these seasoned
operators who are on their second or third company, who
maybe building an AI or outside of AI, that are
getting these very large megarounds, and then other companies that
are struggling to raise those early dollars.
Speaker 2 (34:51):
That being said, we.
Speaker 12 (34:52):
Have companies across different stages and sectors that are continuing
to raise. I think the big question, which Kyle pointed out,
is really what the exit market looks like. And as
we you know, we sat here two years ago Caroline
talking about twenty twenty three being the year.
Speaker 2 (35:05):
Twenty twenty four should be the year.
Speaker 12 (35:07):
I think we're all looking to twenty twenty five to
be the year where we start to see more of
those exits and distributions.
Speaker 4 (35:13):
Do you get that question and that pressure.
Speaker 5 (35:15):
From the LPs for there to be exit opportunities?
Speaker 12 (35:19):
You know, we are a deep tech fund, so we've
always had long life cycles. We invest what we like
to invest in the impossible and turn it into the inevitable.
And so we have patient LPs who know that these
companies take time, and we look for the generational large
companies that turn into into very big outcomes.
Speaker 3 (35:37):
Did any of those LPs want you to be in
the open AI round?
Speaker 2 (35:41):
Well, we'll see.
Speaker 3 (35:43):
Well what's interesting is some of the nuances around that
round A people are sitting up and seeing who's leading it,
but they're also sitting up and saying, oh, they're not
allowed to invest in competitors.
Speaker 2 (35:55):
Is that usual?
Speaker 3 (35:56):
Actually, when you invest in like a runway which you're in,
would ultimately you not go out and reallocate to a
competitor in that space?
Speaker 12 (36:05):
I would say that is normal, but not every fund
approach is that the same way. From our perspective, we
certainly don't intentionally invest in competitive companies. We like to
put our resources, our connections our network behind our investments.
Oftentimes companies will evolve over time and eventually end up intersecting,
and that can certainly happen, but we do try to
be careful to put our eggs in a basket and
(36:26):
really double down on our winners.
Speaker 5 (36:29):
The something you mentioned a moment ago, Dina, that I
think is probably true of whether you're in deep tech
or in AI, in industrials or otherwise, which is the
type of investor coming in is different. You see the
very large mutual funds being a player or Nvidia comes
in as like a strategic you're a sizeable venture firm,
But is it difficult for you to get in on
(36:50):
some rounds because of those new types of player?
Speaker 2 (36:53):
You know, our current fund is over a billion.
Speaker 12 (36:55):
We're investing in everything from incubation through pre ipo, and
so we have ability to construct a portfolio across different stages.
The job of any good VC, of course is to
buy low and sell high, and so we're able to
do that across the spectrum of these companies where we
believe there's still a massive outcome, even investing.
Speaker 2 (37:12):
At a later stage. We will do that and we
have the ability to do that.
Speaker 12 (37:16):
And we also have the ability to start companies ourselves.
Companies in our portfolio like Evolutionary Scale, which is applying
AI to life sciences that we were early into, or
a life health which we were the first institutional capital
in applying AI to the fertility space.
Speaker 3 (37:31):
What about the companies that on as we say AI natives,
you say, there's a lot of excitement in the areas
of intersection, But how are some of the other companies
in the older portfolios able to cope with this current environment?
Speaker 2 (37:45):
Are they steering well?
Speaker 3 (37:45):
Are they managing to ensure that they're cutting costs and
dotting in on revenue growth?
Speaker 12 (37:49):
Absolutely, And it's those two things, well three things, I
would say. One, AI is a way of doing things.
It's not AI for AI's sake, So hopefully it's enabling efficiency,
it's enabling better accuracy, it's enabling.
Speaker 2 (38:01):
Better profit margins.
Speaker 12 (38:02):
And so every company needs to have an answer to that,
not because it's what they need for fundraising, although it
likely is, but also because it's what they need to
survive in the world. This is a huge paradigm shift,
it's a seismic shift. So all of our companies are
doing that, and some of the most exciting applications I've
seen are actually in companies that are very much still
human oriented companies like Waymark in our portfolio, which is
(38:23):
leveraging community health workers to deliver healthcare and medicaid communities,
but are using AI to help predict emergency room admissions
and to help streamline the operations of healthcare providers.
Speaker 4 (38:35):
Dina, you've been busy.
Speaker 5 (38:36):
You're always a busy person, but you've also become an author.
Lina Moe CEO, very quickly tell me about it.
Speaker 12 (38:42):
Yes, Linamo's CEO brand new book just released last week.
It's a story about a young girl who builds a
robot to help shovel snow outside of our house, goes
through the process of building a team raising money, and
was inspired by my own journey as a parent trying
to explain venture cap to a bunch of preschoolers, which,
(39:03):
as it turns out, is just as hard as explaining
to fully grown adults.
Speaker 5 (39:08):
You know, founders are getting younger, but that young I
don't know. Lux Capital General Partner Dina Shaiker, thank you
very much.
Speaker 3 (39:22):
Today's big take how global supply chains are the latest
concern in the Ukraine Russia war. As US designed chips
are finding their way inside Russia made missiles. For more
Bloomberg Stephanie Baker, who joins US now. She's also the
author of a new book, Punishing Putin, Inside the Global
economic war to bring down Russia. Stephanie, you always tell
stories with such depth and humanity. It's a difficult story
(39:44):
to read, to be honest. But what we bring to
our audience now is the intricacies of what chips made
by who are finding their way into certain Russian missiles.
Speaker 4 (39:55):
Right.
Speaker 13 (39:55):
So, if you remember, after the invasion, the US joined
with its European allies and imposed sweeping export controls on
Russia to deny the Russian military access to Western semiconductors
and other technology. And they tighten those restrictions again starting
last year, and there'd been various reports about citing trade
(40:17):
data about components getting through, semiconductors getting through to Russia.
What we wanted to do was really drill down and
go do a deep dive on one missile attack where
Ukrainian investors had documented Western components by specific companies, as
well as examining.
Speaker 2 (40:36):
Their entire database.
