Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. Bloomberg Tech is live
Speaker 1: from the heart of Silicon Valley with Ed Ludlow in
Speaker 1: Van Francisco.
Speaker 2: This is Bloomberg Tech coming up.
Speaker 3: Ali Barber releases its latest Quenn model, its biggest ever,
Speaker 3: claiming performance on par with Anthropic Plus. Amazon surpassed three
Speaker 3: trillion dollars in market value for the first time, extending
Speaker 3: gains after a big cloud and AI driven earnings report
Speaker 3: last week. AWS CEO mcgarman joins us later in the
Speaker 3: hour and how Apple's reinventing itself as a subscription giant.
Speaker 3: Will dive into the details of the iPhone maker's Apple
Speaker 3: Upgrade program and its next era of growth. There's an
Speaker 3: elite club that's getting bigger. Today's big number three trillion dollars.
Speaker 3: Amazon has reached a three trillion dollar market value for
Speaker 3: the first time, becoming just the fifth company ever to
Speaker 3: hit that milestone. The stock training at all time highs
Speaker 3: following its quarterly earnings last Thursday night from Friday into
Speaker 3: this Monday session. This is the biggest two day gain
Speaker 3: on the stock since two thousand and nine, and the
Speaker 3: momentum has really carried through Later in the hour, we're
Speaker 3: going to speak to aw Seo mac Garman, and it
Speaker 3: really was AWS that was the big driver in earnings.
Speaker 3: The AI story, there's a lot to discuss. China's AI
Speaker 3: race accelerates. Ali Barber has unveiled Quen three point eight Max,
Speaker 3: its new flagship AI model, saying it can rival and
Speaker 3: thropics best. It's the latest in a wave of Chinese
Speaker 3: AI breakthroughs, challenging Silicon Valley's lead Bloomberg's equities reporter Henry
Speaker 3: Wren joins us for more. Let's go over the basics,
Speaker 3: Ali Barber sharing details of the model. The model clearly
Speaker 3: on benchmarks, it says is high performance, and the ADRs
Speaker 3: have reacted quite positively here.
Speaker 1: Yeah.
Speaker 4: Indeed, we're seeing Alibaba's ADRs training up about five percent
Speaker 4: in US trading at this point. So the company said
Speaker 4: that it's a new MAX three point eight models rivals
Speaker 4: the US models, the Frontier Labs models at some benchmarks,
Speaker 4: so for example on research reproduction, on agentic use of computers,
Speaker 4: these are strong suits. It also says that its model
Speaker 4: has two point four trillion terms of parameters, and that's
Speaker 4: basically on power with the level that we've been seeing
Speaker 4: for the Keemi K three model, which was out a
Speaker 4: few weeks ago. Also, the company, yes also said something
Speaker 4: about cost. Obviously per token costs, it's a bit lower
Speaker 4: than the US frontier models as.
Speaker 3: Well, two dollars per one million tokens. On the input side,
Speaker 3: you have a really strong command of Chinese technology companies
Speaker 3: from the stock perspective, Right, is Ali barbera name Henry
Speaker 3: that trades on its AI prowess or like some of
Speaker 3: these America can multifaceted companies a different part of its business.
Speaker 4: Yeah, it's the AI story is really important for Ali Baba.
Speaker 4: If we zoom out a bit today, it gains about
Speaker 4: five percent. But if you really look at the trajectory
Speaker 4: since June, you will see that the stock is up
Speaker 4: about thirty five to forty percent from a June low.
Speaker 4: And the key story here is about the more optimism
Speaker 4: in AI. Obviously we're seeing the Quen breakthrough today, but
Speaker 4: really last month the company has a closed store meeting
Speaker 4: with analysts, and analysts came out more optimistic about the
Speaker 4: company's cloud revenue growth. For example, JP Morgan is modeling
Speaker 4: about forty five percent in revenue growth for its cloud
Speaker 4: unit for the June quarter, so there has been an
Speaker 4: acceleration over there, but still on the main business, on
Speaker 4: the e commerce business, because it has been a company
Speaker 4: known for its main shopping site in China, that part
Speaker 4: of business is still lagging, although it's still the cash
Speaker 4: cloud cloud, so to speak. So investors' opinions are still mixed.
Speaker 4: That's why we were seeing sentiment has been pretty weak
Speaker 4: into June, but since drewing some positive AI announcements has
Speaker 4: really been boosting the stock.
Speaker 2: Bloomberg's Henry Wren, thank you very much.
Speaker 3: Ali Barber says its new Queen model delivers frontier AI
Speaker 3: performance and as Henry outlined, at a fraction of the cost,
Speaker 3: could cheaper AI accelerate adoption rather than just pressure pricing.
Speaker 3: Joining us now is Lauren Cassidy, chief investment officer of
Speaker 3: the Founders one hundred ETF, the ETF tracking founders in
Speaker 3: this space meta in Zuckerberg, Musk and SpaceX. The economics
Speaker 3: of AI is really what the Chinese story is putting
Speaker 3: front and center. So I pose that question to you
Speaker 3: drive adoption or lower the tokenomics here?
Speaker 5: Yes, I do.
Speaker 6: See this as a positive in that there's room in
Speaker 6: the world for both open and closed models, and I
Speaker 6: do think it will drive prices a little lower. It
Speaker 6: isn't cheaper than anthropics haiku, but if it is fable,
Speaker 6: fable level performance, and it's about a fit of the price,
Speaker 6: and so I think that you know, that could put
Speaker 6: pressure on the l elms. But overall there's still a
Speaker 6: lot that the American llms have to offer.
Speaker 3: What are the advantages that the US models have to
Speaker 3: your mind, Lauren.
Speaker 6: Trust, reliability, additional features, convenience of not having to modify
Speaker 6: the models. So it just depends what an enterprise is
Speaker 6: looking for, what.
Speaker 5: Fits the best.
Speaker 3: I'm looking at the found one ETF and again you
Speaker 3: feel free to remind us of the thesis on the
Speaker 3: founder side, But you don't have any of the the
Speaker 3: A d rs for some of these big Chinese tech companies.
Speaker 2: What are the reasons for that?
Speaker 6: And I think that we believe that in American innovation
Speaker 6: long term, and just as we've had waves of innovation
Speaker 6: and greater adoption in the country of the steam engine, electricity,
Speaker 6: modern manufacturing, computers, and the Internet, we are now on
Speaker 6: the sixth wave, which is AI. We think it's going
Speaker 6: to be a really big thing. We see tremendous adoption
Speaker 6: over the next decade, and we are very exposed to
Speaker 6: those stocks.
