June 26, 2025 • 42 mins
Bloomberg’s Caroline Hyde and Ed Ludlow discuss Micron’s earnings as its sales surge in its high-bandwidth memory business. Plus, Managing Director of Baird Ted Mortonson discusses opportunities in the defense tech space. Chinese tech giant Xiaomi also says it received more than 200,000 pre-orders for its first electric SUV.
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Speaker 1 (00:04):
Bloomberg Tech is alive from coast to coast, with Caroline
Hide in New York and ev Lolow into San Francisco.
Speaker 2 (00:15):
This is Bloomberg Tech coming up.
Speaker 3 (00:16):
Micron's high bandwidth memory business fuels a sales surge, more
in its earnings results.
Speaker 1 (00:21):
Next, plus how young startup Expo backed by Ultimate Capital,
developed an AI tool that does better than experienced hackers.
Speaker 3 (00:30):
And we dive into talents. Three hundred percent stock rallies
since October. This is defense tech comes increasingly into focus.
Speaker 1 (00:38):
Meanwhile, and focus are the big benchmarks today. The S
and P five hundred ching in on its record high.
All as the market focuses in on the federal Reserve
where we see more rate cups. Can we have three
as soon as this year as we see economic data
come in mix Today, ed, we're looking at a five
tenths of a percent push higher actually on the nast
that one hundred feeling of a risk on attitude, particularly
(00:59):
towards certain chipmakers.
Speaker 4 (01:00):
You're looking at.
Speaker 3 (01:01):
Yeah, Micron, America's biggest maker of memory chips, posted a
really strong forecast for the current period.
Speaker 2 (01:06):
The stock opened up almost two.
Speaker 3 (01:08):
Percent higher, it's now down one percent, and we can
get into the reasons right real quick. In Video, which
has had a sort of tepid morning, is now backed
continuing to hold at a fresh all time high in Micron.
Let's get into Bloomberg Intelligence Analysis with Jake Silverman and
Jake I'm looking through.
Speaker 2 (01:25):
The transcripts as a call.
Speaker 3 (01:26):
The forecast shows demand in the AI context, but I
think pricing, Jake, is a really key conversation here.
Speaker 5 (01:36):
Yeah, absolutely so, AI is a particularly strong tailwind for pricing.
But you have to keep in mind that the consumer
market is still particularly important for Micron, at least think
of smartphones, but also PCs and other SSD products and
D round products. So we're going to have to see
some of those seasonal tailwinds, you know, smartphone PC upgrade,
(02:00):
and those will beneficial pricing, but also structural limitations in
terms of capacity capacity.
Speaker 1 (02:06):
Basically for many of these companies, it's been a supply issue,
haven't been a demand issue, Jake, We've also seen a
demand issue with the shares. You'll see they've out performed
and about fifty percent of the course of year to date.
Was it just that so much was already priced into
the market here?
Speaker 4 (02:20):
How high have expectations been.
Speaker 5 (02:22):
Yeah, I mean expectations have gotten pretty high. I think
as we've seen spot prices and contract prices increase over
the recent weeks and months, that built into some of
those expectations. Again, a high bandwidth memory is something that
continues to be considered fairly important for sentiment in Micron,
but it's also a fairly small percentage of the company's
(02:43):
overall revenue. So there's just pretty high expectations across multiple
facets of the business, and so they're going to need
to continue to gain share in high band with memory.
They're going to need to continue to execute in that regard,
but also across their other AI products, while also managing
the rest of their business, which again drives a lot
of that pricing strength.
Speaker 3 (03:03):
Right, the executives on the call were pretty clear, right, Jake,
the story simple data center growth sequentially in year on
year and that will continue to outperform, and some of
the other businesses not as strong, but in the background,
they're investing in and building out capacity. Just try and
help our audience understand how difficult it is to produce
HBM and what the bottle neck is right now for
(03:25):
Micron and its customers.
Speaker 5 (03:26):
Yeah, so HBM is a little bit more complex, actually
maybe fairly more complex when we think about actually producing
relative to other memory products, especially in DRAM. So it's
stacked HBM. So we've talked about they've talked about twelve
high stack, eight high stack, so that that gives you
the dimensions of how high these DRAM stacks can go.
(03:47):
And as you increase the height, it increases the complexity.
And so the Micron and peers like s k Heinex
are able to charge a premium. And so yield is
a very important topic of conversation when we bring up
complexity and their ability to execute in terms of both
improving the capacity but also improving the yield drives their
ability to increase their share and also increase their groups margin.
Speaker 1 (04:09):
Blue meg Intelligence analyst Jake Silverman and all things Micron,
we appreciate it. Let's keep talking AI and the broader
tech market. J Jacobs black Rock, US head of Equity
ETS is here and I'm looking in astonishment at really
the enthusiasm around the I shares, AI innovation and tech
active ETF interesting in micrones not in there, but the
top holdings are in video and their broad com How
much the investors want to be in on the chip,
(04:31):
the infrastructure names, but broadened.
Speaker 4 (04:33):
Out perhaps well.
Speaker 6 (04:34):
The portfolio manager for this fun, Tony Kim, is really
looking across the value chain for opportunities and artificial intelligence.
But right now where he sees some of the biggest
opportunity is in those infrastructure and hardware names. If you
look at where the money is being spent on AI today,
the almost quarter of a trillion dollars being spent by
the megagapp tech names. It's being concentrated in semiconductor names
(04:54):
and data centers and all the support compute that's going
around that, And so our fund is very much tilted
towards that exposure right.
Speaker 1 (05:00):
Now, tilted towards in video, which is at a record
high as well. I'm just going to see where broad
Comm stands today, but it too has been very close
to record highs throughout.
Speaker 4 (05:08):
It is at a record high today.
Speaker 1 (05:09):
How much well juice is there to go on that
infrastructure play? How much can you continue to sweat at
an ets?
Speaker 6 (05:15):
It's still early. I mean, if we look at the
next several years, we're expecting about seven trillion dollars to
be spent on AI. Capex so we have a long
way to go. There's a lot of dollars to come
into the space. I still think we're in the early innings.
Over time, the exposure will evolve, though. Well, this is
kind of the build out stage of building all that infrastructure.
The next stage is going to be much more about
adaption of AI. Who's commercializing these AI products?
Speaker 3 (05:38):
Jay, your thesis or a part of it is this
overconcentration in megacaps, the fixation with the MAG seven. There's
an interesting side debate which is whether we should rethink
the composition of the MAG seven broad com perhaps making
the strongest case on fundamentals about joining or participating in
that group. All of that to say, like, what should
(05:59):
we do if that's the case, if we have overconcentration.
Speaker 2 (06:02):
Where else do you look?
Speaker 6 (06:03):
Well, whils Street always loves a good acronym for these things,
and maybe it's time for any one. Look, I think
it's really about looking beyond just concentrated megacap tech names. Yes,
they're important players in the AI space, but they don't
encapsulate all of it. You know, we've looked across twenty
thousand different financial advisor portfolios. When we found ninety five
percent of the AI exposure in their portfolios is coming
from megacap tech names, So people are very overweight megacap
(06:26):
tech just you know, largely a function of how the
S and P five hundred is today, but very underweight
the broader kind of long tail of artificial intelligence names
in digital infrastructure, in data in compute, et cetera. So
we really think it's about kind of reducing large cap
tech because there's a lot of concentration there and broadening
it out across the value chain with a fund like BAI.
Speaker 3 (06:47):
What about those non tech sectors that are most impacted
by AI or transformed by AI.
Speaker 6 (06:54):
Where do you want to look Well, I think one
of the more interesting areas is where there's a lot
of data that hasn't been harnessed by artificial intelligence. And
you have to look at the healthcare sector as being
just prime for using all that information around patient data,
around hospital management, around the development of new drugs, around
protein research. There's just so much data that frankly has
(07:15):
been under utilized, and if you can apply artificial intelligence
to it, you can get more efficient, you can reduce
the cost of drug development, you can improve performance, improve
outcomes for patients, which really would make this sector very
attractive one from an artificial intelligence perspective.
Speaker 1 (07:29):
I go back to bai I go back to the
Innovation and Tech Active ETF. Here, most of the top
holdings are US companies. You have to get to number
fifteen to get a Japanese company, and then there's a
sprinkling of the Japanese coming in.
Speaker 4 (07:40):
Is it still US exceptionalism here?
Speaker 2 (07:43):
It is.
Speaker 6 (07:43):
It's a function of where we're seeing the best public
market opportunities and artificial intelligence. It is being led by
the United States. We have some of the lowest costs
of capital, we have some of the most innovative companies.
We have a vibrant startup community that's kind of fueling
IPOs in this space as well. It is a global
trend and we do have global exposure, but right now
the US is very much leading.
Speaker 1 (08:05):
And what about the investors who are piling in just
get us up to speed. It's what about two billion
that's been coming in of late into the from client assets.
Speaker 4 (08:13):
Where are they coming from?
Speaker 6 (08:14):
Yeah, so we've brought in two billion dollars over the
last nine months.
Speaker 2 (08:16):
Now.
Speaker 6 (08:16):
One of the major things that happened is black Rocks
target Allocation model ETF models has allocated to AI. Our
model portfolio managers like Michael Gates have looked at the
landscape and said, we want to reduce large cap tech
exposure and reduce some of our just tech sector exposure
and replace it with artificial intelligence because this is a
high conviction theme that we believe in over the long run,
and so they've been shifting their exposures to get more
(08:38):
pure play in the AI theme.
Speaker 2 (08:41):
Jay Humor May.
Speaker 3 (08:43):
Federal Reserve Chair Pow was posed many questions on the
impact of AI labor markets in the future of the economy.
Speaker 2 (08:50):
And FED policy.
Speaker 3 (08:52):
It was difficult for him to answer, But do you
think about it in those terms? You basically say, I
look at the economy of the United States and the world,
and I try and alculate how structurally things might change
going forward.
Speaker 6 (09:04):
Yeah, I think this is an important area to look
at where AI can augment work right, How can it
make us more efficient? Can we accelerate productivity? Especially in
the context of aging populations around the world. So if
you look at developed markets, in many cases, the growth
of a labor market is slowing, and so you really
almost need AI and that productivity growth to maintain strong
GDP growth across these developed economies. So I think in
(09:25):
many ways, AI is going to be an incredible tool
to boost productivity and frankly a tool that develop markets
need to lead it. This is why we're seeing AI
at the crux of geopolitics, because people policymakers see it
as such an accelerant towards our economy over the long run.
