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