Speaker 2: Let's shift gears a little bit.
Speaker 3: SpaceX has its first quarterly earnings and call Tuesday evening.
Speaker 3: This is what I wrote published this morning. It's the
Speaker 3: first opportunity that SpaceX investors might have to put the
Speaker 3: question of a Tesla SpaceX merger to Elon Musk. Maybe
Speaker 3: you and I've discussed this before from the Tesla side
Speaker 3: of the table, but where does founder one hundred ETF
Speaker 3: stand on that idea?
Speaker 6: Yes, we believe that's inevitable over time. Elon Musk is
Speaker 6: an incredible founder, and he is building the only closed
Speaker 6: loop AI network, and over time there's going to be
Speaker 6: more and more opportunities for Tesla and SpaceX to share.
Speaker 6: They're going to be building Tarifab. I'm really hoping to
Speaker 6: hear details about that build out tomorrow. They'll be sharing chips.
Speaker 6: There's going to be a lot of opportunities for synergies
Speaker 6: between the businesses. It probably makes sense at some point
Speaker 6: to fold Tesla in to the greater mix as we
Speaker 6: work towards data centers in space.
Speaker 3: Lauren Cassidy, a founder one hundred ETF, back on the show,
Speaker 3: thank you very much. Indeed, another top story, one of
Speaker 3: the crypto industry's most trusted storage devices is at the
Speaker 3: center of a major hack. Coinkite, the Canadian company behind
Speaker 3: the cold card Hog hardware wallet, says a software floor
Speaker 3: made some bitcoin recovery keys predictable, allowing hackers to drain
Speaker 3: wallets that were supposed to be kept safely online. According
Speaker 3: to Galaxy Research, more than seventeen hundred bitcoin worth about
Speaker 3: one hundred and ten million dollars has been stolen from
Speaker 3: roughly five thousand different wallets. Coinkite says it has released
Speaker 3: a firmware update to fix the floor. Another stock that
Speaker 3: we're watching because of what happened over the weekend, shares
Speaker 3: of AMC, now modestly higher seven tens percent, had been
Speaker 3: much higher at the open, highest ever total weekend revenue,
Speaker 3: including records for admissions and food and beverage. By the way,
Speaker 3: why the driven driven by the opening of Spider Man
Speaker 3: brand New Day yet to see it, that film grossing
Speaker 3: three hundred and fifty five million dollars domestically in the US.
Speaker 3: Valor Atomics, the company building America's first gigas sites, secured
Speaker 3: a billion dollars in its Series B funding round, led
Speaker 3: by Sequoia. The company also closed a two hundred million
Speaker 3: dollar credit facility to build the words first vertically integrated
Speaker 3: industrial nuclear power company. Joining us now is Valo Atomic
Speaker 3: CEO and founder Isaiah Taylor. You're also fresh off what
Speaker 3: now seems with hindsight, a pretty key demo that was
Speaker 3: a bit of an unlock for this round. You want
Speaker 3: to move quickly, so let's start that. What do you
Speaker 3: need the funding for and how you're going to deploy it.
Speaker 7: Yeah, and thanks for having me on again. Just a
Speaker 7: month ago, I was on the show talking about how
Speaker 7: we became the first startup in history to make nuclear power.
Speaker 7: We did that by powering and Nvidia Blackwell Chip, which
Speaker 7: was an amazing event as the first time that an
Speaker 7: advanced nuclear reactor has powered AI infrastructure directly. So you're right,
Speaker 7: it's been an amazing couple of months. We made a
Speaker 7: lot of progress, and really what this is about is
Speaker 7: giving us the firepower that we need to go build
Speaker 7: the sites. We've now demonstrated nuclear power. This is the
Speaker 7: reactor standing behind me here, and we have to build
Speaker 7: a lot more of these in order to make pace
Speaker 7: with AI.
Speaker 8: AI is building very quickly.
Speaker 7: We need a lot of power in every direction and
Speaker 7: this is really about scale for us. So this is
Speaker 7: the firepower that we need to go and build.
Speaker 3: Sequoia led the round bit. Sean McGuire is also going
Speaker 3: to join your board. Why is that important to you?
Speaker 3: What is it that Sean can can give you other
Speaker 3: than just the check?
Speaker 7: You know, it's been amazing to spend some time with
Speaker 7: Sean over the last few months and get to know
Speaker 7: the rest of the Sakoia team and the partnership. I
Speaker 7: think Sean's a really, really thoughtful person. He spends a
Speaker 7: lot of time with SpaceX and understanding that business model,
Speaker 7: and I think one of the lessons to learn from
Speaker 7: SpaceX is really just the power of scale and pace
Speaker 7: of production, and that's something that we want to do
Speaker 7: in nuclear as well.
Speaker 8: So I think that his.
Speaker 7: Lessons that he's to learn there are going to be
Speaker 7: applied very well to this business, and I'm really excited
Speaker 7: to welcome them to the board.
Speaker 3: You know, the numbers here are really big, right, So
Speaker 3: it's a billion dollar round six billion dollar post money valuation,
Speaker 3: but with respect, you know, this is still early, this
Speaker 3: is nascent, it is high risk, it is technical how
Speaker 3: contingent was that demo that you did just on the
Speaker 3: show a month ago in literally making the round materialize.
Speaker 3: How much did investors want to see that this worked.
Speaker 7: You're right, this is super early, and you know, this
Speaker 7: is a very long journey for us. We see this
Speaker 7: as a multi trillion dollar opportunity. We're going to go
Speaker 7: and build the biggest energy company on Earth. So these
Speaker 7: are the very early days for sure. You know, we
Speaker 7: have a lot to prove still. We want to prove
Speaker 7: pace of production. We want to go from building one
Speaker 7: reactor in a year to six months, to once a month,
Speaker 7: and then even faster than that. So you're right, there's
Speaker 7: still a lot to prove. You know, I think that
Speaker 7: this demonstration was really important. We've said for a long
Speaker 7: time that valar Atomics is a hardware company. We're focused
Speaker 7: on hardware execution and on full vertical integration, and that's
Speaker 7: really what we proved here. We prove that we can
Speaker 7: take a patch of dirt, we can build a reactor
Speaker 7: on it, turn it on, and operate it. And that's
Speaker 7: just one small step, but it's the first of many
Speaker 7: to go and build the nuclear power company or the future.
Speaker 2: Isaiah.
Speaker 3: One of the things you and I have not yet
Speaker 3: discussed is who the customer ends up being. You know,
Speaker 3: you want to build the nuclear power company of the future.