Speaker 13 (40:37):
And what we came up with was that there's one
company whose components keep getting found and more. Our most
frequently found on the battlefield, and that is analog devices.
And we wanted to sort of put a human face
on what was a sort of trade data story to
show that actually Russia's very dependent on Western technology to
(40:58):
guide its missiles missile attacks on Ukraine.
Speaker 5 (41:03):
Stephanie, what was the response from Analog and also I
suppose from the United States to the reporting.
Speaker 13 (41:11):
Right, Well, Analog says they regard this as an illicit
diversion of their products and they do not condone any
of this trade. And what we tried to get into
and the story was explaining the complex supply chain for semiconductors,
that there's a lot of production happening in Southeast Asia.
There are a lot of middlemen acting particularly through Hong Kong,
(41:34):
using shell companies to do this trade. So it's been
very hard to crack down. This is not Analog selling
directly to Russia, and the US has tried to enforce
these export controls through the Commerce Department. That has proven
difficult just because of the global nature of the supply
chain and the many layers that semiconductors get traded through
(41:56):
before actually reaching Russia.
Speaker 5 (41:59):
Bloomberg Phony Baker who's in London. And as a reminder,
the big take is titled Russian Missiles American Chips. Find
it on the Bloomberg Terminal, find it on Bloomberg dot com.
Speaker 4 (42:09):
It is a must read with detailed reporting, Caroline, it is.
Speaker 3 (42:13):
Meanwhile, it's been detailed throughout. That does it for this
edition of Bloomberg Technology. A lot of news when it
comes to the private markets, the tech markets, the public markets.
Speaker 2 (42:23):
As well ed.
Speaker 5 (42:24):
Yeah, probably a historic day. We'll find out on that
big Open AI round recap all the reporting on the podcast.
You know where to find it on the Bloomberg Terminal
as well as online on Apple, Spotify, and iHeart big
shout out to the team in New York City and
everyone here in San Francisco.
Speaker 4 (42:39):
This is Bloomberg Technology.
From Marhard where Innovation of Money and Power colle in
Silicon Valley, NBN. This is Bloomberg Technology with Caroline Hyde
and Ed lud Love.
Speaker 2 (00:25):
Live from New York and San Francisco. This is Bloomberg Technology.
Coming up, open.
Speaker 3 (00:29):
AI's historic funding round. We discussed one of the largest
ever private investments and its new loan agreement securing ten
billion dollars in total liquidity.
Speaker 4 (00:39):
And AI dominates VC deals.
Speaker 5 (00:41):
We have the latest data for venture funding in the
third quarter and in.
Speaker 3 (00:44):
Video insiders cash in on the AI height, selling one
point eight billion dollars of shares this year alone. That
and so much more coming uphead.
Speaker 4 (00:53):
Yeah, straight to our top story.
Speaker 5 (00:54):
Open ai said it has completed a deal to raise
six point six billion dollars in new giving the AI
company a one hundred and fifty seven billion dollar valuation
and bolstering its efforts to build the world's leading generative
AI technology. In the last hour, the startups also announced
a four billion dollar credit line from banks around the world,
(01:16):
giving access to a more than ten billion dollar war chest.
Blion both Rachel Metz joins us on set in San Francisco,
and we've been tracking this for weeks and months and
it's finally done. But the important point is they need
the money because the cutting edge model requires the money
to train and build.
Speaker 6 (01:36):
Yes, they are in a very expensive business. If you
want to build a cutting edge large language model, any
kind of cutting edge AI model, at this point, you're
looking at potentially spending up to hundreds of millions of dollars.
So if you think about multiplying that out over a
couple of billion dollars, I mean it's like, well, you
can train a couple models there, and what if you
train one and you're like, you know what, I'm not
(01:57):
that happy with this. I mean a lot of money. Also,
they need you know, chips, they have staff, they have
all kinds of expenses there. They are bringing in revenue
of course, but it's still costs quite a bit to
do what they're doing.
Speaker 3 (02:09):
It is the future revenue growth, the future profitability. That
means standout names from VC like Thrive Capital, like Coast
a Ventures back the round, but numerous big substantial banks
back the credit facility. We're looking at Goldman, Sachs, JP
Morgan santunder Wells Fargo to name but a few. What
(02:29):
is the future growth model that they're all building one
hundred and fifty seven billion dollar valuation on.
Speaker 6 (02:35):
Rachel, I mean they're looking at businesses using their products
going forward. They're hoping that businesses will increasingly do things
like fine tune the models. They recently made it so
that businesses can do that and use them in different
parts of their workflow and find it useful enough that
they will keep paying for it, and they are starting
(02:57):
to see uptake. They have quite a number of both
individual and business users at this point. They recently passed
the one million business user mark for business users of
chat GBT in particular, But they still have a long
ways to go if they want to get to this
level that this valuation is showing them going to at
some point.
Speaker 5 (03:17):
There's two points I want to make really quick with
my sort of finance coverage on this is a pre
EBITDAR private company or a pre positive EBITDAR private company,
so that it could go to banks and get four
billion dollars in credit is remarkable. And also the eagle
eyed audience will say some of those banks are in Europe.
Speaker 4 (03:36):
That is also remarkable, Rachel.
Speaker 5 (03:38):
When they announced the closing of the equity round, they
also gave us data on how they're doing not necessarily
financial metrics, but like how many people are using open Ai.
Do we know anything about like the scale of this
company in the real world.
Speaker 2 (03:53):
Yes, we do.
Speaker 6 (03:54):
We know that there are I think it's two hundred
and fifty million weekly users of Chat GBT as we
previously reported. They also recently passed more than one million
business users for chat GPT, and that spans a couple
of different products related both to an educational product, they
have a smaller business product like for smaller companies, and
(04:15):
then also like a larger, more enterprise y product. So
they're definitely trying to hit out a lot of different
people in a lot of different areas, and they are
doing it. They are they are certainly bringing in revenue,
and they are seeing users. Uh. I think what remains
to be seen is how well this will all work
over time? What kind of you know, investors have to
be willing to wait. They have to be very patient.