Speaker 3 (09:41):
Throughout the show in the day, actually we're going to
be talking about Patenteer and it makes me think about
not just software, but this kind of broader American effort
to reindustrialize the country in a number of sectors, defense,
artificial intelligence, data centers. Is there some kind of big
picture effect that you're trying to jump on to on
this reindustrialization the manufacturing of stuff here in America.
Speaker 6 (10:05):
Well, this is really at the intersection of several themes.
You know, We've looked at five mega forces around the
world that are kind of changing the long term trajectory
of economies, and one of them is aging populations, which
you've mentioned, one of them is artificial intelligence, and the
third one is really geopolitical fragmentation. All of these are
combining to bring in you know, certain themes like infrastructure.
How when we see that we want to build more
(10:26):
in the United States, we have to have better roads,
better highways, better waterways, better power to accelerate that. How
do we have the best technology in the world through
artificial intelligence and leaning into that segment. So really, yes,
all of these things are kind of colliding here to
really lead some of the best economic opportunities in the
United States.
Speaker 3 (10:47):
J Jacobs a black Rocket's great to have you back
on Bloomberg Tech.
Speaker 2 (10:50):
Thank you very much.
Speaker 3 (10:51):
Coming up, China gives approval for more M and A
among its tech giants. It's a big story we're watching
and that's next. This is Bloomberg Tech.
Speaker 4 (11:09):
This time now for Talking Tech.
Speaker 1 (11:11):
Have verst up a growing number of Chinese AI startups
where they are looking to list in Hong Kong. That
could include Rikonover Technologies. It's a firm specializing in visual
perception look. According to sources, the company, which is backed
by Intel Capital, green Und Holdings, is looking to raise
about one hundred million dollars from the listing that could
happen later this year. In more listing news, In fact,
(11:31):
digital payments provider Pine Labs has filed to go public
in India, and the company, whose shareholders include PayPal, will
seek to raise as much as twenty six billion rupees
that's around three hundred and.
Speaker 4 (11:40):
Three million dollars.
Speaker 1 (11:41):
Indian capital markets, of course, are seeing a resurgence in listings,
fueled in part by the government's push to digitize the economy.
Speaker 4 (11:48):
And the president and CEO of Tokyo.
Speaker 1 (11:51):
Electron well as shrugging off concerns about rising competition from China,
he spoke exclusively with Bloomberg's Cherryan in Tokyo.
Speaker 7 (11:58):
How got I think you possible to maintain the difference
in technology between China and our company. I'm sure that
Chinese vendors are trying to catch up with us, but
we must be faster. We can be faster than them
in technology innovation, and that's how we can maintain or
increase the difference. We are the spe manufacturer, but we
(12:19):
are not chip makers. So for us, it is key
to work with the world leading chip manufacturer to develop
the best in the world process and best in the
world equipment.
Speaker 1 (12:30):
You can watch the full interview on Bloomberg Tech Asia
catch a premiere as tomorrow at eight thirty pm Eastern
Time eight thirty am in Hong Kong.
Speaker 2 (12:38):
Ed stay in Asia.
Speaker 3 (12:40):
Jaomi says they've received more than two hundred thousand pre
orders for its first electric suv, the Yu seven, in
just three minutes.
Speaker 2 (12:48):
For more Bloombag.
Speaker 3 (12:49):
Peter Elstrom joins us and on the live feed during
the presentation, I noticed there were several million people tuned
in on x What do we know about this new
suv and the appetite here for Jaomi.
Speaker 8 (13:03):
Yeah, the excitement around show Me and its electric vehicles
is quite something. The founder late June, just did this
presentation in Beijing a little while ago, and he talked
about this new suv. It's going to be priced around
thirty five thousand dollars at the low end, it'll go
up to about forty six thousand dollars. And he took
aim directly at Tesla. Tesla's model why is the best
(13:23):
selling suv in China right now, And he's going directly
after them. He wants to be able to compete with
them on price and on features, and so far they've
been gaining a lot of ground. Now. Show Me, a course,
is best known for its smartphones. They began by competing
against Apple with their smartphones. They did a lot of
innovative things with that company. Late June kind of modeled
himself after Steve Jobs for a even with black turtlenecks.
(13:46):
But now they've been diversifying into a number of different areas,
including appliances, even luggage. When I visited them in Beijing,
they had all sorts of goods out there. But this
move into cars is really being something different. The stock
has taken off, the share are really soaring. They've tripled
over the past year, in fact, and I think you're
seeing this now reflected in the strong demand for their
(14:06):
new SUV.
Speaker 1 (14:08):
I mean extraordinary two hundred thousand and three minutes. You've
got to undred eighty nine thousand in one hour. Peter,
there was a worry about almost innovation happening too quickly
and a crash that happened with the S seven.
Speaker 4 (14:20):
Is that sort of being shrugged.
Speaker 8 (14:21):
Off right, Yeah, you're referring there was a there was
a crash in China with a Shami car where it
led to a fatality. They did put a they hit
the pause button on some of their sales at that
point to look at the technology within the car. But
now they're moving forward. They introduced this new vehicle. They
feel like they put them that behind them and now
they're you know, they're they're seeing strong customer demand for
(14:44):
these cars. As we're talking a little bit about before.
They look very much like Porsches. You know, you can
get effectively a porstial looking car. It's an EV for
thirty five thousand dollars. Chinese consumers like that offer.
Speaker 3 (14:56):
I find policy in China on tech companies so interesting.
It's either restrictive, right you think about the video games
industry in the.
Speaker 2 (15:02):
Last couple of years now allowing M and A.
Speaker 3 (15:05):
Are you able to summarize, Peter, what the Chinese government's
attitude is towards the tech sector overall.
Speaker 8 (15:12):
Oh, that's a big ass, but I'll do what I
can anyways. Yeah, I mean, certainly, what you saw in
the twenty teens, in particular, was growing domination by a
couple of the biggest technology companies there, especially Ali Baba
and Tencent. They put tons of money into startups. They
had scores, probably hundreds of companies that they invested in,
and they had these ecosystems that they kind of controlled,
(15:35):
and that really lasted during the boom years after Ali
Baba went public and showed that you can make a
lot of money on some of these Chinese tech stocks.
In particular, we had this big crackdown, the jackmar crackdown,
after he spoke out against regulators. The ant group IPO
was pulled, and after that, essentially all this m and
A stopped. There was no more consolidation. In fact, the
companies had to roll back a lot of the plants
(15:58):
that they had. Ali Baba sold off a bunch of
its assets too. And now what we're seeing partly because
the Chinese economy is a little baracky at this point,
they need more support from the private sector. They've given
more support to the tech companies in particular, they've seen
some new breakthroughs truth too, like deep seekin Ai. Huawei
has made a lot of progress in different areas too.
(16:18):
So now Alibab and Tensen are able to go back
to doing some M and A. They're beginning to do
a little bit, and it's nothing like the scale that
they did in the past, but they are able to
make some acquisitions.
Speaker 3 (16:29):
Bloomberg's Peter Elstrom answering the difficult question, thank you very much.
After receiving a tepid response for investors when it went
public back in March. Core We've stock has had a
meteoric rise around three hundred percent, has propelled the company's
(16:49):
CEO into the ranks for the world's richest with some
unusual speed. Bloomberg's Dillon Slow And joins us and has
the profile. This is like key tech wealth coverage, right,
a slow start on the ip but things change and
now a key figurehead has a pretty healthy net.
Speaker 9 (17:05):
Wealth exactly, Yes, just like you were saying, kind of
in some ways mirroring sort of the trajectory of the
IPO market more generally over the course of the year.
So when this company debuted in mid March, they were
initially seeking to raise at about a thirty five billion
dollar valuation, ended up completing the offering about a twenty
three billion dollar valuation.
Speaker 2 (17:22):
So well below that.
Speaker 9 (17:23):
Actually, the ceo mic and Trader came on Bloomberg Television
and told us that without a big order from Nvidia,
one of their largest investors, the deal might not even
have closed. So this stock traded pretty flat for about
two months after then, but it's off as again, as
you said, about three hundred percent in cent and that's
generated some really significant wealth gains, not just for the CEO,
but for other co founders and early investors too.
Speaker 1 (17:44):
I know he's now the three hundred and eleventh richest person.
He's ahead of Robert Craft I think of Magnetar and
some of the other key companies that backed them early.
What's interesting is he managed to go out there and
start to convince the market of the business model. Perhaps
got misunderstood or underrun appreciated when the IPO came out.
Speaker 9 (18:02):
Yeah, absolutely, And you know, the stock really started picking
up after the report of their first court earnings. They
beat estimates there and Nvidia also disclosed it they'd increase
the size of their stake, and it's really been all
up from there. It's gotten a lot of retail interest too,
so generated some sort of meme stocky comparisons from some commentators,
but for in traders specifically, his networth right now standing
at about ten point three billion dollars, and it's not
(18:23):
just the size of that, but it's the speed as well.
For the Bloomberg Billionaires Index, all of the billionaires we track,
the average time it takes for someone to go from
a five billion to a ten billion dollar net worth
is just about three years and four months and trader
did it in twelve trading days, so far faster than
the average person.
Speaker 1 (18:40):
Now do Circle founder Jeremy Lair. I'm sure you're on
that one too, Dylan Sloan, appreciate your time.
Speaker 4 (18:45):
Thank you. Now, let's talk about.
Speaker 1 (18:47):
A US district judge who has just ruled that Anthropics
use millions of books without payment to train its models,
and it's legal under copyright law, falling under the fair
use doctrine, a move that could actually kind of cripple
a rights holder's ability to monetize.
Speaker 4 (19:03):
On AI as KOed Bloomberg Opinions. Dave Lee's take here.
Speaker 1 (19:06):
It's a fascinating read, and you go into the intricacies
of how Anthropic first of all did it, And they
did it perhaps with a mixture of pirated book copies,
but then they actually started burning physical books, taking out
the spine and copying them into the computer.
Speaker 10 (19:21):
Yeah, so they went out and they acquired pirated copies
of more than seven million books to.
Speaker 2 (19:26):
Train into their models.
Speaker 10 (19:28):
After a short while, they thought, well, maybe there's a
better way to do this, and they bought the physical
used copies from distributors of used books and started chopping
off the spines. Cutting down the pages and ingesting those
into their research libraries.