Speaker 3: Who You've explained the scale of the tech you've powered
Speaker 3: one black Well chip, and I think that's important context
Speaker 3: of the audience. But who do you ultimately sell it to.
Speaker 7: It's a really good question. I think that nuclear and
Speaker 7: energy in general is a bit noisy right now. You
Speaker 7: see a lot of deals getting signed that maybe are binding,
Speaker 7: maybe are not.
Speaker 8: We've been really really.
Speaker 7: Focused and disciplined on this point that we believe this
Speaker 7: is a hardware execution problem. Everyone needs energy, they need
Speaker 7: it at any price, they can get it as fast
Speaker 7: as they can get it, and so really really focused
Speaker 7: on just executing.
Speaker 8: In the hardware and bringing new power online.
Speaker 7: And I think once we get that new power online,
Speaker 7: that'll open us up to a bunch of really interesting
Speaker 7: customers who have large balance sheets. We depend on energy
Speaker 7: in order to build what they see is the future
Speaker 7: as well. And so that's you know, there's a handful
Speaker 7: of customers there that are interested in what we're doing.
Speaker 7: But we're going to stay focused and we're going to
Speaker 7: stay focused on hard works.
Speaker 3: Isaiah I don't know how much you want to talk
Speaker 3: about finance. I don't know if you're the finance guy
Speaker 3: in truth at Valor. But an interesting credit facility Palm
Speaker 3: Lucky's Arabor and JP Morgan. You know it's two hundred
Speaker 3: million dollar facility. But why was that important? You really
Speaker 3: sort of put it high up in the announcement today.
Speaker 7: You know, it is important to us, you know, if
Speaker 7: the long term of this business right, we don't want
Speaker 7: to be relying entirely on equity, and we think that
Speaker 7: power is a uniquely debt financible.
Speaker 8: Thing, and so moving this company from.
Speaker 7: Something that's equity financed to debt finance is a long
Speaker 7: term goal of ours. And it's really great to be
Speaker 7: working with partners like Airbor who led this around, and
Speaker 7: JP Morgan Pressing Cove and the Hercules as well coming
Speaker 7: into it, and we're really starting to demonstrate to the
Speaker 7: market that this is a business that can take large
Speaker 7: amounts of credit, deploy it very well.
Speaker 8: Get the yield on that.
Speaker 7: And this is how we're going to run the business
Speaker 7: going forward, is that these reactors will be financed. They'll
Speaker 7: be financed by customers by different ways of putting these
Speaker 7: tranches together and that's really how we're going to go
Speaker 7: and build all of this CAPEX. So we're excited to
Speaker 7: start to demonstrate.
Speaker 3: This with airpor Isaiah, let's end the conversation of talking
Speaker 3: about America's attitude and progress on your industry? Is America
Speaker 3: moving fast enough so that you can do the things
Speaker 3: that you want to do on the timelines that you've
Speaker 3: set out.
Speaker 7: Look, it never feels like we're moving fast enough, right
Speaker 7: We want to move so much faster than we are today.
Speaker 7: China has about fourteen nuclear reactors under construction right now,
Speaker 7: and we're just starting to break ground on our next
Speaker 7: one here, So we need to move faster. If we
Speaker 7: want to win on AI, we have to go faster
Speaker 7: in all forms of power generation, but especially nuclear. I
Speaker 7: think nuclear is uniquely well suited to win the AI race.
Speaker 7: It's clean, it scales very well, you can build lots
Speaker 7: of it in one place next to a large data center.
Speaker 7: There's a lot of things that work really well for this.
Speaker 7: But frankly, we do need to move faster, and that's
Speaker 7: why we're so focused on the hardware.
Speaker 5: Secution.
Speaker 3: Valaatomics CEO and founder Isaiah Taylor back on the show,
Speaker 3: thank you very much. Indeed, let's get to the earning story.
Speaker 3: Stay with AI up next. Palenteer set to report its
Speaker 3: second quarter earnings today after the closing bell. Joining US
Speaker 3: Bloomberg's Lazett Chapman leads our coverage of Palenteer. You know,
Speaker 3: it's so interesting we go with these periods of times
Speaker 3: where we talk about plantic constantly, then maybe it got
Speaker 3: a little quiet. Ultimately, the company has a lot of momentum. Right,
Speaker 3: what are you embracing for?
Speaker 9: Right, It's a pressure cooker quarter.
Speaker 6: Right.
Speaker 9: They have a history of always beating or exceeding analyst
Speaker 9: revenue or analyst estimates for every quarter on.
Speaker 2: Revenue, et cetera.
Speaker 9: So this is already the expectation that they're going to
Speaker 9: beat or exceed, and so even if they raise their guidance,
Speaker 9: it's kind of like, so what you do this every quarter?
Speaker 9: And so the big thing that people are going to
Speaker 9: be watching right now is the concentration of sales, whether
Speaker 9: it's in the US, whether it's international. This quarter they
Speaker 9: are expecting really blockbuster growth for US commercial sales. This
Speaker 9: has been its strongest area of growth, and next quarter
Speaker 9: for the first time ever in its history, Analysts expect
Speaker 9: them to exceed, have commercial growth exceed government growth. So
Speaker 9: what they're going to be looking for this quarter is
Speaker 9: has it continue that trajectory and how are they doing internationally,
Speaker 9: which is something that we've talked about and we've had
Speaker 9: Mark on and some other people on. So that's something
Speaker 9: that they're going to be looking at.
Speaker 3: It's a really big point because you know, in the
Speaker 3: news headlines, Palente comes up in the context of its
Speaker 3: work with the Pentagon or with different arms of the
Speaker 3: US government in a defense context, but they also have
Speaker 3: a lot of commercial case studies. So that's the moment
Speaker 3: in time it flips to commercial. But give us the basics,
Speaker 3: like what Palenti's business does, right, we always have to
Speaker 3: remind us us all what is palent is?
Speaker 9: Yeah, it is AI software that allows people to make
Speaker 9: the best use of the information that they have to
Speaker 9: gather data from all across different you know, sources that
Speaker 9: they have to integrate it, make sense of it, map it,
Speaker 9: and then throw an LLM up against it, whether it
Speaker 9: is you know from you know, from whichever company, whether
Speaker 9: they're agnostic exactly exactly. And so they've worked a lot
Speaker 9: on showing different partnerships that they have with some of
Speaker 9: the major players. That's something that they're going to talk
Speaker 9: about today, I'm sure, along with partnerships with NVIDIAs some
Speaker 9: of the rest. They have gotten a lot of attention
Speaker 9: for their work with defense, but it's actually the commercial
Speaker 9: which is their fastest growing and so we'll see how
Speaker 9: they do.