Speaker 4 (04:37):
Right.
Speaker 2 (04:37):
This is not like your.
Speaker 6 (04:38):
Average startup where it's like, well, y, you know, you
might get a short term return and then maybe you'll
get a long term return. This is like, well, you're
gonna have to wait and see what we.
Speaker 2 (04:46):
Come up with. Over time. Rachel Metz, we thank you
so much.
Speaker 3 (04:50):
Meanwhile, Coast and Adventures participated in the Open AI round.
As we mentioned, tune in tomorrow our interview with Vinode
Coast and on this and of course AI's future impact.
Now we tend to another key story. US prosecutors are
broadening a probe of potential price fixing by German software
maker SAP and tech reseller Carasoft, seeking to examine the
company's work with almost one hundred government agencies.
Speaker 2 (05:12):
It's according to a new court record. Imers Jake Bleiberg
is here with more.
Speaker 3 (05:16):
You've been sifting through these court documents, remind us what
is being investigated, if not accused quite yet.
Speaker 7 (05:23):
Absolutely, the investigation is looking at the companies you mentioned, SAP, Kerosoft,
and then some other companies, the identities of which we
don't all know, for a potential scheme. And I should
stress that it's potential, not proven, to fix the prices,
to inflate the prices in sales of SAP technology to
(05:46):
the US government.
Speaker 5 (05:49):
Jake, you joined us the other day to discuss your
original reporting. What I'm trying to do is understand what's
new here. One hundred agencies is more than the agencies
you outline the other day. That's new, But is there
an expansion in the scope of what they're looking at.
Have they discovered more information that prompted more agencies to
say we better get on board with this.
Speaker 7 (06:10):
Absolutely, it's difficult to say what the prosecutors have discovered
at this point.
Speaker 4 (06:16):
And something we do.
Speaker 7 (06:17):
Know is that they say they've been having difficulty getting
information from the company. Sort of at the heart of
this Kerasoft. But as you point to, what has happened
is they went from an investigation primarily focused on sales
to the Department of Defense and then just as of July,
(06:37):
broaden this out pretty dramatically to look at sales to
ninety four or as many as ninety four civilian government
agencies as well.
Speaker 3 (06:48):
We're looking now at the statements coming from the company's
SAP saying it follows the rules around disclosing legal risks
are based on the current circumstances. There was still no
requirement to report on the individual cases. Karasoft also gave
us a statement. But ultimately, how are they going to
be interacting with these hundreds of agencies?
Speaker 2 (07:05):
What role do they now play in this?
Speaker 4 (07:08):
It's a great question.
Speaker 7 (07:09):
The sort of historic role that both of these companies
have played is by putting out a product. SAP makes
all sorts of workforce software, time cards, HR software, and
the complicated process of selling that sort of software to
the US government is sort of handled by Carasoft, which
(07:33):
stands in the middle and does a lot of the
difficult work of helping the software manufacturer navigate.
Speaker 4 (07:39):
These regulatory hurdles.
Speaker 7 (07:41):
So what those relationships will look like going forward in
the middle of this investigation is a big open question.
Speaker 5 (07:48):
Bloomberg's Jake Blybag, who broke the original story and continues
across the developing story, Thank you very much. Now coming
up here on this show, is job displacement caused by
AI something to brace for or is this just all hype?
We discussed with MIT economist Darren Smoglu, who gives us
his more skeptical view on what's really happening with AI
(08:12):
in the jobs market.
Speaker 4 (08:13):
This is Bloomberg Technology.
Speaker 3 (08:24):
Softbag founder Asoshi's son has sketched out one of the
most aggressive timelines for the adoption of AI yet, envisioning
a near future where the technology would run entire households
from monitoring the health of family members to grocery shopping now.
In a speech add an annual forum for enterprise clients
earlier today, Sun said that artificial general intelligence or AGI would.
Speaker 2 (08:46):
Arrive within the next two to three years.
Speaker 5 (08:49):
ED, but not everyone is so bullish on AI, at
least not when it comes to jobs. Darren Asmoglu, a
renowned professor at MIT, says that by his calculation, only
a small percent of all jobs round five percent is
right to be taken over at least heavily aided by
AI over the next decade. Darren Asamogli joins us now
(09:13):
and welcome to the program. This was one of the
most read stories on Bloomberg in the last twenty four hours.
There's no surprise about that. It has all of the
facets of a story that would you know, just engage
our audience on Bloomberg technology. Let's get specifics why only
five percent of jobs and which sectors in industries are
(09:34):
you basing your thesis on.
Speaker 8 (09:36):
Well, thanks, Ed, It's great to be on the program.
I think right now there is a lot of potential excitement,
perhaps hyper about AI, but if you look at its
current capabilities, you know we are very far from AI,
either general to AI or other types of AI performing
(09:59):
any of the tasks that involve a heavy level of
interaction with the physical world construction work, manufacturing work, carpentry.
Those perhaps one day will be much more feasible, for example,
if AI becomes so much more advanced, so much more reliable,
and can be integrated with so much better robots, for instance,
(10:22):
But it's not something that's going to happen in the
next five or ten years now. There's a lot of
other potential for future AI, perhaps to perform some social tasks,
but those are not going to be possible right now either.
You know you're not going to go to an AI
psychiatrist anytime soon, So if you stip out all of these,
(10:44):
you're not going to be left with much more than
five percent of the economy.
Speaker 5 (10:49):
Professor may I jump in and push back with a
point raised by our audience when I said you were
coming on, which is that AI technology is exponential, much
in the way that the invention of electricity with time
led to all sorts of breakthroughs. Right now, you're saying
five percent of jobs, But in two years or five
years from now, would you need to rethink your thesis
(11:13):
or redo your calculations.
