Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive
Speaker 1: from coast to coast with Caroline Hide in New York
Speaker 1: and ever Low in sentrancs go.
Speaker 2: This is Bloomberg Tech coming up. Google agrees to create
Speaker 2: an AI cloud business with Blackstone, which will run on
Speaker 2: Google's homegrown AI chips.
Speaker 3: Plus, the legal battle between Elon Musk and his Open
Speaker 3: Ai co founders ends with a jewelry ruling Musk waited
Speaker 3: too long to soon. We'll dive into the details of
Speaker 3: the verdict.
Speaker 2: A Meta Betts Big on Louisiana for the world's biggest
Speaker 2: AI facility. This is It plans AI related layoffs this week.
Speaker 3: AI related layoffs a theme for the market, but AI
Speaker 3: lack of exuberance pounding the market once again with actually
Speaker 3: yields pushing higher Riskill focused on geopolitics, said, but we're
Speaker 3: looking at a third straight day of losses on the
Speaker 3: laws that one hundred or off five out a percentage point.
Speaker 3: We're off about three percent in those three training days.
Speaker 3: As we just get a little bit of worry that
Speaker 3: we went too far, too farst on the hardware side
Speaker 3: of things, I shine a light on the Semiconductor Index.
Speaker 3: The SOCKS is coming off by two percent. In fact,
Speaker 3: we're down by eight nine percent. We're on the cusp
Speaker 3: of some sort of well recalibration of where we've been
Speaker 3: in this run up. Yes, it was about seventy percent
Speaker 3: from the end of March, but now are we on
Speaker 3: the verge of a correction. We're down almost eight or
Speaker 3: nine percent, as I say, but a rotation. Some money
Speaker 3: moving into the software stocks. You've got key earnings coming
Speaker 3: from software and hardware over the next few days.
Speaker 4: Neo clouds down.
Speaker 2: The news Blackstone and Google forming a new company to
Speaker 2: be a neocloud. Blackstone brings five billion dollars. There's debt financing.
Speaker 2: Five hundred megawats is the target. Google's TPUs tensor processing
Speaker 2: units are the chips. And look at those names that
Speaker 2: are down Core weave, Ironebuus in particular, all very Nvidia
Speaker 2: focused architectures. But neoclouds all the same. Competition seems to
Speaker 2: be coming it does.
Speaker 3: That's scuss the impact of Google blackstory. The partnership ed
Speaker 3: Brie Big Intelligence says this pact could be a major
Speaker 3: boost for the tech giants. Chips business Managsing, who wrote
Speaker 3: that React joins us now. And what's so interesting is, yes,
Speaker 3: the equity comes from Blackstone five billion, it could be
Speaker 3: leveraged up to twenty five billion dollars. But this is
Speaker 3: just another way for Alphabet to get its hardware out
Speaker 3: there but not actually have to build the data centers.
Speaker 3: It feels like.
Speaker 5: Yeah, and look, when it comes to Nvidia, their ecosystem
Speaker 5: of neo cloud players is pretty big. I mean, you
Speaker 5: had a few of those on the on your screen.
Speaker 5: And when it comes to Google, you know, you have
Speaker 5: got terrible cipher mining, but there aren't a lot of
Speaker 5: you know, TPU providers. And that's where you know, when
Speaker 5: Anthropics says they want to use almost two hundred billion
Speaker 5: dollars of capacity from Google, Google has to find a
Speaker 5: way to you know, wrap that up outside of their
Speaker 5: own cloud. And that's where I think this sort of
Speaker 5: a transaction is quite interesting. Where Blackstone is putting the
Speaker 5: money and also has got live capacity that they can
Speaker 5: bring online by twenty twenty seven, which is what makes
Speaker 5: this very attractive from a Google standpoint.
Speaker 2: Hey, Mandy, what's the Bloomberg intelligence thesis on the business
Speaker 2: model of setting up a neocloud for the TPU?
Speaker 6: Right?
Speaker 2: Because Google Cloud, you know, they have capacity that they
Speaker 2: could get to third party customers. Why set up a
Speaker 2: new standalone new code.
Speaker 7: Yeah.