Speaker 3: Alex carp the CEO, is vocal. Let's say, he also
Speaker 3: talks about the markets sometimes, but is there a clear
Speaker 3: Palentist stock story of this year of the last year,
Speaker 3: like how has the market reacted to them?
Speaker 8: Right?
Speaker 9: The market had massive expectations at the end of last year.
Speaker 10: The stock was up.
Speaker 9: It was almost up to two hundred or so, and
Speaker 9: since then it's plummeted from that high. It was trading
Speaker 9: at something like two hundred and four twenty seven x earnings.
Speaker 9: Then now it's down to about sixty seven x earnings,
Speaker 9: which is down from its five year average of ninety
Speaker 9: eight x earnings. But it's still one of the most
Speaker 9: expensive stocks on the S and P. So a lot
Speaker 9: of a lot of investors are wondering where that disconnect
Speaker 9: is and whether it's really worth what it said it
Speaker 9: was going to be able to deliver.
Speaker 3: This seems like a big one, a big one for
Speaker 3: Market's Bloomberg's the set Chapman who covers Panenter but also
Speaker 3: defense tech bench Capital. Thank you very much. Indeed, now
Speaker 3: coming up, Apple's changing the way if you buyas devices,
Speaker 3: why monthly payments could become the new normal?
Speaker 2: Power On. This is Bloomberg Tech.
Speaker 3: Preak check on Amazon shares at all time highs. They've
Speaker 3: joined the three trillion dollar market cap club and this
Speaker 3: is the biggest two day game they've posted since two
Speaker 3: thousand and nine. After earnings later in the hour, we're
Speaker 3: going to speak to AWSCO, maccarm and AWS, Amazon's key
Speaker 3: cloud computing unit. Apple is making a big bet that
Speaker 3: customers would rather pay by the month than all at once.
Speaker 3: It's the new Apple Upgrade program, designed to make your
Speaker 3: upgrading your device film more like a subscription. Bloomas Mark
Speaker 3: German here with the latest power on from this weekend.
Speaker 3: It's been really interesting to see the rollout of this.
Speaker 3: What are you trying to capture in this this power on? Like,
Speaker 3: what where do you think this is headed?
Speaker 11: Yeah, the fact of the matter is is that you're
Speaker 11: going to see a change over time from sticker prices
Speaker 11: to subscription prices. The carriers have been trying this for years.
Speaker 11: It's been extremely successful for the carriers in the US. Internationally, obviously,
Speaker 11: Apple has gotten on a really good schedule with its
Speaker 11: new new products, obviously new iPhones and Apple watches every September.
Speaker 11: The iPad cadence has really become fall in Spring the Mac.
Speaker 11: You know, depending on which Mac you get, you're thinking
Speaker 11: fall or spring as well well. And so there are
Speaker 11: upgrade cycles for consumers. Right, maybe I'm going to get
Speaker 11: a new phone every three years, maybe I'm going to
Speaker 11: get a new computer every five years. But making it
Speaker 11: a subscription is going to get people into getting a
Speaker 11: new phone more frequently.
Speaker 10: They could give those phones then back to Apple.
Speaker 11: Apple could resell them on secondary markets. They can reuse
Speaker 11: the parts for new devices, right, which creates a big
Speaker 11: cost savings and improve margins for them there too as
Speaker 11: well as that secondary phone business. And then the consumer
Speaker 11: is paying on a recurring schedule, so the payments to
Speaker 11: Apple never stop and over the long term you're going
Speaker 11: to see Apple creating far more revenue in profit because
Speaker 11: of this program. In fact, Wall Street has been begging
Speaker 11: Apple to do this for over half a decade. And
Speaker 11: so it's a long time coming.
Speaker 3: So this weekend I did my first Apple up grade.
Speaker 3: I took my twenty twenty Macair with an M one chip,
Speaker 3: and I took the latest Macare thirteen inches with an
Speaker 3: M five chip, and I did the math and it's
Speaker 3: a great deal. Basically I can trade in still and
Speaker 3: still do the Klana Apple up grade. The thing that
Speaker 3: jumped out is I got to wait three weeks for
Speaker 3: that Macare. That's still an issue.
Speaker 11: Yes, So as we wrote in power On as well
Speaker 11: this weekend, you know, the Max Studio and the Macmini,
Speaker 11: those are no longer the only Max with extreme supply shortages.
Speaker 11: Now it's the most popular Mac which is of course
Speaker 11: the MacBook Air, and new orders of the macbookare are
Speaker 11: not arriving at.
Speaker 10: This point until early September.
Speaker 11: So you're seeing the supply chain shortage shift from niche
Speaker 11: computers to the company's most popular computer.
Speaker 10: So that's not necessarily great.
Speaker 11: And so what they're doing now in terms of their
Speaker 11: marketing online and in stores, they're pushing people towards the
Speaker 11: base level M five MacBook Pro, the fourteen inch, which
Speaker 11: they have a lot of supply of still, and they
Speaker 11: want to sort of dwindle that down because they're launching
Speaker 11: the new M six version in just a couple months
Speaker 11: from now.
Speaker 2: Mark just very quickly.
Speaker 3: We have a story on the terminal about how Apple's
Speaker 3: SerII stacks up against the new Chatch GPT.
Speaker 2: What do we need to know?
Speaker 11: Apple has a huge advantage by having SERIAI built into
Speaker 11: every iPhone now that can run iOS twenty seven and
Speaker 11: the latest large language models. It's competent, right. The promise
Speaker 11: of Siri has been there for fifteen years. It's never
Speaker 11: really worked. Now it works. It's nowhere near as good
Speaker 11: or as capable as Chad GPT, but the floor has
Speaker 11: improved tremendously.
Speaker 2: Bloombergs smart German with the latest power on. Thank you
Speaker 2: very much.
Speaker 3: Amazon has blown past three trillion dollars in market value
Speaker 3: after its cloud unit AWS drove big earnings performance last week.
Speaker 3: The company says it's AI business is hit a revenue
Speaker 3: run rate of twenty five billion dollars, and it's chip
Speaker 3: business not the same milestone. Amazon also raised its capex
Speaker 3: plans for this year to two hundred and twenty billion
Speaker 3: dollars as it joins the chorus of tech companies backing
Speaker 3: American Open Models AWS CEO Matt Garman joins US now
Speaker 3: on Bloomberg Television and Bloomberg Radio. Matt, it's great to
Speaker 3: have you back on the show. You know, this is
Speaker 3: the fastest growth for AWS in nearly five years. But
Speaker 3: to kind of capture moment in time, could we start
Speaker 3: by talking about how much of that was driven by
Speaker 3: the frontier labs, the big ones Open AI and Thropic,
Speaker 3: or how much of it was something broader across the enterprise,
Speaker 3: something bigger in AI.