Speaker 8 (11:15):
I should have prefaced this by saying there's a huge
amount of uncertainty in any forecast about AI, and apologies
that I didn't do that. I tried to do that
all the time. I was very excited. I just jumped
into it. There's a huge amount of uncertainty, and one
source of uncertainty is exactly what's gonna happen with AI
in the next several years. I don't think that the
(11:37):
most optimistic views in the industry, which sometimes people refer
to as scaling laws, actually will hold water when you
look at it within the next five years or ten years,
which say, you know, just double the amount of data,
double the amount of computer power, and then you're gonna
get double the amount of capabilities. Because to do that
(11:59):
we would actual need higher quality data. So if you
want AI to do the job of a carpenter, you
really need a completely different kettle of fish when it
comes to the kinds of data, and something like that
might be feasible with a different architecture of AI, but
right now all of the money is going into the
sort of the basic dominant architecture, which has its limitations
(12:22):
both in terms of reliability in terms of high level reasoning.
So that's the basis of my belief that, of course
generative AI and other types of AI will improve, but
we're not going to see a qualitative jump within the
next five to ten years.
Speaker 3 (12:37):
So as like your belief, what is exactly based on
what data, what historical norms are you looking back on
to drive and push forward on this five percent take?
Speaker 8 (12:47):
Yeah, I think this is why there is so much uncertainty.
There's nothing that's identical to generative AI in the past,
and that's part of the reason why people can hold
very different beliefs. But what I'm basing that on is,
first of all, other waves of digital technologies that promised
a lot of automation, sometimes a lot of productivity improvements,
(13:08):
sometimes a lot of changes in the way that we
would organize our offices and things like that, and at
the end, all of those changes have been very gradual.
And also what we have seen over the last two
and a half years, where you know, there have been advances,
but the advances haven't really been sort of qualitative in nature.
(13:29):
They haven't really exceeded the sort of the basic capabilities
of GPT three point five or three point GPT four.
So there will be advances, but I don't think any
of those advances will very quickly change the way that
we do various tasks in the economy. So, for example,
(13:50):
I do not believe that in five years time, when
we look at the labor market, we're going to see
certain occupations that will have completely disappeared.
Speaker 2 (13:59):
Think you would say that they would be augmented.
Speaker 3 (14:03):
The idea is, perhaps the optimist view is we will
not lose lots of people from the labor force, but
their productivity will be scaled.
Speaker 8 (14:10):
Where you think that's a yes, I think that's a
very very interesting and important point. I am not an
AI denier or an AI pessimist. I actually believe AI
has a lot of potential, And in fact, the real
potential is exactly what you said, Caroline, which is that
AI becomes a tool for workers to boost their productivity.
(14:32):
And again we're seeing some of that happening. You know,
Microsoft has a lot of co pilots. You know, some
of them work and they give some productivity improvements. There
are a few areas where we're seeing really phenomenal improvements, like,
for example, if you want to write simple subroutines in
one of the common programming languages. You know, GPT four
(14:52):
is great. Before then getthub copilot was pretty good. So
there are some things in which that sort of help
to decision makers as possible. But again, when you look
at the whole economy, that means helping carpenters, electricians, plumbers,
blue collar workers, construction workers, transport workers, people who are
doing teaching, people who are doing journalism. Those are things
(15:16):
that could be achieved perhaps at some point, but the
reliability and the reasoning of the models is not up
to the task yet.
Speaker 5 (15:24):
Do you see specific job creation in specific industries from AI.
Speaker 8 (15:31):
Well, there is one class of jobs where AI is
leading a big boost, which is people who have AI fluency,
either people who are AI programmers, AI integrators, or other
AI related service activities. But in my research, albeit from
a previous wave of AI in the late twenty tens,
(15:54):
we didn't see any other job category get a boost
in terms of hiring. And there are some other jobs
that I think there will be some retrenchment. So if
you're in IT security and you're doing so routine end
of IT security, there will be declines and job vacancies
in that area because some of these AI tools can
actually perform that quite well.
Speaker 3 (16:14):
When you see the headline that open ai is worth
one hundred and fifty seven billion dollars, when you see
that in Video is now worth almost three trillion, what
do you make of that in terms of how truly
the capital markets are analyzing the growth here.
Speaker 8 (16:30):
Well, I think there's a difference between Nvidia and open Ai.
Nvidia is riding a wave which is based on the
belief that those chips are going to become more valuable
because generative AI and other types of AI are going
to continue to boom, but they are generating revenues. Open ai,
on the other hand, I think does hasn't found a
(16:51):
revenue model that could justify the types of valuations we
are seeing at the moment now. It may well be
that in the future suddenly their API is going to
be so valuable and other firms are going to start
building on it, but it doesn't seem like there are
the kinds of applications that can have deep impact on
(17:13):
the productivity of workers or the automation of firms that
are going to be sold within the next five years
ten years. So I'm a little bit skeptical. But on
the other hand, open ai is also emerging as the
market leader, and the current ecosystem in the digital world
is right firms that take over the market and they
can use all of the data. They can you know,
(17:35):
interact with the consumers or the programmers directly. Those have
become very valuable because of venture capital or other deep
pocketed funders.
Speaker 3 (17:43):
Can't wait to see the response to this interview. I'm
sure someone has some thoughts. It economics professor drown Asmlgloo.
We appreciate your time, Aura. It's just world a new
flagship device with the Ring four of dating its popular
smart rings with new sensors, but a battery life and
(18:05):
about an algorithm. This is competition is really heating up.
Samsung of course, debuting its own Galaxy Ring for more
or a CEO Tom Hale joins us, So, how does
this make me distinct from the crowd.
Speaker 9 (18:17):
Well, the thing about the or Ring four is that
it's slimmer, sleeker, thinner, better, of course, and the feel
of the ring is what matters to many people because
there's a lot of technology packed in here.
Speaker 4 (18:27):
You want it to be small and compact.
Speaker 9 (18:29):
Maybe more importantly, we've taken a big leap forward in
sensing with something we call smart sensing, and smart sensing
adjusts dynamically to your body because not everyone's the same.
Your anatomy is not the same, your physiology is not
the same, your skin color is not the same, and
we adjust dynamically even as you rotate the ring a
little bit, we actually are able to keep the most
accurate signal.