Speaker 2 (19:41):
They called it, which was.
Speaker 10 (19:42):
Then used to train the large language model. And they
were sued by three authors whose books were in both
the pirated copies but also the physical copies as well,
and they said, look, the fact that you're doing this
to create a model and we get no compensation for
that shouldn't be considered fair use, which is this sort
of carve out and copyright law that says, if what
(20:05):
you do is sufficiently transformative and doesn't harm the commercial
prospects of the original work, then you'll find to use
it in some degree. And the judge in this case,
and it's one of the number of AI cases like
this currently active, the judge in this case said, yes,
he writes, this is fair use in this.
Speaker 4 (20:22):
It not the pirated one, not the pirated one.
Speaker 10 (20:25):
Yes.
Speaker 3 (20:26):
I think the main response at the time was that
an appeal is likely, but you're really interesting what you said.
It's not the only thing happening in isolation. People were
trying to get the read through to others like Meta
for example, and kind of work out what happens next,
because on the face of it, it's good for generative
AI but the companies are going to struggle to navigate this.
Speaker 10 (20:46):
Yes, I mean, look, it really hinges on. If it
is fair use, then companies are free to ingest all
this information without paying anybody and do what they want
with it. And of course the AI industry is incredibly
clean on that many you know, respective commentations and copyright law.
I think that is the case as well. The danger
is is that AI is unlike anything we've seen before
(21:08):
in terms of you know, finding knowledge and reading new information.
And what if and this is the sort of doomsday
scenario from publishers. What if people stop buying books because
they can just get the information they need from AI.
Speaker 2 (21:22):
And also, you.
Speaker 10 (21:22):
Know, where is the incentive of people to write new
books if when they do write it, they just get
sucked up into the machine and they don't see any
sort of commercial benefit that is able to write stay
in the practice of doing the hard work of writing
a book.
Speaker 3 (21:36):
Daily of Bloomberg Opinion another great column.
Speaker 2 (21:38):
Thank you very much.
Speaker 3 (21:46):
Welcome back to Bloomberg Texts and Breaking News. I've just
reported with Bloomberg's Dana Hole that Omeed Afshar, who is
a key lieutenant and has been a key lieutenant of
Elon Musket Tesla has left the company in recent days.
This is somebody that was in charge of manufacturing in
sales for North America and Europe, and what sources are
(22:07):
telling us is that he has left. He's also no
longer in the directory at Tesla. There's a lot that
we don't know, Caro. I've emailed Elon Musk to ask
him what's going on and why Omeed left the company.
You'll remember we've done some reporting on him in the
past and asked about some reporting that he's been involved
in about internal audits, internal reviews. But it's one of
(22:30):
many recent departures from Tesla's and the market was playing
attention with a move lower and.
Speaker 4 (22:34):
Look, Asha had a tough job, right.
Speaker 1 (22:36):
It was last year he was promoted into the office
of the CEO and he was overseeing some really significant
areas of sales and manufacturing in some pain point areas
for Tesla, largely because perhaps a political backlash to.
Speaker 4 (22:47):
One Elon Musk.
Speaker 3 (22:48):
Right, he'd been in the office of the CEO for
quite a while. He was kind of like Elon Musk's
chief of staff, so to speak. But then he got
more responsibility and he was very key on Austin getting
Austin set up. You know, I'm interested to know what happened,
but it's one of several departures in recent months of
people that are kind of long standing in health senior roles.
(23:10):
In a period of time where Elon was elsewhere.
Speaker 1 (23:12):
He's elsewhere politically, and also the sales focus has gone elsewhere.
When I'm thinking about today's extraordinary numbers around Shaomi's latest
suv going straight for the Tesla buyer, this is really
a difficult moment for Elon.
Speaker 4 (23:27):
No wonder He's come back as CEO.
Speaker 3 (23:30):
Right, so you know, like the big picture is that
Tesla in the future is focused on Robotaxi and they
had a successful launch of a small reduced service in
Austin and Optimist. But the reality is that Ben but
Butter is still selling cars and in the first six
months of this year, lots of data in all markets
that Must's association with the.
Speaker 2 (23:46):
Administration was hurting sales.
Speaker 3 (23:47):
But also like competition with hybrids, increased competition from other
model providers and other name brands in Europe for example.
But in Omeid Avshah's case, and again to recap sources
of telling us. He's left the company with someone so
close to Elon Musk with a lot of responsibility. It's
one in a chain of high profile executives. For example,
Milan Kovac, who is leading the Optimist program, also left
(24:10):
that We reported listening. When we get more, we'll keep
an eye on it. I'm also looking at Palenteer. This
is a stock that since October is up three hundred
percent year to date, up ninety percent. One of the
best performers there is its performance as a company in
cordly earnings. But this kind of macro and geopolitical environment
that we're in right now, Caro, that speaks to the
(24:31):
core of this story. And right now, this emphasis on
defense technology, that's what we're hearing about on a weekly
basis right It.
Speaker 1 (24:38):
Is because of the geopolitics that we currently confront escalating
US China rivalry, to conflicts in Europe and the Middle East,
geopolitical pressure. Said, they are driving a new way of
defense innovation. Let's talk about what that means to the
markets for your tech investments. Ted Mortensen is with US
Imagine director at BED. You yourself have a rich history
in defense from an active of his perspective, Ted, but
(25:01):
I'm interested is to therefore, what the active innovation play is.
Speaker 4 (25:05):
How do you invest into this moment.
Speaker 11 (25:08):
It's kind of fragmented right now, but Pallenteer is obviously
the purest play. And if if you look at the
latest conflicts on you know, coming out of Israel and
Iran and also Ukraine and Russia, these advanced technologies that
are being used are giving both Israel and Ukraine heads
up as it relates to their adversaries. Its number one,
(25:32):
number two. Just recently with NATO increasing their budgets up
to five percent GDP, the defense spend as well as
the US with a big beautiful bill is straight up.
So you're going to see this pivot to JENNAI being
embedded in all weapons systems. And you know, right now,
(25:52):
JENNYI is a national security discussion. If you look at Pallenteer,
they're the first mover, and I think there's a few
issues on the reason why it's up. They signed Israel,
they signed the Ukraine, they signed NATO post DOGE. Also
their solution to all the federal agency problems also in
(26:14):
DoD spanding. So they're one of the purest production ready
jen AI solutions where they can aggregate. I wish I
had it when I flew all this unbelievable Intel data
on a translation layer that you can see at real time.
Speaker 1 (26:31):
But like the mag seven in many ways, it's a
very concentrated defense tech play. I mean, we're at a
record high for palent here. It's been an extraordinary up
into the right move for the stock. Where else if
you're looking for diversification, can you go?
Speaker 2 (26:46):
You can go.
Speaker 11 (26:47):
Recently, we just had a report on aero environment AVAV.
They just bought a real stunning private company called Blue Halo,
which it gets aero environment way from their switchblade devices
on the drone side. But what blue Halo gives them
is an entry into cybersecurity, satellite and high energy weapons.
(27:12):
That's that's another play. Unfortunately from the private perspective. I
know ed you've talked about angel In in other shows.
Andrew is a private company that is almost a case
study and how the US military is re architecting their
defense budgets. These are high R o I C devices
(27:34):
that really go against you know, the traditional spend of
billion dollar programs that are under budget. They're very effective
and they're really changing the rules of the game.
Speaker 3 (27:44):
Ted, what you just said traditional spend. When I look
at companies like Palanteer and how they behave, they do
behave like traditional primes, big contract manufacturers to the government
because they basically say, I serve the US and its
allies only.
Speaker 2 (28:01):
How does that help them? It helps them.
Speaker 11 (28:04):
I think if you look at the traditional primes like
Lockheat or Raytheon, for example, they're known for hardware, They're
not known for gen AI software. This is why pallunteers
being brought in as kind of a pseudo prime in
almost all these new next generation defense contracts. They are
the software layer. The other aspect of this. When you
(28:28):
look at the spend, you look at what drone technology
and I think in the future, when you really look
at this on andrel I would not be surprised if
you have self drones flying on each wing of an
F thirty five.
Speaker 12 (28:44):
That changes the rules of the game.
Speaker 11 (28:46):
And when we talk about boots on the ground, I
mean you talked about Tesla early with Optimus. I think
you're going to see machines on the ground in the
next five to ten years. And that's a paradigm shift
from the defense budget standpoint.
Speaker 3 (29:00):
Right Ted Mortenson of Bad Great conversation, Thank you very much.
I want to stick with defense tech. Amid the conflicting
assessments from Washington about the effectiveness of the US strikes
on Iran. Let's stick into the supply chain resilience of
the US government aimed to modernize US commercial and government
data with its ARC software streaming defense acquisitions for customers,
(29:23):
includes the US Army, Navy. Let's get to Tara Murphy
Dherty Gavini CEO. There's anywhere we could take this right,
but let's just start with the basics. The US government
and its military industrial complex or the defense industrial base.
How modern is it in the scheme of everything Ted
and we just discussed on the show.
Speaker 13 (29:46):
It's getting more modern, I would say, the reality is
that today the defense industrial base is still quite traditional.
Speaker 12 (29:55):
And you can look at the recent strikes on Iran
as a perfect.
Speaker 13 (29:59):
Example of Yes, we know that fifth generation fighters escorted
B two bombers to Iran to drop the bombs. Maybe
those were F thirty five's, but there were likely some
F twenty twos in there as well.
Speaker 12 (30:12):
Those F twenty two jets and the.
Speaker 13 (30:14):
B two bombers were operationally deployed first in nineteen ninety seven,
So a lot of American military capabilities actually.
Speaker 12 (30:21):
Quite old, quite old.
Speaker 1 (30:23):
And I'm looking at what the DoD nine hundred and
sixty one billion dollar budget for the fiscal year starting
in October the first actually looks like I mean, I'm
sure you've read through the seventy five page procurement request
at the moment, but almost five billions cann be spent
on B twenty one self bomber production. There's going to
be thirty seven THOUD missiles, There's going to be twenty
four Air Force F thirty fives TARA. When you go
(30:43):
through that seventy five report page report, is there enough
of the new tech that we're talking about the supply
chain that you'll.