Speaker 12: Yeah, it's actually across the board this growth that we're
Speaker 12: seeing right now, and much of that is some of
Speaker 12: the AI labs that are building their models on top
Speaker 12: of AWS, but actually a lot of that growth is
Speaker 12: spread across all of our startup and enterprise customers, where
Speaker 12: AI is really impacting almost every single industry. And so
Speaker 12: whether it's financial services companies or healthcare companies, or retail
Speaker 12: companies or media companies, Really the growth is coming across
Speaker 12: the board as companies of all different sizes in all
Speaker 12: different industries are looking to use AI to grow their business.
Speaker 12: And so we're seeing a lot of growth from the
Speaker 12: frontier labs. But for AWS, we're not like some others,
Speaker 12: maybe that's concentrated on just one or two large customers,
Speaker 12: but it's actually growth from a really broad set of customers,
Speaker 12: which is nice to see.
Speaker 5: Matt.
Speaker 3: When AWS says the AI business has a revenue run
Speaker 3: rate of twenty five billion dollars, what does that mean?
Speaker 2: What does the figuring compass?
Speaker 12: Yeah, that includes both training from very large companies like
Speaker 12: Anthropic and open Ai and other large tech companies, as
Speaker 12: well as many startups. But it also and then a
Speaker 12: big chunk of that is really inferenced that that broad
Speaker 12: swath of companies are doing. And so as companies think
Speaker 12: about how they take models in something on Amazon Bedrock
Speaker 12: and run those models to get value out of their business,
Speaker 12: some of them are automating processes. Many of them are
Speaker 12: running agentic workloads that they build on AWS to further
Speaker 12: drive efficiencies in their business or deliver new customer experiences.
Speaker 12: We consider all of that work, whether it's agent growth,
Speaker 12: whether it's inference, and some of that is training new models,
Speaker 12: all of that compasses the AI business for us.
Speaker 3: I think I've asked you this question at various points
Speaker 3: in time since you became AWS CEO. Is there a
Speaker 3: percentage split right now? Training versus inference that you can
Speaker 3: give me.
Speaker 12: Yeah, you do. And it actually keeps shifting, I would
Speaker 12: say more and more. It keeps shifting more towards inference.
Speaker 12: I think we still see large training clusters being used
Speaker 12: by a number of companies, but as these as these
Speaker 12: models get really popular and really powerful, more and more
Speaker 12: companies are integrating that inference into their workloads. So, you know,
Speaker 12: I don't know the exact percentage today, but it keeps
Speaker 12: shifting more and more towards inference, and we expect that
Speaker 12: to continue as the economics makes sense where you really
Speaker 12: want most of that cost and spend being where value
Speaker 12: is being created for end customers.
Speaker 3: Amazon's overall CAPEX number for this year is very big,
Speaker 3: two hundred and twenty billion dollars, so it's up twenty billion,
Speaker 3: and Andy Jesse explained that's mostly AI, but it also
Speaker 3: accounts for higher memory pricing. Right, capex higher because the
Speaker 3: cost environment's higher. But from aws's perspective, what's the trajectory
Speaker 3: for next year? You expect that capex will be biggest
Speaker 3: still because I think one of the things that Amazon
Speaker 3: is quite clear about is that even at two hundred
Speaker 3: and twenty billion, dollars, it might not be enough to
Speaker 3: meet current demand.
Speaker 12: Yeah, one of the things that we're quite excited about
Speaker 12: is just the potential business for us is just massive,
Speaker 12: and we see this as a huge opportunity for us
Speaker 12: to really invest and help customers take advantage of the
Speaker 12: AI opportunity, and so we will keep investing. We think
Speaker 12: that there's a big opportunity for us and for customers,
Speaker 12: And as Andy kind of called out last week, we
Speaker 12: have really great insight into what that demand is going
Speaker 12: to be from customers, and so when we invest and
Speaker 12: we will keep investing in kepex next year as well,
Speaker 12: we have great insight into when that revenue is going
Speaker 12: to land. And so it's pretty well known for us.
Speaker 12: And as Andy mentioned, much of our capacity has already
Speaker 12: spoken through through the end of twenty seven and even
Speaker 12: through much of twenty eight, and so as we're investing,
Speaker 12: we're getting five year commitments from customers. We're getting these
Speaker 12: long term commitments, and so we're out there making investments
Speaker 12: to keep being able to grow the business and try
Speaker 12: to meet customer demand. But as you say, today, demands
Speaker 12: still significantly outstriped supply, and we're trying to build and
Speaker 12: invest to keep up with what customers are asking for.
Speaker 3: And so we expect the CAPEX number will be bigger
Speaker 3: next year than it is this year.
Speaker 12: I expect us to keep investing as we see opportunities,
Speaker 12: and some of that will see how the market continues
Speaker 12: to grow. But right now we're excited about our investments
Speaker 12: and we'll continue to invest.
Speaker 3: The chip business has also got a lot of momentum.
Speaker 3: You know, Trainium for some time has been a big
Speaker 3: part of the strategy, and we've discussed that. I've been
Speaker 3: able to go to Austin spend a lot of time
Speaker 3: in Annapurna Labs to look at the server design. Let's
Speaker 3: start by asking what when you say the chip business
Speaker 3: has a revenue run rate in twenty five billion dollars,
Speaker 3: what does that mean? That is the business of selling
Speaker 3: the chips to third parties or renting out capacity based
Speaker 3: on the chips.
Speaker 12: Yeah, renting out capacity based on those chips. Today we
Speaker 12: run all of our own chips inside of the AWS
Speaker 12: cloud and that includes both Trainium chips as well as
Speaker 12: Graviton chips or which our general purpose processors. Graviton is
Speaker 12: incredibly popular. We've been building Graviton for many years now,
Speaker 12: and in fact, almost all of our large customers use
Speaker 12: Graviton as some part of their deployment, and it's a
Speaker 12: key part of how help customers deliver extra value by
Speaker 12: lowering their costs. Trainium is wildly popular and as we've
Speaker 12: mentioned a couple of times now, we're largely sold out
Speaker 12: through the end of next year for Trainium capacity and
Speaker 12: it's really really popular. We're starting to see both large
Speaker 12: customers as well as startups really love the cost benefits
Speaker 12: of running on Trainium and having that choice in a
Speaker 12: cloud where you can run on purpose built processors like
Speaker 12: Trainium that give you really great AI performance, together with
Speaker 12: Nvidia chips for when you need some of that processing
Speaker 12: for GPUs as well, gives customers the right mix that
Speaker 12: they're oftentimes looking for, and so we find that combination
Speaker 12: to be quite powerful and our Trainium three chips are
Speaker 12: really really popular with customers.