Speaker 5 (18:51):
Tom, who do you consider it to be the composition
for this ring? Is it other rings or is it
other form fact? As a device, I think a lot
about watches it the moment, particularly having just been at
Apples event in recent weeks.
Speaker 9 (19:06):
What's interesting to me is that amongst our users, almost
two thirds wear a second wearable, usually a smart watch.
On the smart watch great for daytime notifications, you're getting
alerts all the time, but has an achilles heel, which
is battery life.
Speaker 4 (19:20):
And the ring is.
Speaker 9 (19:21):
Something that doesn't ask for your attention, doesn't send you notifications.
It's just in the background, seamlessly fitting into your life,
capturing your physiology so that you don't have to pay.
Speaker 4 (19:32):
A ton of attention to it.
Speaker 9 (19:33):
And as a result, you have an eight day battery
life with the or four ring. And so what that's
really interesting to think about is that you just don't
have to worry about your health as much, and then
therefore the watch in the ring can be compatible. So
in many ways we find these things to be two
devices that can work together on one person's body.
Speaker 3 (19:51):
And what's interesting is you've been working with other companies
that make other devices. We understand from Mark German's reporting
that you've been working alongside Meta's Raband team, for example. Well,
how do you see integration with other businesses going.
Speaker 9 (20:03):
Well, we've got so many great partners that we work with.
We haven't announced anything formally with Meta, but you can
imagine this world where you have this cloud of devices
on your body that you're using in different contexts. Maybe
it's headphones, maybe it's glasses with an AI assistant, And
how does your busiological state and something that you've got
on your body all the time work, maybe as a controller,
(20:26):
maybe as a way to guide, maybe as a way
to provide input, maybe as a way to give you
your other wearables a sense of whether you're stressed or
whether you're well rested, whether you're ready. There's a lot
of really interesting opportunities to explore when you think about
a permanently worn device that's oriented around your health that's
on your body. Twenty four to seven.
Speaker 5 (20:44):
Tom, we've just shown your latest financials and the trajectory
of this company. Your focus this point has been technology
and innovation. But where do you see this company going
from here? The direction for the business.
Speaker 9 (21:00):
Yeah, I mean, I think there's a lot of headroom
for us to grow just simply in the ring category.
Rings are new. People are just learning about the benefits
of long term health tracking, learning about the benefits of
getting sleep, learning about the understanding of their body. So
you know, the way the ring works is it can
tell you when you're getting sick, it can tell you
when you're doing well.
Speaker 4 (21:20):
It gives you.
Speaker 9 (21:20):
Lots of information and lots of insights, even an AI
coach that helps you make behavior changes. And I think
there's a lot of headroom just in that category. But
as you look beyond that, not only is it interaction
with other devices, but it might be potentially other devices
that you might see, Like we've seen prototypes for a
locket that sits on your chest. We've seen prototypes for
things that look more like designer rings. We introduced a
(21:42):
product with Gucci a couple of years back where we
have something that looks much more like jewelry and much
more like you know, much less like a piece of technology,
and it really fits into your life. So I think
the future is very bright for Rings. Lots of headroom
for us to grow this business. But more importantly, I
think people being aware of their health and understanding how
to manage their health is just a really big opportunity.
(22:04):
Everybody on the planet should have one of these things.
Speaker 4 (22:07):
Tom Hale or a CEO, good to catch up, Thank you.
Speaker 2 (22:17):
Welcome back to read Technology.
Speaker 5 (22:18):
I'm Caroline Hid in New York and Amed Lovelow in
San Francisco. If you're just joining us this fine Thursday morning,
or waking up to financial markets as a technology investor,
this is what it looks like Now's that one hundred
is kind of flat. There's a modest outperformance in semiconductors,
with the modest gain on the socks. Bitcoins have been
under pressure throughout the US morning session. If you're an investor,
(22:39):
it's been about weighing an escalating conflict in the Middle East,
with some economic data, a lot of hype around AI,
but no strong movement in either direction apart from a
few single names.
Speaker 4 (22:49):
One of them is in Nvidia.
Speaker 5 (22:51):
In an interview last night, Jensen Wang, the CEO, saying
that demand for Blackwell the latest GPU is insane. No
direct correlation, but the at one point trading its highest
level since August. Then ev go on track for its
biggest jump since twenty twenty one, trading its highest level
I think since May of twenty twenty three.
Speaker 4 (23:10):
It secured a one point.
Speaker 5 (23:11):
One billion dollar loan from the Department of Energy. Those
are two kind of movers. A lot going on, but
in video in particular, on a daily basis, it's still
the name that people are talking about character.
Speaker 3 (23:21):
Because it's worth more than three trillion dollars when you're
looking at its market capitalization and look insiders, they've been
cashing in.
Speaker 2 (23:28):
On what is a huge valuation jump.
Speaker 3 (23:30):
They've actually sold one is worth more than one point
eight billion dollars in shares so far this year. The
selling is it expected. Jess Menton is here to put
this into context. We often see insiders sell shares and
feels a lot when the market caps up so much.
Speaker 10 (23:45):
That's right, and this is in focus, and this is
a really the great story from Jeron Wodenstein and Crimin
Renicky on our equities team that put this together. And
whenever this happens, people want to question a company whether
or not there's growth concerns and things like that. But Jensen,
of course the CEO, this was pre planned and he
actually went through and did this from mid June until
mid of last month. That actually correlated with obviously the
(24:05):
drawdown that we saw with the stock because there was
such a huge run up. I mean, it's still up
close to like one hundred and fifty percent year to date,
but of course it's still down from that June peak
around nine percent, and still the S and P five
hundred has been able to rally even without one of
the biggest wings, but at a certain point it actually
eclipsed Microsoft and Apple and that market capitalization. But moving forward,
there's actually supposed to be additional sales, so in Vidia's
(24:26):
director is still supposed to sell about three million additional shares.
So that's kind of a question mark of whether or not,
well we still continue to see the stock held back
a little bit, even though we've seen it rally and
come back from some of those lows that we saw
earlier this summer, or will keep those gains in check,
but of course I was talking to you all about
this yesterday. But evercre actually made a call for chip
makers and is more optimistic that we would see a
rebound in the fourth quarter of this year.