Speaker 13 (30:49):
Analyze, there's definitely still not enough. This is one of
the major imperatives for US national security right now is
the need for modernizing these weapons, systems and platforms, these
major capabilities. And this is what so much of the
defense tech industry, the companies that you are just referring to, Gavini,
Palanteer Andral have been clamoring for in Washington, DC, which
(31:14):
is the Department is spending huge amounts of money trying
to sustain these legacy platforms. More than seventy percent of
the entire cost of a jet, for example, or a
submarine is spent during its sustainan phase. The United States
needs modern capabilities not just to effectively fight war, but
(31:36):
in order to be able to afford the wars.
Speaker 12 (31:39):
That we need to deter and win.
Speaker 1 (31:42):
You just said you are going to the administration, You're
going into government and lobbying saying this needs to change.
Speaker 4 (31:48):
Just talk to us with the data with which you
were able to provide.
Speaker 1 (31:50):
I'm sort of fascinated with what ARC is doing Gavini's Defense.
Speaker 4 (31:54):
Acquisition software platform. What does it tell you? What does
it show?
Speaker 12 (31:59):
It shows quite a bit.
Speaker 13 (32:00):
So defense acquisition software is really designed to replace the
incredibly manual processes that the Department uses today to manage
the life cycle of these weapons systems. In platform, so
cradle to grave, how you design these systems through their
sustain and their modernization, managing parts and managing suppliers Today,
(32:22):
Somewhat unbelievably, the United States DoD does that.
Speaker 12 (32:26):
Primarily in spreadsheets.
Speaker 13 (32:28):
A lot of people are involved in what are very
slow processes, and software, and especially AI driven software like
arc is, can really accelerate those processes. The other really
important piece of ARC is the integrated data set that
exists in the software and this is Gavini's proprietary data
(32:48):
set which gives DoD visibility into these global supply chains
down to the part level, down to run materials and microelectronics.
And this is essential in order to come up with
the modern kinds of systems that we need and make
them rest and available for the warfighter really quick.
Speaker 2 (33:08):
We just have thirty seconds.
Speaker 3 (33:09):
On the other side of the table, is this government
and this Pentagon better on the procurement side.
Speaker 12 (33:16):
It's trying to be.
Speaker 2 (33:17):
So.
Speaker 13 (33:17):
We've seen executive orders on defense acquisition. We've seen calls
to enforce the Federal Acquisition Streamlining Act, which mandates that
government agencies by commercial first, especially software, instead of taking
on failed IT development projects.
Speaker 12 (33:33):
What we need to see now.
Speaker 13 (33:34):
Is will those policy decisions, will those will that guidance
be implemented. If implementation can happen, we will see tremendously
positive results.
Speaker 1 (33:45):
Tarfage Docs, we thank you of Gavini fascinating on all
things defense procurement. Meanwhile, coming up, we're going to talk
to the CEO behind an AI hacking tool. His lead
investor is going to join us too about the proactive
defense against sliver attacks.
Speaker 4 (33:59):
This is what we've got.
Speaker 1 (34:12):
A one year old startup has developed an aitol that
is better at identifying many software vulnerabilities than experienced hackers.
The startup, called Expo, has recently closed a seventy five
million dollar funding round led by Ultimeter Capital. Exposed founder
and CEO or her De Moor is with US. Ultimate
partner Appaul of Agowell.
Speaker 4 (34:31):
Is also with us as well. Or Her I start
with you.
Speaker 1 (34:34):
Why is it so important that you the AI version
of a hacker is at the top of Hackerwe's US leaderboard.
Speaker 14 (34:42):
Thank you very much for having us so it's the
first time ever that a machine and not a human
is at the top of the Hackerwom leaderboard for the US.
Hackerwom is a platform that connects Hackhouse with companies who
want their systems to be tested, and they maintained the
leaderboards ranking the hackers according to whose bugs have been
(35:09):
accepted by the customers of Hakawan, and currently the top
in the US is our AI.
Speaker 1 (35:17):
What's so interesting is that you are like the AI
guy among many, but really you're driving the portfolio allocations
for AI over at Altimeter, I'm thinking some of the
open AI investments that you made, some of the others.
I mean, we see such pedigree coming from a man
who helped.
Speaker 4 (35:34):
Develop GitHub copilot.
Speaker 1 (35:35):
Is that what attracted you to Expo or is it
the fact of what it can achieve?
Speaker 15 (35:39):
You know, before we even met, we've been studying the
space and very simply, cyber attacks are on the rise.
Software is more vulnerable, a lot more engineers, a lot
more code developed with AI. And by the way, these
models are trained on open source software, which is more vulnerable.
Speaker 2 (35:55):
That's on one side.
Speaker 15 (35:57):
And then I met oohe which our first meeting felt
like the fifth meeting because of his ambition to build
the cybersecurity platform. In the age of AI, CIOs want less,
not more. They're fatigued in alert tonight right now, and
you know who has vision to build Expo, help you
find vulnerabilities, fix them automatically, and ultimately building the cybersecurity
(36:19):
platform is a big one. It's probably the most important
business being built right now, not because it'll be a
great opportunity, but because it must be built. If we
don't build it, the bad guys have the technology and
we've got to put it in the hands of the
good guys in the free world.
Speaker 2 (36:33):
Oh thank you for joining us on the show.
Speaker 3 (36:35):
I've been trying to think about what this represents, right,
the swarm is always on. It represents what an army,
if humans could do twenty four to seven to identify
the vulnerability. But the question is what happens next for
your company? And I'm assuming that you're trying to engineer
towards the swarm, also reacting, putting into place fixes when
(36:57):
those vulnerabilities are identified.
Speaker 14 (37:00):
That's right. So even today, the AI is already identifying
vulnerabilities at some of the top company companies in the
country are companies like palle Alter Networks, are at and T, Disney, Sony,
and the list goes on and on. Now, of course
(37:22):
it finds these vulnerabilities, but they need to be fixed
as well. We're very lucky that all these companies that
we've been working with have been extremely pretty active immediately
fixing the problems as they were pointed out. It's a
natural evolution, but eventually an AI will be able to
do some of the fixes as well.
Speaker 3 (37:43):
Paul, I know you as an operator, you know you're
pretty handy with software. What are you going to do
to help this company grow and scale as a commercial entity.
What do they need to focus on to convince the
marketplace that an AI swarm is a better then a
human team of hackers.
Speaker 15 (38:05):
And we are fighting against time. Time is our biggest competition. Really,
if you had three weeks ahead of the bad guys,
you're saving.
Speaker 2 (38:16):
Three weeks worth of vulnerabilities.
Speaker 15 (38:18):
And cyber tends to be a game of cat and mouse.
Sometimes you've got the offensive teams ahead and other times
you've got the defensive teams ahead. And so the number
one thing we're focused on is speed. That's why we're
here today. That's why we're educating the world about what
we're doing. We work with a lot of companies, as
we have mentioned, helping them secure their perimeter before the
bad guys get in.
Speaker 1 (38:41):
What's so interesting is, of course, when Ed calls you
an operator, you came from Palenteer, you're leading the charge.
When you're looking at the AI investment opportunities, when we
think about open AI investment, when we also think about
clean When you think about this moment, because you're also
exposed to ANDREILSPACEX, is this the moment for defense tech,
whether it comes in a cyber capacity, it comes in
a hard tech capacity.
Speaker 15 (39:02):
Look, I think at the highest abstraction, AI is having
great impact across fields. This is defense, cybersecurity, customer service,
software engineering. These are large industries that are going through
reinvention and ultimately it's raising the ceiling for performance of
the best professionals in cybersecurity, like what we are doing
(39:22):
at EXPOU, and raising the floor for all the mundane tasks.
In the case of EXPOU, for example, you've got to
do reconnaissance, you've got to do scanning and.
Speaker 2 (39:31):
Exploitation and report building.
Speaker 15 (39:32):
These a part of that is just mundane work, but
also the best hackers in the world now better off
with XPOW in your toolkit rather than without.
Speaker 3 (39:42):
Right, Oh, you are going from this point rate limited
by compute and tokens. Just explain the pathway for your
company and the bottlenecks that you might face.
Speaker 14 (39:54):
So currently it's we can we have no problems with
the amount of compute. It's actually not that intensive. We
can easily serve the customers that we're currently working with.
We are, however, very much focused on working with the
(40:17):
top companies that have the biggest our need for better security,
financial services, healthcare, those types of those types of industries.
Speaker 3 (40:30):
All right, that was that Paul vagaryle partner at Ultimated Capital,
and I'll hear the more.
Speaker 2 (40:34):
CEO and founder of X thank you both very much.
Speaker 3 (40:38):
Salesforce is developing an AI product that can handle tasks
like customer service without human supervision. CEO Mark Benioff says
the tour has reached ninety three percent accuracy. He spoke
with Bloomberg's Emily Chang. Take a listen.
Speaker 16 (40:53):
You founded the company now twenty five years ago, so
you've seen the rise of mobile and social and the
cloud and now AI. How has the CEO job changed
for you?
Speaker 17 (41:02):
Well, the CEO chop is really changing fast, you know,
because it used to be I felt very alone at
the top, But now, like I just finished writing the
business plan for this year, and I always do that
with someone else, like I take one of our executives.
And for the last three years, I've also have found
a new partner in AI. So I have an AI partner,
(41:25):
I have a human partner, and it's the three of
us who are writing the plan together. So it's a
little less lonely at the top of AI.
Speaker 16 (41:31):
You said you won't hire any more coders at Salesforce,
and you've said today's CEOs will be the last to
manage all human workforces.
Speaker 4 (41:41):
What does this mean for businesses?
Speaker 17 (41:43):
Digital labor is going to be everything from AI agents
to robots, and I do think you know to your point,
you know, CEOs have to make sure their values are
in the right place and that values bring value.
Speaker 12 (41:53):
Could an agent replace you one day?
Speaker 17 (41:55):
I hope so, you hope?
Speaker 12 (41:57):
So?
Speaker 17 (41:57):
I mean, of course I'm partially kidding. You know that
we're becoming more automated.
Speaker 1 (42:02):
You can see Emily Chang's full conversation with Salesforce CEO
Mark Benioff. It's on the circuit Errington Knight in eight
pm Easton. Now that does it for this edition of
Bloomberg Tech. What a whirlwind from your breaking scoop at Tesla.
Speaker 3 (42:15):
Just remind us a couple of days of testimony, and
now we have breaking news from Tesla that Omi dash
Shah has basically been fired by Elon Musk. Recap that
story and all the others on the podcast. You know
where to find it, the Bloomberg Tech Pod on the Terminal,
as well as online on Apple, Spotify and on iHeart
from New York City and San Francisco.