Speaker 3: Right now, we're live on Bloomberg Television and Bloomberg Radio.
Speaker 2: This is Bloomberg Tech.
Speaker 3: In conversation with Matt garm and, the CEO of AWS,
Speaker 3: explain that the difference in economics between capacity based on
Speaker 3: Trainium and capacity based on Blackwell, for example, like what
Speaker 3: is the selling point of going with Amazon Silicon.
Speaker 2: Yeah, we think that.
Speaker 12: Look, we think customers want choice, and so we offer
Speaker 12: great offerings for both products. Some customers really like to
Speaker 12: build on in Vidia GPUs and those are fantastic, and
Speaker 12: we're one of Nvidia's absolute largest customers in the world.
Speaker 12: We've been offering in Vidia GPUs in the cloud for
Speaker 12: over a decade now, and AWS is the most scalable
Speaker 12: and secure and stable place to run in Vidia servers anywhere,
Speaker 12: and so we're very excited about that business. But when
Speaker 12: you add Trainium, we're able to lower the ca for
Speaker 12: many workloads, and so customers like to have that opportunity
Speaker 12: where they can take these really massively scaled AI workloads
Speaker 12: or inference lart workloads where we can tune them because
Speaker 12: we kind of control that whole stack. We control the
Speaker 12: training chips, the data centers, and the inference stack and
Speaker 12: can really tune that whole stack. And that helps customers
Speaker 12: lower their costs and improve performance. And we're really starting
Speaker 12: to see that flywheel go where model providers of all
Speaker 12: types and customers love that they get that value and
Speaker 12: great performance. And we think that that's a real flywheel
Speaker 12: that we can keep turning and are quite excited about
Speaker 12: continuing to grow that business.
Speaker 2: Could you make it tangible for me? What is the
Speaker 2: cost saving?
Speaker 12: It's workload by workloads, so there's not like a specific
Speaker 12: cost savings, but for workloads where we see this optimization happen,
Speaker 12: customers can oftentimes save twenty thirty percent off of their
Speaker 12: inference costs when they run that on Trainum.
Speaker 2: Interesting.
Speaker 3: Would you consider selling the chips outright as opposed to
Speaker 3: capacity based on them.
Speaker 12: Yeah, we've mentioned that we might consider that in the future.
Speaker 12: Right now, we have so much demand inside of the
Speaker 12: AWS cloud that we really love that business, and so
Speaker 12: that's the place we're focusing right now. But it's an
Speaker 12: interesting opportunity and it's something that we would definitely consider
Speaker 12: in the future.
Speaker 3: The other big development was AWS signing the open Weights letter.
Speaker 3: You yourself communicated that Why was it important to you,
Speaker 3: Matt to sign that and participate in that?
Speaker 5: Yeah?
Speaker 12: I think that Again, a lot of this boils down
Speaker 12: to customers wanting choice, and the big frontier labs have
Speaker 12: awesome models today, whether it's open AI running on bedrock,
Speaker 12: whether it's Anthropic running on bedrock, Customers really love using
Speaker 12: those models. But they also like being able to customize models,
Speaker 12: and so having a broad ecosystem of open weights models,
Speaker 12: I think is incredibly important for innovation. It's important for
Speaker 12: our customers, and so you think about things like the
Speaker 12: Nematron models from Nvideo, or you think about Kimmi three
Speaker 12: or some of the Chinese open weights models. Those really
Speaker 12: help customers be able to customize to their own data
Speaker 12: and really be able to innovate. And so we think
Speaker 12: that it's important to not overlegislate there and give that
Speaker 12: flexibility for customers to use whichever models they find to
Speaker 12: be the best fit. And that's actually why we really
Speaker 12: focus on having all of those available inside of Bedrock,
Speaker 12: so that customers can choose which ones they want to use.
Speaker 3: Not to over legislate. I mean, I had a conversation
Speaker 3: with Jensen Wong the day the letter was posted about
Speaker 3: why then, what is the rationale? It does seem like
Speaker 3: the concern is that the US government overly regulates open models.
Speaker 3: Was that sort of a motivation for you?
Speaker 12: Yeah, I think that's the concern, and I think you
Speaker 12: just want to make sure that we kind of have
Speaker 12: an even playing field, and it doesn't mean that there's
Speaker 12: none by the way, I think there should probably be
Speaker 12: the same level of oversight of both frontier models as
Speaker 12: well as open weights models, and I think we should
Speaker 12: have a consistent framework, but kind of making sure that
Speaker 12: folks realize how important that is to what customers and
Speaker 12: are into is out there building on and that those
Speaker 12: open weights are a key building block of that, and
Speaker 12: we want to make sure that, however legislation lands, it
Speaker 12: lands evenly across all of those.
Speaker 3: Matt a question from our Bloomberg Tech audience for you
Speaker 3: is aws's attitude towards Kimmy K three. The open weight
Speaker 3: was released touly twenty seventh. You know, given the platform's
Speaker 3: AWS offers, what is the plan there.
Speaker 5: Yeah, it's a great model.
Speaker 12: The team there has done a really nice job and
Speaker 12: we see really great performance there, and we'll continue to
Speaker 12: support in bedrock offering the Kimmi models. I think the
Speaker 12: interesting thing is also as you see many of these
Speaker 12: open weight companies, they're starting to think about how they
Speaker 12: make money in these models as well, and so they're
Speaker 12: starting to introduce licensing around some of these open weights
Speaker 12: models as when customers want to run them in a
Speaker 12: cloud environment, and so I anticipate that there's going to
Speaker 12: be a blending of some of these models too, where
Speaker 12: these companies won't continue to spend lots of money and
Speaker 12: then just offer their IP up to the world. They're
Speaker 12: going to be licensing models. They're going to have ways
Speaker 12: of making money on those as well. And you're starting
Speaker 12: to see that with some of the open weights models
Speaker 12: actually having some licensing around them. And so we'll keep
Speaker 12: supporting these in Bedrock and working with those companies in
Speaker 12: order to offer these in the best possible way.
Speaker 3: That's why I'd like to end the conversation the business
Speaker 3: case and economic opportunity for open models from aws's perspective.
Speaker 3: So if the model makers themselves would like to make money,
Speaker 3: you know, how does AWS see that going in your
Speaker 3: favor to make money from wide use of open models?