Speaker 5 (24:48):
Suggests for so many people watching Bloombog technology, it will
be a familiar story. It is a classic in Silicon
Valley wealth creation from stock compensation. You sell shares over
time you get more money than you could ever have
dreamed of. But there is a paragraph in the story
that raises the question of whether or not the sales
inspire confidence in the stock.
Speaker 4 (25:10):
Do they inspire confidence or not?
Speaker 10 (25:13):
Well, there's someone too that when it comes to portfolio
managers that the reporters were speaking with, and Kim Mahoney
was actually one of them at for Mahony Asset Management,
and he was talking about sometimes you shouldn't read too
much into it, say, for instance, Jensen was already pre planned.
But a lot of times it's not just because of
reasons of growth concerns about the company. Obviously, you were
just mentioning earlier ed about how the CEO is talking
(25:34):
about this insane demand for the Blackwell chips. Of course,
there was a lot of scrutiny in recent weeks because
obviously the investors want the valuation of the company to
justify those future earnings and the growth. But still those
executive directors in the company, they sold about eleven million
shares so far in twenty twenty four, and so to
put that into context, that's the most since twenty twenty
when you are excluding, of course different stock splits like
(25:55):
earlier this year and in twenty twenty one. But you
do have some portfolio managers arguing it's not just because
of growth concerns.
Speaker 5 (26:01):
Ed Bloombergs just meant it brilliant as always, Thank you
very much. Now it's launched ay for the Roundhill China
Dragons ETF. It tracks an equal weighted basket of Chinese
tech companies under the ticker drag Bloombergs. Isabel A had
a story that hit the wire in the website in
the last couple of hours.
Speaker 4 (26:20):
What's the idea behind the CTF.
Speaker 11 (26:22):
So this tracks a basket that Roundhill made. So it's
five to ten Chinese companies that they can they qualified
as those that impress, those that exhibit great economies of scale,
competitive advantages, and really basically companies that they believe in.
So they're five to ten stocks and for another are nine.
These includes pdd Ali, Baba, may Twan, buid net Ease.
(26:42):
And what sets this apart from the other ets out
there that track Chinese linked stocks is that it's more targeted.
We have the biggest I shares one attracts some thirty.
We have k Webcrane shares attracts some thirty or fifty.
So this is just five to ten and that's what
they say. You don't want those little companies diluting you're
trying to exposure.
Speaker 3 (27:01):
These are megacap tech names, in particular Isabelle. And the
timing is kind of beautiful. It comes in line with
everyone getting over excited in a fomo feel around Chinese stocks.
Speaker 2 (27:13):
Was it always plans to come out. Now, that's the
thing with ETFs.
Speaker 11 (27:17):
You file for they filed earlier this year, you don't
really know when it will come out. So they said
that the timing couldn't have been better. But then they
said they also really just make products when they see
investor demand. And that actually is what caught my attention,
because even if we all hear these kind of negative
rhetoric around China, there are still investors who want China. Remember,
there are two ways to look at China. It's too cheap,
(27:37):
so let's buy it, or it's too cheap so let's
kind of stay away. And it's proving that the former
is still kind of that their echo calls are kind
of loud because for Roundhill to launch and ETF like
this just really showcases the demand of clients. But for
now it's trading today and it's really interesting. It's also
cheaper than some of its peers. It's only at fifty
nine basis points.
Speaker 5 (27:58):
I guess it's also for us like an interesting data
set here on the show, we often look at the
NASA Golden Dragon Index as like a barometer sentiment towards
China tech. How unique is this ets in the kind
of landscape of products where they first are there more
to come?
Speaker 11 (28:14):
It's unique in the sense that it's round here. Round
Hill's selection for now, they're only nine. They're only going
to limit it to five to ten, and they can
drop stocks that they think doesn't show economies of scale
or solid fundamentals or competitive advantages. So that is kind
of very interesting because if you look at the Bloomberg
Magnificent seven Index, it only really tracks those magnificent seven
(28:36):
stocks and a's that one hundred tracks all the big
tech stocks. So to an extent, some investors really just
want those targeted focus You don't want this broad based index.
You just want this little slice of the market.
Speaker 3 (28:49):
Being backs as well. LEI, thanks for bringing it to us.
Coming up, where is the bench money going? Funnily enough
if you'll probably guess given the open AI News got
the latest state to the pitch book analyst Carl Stamford,
and we also dig into it all with the VC
Dinis Shiker.
Speaker 2 (29:06):
This is Bloomberg.
Speaker 3 (29:17):
Poolside is a startup building AI software for programmers, who
just raised five hundred million dollars from investors ahead of
the company's plans to release an initial product.
Speaker 2 (29:25):
And the round was led by Bane.
Speaker 3 (29:26):
Capital Ventures and includes funds from DST Globals, Stepstone Groups,
City Ventures, and HSBC Ventures, Poolside said in a statement yesterday. Now,
as Bloomberg reported last month, the new financing gives a
startup foundation of three billion dollars.
Speaker 5 (29:40):
Venture deal making hobbled along at a slightly better pace
than a year ago in dollar terms, but investors are
getting more selective and cash went to just a handful
of companies. Open AI's latest funded raising bodes more of
the same to come for the current quarter and beyond.
Let's bring in Carl Stanford from Pitchbook, who's been crunched
that data, and I point out from the offset that
(30:03):
the data to date does not include that open Ai round.
We can get to it, but summarize the pitch book
data as of third quarter.
Speaker 1 (30:13):
Right it does not include that open aideal. But what
we've seen is that venture still continues to be a
really slow market. When you look at exits and you
look at fundraising, you can really see why that is.
There's nothing coming out of the market right now. And
some of the US during Q three there's about thirty
seven and a half billion invested, which is lower than
the quarter before, but that had a few large deals.
(30:33):
But there's nothing really exciting happening outside of AI in
terms of investments being made.