Speaker 2 (42:34):
This is Bloomberg Tech
Bloomberg Tech is alive from coast to coast, with Caroline
Hide in New York and ev Lolow into San Francisco.
Speaker 2 (00:15):
This is Bloomberg Tech coming up.
Speaker 3 (00:16):
Micron's high bandwidth memory business fuels a sales surge, more
in its earnings results.
Speaker 1 (00:21):
Next, plus how young startup Expo backed by Ultimate Capital,
developed an AI tool that does better than experienced hackers.
Speaker 3 (00:30):
And we dive into talents. Three hundred percent stock rallies
since October. This is defense tech comes increasingly into focus.
Speaker 1 (00:38):
Meanwhile, and focus are the big benchmarks today. The S
and P five hundred ching in on its record high.
All as the market focuses in on the federal Reserve
where we see more rate cups. Can we have three
as soon as this year as we see economic data
come in mix Today, ed, we're looking at a five
tenths of a percent push higher actually on the nast
that one hundred feeling of a risk on attitude, particularly
(00:59):
towards certain chipmakers.
Speaker 4 (01:00):
You're looking at.
Speaker 3 (01:01):
Yeah, Micron, America's biggest maker of memory chips, posted a
really strong forecast for the current period.
Speaker 2 (01:06):
The stock opened up almost two.
Speaker 3 (01:08):
Percent higher, it's now down one percent, and we can
get into the reasons right real quick. In Video, which
has had a sort of tepid morning, is now backed
continuing to hold at a fresh all time high in Micron.
Let's get into Bloomberg Intelligence Analysis with Jake Silverman and
Jake I'm looking through.
Speaker 2 (01:25):
The transcripts as a call.
Speaker 3 (01:26):
The forecast shows demand in the AI context, but I
think pricing, Jake, is a really key conversation here.
Speaker 5 (01:36):
Yeah, absolutely so, AI is a particularly strong tailwind for pricing.
But you have to keep in mind that the consumer
market is still particularly important for Micron, at least think
of smartphones, but also PCs and other SSD products and
D round products. So we're going to have to see
some of those seasonal tailwinds, you know, smartphone PC upgrade,
(02:00):
and those will beneficial pricing, but also structural limitations in
terms of capacity capacity.
Speaker 1 (02:06):
Basically for many of these companies, it's been a supply issue,
haven't been a demand issue, Jake, We've also seen a
demand issue with the shares. You'll see they've out performed
and about fifty percent of the course of year to date.
Was it just that so much was already priced into
the market here?
Speaker 4 (02:20):
How high have expectations been.
Speaker 5 (02:22):
Yeah, I mean expectations have gotten pretty high. I think
as we've seen spot prices and contract prices increase over
the recent weeks and months, that built into some of
those expectations. Again, a high bandwidth memory is something that
continues to be considered fairly important for sentiment in Micron,
but it's also a fairly small percentage of the company's
(02:43):
overall revenue. So there's just pretty high expectations across multiple
facets of the business, and so they're going to need
to continue to gain share in high band with memory.
They're going to need to continue to execute in that regard,
but also across their other AI products, while also managing
the rest of their business, which again drives a lot
of that pricing strength.
Speaker 3 (03:03):
Right, the executives on the call were pretty clear, right, Jake,
the story simple data center growth sequentially in year on
year and that will continue to outperform, and some of
the other businesses not as strong, but in the background,
they're investing in and building out capacity. Just try and
help our audience understand how difficult it is to produce
HBM and what the bottle neck is right now for
(03:25):
Micron and its customers.
Speaker 5 (03:26):
Yeah, so HBM is a little bit more complex, actually
maybe fairly more complex when we think about actually producing
relative to other memory products, especially in DRAM. So it's
stacked HBM. So we've talked about they've talked about twelve
high stack, eight high stack, so that that gives you
the dimensions of how high these DRAM stacks can go.
(03:47):
And as you increase the height, it increases the complexity.
And so the Micron and peers like s k Heinex
are able to charge a premium. And so yield is
a very important topic of conversation when we bring up
complexity and their ability to execute in terms of both
improving the capacity but also improving the yield drives their
ability to increase their share and also increase their groups margin.
Speaker 1 (04:09):
Blue meg Intelligence analyst Jake Silverman and all things Micron,
we appreciate it. Let's keep talking AI and the broader
tech market. J Jacobs black Rock, US head of Equity
ETS is here and I'm looking in astonishment at really
the enthusiasm around the I shares, AI innovation and tech
active ETF interesting in micrones not in there, but the
top holdings are in video and their broad com How
much the investors want to be in on the chip,
(04:31):
the infrastructure names, but broadened.
Speaker 4 (04:33):
Out perhaps well.
Speaker 6 (04:34):
The portfolio manager for this fun, Tony Kim, is really
looking across the value chain for opportunities and artificial intelligence.
But right now where he sees some of the biggest
opportunity is in those infrastructure and hardware names. If you
look at where the money is being spent on AI today,
the almost quarter of a trillion dollars being spent by
the megagapp tech names. It's being concentrated in semiconductor names
(04:54):
and data centers and all the support compute that's going
around that, And so our fund is very much tilted
towards that exposure right.
Speaker 1 (05:00):
Now, tilted towards in video, which is at a record
high as well. I'm just going to see where broad
Comm stands today, but it too has been very close
to record highs throughout.
Speaker 4 (05:08):
It is at a record high today.
Speaker 1 (05:09):
How much well juice is there to go on that
infrastructure play? How much can you continue to sweat at
an ets?
Speaker 6 (05:15):
It's still early. I mean, if we look at the
next several years, we're expecting about seven trillion dollars to
be spent on AI. Capex so we have a long
way to go. There's a lot of dollars to come
into the space. I still think we're in the early innings.
Over time, the exposure will evolve, though. Well, this is
kind of the build out stage of building all that infrastructure.
The next stage is going to be much more about
adaption of AI. Who's commercializing these AI products?
Speaker 3 (05:38):
Jay, your thesis or a part of it is this
overconcentration in megacaps, the fixation with the MAG seven. There's
an interesting side debate which is whether we should rethink
the composition of the MAG seven broad com perhaps making
the strongest case on fundamentals about joining or participating in
that group. All of that to say, like, what should
(05:59):
we do if that's the case, if we have overconcentration.
Speaker 2 (06:02):
Where else do you look?
Speaker 6 (06:03):
Well, whils Street always loves a good acronym for these things,
and maybe it's time for any one. Look, I think
it's really about looking beyond just concentrated megacap tech names. Yes,
they're important players in the AI space, but they don't
encapsulate all of it. You know, we've looked across twenty
thousand different financial advisor portfolios. When we found ninety five
percent of the AI exposure in their portfolios is coming
from megacap tech names, So people are very overweight megacap
(06:26):
tech just you know, largely a function of how the
S and P five hundred is today, but very underweight
the broader kind of long tail of artificial intelligence names
in digital infrastructure, in data in compute, et cetera. So
we really think it's about kind of reducing large cap
tech because there's a lot of concentration there and broadening
it out across the value chain with a fund like BAI.
Speaker 3 (06:47):
What about those non tech sectors that are most impacted
by AI or transformed by AI.
Speaker 6 (06:54):
Where do you want to look Well, I think one
of the more interesting areas is where there's a lot
of data that hasn't been harnessed by artificial intelligence. And
you have to look at the healthcare sector as being
just prime for using all that information around patient data,
around hospital management, around the development of new drugs, around
protein research. There's just so much data that frankly has
(07:15):
been under utilized, and if you can apply artificial intelligence
to it, you can get more efficient, you can reduce
the cost of drug development, you can improve performance, improve
outcomes for patients, which really would make this sector very
attractive one from an artificial intelligence perspective.
Speaker 1 (07:29):
I go back to bai I go back to the
Innovation and Tech Active ETF. Here, most of the top
holdings are US companies. You have to get to number
fifteen to get a Japanese company, and then there's a
sprinkling of the Japanese coming in.
Speaker 4 (07:40):
Is it still US exceptionalism here?
Speaker 2 (07:43):
It is.
Speaker 6 (07:43):
It's a function of where we're seeing the best public
market opportunities and artificial intelligence. It is being led by
the United States. We have some of the lowest costs
of capital, we have some of the most innovative companies.
We have a vibrant startup community that's kind of fueling
IPOs in this space as well. It is a global
trend and we do have global exposure, but right now
the US is very much leading.
Speaker 1 (08:05):
And what about the investors who are piling in just
get us up to speed. It's what about two billion
that's been coming in of late into the from client assets.
Speaker 4 (08:13):
Where are they coming from?
Speaker 6 (08:14):
Yeah, so we've brought in two billion dollars over the
last nine months.
Speaker 2 (08:16):
Now.
Speaker 6 (08:16):
One of the major things that happened is black Rocks
target Allocation model ETF models has allocated to AI. Our
model portfolio managers like Michael Gates have looked at the
landscape and said, we want to reduce large cap tech
exposure and reduce some of our just tech sector exposure
and replace it with artificial intelligence because this is a
high conviction theme that we believe in over the long run,
and so they've been shifting their exposures to get more
(08:38):
pure play in the AI theme.
Speaker 2 (08:41):
Jay Humor May.
Speaker 3 (08:43):
Federal Reserve Chair Pow was posed many questions on the
impact of AI labor markets in the future of the economy.
Speaker 2 (08:50):
And FED policy.
Speaker 3 (08:52):
It was difficult for him to answer, But do you
think about it in those terms? You basically say, I
look at the economy of the United States and the world,
and I try and alculate how structurally things might change
going forward.
Speaker 6 (09:04):
Yeah, I think this is an important area to look
at where AI can augment work right, How can it
make us more efficient? Can we accelerate productivity? Especially in
the context of aging populations around the world. So if
you look at developed markets, in many cases, the growth
of a labor market is slowing, and so you really
almost need AI and that productivity growth to maintain strong
GDP growth across these developed economies. So I think in
(09:25):
many ways, AI is going to be an incredible tool
to boost productivity and frankly a tool that develop markets
need to lead it. This is why we're seeing AI
at the crux of geopolitics, because people policymakers see it
as such an accelerant towards our economy over the long run.