Speaker 12: Yeah, yeah, I mean we basically that is exactly what AWS.
Speaker 12: It's a great platform for companies to come and offer
Speaker 12: their IP and their capabilities to the world, and so everybody,
Speaker 12: whether they're startups, whether they're governments, whether they're large enterprises,
Speaker 12: everybody can build on top of AWS. And if they
Speaker 12: have choice and they have access to these different models,
Speaker 12: it allows companies to be able to come and monetize
Speaker 12: them and sell when they have you to customers to
Speaker 12: be able to offer value when they think that they
Speaker 12: can go at lower prices or better performance. And so
Speaker 12: having that open platform allows everybody to have that competitive chance.
Speaker 12: And AWS is a fantastic partner for all these model
Speaker 12: providers to get access to the broad set of customers.
Speaker 12: And so it's a great ecosystem where model providers benefit
Speaker 12: and customers benefit by having all these in the same place.
Speaker 3: Matt Garman, COOFAWS, Amazon Web Services back on Bloomberg Tech,
Speaker 3: thank you very much. Now, coming up, home battery startup
Speaker 3: base Power has a new valuation thirteen billion dollars. We're
Speaker 3: going to talk to CEO Zach Dell about its latest
Speaker 3: funding round and the launch of its US built.
Speaker 2: Home powering battery. That's next. This is Bloomberg Tech.
Speaker 3: Rising demand for electricity in US is fueling investor interest
Speaker 3: in backing battery startups, among them base Power, which just
Speaker 3: closed a one billion dollar Series D round at a
Speaker 3: thirteen billion dollar post money valuation. Base Power CEO and
Speaker 3: co founder Zach Dell joins US now in Bloomberg Tech.
Speaker 3: A big round, right, and you know, inevitably part of
Speaker 3: needing the funds is to scale to get moving on
Speaker 3: the operations side. But let's start there, Like, what is
Speaker 3: it you want to do in the first instance, Zac, Yeah, Well.
Speaker 13: We really want to scale energy infrastructure to meet rising
Speaker 13: demand for power. So we build a hardware product that
Speaker 13: we install on homes, and we leverage a home battery
Speaker 13: that we design and manufacture ourselves, and we leverage those
Speaker 13: batteries to support the grid in times of high demand.
Speaker 5: So we're adding to basilely to the system to meet this.
Speaker 13: Rising demand from AI electrification, of heavy industry, of transportation.
Speaker 13: We're adding capacity the system through distributed batteries. The grid
Speaker 13: is able to use those batteries when demand is high,
Speaker 13: and the homeowners that are have those batteries in sold
Speaker 13: on their home are able to leverage those batteries when
Speaker 13: the grid.
Speaker 5: Goes out, Zach.
Speaker 3: This is a residential product right at a basic level.
Speaker 3: How tied is your fate and future to the adoption
Speaker 3: of solar in this country?
Speaker 5: Not really at all.
Speaker 13: Solar is a generation technology much like wind or gas
Speaker 13: or coal, and batteries are really mork into a.
Speaker 5: Transmission and distribution technology.
Speaker 13: So the way to think about it is that polls
Speaker 13: and wires move energy through space and batteries move energy
Speaker 13: through time, and so the battery is really a utilization
Speaker 13: tool that is helping increase the capacity factor of the
Speaker 13: system and bring down costs for everybody.
Speaker 3: So I ask you that, because the energy or electricity
Speaker 3: generation isn't the problem here, what is the problem that
Speaker 3: the base power is trying to solve for?
Speaker 13: Yeah, we've got a utilization problem on the grid today.
Speaker 13: So the grid is really built for peak demand, which
Speaker 13: means that most of the time we're not utilizing all
Speaker 13: of the infrastructure, which ends up being very expensive for
Speaker 13: rate payers or consumers of electricity. So by deploying batteries
Speaker 13: to the edge of the grid, you're able to increase
Speaker 13: the utilization, increase the capacity factor, and thereby lower costs
Speaker 13: for consumers.
Speaker 2: At home.
Speaker 3: I have a Tesla power Will three. It does rely
Speaker 3: on solar to charge it during the daytime. But let's
Speaker 3: talk about that as a comparison or a case study.
Speaker 3: At the technology level, the base call is better.
Speaker 2: How is different.
Speaker 5: How it's really designed to be a grid resource.
Speaker 13: So it's almost three maybe over three times the size,
Speaker 13: it's installed much faster, it's actually owned and operated by
Speaker 13: us the company based power and used as a grid resource.
Speaker 13: So when you go buy a home battery or a
Speaker 13: home generator, it's owned by the homeowner and it's really
Speaker 13: only there when the grid goes out. Our asset is
Speaker 13: really a piece of grid infrastructure. And so in partnership
Speaker 13: some of our utility partners, those batteries are used as
Speaker 13: a grid resource by the utility in times of high
Speaker 13: demand like I mentioned earlier, and then in the deregulated
Speaker 13: markets in Texas and Illinois where we operate, we use
Speaker 13: those batteries as a whole seal power asset. So we're
Speaker 13: really operating a fleet of infrastructure. Whereas those companies that
Speaker 13: sell batteries or generators, they're just trying to sell high
Speaker 13: margin hardware outfront. And our view is that batteries are
Speaker 13: really an infrastructure asset, and they're better sold and built
Speaker 13: kind of as such, right, and not really as a
Speaker 13: high margin product.
Speaker 2: Zach.
Speaker 3: I also feel like this is a Texas story from
Speaker 3: the manufacturing standpoint, right, you know this is going to
Speaker 3: be an American built technology. What were the challenges in
Speaker 3: establishing Texas is the base, the supply chain, making this
Speaker 3: an economically viable plan.
Speaker 13: Well, Texas is a fantastic place to build companies and
Speaker 13: also to establish manufacturing. And we see actually huge advantages
Speaker 13: in co locating engineering and manufacturing because the team that
Speaker 13: designs the product needs to be able to be very
Speaker 13: close to the team that builds the product. And so
Speaker 13: by coupling engineering and manufacturing and having that done by
Speaker 13: one team, one company, and one location, you get a
Speaker 13: bunch of efficiencies. It is much easier to iterate and
Speaker 13: you can move a lot faster.
Speaker 2: Should we talk about some of your investors in the round?
Speaker 3: What was the importance of assembling that group beyond just
Speaker 3: the checks that came in. What are you hoping to
Speaker 3: leverage from their experiences and their expertise. We're showing ribit
Speaker 3: Co two valor Ultimate Sense Capital D one.
Speaker 5: Yeah.