Speaker 3 (30:38):
Right now, Where is the excitement happening in AI?
Speaker 2 (30:41):
From a geographical perspective.
Speaker 1 (30:42):
Club right, it's happening in San Francisco, It's happening here
in the US.
Speaker 2 (30:47):
Right.
Speaker 1 (30:47):
If you look at open AI, I think the deal
that just close shows two things. One, it shows the
incredible amount of capital that AI needs and the cost
that these companies are incurring, and also shows the excitement
around own AI in the technology. Right, if you look
at who is in that Nvidia, Microsoft, They Thrive Capital,
soft Bank, you know, all of these all these investors
(31:08):
are looking at this deal and this company has something
that's going to be able to provide them huge returns
moving down down the road, right, And that's how you know,
many of these investors have looked at AI, you know,
up and down the venture life cycle, and so that
has definitely been the interest area of interest for investors,
you know, in the USN and globally up to this point.
Speaker 5 (31:28):
So if we got on the basis that the data
we're showing on the screen as of September thirtieth does
not include the open AI round, how does it change
the trajectory for twenty twenty four against prior years when
we do take that round into account.
Speaker 1 (31:46):
Yeah, right, I mean I think we can look at
it and say, yeah, and obviously it is going to
make twenty twenty four look much better. But if it's
only one deal, it's not really capital available for the
entire marketing. And I think something that something we've been
saying with past quarters rounds of core Weave, Toropic, these
are very exciting, interesting, you know, scaling companies, But that's
not what the rest of the market is seeing.
Speaker 3 (32:07):
Right.
Speaker 1 (32:07):
Valuations in AI are forty percent higher than in other verticals,
deal sizes are much larger. Obviously, six point six billion
dollars is not a typical deal that many of these
companies should expect anytime soon or ever. And so when
you talk about the trajectory of the dollar value dollars
going into the US world, the global venture market, I
think that really needs to be taken into account.
Speaker 2 (32:29):
What unplugs for the rest.
Speaker 3 (32:31):
If you're not AI native, but you're AI adopting and
you've got a decent run rate in terms of revenue,
do we need more exits to be able to see
the money come back in?
Speaker 4 (32:41):
Yeah?
Speaker 1 (32:42):
Right, I mean exits are still the kind of dam
of the of vanter activity. When we look at distributions
that are coming out of the market, we know that
there has been very very little for the past two years.
Even the IPOs of Q one and Q two did
not We're not able to sustain the venture market. And
so we take how large the AUM has grown for
(33:04):
VC in the past few years. Then just consider that
all of that is stuck private and LPs have no
way to use that cash for more investments or to
recycle it back into venture. You can really start to
see why there's such a slow market over the past
few quarters and something we should expect for the coming
quarters as well.
Speaker 3 (33:22):
Kyle Stanfa Pitchfoot, lead VC research on list.
Speaker 2 (33:24):
Me, thank you.
Speaker 3 (33:26):
Let's got some more analysis from the horse's mouth. Someone
who's in VC. Lux Capital general partner Diana Shacker, joins us. Now,
Dina does not feel what you're seeing a tone of
two hobs.
Speaker 12 (33:35):
Why now you know it has in many ways a
tale of two cities. But I don't think I would
agree with the sentence that there's nothing exciting outside of AI,
and at Lux we love to invest in the intersections.
In fact, we just had our AI summit here in
New York on Tuesday, and what you see is a
lot of AI, but AI intersecting intersecting with life sciences,
intersecting with physical intelligence, intersecting with health tech, even with
(33:59):
medic Caid care deliveries. So while I do think AI
is very exciting, it's an area we've been investing in
for quite some time. It's not necessarily the only area
that we're seeing exciting investments these days.
Speaker 5 (34:13):
That was the point when you launched a new fund, right,
I remember all the things that I get excited about robotics,
dare I say life sciences? But has it been an
easy environment to cut checks in because you sometimes have
to find willing partners who have the same level of
excitement that you do in those fields.
Speaker 12 (34:31):
Yes, these are all areas we are still excited in.
And I think one way in which it's a tale
of two cities is that you're seeing these these seasoned
operators who are on their second or third company, who
maybe building an AI or outside of AI, that are
getting these very large megarounds, and then other companies that
are struggling to raise those early dollars.
Speaker 2 (34:51):
That being said, we.
Speaker 12 (34:52):
Have companies across different stages and sectors that are continuing
to raise. I think the big question, which Kyle pointed out,
is really what the exit market looks like. And as
we you know, we sat here two years ago Caroline
talking about twenty twenty three being the year.
Speaker 2 (35:05):
Twenty twenty four should be the year.
Speaker 12 (35:07):
I think we're all looking to twenty twenty five to
be the year where we start to see more of
those exits and distributions.
Speaker 4 (35:13):
Do you get that question and that pressure.
Speaker 5 (35:15):
From the LPs for there to be exit opportunities?
Speaker 12 (35:19):
You know, we are a deep tech fund, so we've
always had long life cycles. We invest what we like
to invest in the impossible and turn it into the inevitable.
And so we have patient LPs who know that these
companies take time, and we look for the generational large
companies that turn into into very big outcomes.
Speaker 3 (35:37):
Did any of those LPs want you to be in
the open AI round?
Speaker 2 (35:41):
Well, we'll see.
Speaker 3 (35:43):
Well what's interesting is some of the nuances around that
round A people are sitting up and seeing who's leading it,
but they're also sitting up and saying, oh, they're not
allowed to invest in competitors.
Speaker 2 (35:55):
Is that usual?
Speaker 3 (35:56):
Actually, when you invest in like a runway which you're in,
would ultimately you not go out and reallocate to a
competitor in that space?
Speaker 12 (36:05):
I would say that is normal, but not every fund
approach is that the same way. From our perspective, we
certainly don't intentionally invest in competitive companies. We like to
put our resources, our connections our network behind our investments.
Oftentimes companies will evolve over time and eventually end up intersecting,
and that can certainly happen, but we do try to
be careful to put our eggs in a basket and
(36:26):
really double down on our winners.