Speaker 3 (09:41):
Throughout the show in the day, actually we're going to
be talking about Patenteer and it makes me think about
not just software, but this kind of broader American effort
to reindustrialize the country in a number of sectors, defense,
artificial intelligence, data centers. Is there some kind of big
picture effect that you're trying to jump on to on
this reindustrialization the manufacturing of stuff here in America.
Speaker 6 (10:05):
Well, this is really at the intersection of several themes.
You know, We've looked at five mega forces around the
world that are kind of changing the long term trajectory
of economies, and one of them is aging populations, which
you've mentioned, one of them is artificial intelligence, and the
third one is really geopolitical fragmentation. All of these are
combining to bring in you know, certain themes like infrastructure.
How when we see that we want to build more
(10:26):
in the United States, we have to have better roads,
better highways, better waterways, better power to accelerate that. How
do we have the best technology in the world through
artificial intelligence and leaning into that segment. So really, yes,
all of these things are kind of colliding here to
really lead some of the best economic opportunities in the
United States.
Speaker 3 (10:47):
J Jacobs a black Rocket's great to have you back
on Bloomberg Tech.
Speaker 2 (10:50):
Thank you very much.
Speaker 3 (10:51):
Coming up, China gives approval for more M and A
among its tech giants. It's a big story we're watching
and that's next. This is Bloomberg Tech.
Speaker 4 (11:09):
This time now for Talking Tech.
Speaker 1 (11:11):
Have verst up a growing number of Chinese AI startups
where they are looking to list in Hong Kong. That
could include Rikonover Technologies. It's a firm specializing in visual
perception look. According to sources, the company, which is backed
by Intel Capital, green Und Holdings, is looking to raise
about one hundred million dollars from the listing that could
happen later this year. In more listing news, In fact,
(11:31):
digital payments provider Pine Labs has filed to go public
in India, and the company, whose shareholders include PayPal, will
seek to raise as much as twenty six billion rupees
that's around three hundred and.
Speaker 4 (11:40):
Three million dollars.
Speaker 1 (11:41):
Indian capital markets, of course, are seeing a resurgence in listings,
fueled in part by the government's push to digitize the economy.
Speaker 4 (11:48):
And the president and CEO of Tokyo.
Speaker 1 (11:51):
Electron well as shrugging off concerns about rising competition from China,
he spoke exclusively with Bloomberg's Cherryan in Tokyo.
Speaker 7 (11:58):
How got I think you possible to maintain the difference
in technology between China and our company. I'm sure that
Chinese vendors are trying to catch up with us, but
we must be faster. We can be faster than them
in technology innovation, and that's how we can maintain or
increase the difference. We are the spe manufacturer, but we
(12:19):
are not chip makers. So for us, it is key
to work with the world leading chip manufacturer to develop
the best in the world process and best in the
world equipment.
Speaker 1 (12:30):
You can watch the full interview on Bloomberg Tech Asia
catch a premiere as tomorrow at eight thirty pm Eastern
Time eight thirty am in Hong Kong.
Speaker 2 (12:38):
Ed stay in Asia.
Speaker 3 (12:40):
Jaomi says they've received more than two hundred thousand pre
orders for its first electric suv, the Yu seven, in
just three minutes.
Speaker 2 (12:48):
For more Bloombag.
Speaker 3 (12:49):
Peter Elstrom joins us and on the live feed during
the presentation, I noticed there were several million people tuned
in on x What do we know about this new
suv and the appetite here for Jaomi.
Speaker 8 (13:03):
Yeah, the excitement around show Me and its electric vehicles
is quite something. The founder late June, just did this
presentation in Beijing a little while ago, and he talked
about this new suv. It's going to be priced around
thirty five thousand dollars at the low end, it'll go
up to about forty six thousand dollars. And he took
aim directly at Tesla. Tesla's model why is the best
(13:23):
selling suv in China right now, And he's going directly
after them. He wants to be able to compete with
them on price and on features, and so far they've
been gaining a lot of ground. Now. Show Me, a course,
is best known for its smartphones. They began by competing
against Apple with their smartphones. They did a lot of
innovative things with that company. Late June kind of modeled
himself after Steve Jobs for a even with black turtlenecks.
(13:46):
But now they've been diversifying into a number of different areas,
including appliances, even luggage. When I visited them in Beijing,
they had all sorts of goods out there. But this
move into cars is really being something different. The stock
has taken off, the share are really soaring. They've tripled
over the past year, in fact, and I think you're
seeing this now reflected in the strong demand for their
(14:06):
new SUV.
Speaker 1 (14:08):
I mean extraordinary two hundred thousand and three minutes. You've
got to undred eighty nine thousand in one hour. Peter,
there was a worry about almost innovation happening too quickly
and a crash that happened with the S seven.
Speaker 4 (14:20):
Is that sort of being shrugged.
Speaker 8 (14:21):
Off right, Yeah, you're referring there was a there was
a crash in China with a Shami car where it
led to a fatality. They did put a they hit
the pause button on some of their sales at that
point to look at the technology within the car. But
now they're moving forward. They introduced this new vehicle. They
feel like they put them that behind them and now
they're you know, they're they're seeing strong customer demand for
(14:44):
these cars. As we're talking a little bit about before.
They look very much like Porsches. You know, you can
get effectively a porstial looking car. It's an EV for
thirty five thousand dollars. Chinese consumers like that offer.
Speaker 3 (14:56):
I find policy in China on tech companies so interesting.
It's either restrictive, right you think about the video games
industry in the.
Speaker 2 (15:02):
Last couple of years now allowing M and A.
Speaker 3 (15:05):
Are you able to summarize, Peter, what the Chinese government's
attitude is towards the tech sector overall.
Speaker 8 (15:12):
Oh, that's a big ass, but I'll do what I
can anyways. Yeah, I mean, certainly, what you saw in
the twenty teens, in particular, was growing domination by a
couple of the biggest technology companies there, especially Ali Baba
and Tencent. They put tons of money into startups. They
had scores, probably hundreds of companies that they invested in,
and they had these ecosystems that they kind of controlled,
(15:35):
and that really lasted during the boom years after Ali
Baba went public and showed that you can make a
lot of money on some of these Chinese tech stocks.
In particular, we had this big crackdown, the jackmar crackdown,
after he spoke out against regulators. The ant group IPO
was pulled, and after that, essentially all this m and
A stopped. There was no more consolidation. In fact, the
companies had to roll back a lot of the plants
(15:58):
that they had. Ali Baba sold off a bunch of
its assets too. And now what we're seeing partly because
the Chinese economy is a little baracky at this point,
they need more support from the private sector. They've given
more support to the tech companies in particular, they've seen
some new breakthroughs truth too, like deep seekin Ai. Huawei
has made a lot of progress in different areas too.
(16:18):
So now Alibab and Tensen are able to go back
to doing some M and A. They're beginning to do
a little bit, and it's nothing like the scale that
they did in the past, but they are able to
make some acquisitions.
Speaker 3 (16:29):
Bloomberg's Peter Elstrom answering the difficult question, thank you very much.
After receiving a tepid response for investors when it went
public back in March. Core We've stock has had a
meteoric rise around three hundred percent, has propelled the company's
(16:49):
CEO into the ranks for the world's richest with some
unusual speed. Bloomberg's Dillon Slow And joins us and has
the profile. This is like key tech wealth coverage, right,
a slow start on the ip but things change and
now a key figurehead has a pretty healthy net.
Speaker 9 (17:05):
Wealth exactly, Yes, just like you were saying, kind of
in some ways mirroring sort of the trajectory of the
IPO market more generally over the course of the year.
So when this company debuted in mid March, they were
initially seeking to raise at about a thirty five billion
dollar valuation, ended up completing the offering about a twenty
three billion dollar valuation.
Speaker 2 (17:22):
So well below that.
Speaker 9 (17:23):
Actually, the ceo mic and Trader came on Bloomberg Television
and told us that without a big order from Nvidia,
one of their largest investors, the deal might not even
have closed. So this stock traded pretty flat for about
two months after then, but it's off as again, as
you said, about three hundred percent in cent and that's
generated some really significant wealth gains, not just for the CEO,
but for other co founders and early investors too.
Speaker 1 (17:44):
I know he's now the three hundred and eleventh richest person.
He's ahead of Robert Craft I think of Magnetar and
some of the other key companies that backed them early.
What's interesting is he managed to go out there and
start to convince the market of the business model. Perhaps
got misunderstood or underrun appreciated when the IPO came out.
Speaker 9 (18:02):
Yeah, absolutely, And you know, the stock really started picking
up after the report of their first court earnings. They
beat estimates there and Nvidia also disclosed it they'd increase
the size of their stake, and it's really been all
up from there. It's gotten a lot of retail interest too,
so generated some sort of meme stocky comparisons from some commentators,
but for in traders specifically, his networth right now standing
at about ten point three billion dollars, and it's not
(18:23):
just the size of that, but it's the speed as well.
For the Bloomberg Billionaires Index, all of the billionaires we track,
the average time it takes for someone to go from
a five billion to a ten billion dollar net worth
is just about three years and four months and trader
did it in twelve trading days, so far faster than
the average person.
Speaker 1 (18:40):
Now do Circle founder Jeremy Lair. I'm sure you're on
that one too, Dylan Sloan, appreciate your time.
Speaker 4 (18:45):
Thank you. Now, let's talk about.
Speaker 1 (18:47):
A US district judge who has just ruled that Anthropics
use millions of books without payment to train its models,
and it's legal under copyright law, falling under the fair
use doctrine, a move that could actually kind of cripple
a rights holder's ability to monetize.
Speaker 4 (19:03):
On AI as KOed Bloomberg Opinions. Dave Lee's take here.
Speaker 1 (19:06):
It's a fascinating read, and you go into the intricacies
of how Anthropic first of all did it, And they
did it perhaps with a mixture of pirated book copies,
but then they actually started burning physical books, taking out
the spine and copying them into the computer.
Speaker 10 (19:21):
Yeah, so they went out and they acquired pirated copies
of more than seven million books to.
Speaker 2 (19:26):
Train into their models.
Speaker 10 (19:28):
After a short while, they thought, well, maybe there's a
better way to do this, and they bought the physical
used copies from distributors of used books and started chopping
off the spines. Cutting down the pages and ingesting those
into their research libraries.
Speaker 2 (19:41):
They called it, which was.