Speaker 13: I mean, we're building the company to compound over many decades,
Speaker 13: and we want to establish a cap table that is
Speaker 13: aligned with that kind of long term thinking. So these
Speaker 13: investors who joined our capitable today and who've been investing
Speaker 13: with us now for a couple of rounds, they see
Speaker 13: the opportunity to scale the business across the US internationally
Speaker 13: and do that over a long period of time. And
Speaker 13: they add a lot of interesting insights perspectives, and they're
Speaker 13: really are thought partners and our operating partners day to day.
Speaker 5: So we're super lucky to have a whole.
Speaker 13: Host of new investors joining the cap table and then
Speaker 13: basically all of our majorgitcing investors reinvesting in the company.
Speaker 3: Earlier in the program, we had Valor Atomic CEO Isiah
Speaker 3: Taylor on you know, different part of the energy stack,
Speaker 3: but we talked about how is America doing in this domain?
Speaker 8: Right?
Speaker 3: We talk a lot about China, how quickly China moves
Speaker 3: I guess at the nation level and at the federal level,
Speaker 3: are you getting everything you need, Zack to be able
Speaker 3: to execute in the way you want?
Speaker 2: Get the regulatory support?
Speaker 13: Yeah, Look, I think there's a lot of energy being applied,
Speaker 13: no pun intended to the space today, whether that's from
Speaker 13: the regulators or policy makers, but also entrepreneurs like like
Speaker 13: you know, our team at Base and the folks you
Speaker 13: mentioned earlier, some of the other companies entering the space.
Speaker 13: I mean, when we started Base three years ago, it
Speaker 13: was kind of unique to start an energy technology company.
Speaker 13: Either were not a lot of those out there, and
Speaker 13: now they're very common and you see them pop up
Speaker 13: all the time, and we love that. We think that
Speaker 13: the industry needs more great entrepreneurs and teams solving hard
Speaker 13: problems and helping us scale our capacity to consume electricity
Speaker 13: in this country. So I think we're in a really
Speaker 13: good spot and we've just got to keep executing relentlessly
Speaker 13: and building great solutions to some of these hard problems
Speaker 13: in the energy industry.
Speaker 3: You're building across the electric stack, and I kind of
Speaker 3: like read a lot about you and think you're pitching
Speaker 3: yourselves as like a next generation utility almost, And I
Speaker 3: think we should end the conversation with like, what is
Speaker 3: your relationship like with the existing utilities with the rest
Speaker 3: of the grid, because you're all kind of trying to
Speaker 3: move together in the same direction.
Speaker 13: Yeah, I wouldn't think of us really as a next
Speaker 13: generation utility. I would think of us as a modern
Speaker 13: energy technology company that is a provider of choice to
Speaker 13: the utilities to scale their infrastructure. So we work very
Speaker 13: closely with utilities with all kinds of utilities, with municipal
Speaker 13: utilities like Austin Energy, with co ops like Coserve and Gveck,
Speaker 13: with Investorr owned utilities like all Pass Electric and we
Speaker 13: build them technology solutions so they can scale their infrastructure
Speaker 13: and meet the moment, meet the rising demand that's coming
Speaker 13: from AI and all these things that you discuss all
Speaker 13: the time. There's an incredible inflection happening and energy consumption
Speaker 13: in America, and it's never been more important for the
Speaker 13: utilities to kind of step up and adapt, and we
Speaker 13: are really helping them do that. And it's our honor
Speaker 13: to work with the utilities. They're incredible partners and they
Speaker 13: have a huge responsibility in this coming decade, and we're
Speaker 13: really excited to partner with them.
Speaker 3: Zach very quickly, what's it like trying to hire right
Speaker 3: now the talent you need.
Speaker 13: Look, I think that we have an incredibly mission driven
Speaker 13: culture and company, and there's a lot of people out there,
Speaker 13: Hopefully some of them are watching the show that feels
Speaker 13: strongly that's scaling our capacity consumer electricity and really driving
Speaker 13: towards energy abundance on the path to human prosperity is
Speaker 13: one of the most uplifting and exciting missions that you
Speaker 13: can work on. And so we've had the great fortune
Speaker 13: of having tons of the best engineers in the world
Speaker 13: come to base and say, Hey, this is the mission
Speaker 13: I've got to be a part of and so we've
Speaker 13: had a really great time, frankly building out an incredible
Speaker 13: team Dan and Austin of just very mission aligned individuals,
Speaker 13: and we're excited to continue to grow that team as
Speaker 13: we conin to scale a business.
Speaker 3: Zach Dell, co founder and CEO of Based Power, thank
Speaker 3: you very much. In tea, there's a lot of other
Speaker 3: tech headlines. It's time for talking tech and first start
Speaker 3: South Korean AI chit designer DPEX secured funding it roughly
Speaker 3: four times its previous valuation, buffing the firm to two
Speaker 3: point two billion dollars. The news comes months after the startup,
Speaker 3: which developed semiconductor architecture tailored for AI tasks, said it
Speaker 3: secured over thirty mass production contracts from customers across eight
Speaker 3: countries plus. According to a PwC survey the thousand finance executives,
Speaker 3: eighty six percent of his ex said they thought AI
Speaker 3: training was more valuable than an MBA for new hires.
Speaker 3: Ninety one percent of those execs also said they were
Speaker 3: willing to pay according increasing compensation for AI literate employees,
Speaker 3: pointing to a growing urgency for firms to adopt AI
Speaker 3: tech and Spider Man Brand New Day was the biggest
Speaker 3: debut in Hollywood history, with the movie opening to three
Speaker 3: hundred and sixty million dollars in the US and Canada.
Speaker 3: Was a smashing success in China too, hauling the country
Speaker 3: out of its post pandemic Hollywood slump and contributing to
Speaker 3: a global box office debut of nine hundred twenty seven
Speaker 3: million dollars. That does it for this edition of Bloomberg Tech.
Speaker 3: These are the earnings that we're looking at this week.
Speaker 3: Earnings continues. We've got Palenteer SpaceX first ever earnings report
Speaker 3: and call as a public company, AMD a big one
Speaker 3: in the AI infrastructure space, and then later a focus
Speaker 3: on entertainment, the economy Paramount, Disney Uber all on Wednesday,
Speaker 3: Sorry Disney and Uber on Wednesday Recap Everything on the.
Speaker 2: Podcast was a pretty fast start to the week.
Speaker 3: You know where to find it on the terminal, on
Speaker 3: all Bloomberg platforms and online on Apple, Spotify, and iHeart.
Speaker 2: Have a great week. This is Bloomberg Tech.