Speaker 5 (36:29):
The something you mentioned a moment ago, Dina, that I
think is probably true of whether you're in deep tech
or in AI, in industrials or otherwise, which is the
type of investor coming in is different. You see the
very large mutual funds being a player or Nvidia comes
in as like a strategic you're a sizeable venture firm,
But is it difficult for you to get in on
(36:50):
some rounds because of those new types of player?
Speaker 2 (36:53):
You know, our current fund is over a billion.
Speaker 12 (36:55):
We're investing in everything from incubation through pre ipo, and
so we have ability to construct a portfolio across different stages.
The job of any good VC, of course is to
buy low and sell high, and so we're able to
do that across the spectrum of these companies where we
believe there's still a massive outcome, even investing.
Speaker 2 (37:12):
At a later stage. We will do that and we
have the ability to do that.
Speaker 12 (37:16):
And we also have the ability to start companies ourselves.
Companies in our portfolio like Evolutionary Scale, which is applying
AI to life sciences that we were early into, or
a life health which we were the first institutional capital
in applying AI to the fertility space.
Speaker 3 (37:31):
What about the companies that on as we say AI natives,
you say, there's a lot of excitement in the areas
of intersection, But how are some of the other companies
in the older portfolios able to cope with this current environment?
Speaker 2 (37:45):
Are they steering well?
Speaker 3 (37:45):
Are they managing to ensure that they're cutting costs and
dotting in on revenue growth?
Speaker 12 (37:49):
Absolutely, And it's those two things, well three things, I
would say. One, AI is a way of doing things.
It's not AI for AI's sake, So hopefully it's enabling efficiency,
it's enabling better accuracy, it's enabling.
Speaker 2 (38:01):
Better profit margins.
Speaker 12 (38:02):
And so every company needs to have an answer to that,
not because it's what they need for fundraising, although it
likely is, but also because it's what they need to
survive in the world. This is a huge paradigm shift,
it's a seismic shift. So all of our companies are
doing that, and some of the most exciting applications I've
seen are actually in companies that are very much still
human oriented companies like Waymark in our portfolio, which is
(38:23):
leveraging community health workers to deliver healthcare and medicaid communities,
but are using AI to help predict emergency room admissions
and to help streamline the operations of healthcare providers.
Speaker 4 (38:35):
Dina, you've been busy.
Speaker 5 (38:36):
You're always a busy person, but you've also become an author.
Lina Moe CEO, very quickly tell me about it.
Speaker 12 (38:42):
Yes, Linamo's CEO brand new book just released last week.
It's a story about a young girl who builds a
robot to help shovel snow outside of our house, goes
through the process of building a team raising money, and
was inspired by my own journey as a parent trying
to explain venture cap to a bunch of preschoolers, which,
(39:03):
as it turns out, is just as hard as explaining
to fully grown adults.
Speaker 5 (39:08):
You know, founders are getting younger, but that young I
don't know. Lux Capital General Partner Dina Shaiker, thank you
very much.
Speaker 3 (39:22):
Today's big take how global supply chains are the latest
concern in the Ukraine Russia war. As US designed chips
are finding their way inside Russia made missiles. For more
Bloomberg Stephanie Baker, who joins US now. She's also the
author of a new book, Punishing Putin, Inside the Global
economic war to bring down Russia. Stephanie, you always tell
stories with such depth and humanity. It's a difficult story
(39:44):
to read, to be honest. But what we bring to
our audience now is the intricacies of what chips made
by who are finding their way into certain Russian missiles.
Speaker 4 (39:55):
Right.
Speaker 13 (39:55):
So, if you remember, after the invasion, the US joined
with its European allies and imposed sweeping export controls on
Russia to deny the Russian military access to Western semiconductors
and other technology. And they tighten those restrictions again starting
last year, and there'd been various reports about citing trade
(40:17):
data about components getting through, semiconductors getting through to Russia.
What we wanted to do was really drill down and
go do a deep dive on one missile attack where
Ukrainian investors had documented Western components by specific companies, as
well as examining.
Speaker 2 (40:36):
Their entire database.
Speaker 13 (40:37):
And what we came up with was that there's one
company whose components keep getting found and more. Our most
frequently found on the battlefield, and that is analog devices.
And we wanted to sort of put a human face
on what was a sort of trade data story to
show that actually Russia's very dependent on Western technology to
(40:58):
guide its missiles missile attacks on Ukraine.
Speaker 5 (41:03):
Stephanie, what was the response from Analog and also I
suppose from the United States to the reporting.
Speaker 13 (41:11):
Right, Well, Analog says they regard this as an illicit
diversion of their products and they do not condone any
of this trade. And what we tried to get into
and the story was explaining the complex supply chain for semiconductors,
that there's a lot of production happening in Southeast Asia.
There are a lot of middlemen acting particularly through Hong Kong,
(41:34):
using shell companies to do this trade. So it's been
very hard to crack down. This is not Analog selling
directly to Russia, and the US has tried to enforce
these export controls through the Commerce Department. That has proven
difficult just because of the global nature of the supply
chain and the many layers that semiconductors get traded through
(41:56):
before actually reaching Russia.
Speaker 5 (41:59):
Bloomberg Phony Baker who's in London. And as a reminder,
the big take is titled Russian Missiles American Chips. Find
it on the Bloomberg Terminal, find it on Bloomberg dot com.
Speaker 4 (42:09):
It is a must read with detailed reporting, Caroline, it is.
Speaker 3 (42:13):
Meanwhile, it's been detailed throughout. That does it for this
edition of Bloomberg Technology. A lot of news when it
comes to the private markets, the tech markets, the public markets.
Speaker 2 (42:23):
As well ed.
Speaker 5 (42:24):
Yeah, probably a historic day. We'll find out on that
big Open AI round recap all the reporting on the podcast.
You know where to find it on the Bloomberg Terminal
as well as online on Apple, Spotify, and iHeart big
shout out to the team in New York City and
everyone here in San Francisco.
Speaker 4 (42:39):
This is Bloomberg Technology.
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