Speaker 10 (19:42):
Then used to train the large language model. And they
were sued by three authors whose books were in both
the pirated copies but also the physical copies as well,
and they said, look, the fact that you're doing this
to create a model and we get no compensation for
that shouldn't be considered fair use, which is this sort
of carve out and copyright law that says, if what
(20:05):
you do is sufficiently transformative and doesn't harm the commercial
prospects of the original work, then you'll find to use
it in some degree. And the judge in this case,
and it's one of the number of AI cases like
this currently active, the judge in this case said, yes,
he writes, this is fair use in this.
Speaker 4 (20:22):
It not the pirated one, not the pirated one.
Speaker 10 (20:25):
Yes.
Speaker 3 (20:26):
I think the main response at the time was that
an appeal is likely, but you're really interesting what you said.
It's not the only thing happening in isolation. People were
trying to get the read through to others like Meta
for example, and kind of work out what happens next,
because on the face of it, it's good for generative
AI but the companies are going to struggle to navigate this.
Speaker 10 (20:46):
Yes, I mean, look, it really hinges on. If it
is fair use, then companies are free to ingest all
this information without paying anybody and do what they want
with it. And of course the AI industry is incredibly
clean on that many you know, respective commentations and copyright law.
I think that is the case as well. The danger
is is that AI is unlike anything we've seen before
(21:08):
in terms of you know, finding knowledge and reading new information.
And what if and this is the sort of doomsday
scenario from publishers. What if people stop buying books because
they can just get the information they need from AI.
Speaker 2 (21:22):
And also, you.
Speaker 10 (21:22):
Know, where is the incentive of people to write new
books if when they do write it, they just get
sucked up into the machine and they don't see any
sort of commercial benefit that is able to write stay
in the practice of doing the hard work of writing
a book.
Speaker 3 (21:36):
Daily of Bloomberg Opinion another great column.
Speaker 2 (21:38):
Thank you very much.
Speaker 3 (21:46):
Welcome back to Bloomberg Texts and Breaking News. I've just
reported with Bloomberg's Dana Hole that Omeed Afshar, who is
a key lieutenant and has been a key lieutenant of
Elon Musket Tesla has left the company in recent days.
This is somebody that was in charge of manufacturing in
sales for North America and Europe, and what sources are
(22:07):
telling us is that he has left. He's also no
longer in the directory at Tesla. There's a lot that
we don't know, Caro. I've emailed Elon Musk to ask
him what's going on and why Omeed left the company.
You'll remember we've done some reporting on him in the
past and asked about some reporting that he's been involved
in about internal audits, internal reviews. But it's one of
(22:30):
many recent departures from Tesla's and the market was playing
attention with a move lower and.
Speaker 4 (22:34):
Look, Asha had a tough job, right.
Speaker 1 (22:36):
It was last year he was promoted into the office
of the CEO and he was overseeing some really significant
areas of sales and manufacturing in some pain point areas
for Tesla, largely because perhaps a political backlash to.
Speaker 4 (22:47):
One Elon Musk.
Speaker 3 (22:48):
Right, he'd been in the office of the CEO for
quite a while. He was kind of like Elon Musk's
chief of staff, so to speak. But then he got
more responsibility and he was very key on Austin getting
Austin set up. You know, I'm interested to know what happened,
but it's one of several departures in recent months of
people that are kind of long standing in health senior roles.
(23:10):
In a period of time where Elon was elsewhere.
Speaker 1 (23:12):
He's elsewhere politically, and also the sales focus has gone elsewhere.
When I'm thinking about today's extraordinary numbers around Shaomi's latest
suv going straight for the Tesla buyer, this is really
a difficult moment for Elon.
Speaker 4 (23:27):
No wonder He's come back as CEO.
Speaker 3 (23:30):
Right, so you know, like the big picture is that
Tesla in the future is focused on Robotaxi and they
had a successful launch of a small reduced service in
Austin and Optimist. But the reality is that Ben but
Butter is still selling cars and in the first six
months of this year, lots of data in all markets
that Must's association with the.
Speaker 2 (23:46):
Administration was hurting sales.
Speaker 3 (23:47):
But also like competition with hybrids, increased competition from other
model providers and other name brands in Europe for example.
But in Omeid Avshah's case, and again to recap sources
of telling us. He's left the company with someone so
close to Elon Musk with a lot of responsibility. It's
one in a chain of high profile executives. For example,
Milan Kovac, who is leading the Optimist program, also left
(24:10):
that We reported listening. When we get more, we'll keep
an eye on it. I'm also looking at Palenteer. This
is a stock that since October is up three hundred
percent year to date, up ninety percent. One of the
best performers there is its performance as a company in
cordly earnings. But this kind of macro and geopolitical environment
that we're in right now, Caro, that speaks to the
(24:31):
core of this story. And right now, this emphasis on
defense technology, that's what we're hearing about on a weekly
basis right It.
Speaker 1 (24:38):
Is because of the geopolitics that we currently confront escalating
US China rivalry, to conflicts in Europe and the Middle East,
geopolitical pressure. Said, they are driving a new way of
defense innovation. Let's talk about what that means to the
markets for your tech investments. Ted Mortensen is with US
Imagine director at BED. You yourself have a rich history
in defense from an active of his perspective, Ted, but
(25:01):
I'm interested is to therefore, what the active innovation play is.
Speaker 4 (25:05):
How do you invest into this moment.
Speaker 11 (25:08):
It's kind of fragmented right now, but Pallenteer is obviously
the purest play. And if if you look at the
latest conflicts on you know, coming out of Israel and
Iran and also Ukraine and Russia, these advanced technologies that
are being used are giving both Israel and Ukraine heads
up as it relates to their adversaries. Its number one,
(25:32):
number two. Just recently with NATO increasing their budgets up
to five percent GDP, the defense spend as well as
the US with a big beautiful bill is straight up.
So you're going to see this pivot to JENNAI being
embedded in all weapons systems. And you know, right now,
(25:52):
JENNYI is a national security discussion. If you look at Pallenteer,
they're the first mover, and I think there's a few
issues on the reason why it's up. They signed Israel,
they signed the Ukraine, they signed NATO post DOGE. Also
their solution to all the federal agency problems also in
(26:14):
DoD spanding. So they're one of the purest production ready
jen AI solutions where they can aggregate. I wish I
had it when I flew all this unbelievable Intel data
on a translation layer that you can see at real time.
Speaker 1 (26:31):
But like the mag seven in many ways, it's a
very concentrated defense tech play. I mean, we're at a
record high for palent here. It's been an extraordinary up
into the right move for the stock. Where else if
you're looking for diversification, can you go?
Speaker 2 (26:46):
You can go.
Speaker 11 (26:47):
Recently, we just had a report on aero environment AVAV.
They just bought a real stunning private company called Blue Halo,
which it gets aero environment way from their switchblade devices
on the drone side. But what blue Halo gives them
is an entry into cybersecurity, satellite and high energy weapons.
(27:12):
That's that's another play. Unfortunately from the private perspective. I
know ed you've talked about angel In in other shows.
Andrew is a private company that is almost a case
study and how the US military is re architecting their
defense budgets. These are high R o I C devices
(27:34):
that really go against you know, the traditional spend of
billion dollar programs that are under budget. They're very effective
and they're really changing the rules of the game.
Speaker 3 (27:44):
Ted, what you just said traditional spend. When I look
at companies like Palanteer and how they behave, they do
behave like traditional primes, big contract manufacturers to the government
because they basically say, I serve the US and its
allies only.
Speaker 2 (28:01):
How does that help them? It helps them.
Speaker 11 (28:04):
I think if you look at the traditional primes like
Lockheat or Raytheon, for example, they're known for hardware, They're
not known for gen AI software. This is why pallunteers
being brought in as kind of a pseudo prime in
almost all these new next generation defense contracts. They are
the software layer. The other aspect of this. When you
(28:28):
look at the spend, you look at what drone technology
and I think in the future, when you really look
at this on andrel I would not be surprised if
you have self drones flying on each wing of an
F thirty five.
Speaker 12 (28:44):
That changes the rules of the game.
Speaker 11 (28:46):
And when we talk about boots on the ground, I
mean you talked about Tesla early with Optimus. I think
you're going to see machines on the ground in the
next five to ten years. And that's a paradigm shift
from the defense budget standpoint.
Speaker 3 (29:00):
Right Ted Mortenson of Bad Great conversation, Thank you very much.
I want to stick with defense tech. Amid the conflicting
assessments from Washington about the effectiveness of the US strikes
on Iran. Let's stick into the supply chain resilience of
the US government aimed to modernize US commercial and government
data with its ARC software streaming defense acquisitions for customers,
(29:23):
includes the US Army, Navy. Let's get to Tara Murphy
Dherty Gavini CEO. There's anywhere we could take this right,
but let's just start with the basics. The US government
and its military industrial complex or the defense industrial base.
How modern is it in the scheme of everything Ted
and we just discussed on the show.
Speaker 13 (29:46):
It's getting more modern, I would say, the reality is
that today the defense industrial base is still quite traditional.
Speaker 12 (29:55):
And you can look at the recent strikes on Iran
as a perfect.
Speaker 13 (29:59):
Example of Yes, we know that fifth generation fighters escorted
B two bombers to Iran to drop the bombs. Maybe
those were F thirty five's, but there were likely some
F twenty twos in there as well.
Speaker 12 (30:12):
Those F twenty two jets and the.
Speaker 13 (30:14):
B two bombers were operationally deployed first in nineteen ninety seven,
So a lot of American military capabilities actually.
Speaker 12 (30:21):
Quite old, quite old.
Speaker 1 (30:23):
And I'm looking at what the DoD nine hundred and
sixty one billion dollar budget for the fiscal year starting
in October the first actually looks like I mean, I'm
sure you've read through the seventy five page procurement request
at the moment, but almost five billions cann be spent
on B twenty one self bomber production. There's going to
be thirty seven THOUD missiles, There's going to be twenty
four Air Force F thirty fives TARA. When you go
(30:43):
through that seventy five report page report, is there enough
of the new tech that we're talking about the supply
chain that you'll.
Speaker 13 (30:49):
Analyze, there's definitely still not enough. This is one of
the major imperatives for US national security right now is
the need for modernizing these weapons, systems and platforms, these
major capabilities. And this is what so much of the
defense tech industry, the companies that you are just referring to, Gavini,
Palanteer Andral have been clamoring for in Washington, DC, which
(31:14):
is the Department is spending huge amounts of money trying
to sustain these legacy platforms. More than seventy percent of
the entire cost of a jet, for example, or a
submarine is spent during its sustainan phase. The United States
needs modern capabilities not just to effectively fight war, but
(31:36):
in order to be able to afford the wars.
Speaker 12 (31:39):
That we need to deter and win.
Speaker 1 (31:42):
You just said you are going to the administration, You're
going into government and lobbying saying this needs to change.
Speaker 4 (31:48):
Just talk to us with the data with which you
were able to provide.
Speaker 1 (31:50):
I'm sort of fascinated with what ARC is doing Gavini's Defense.
Speaker 4 (31:54):
Acquisition software platform. What does it tell you? What does
it show?
Speaker 12 (31:59):
It shows quite a bit.
Speaker 13 (32:00):
So defense acquisition software is really designed to replace the
incredibly manual processes that the Department uses today to manage
the life cycle of these weapons systems. In platform, so
cradle to grave, how you design these systems through their
sustain and their modernization, managing parts and managing suppliers Today,
(32:22):
Somewhat unbelievably, the United States DoD does that.
Speaker 12 (32:26):
Primarily in spreadsheets.
Speaker 13 (32:28):
A lot of people are involved in what are very
slow processes, and software, and especially AI driven software like
arc is, can really accelerate those processes. The other really
important piece of ARC is the integrated data set that
exists in the software and this is Gavini's proprietary data
(32:48):
set which gives DoD visibility into these global supply chains
down to the part level, down to run materials and microelectronics.
And this is essential in order to come up with
the modern kinds of systems that we need and make
them rest and available for the warfighter really quick.
Speaker 2 (33:08):
We just have thirty seconds.
Speaker 3 (33:09):
On the other side of the table, is this government
and this Pentagon better on the procurement side.
Speaker 12 (33:16):
It's trying to be.
Speaker 2 (33:17):
So.
Speaker 13 (33:17):
We've seen executive orders on defense acquisition. We've seen calls
to enforce the Federal Acquisition Streamlining Act, which mandates that
government agencies by commercial first, especially software, instead of taking
on failed IT development projects.
Speaker 12 (33:33):
What we need to see now.
Speaker 13 (33:34):
Is will those policy decisions, will those will that guidance
be implemented. If implementation can happen, we will see tremendously
positive results.
Speaker 1 (33:45):
Tarfage Docs, we thank you of Gavini fascinating on all
things defense procurement. Meanwhile, coming up, we're going to talk
to the CEO behind an AI hacking tool. His lead
investor is going to join us too about the proactive
defense against sliver attacks.
Speaker 4 (33:59):
This is what we've got.
Speaker 1 (34:12):
A one year old startup has developed an aitol that
is better at identifying many software vulnerabilities than experienced hackers.
The startup, called Expo, has recently closed a seventy five
million dollar funding round led by Ultimeter Capital. Exposed founder
and CEO or her De Moor is with US. Ultimate
partner Appaul of Agowell.
Speaker 4 (34:31):
Is also with us as well. Or Her I start
with you.
Speaker 1 (34:34):
Why is it so important that you the AI version
of a hacker is at the top of Hackerwe's US leaderboard.
Speaker 14 (34:42):
Thank you very much for having us so it's the
first time ever that a machine and not a human
is at the top of the Hackerwom leaderboard for the US.
Hackerwom is a platform that connects Hackhouse with companies who
want their systems to be tested, and they maintained the
leaderboards ranking the hackers according to whose bugs have been
(35:09):
accepted by the customers of Hakawan, and currently the top
in the US is our AI.
Speaker 1 (35:17):
What's so interesting is that you are like the AI
guy among many, but really you're driving the portfolio allocations
for AI over at Altimeter, I'm thinking some of the
open AI investments that you made, some of the others.
I mean, we see such pedigree coming from a man
who helped.
Speaker 4 (35:34):
Develop GitHub copilot.
Speaker 1 (35:35):
Is that what attracted you to Expo or is it
the fact of what it can achieve?
Speaker 15 (35:39):
You know, before we even met, we've been studying the
space and very simply, cyber attacks are on the rise.
Software is more vulnerable, a lot more engineers, a lot
more code developed with AI. And by the way, these
models are trained on open source software, which is more vulnerable.
Speaker 2 (35:55):
That's on one side.
Speaker 15 (35:57):
And then I met oohe which our first meeting felt
like the fifth meeting because of his ambition to build
the cybersecurity platform. In the age of AI, CIOs want less,
not more. They're fatigued in alert tonight right now, and
you know who has vision to build Expo, help you
find vulnerabilities, fix them automatically, and ultimately building the cybersecurity
(36:19):
platform is a big one. It's probably the most important
business being built right now, not because it'll be a
great opportunity, but because it must be built. If we
don't build it, the bad guys have the technology and
we've got to put it in the hands of the
good guys in the free world.
Speaker 2 (36:33):
Oh thank you for joining us on the show.
Speaker 3 (36:35):
I've been trying to think about what this represents, right,
the swarm is always on. It represents what an army,
if humans could do twenty four to seven to identify
the vulnerability. But the question is what happens next for
your company? And I'm assuming that you're trying to engineer
towards the swarm, also reacting, putting into place fixes when
(36:57):
those vulnerabilities are identified.
Speaker 14 (37:00):
That's right. So even today, the AI is already identifying
vulnerabilities at some of the top company companies in the
country are companies like palle Alter Networks, are at and T, Disney, Sony,
and the list goes on and on. Now, of course
(37:22):
it finds these vulnerabilities, but they need to be fixed
as well. We're very lucky that all these companies that
we've been working with have been extremely pretty active immediately
fixing the problems as they were pointed out. It's a
natural evolution, but eventually an AI will be able to
do some of the fixes as well.
Speaker 3 (37:43):
Paul, I know you as an operator, you know you're
pretty handy with software. What are you going to do
to help this company grow and scale as a commercial entity.
What do they need to focus on to convince the
marketplace that an AI swarm is a better then a
human team of hackers.
Speaker 15 (38:05):
And we are fighting against time. Time is our biggest competition. Really,
if you had three weeks ahead of the bad guys,
you're saving.
Speaker 2 (38:16):
Three weeks worth of vulnerabilities.
Speaker 15 (38:18):
And cyber tends to be a game of cat and mouse.
Sometimes you've got the offensive teams ahead and other times
you've got the defensive teams ahead. And so the number
one thing we're focused on is speed. That's why we're
here today. That's why we're educating the world about what
we're doing. We work with a lot of companies, as
we have mentioned, helping them secure their perimeter before the
bad guys get in.
Speaker 1 (38:41):
What's so interesting is, of course, when Ed calls you
an operator, you came from Palenteer, you're leading the charge.
When you're looking at the AI investment opportunities, when we
think about open AI investment, when we also think about
clean When you think about this moment, because you're also
exposed to ANDREILSPACEX, is this the moment for defense tech,
whether it comes in a cyber capacity, it comes in
a hard tech capacity.
Speaker 15 (39:02):
Look, I think at the highest abstraction, AI is having
great impact across fields. This is defense, cybersecurity, customer service,
software engineering. These are large industries that are going through
reinvention and ultimately it's raising the ceiling for performance of
the best professionals in cybersecurity, like what we are doing
(39:22):
at EXPOU, and raising the floor for all the mundane tasks.
In the case of EXPOU, for example, you've got to
do reconnaissance, you've got to do scanning and.
Speaker 2 (39:31):
Exploitation and report building.
Speaker 15 (39:32):
These a part of that is just mundane work, but
also the best hackers in the world now better off
with XPOW in your toolkit rather than without.
Speaker 3 (39:42):
Right, Oh, you are going from this point rate limited
by compute and tokens. Just explain the pathway for your
company and the bottlenecks that you might face.
Speaker 14 (39:54):
So currently it's we can we have no problems with
the amount of compute. It's actually not that intensive. We
can easily serve the customers that we're currently working with.
We are, however, very much focused on working with the
(40:17):
top companies that have the biggest our need for better security,
financial services, healthcare, those types of those types of industries.
Speaker 3 (40:30):
All right, that was that Paul vagaryle partner at Ultimated Capital,
and I'll hear the more.
Speaker 2 (40:34):
CEO and founder of X thank you both very much.
Speaker 3 (40:38):
Salesforce is developing an AI product that can handle tasks
like customer service without human supervision. CEO Mark Benioff says
the tour has reached ninety three percent accuracy. He spoke
with Bloomberg's Emily Chang. Take a listen.
Speaker 16 (40:53):
You founded the company now twenty five years ago, so
you've seen the rise of mobile and social and the
cloud and now AI. How has the CEO job changed
for you?
Speaker 17 (41:02):
Well, the CEO chop is really changing fast, you know,
because it used to be I felt very alone at
the top, But now, like I just finished writing the
business plan for this year, and I always do that
with someone else, like I take one of our executives.
And for the last three years, I've also have found
a new partner in AI. So I have an AI partner,
(41:25):
I have a human partner, and it's the three of
us who are writing the plan together. So it's a
little less lonely at the top of AI.
Speaker 16 (41:31):
You said you won't hire any more coders at Salesforce,
and you've said today's CEOs will be the last to
manage all human workforces.
Speaker 4 (41:41):
What does this mean for businesses?
Speaker 17 (41:43):
Digital labor is going to be everything from AI agents
to robots, and I do think you know to your point,
you know, CEOs have to make sure their values are
in the right place and that values bring value.
Speaker 12 (41:53):
Could an agent replace you one day?
Speaker 17 (41:55):
I hope so, you hope?
Speaker 12 (41:57):
So?
Speaker 17 (41:57):
I mean, of course I'm partially kidding. You know that
we're becoming more automated.
Speaker 1 (42:02):
You can see Emily Chang's full conversation with Salesforce CEO
Mark Benioff. It's on the circuit Errington Knight in eight
pm Easton. Now that does it for this edition of
Bloomberg Tech. What a whirlwind from your breaking scoop at Tesla.
Speaker 3 (42:15):
Just remind us a couple of days of testimony, and
now we have breaking news from Tesla that Omi dash
Shah has basically been fired by Elon Musk. Recap that
story and all the others on the podcast. You know
where to find it, the Bloomberg Tech Pod on the Terminal,
as well as online on Apple, Spotify and on iHeart
from New York City and San Francisco.
Speaker 2 (42:34):
This is Bloomberg Tech
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