Speaker 5: So in the case of Google Cloud, you know, they
Speaker 5: are serving that traffic from Google's data centers. I mean
Speaker 5: in this case, you know, having a neocloud provider use
Speaker 5: Google TPUs and then everything else is taken care of
Speaker 5: by a blackstown in this case, whether it's you know,
Speaker 5: the power or the cooling or the you know, even
Speaker 5: getting the land for that data center. So from that perspective,
Speaker 5: having that live capacity is what you know, makes this
Speaker 5: different from Google having to do it on their own,
Speaker 5: which will be a lot more aggreed in terms of
Speaker 5: how much gigawad they can bring online in twenty twenty six,
Speaker 5: twenty twenty seven and beyond, whereas this would come life
Speaker 5: much faster given the involvement of blacksture.
Speaker 2: Man deep Seeing, who leads technology research at Bloomberg Intelligence.
Speaker 2: Thank you very much. Let's take it today. A look
Speaker 2: at today's big number. Seven thousand. That's how many workers
Speaker 2: Medas resigning to new jobs related to AI. That's according
Speaker 2: to an internal memo. This comes on the eve of
Speaker 2: a ten percent staff cut tomorrow to improve efficiency and
Speaker 2: quote offset metas investments in AI. AAR related job cuts
Speaker 2: are the talk of Wall Street right now. Is Standard
Speaker 2: Chartered CEO Bill Winters also saying his company plans to
Speaker 2: cut more than fifteen percent of its supports staff by
Speaker 2: twenty thirty, aiming to replace quote lower value human capital
Speaker 2: with AI. Martin Norton is MPOWER Chief Investment Strategists, and
Speaker 2: I'm going to ask you straight up, it's an interesting
Speaker 2: balancing act cutting rolls and saying that this is not
Speaker 2: necessarily a trim downsize, it's a reallocation a priority to AI.
Speaker 2: As an investor, what signal does that give you?
Speaker 8: Well, it's not the only piece of data that we
Speaker 8: have as companies do that. We hear a lot of
Speaker 8: different announcements of companies making reductions to their workforce related
Speaker 8: to AI. I think a lot of these are idiosyncratic.
Speaker 8: When we're looking at the broad economy at the moment,
Speaker 8: we know that the broad economy added labor upon labor
Speaker 8: and the wake of the pandemic, and now there's a
Speaker 8: bit of right sizing, and so in some cases, I
Speaker 8: do think companies are adding the AI moniker to make
Speaker 8: it feel very forward looking to maybe AI whitewash it,
Speaker 8: but not necessarily a sign of the times in terms
Speaker 8: of very broad layoffs across the economy. In fact, one
Speaker 8: of the areas that I'm looking more closely for signs
Speaker 8: of an AI impact is more on the hiring side,
Speaker 8: where people are maybe slower to higher than they otherwise
Speaker 8: would because of AI. But yes, there are these idiosyncratic
Speaker 8: reports that suggest we are seeing a little bit of
Speaker 8: movement on that front.
Speaker 3: I'm sorry, language matters, lower value, human capital, the extraordinary
Speaker 3: choice of words, but Marta putting that to one side,
Speaker 3: there is anxiety out there of labor and people who
Speaker 3: are affected. But when you're thinking about how we see
Speaker 3: actual businesses lean into this moment, are we still seeing
Speaker 3: adoption taking root in the way you anticipated? Are we
Speaker 3: seeing the people the label that is able to use
Speaker 3: AI being more productive with it?
Speaker 8: You know, I think those early signs that are pretty
Speaker 8: positive in terms of adoption by current employees. So I
Speaker 8: think everyone at this point is using the chatbots on
Speaker 8: a regular basis to do, you know, low value research.
Speaker 8: But I think the bigger question is this AI agent
Speaker 8: deployment what that looks like? And you are seeing companies
Speaker 8: talking about that in real time and beginning to structure
Speaker 8: workflows around it. I think we're very early obviously on
Speaker 8: the adoption of that. But that is where I think
Speaker 8: a lot of this AI productivity can stem from.
Speaker 2: Modern the market's trading, in part in anticipation of Nvidia.
Speaker 2: After the closing bell Wednesday. Yesterday, I spoke to Nvidia
Speaker 2: CEO Jensen Wang. This is how he frames the state
Speaker 2: of play.
Speaker 9: We have the largest supply chain in the world. Our
Speaker 9: partners have done a great job securing supply for us,
Speaker 9: and so all of the pieces go together. The silicon,
Speaker 9: photonics is lined up, Everything is all lined up. It's
Speaker 9: just that the demand is much greater than the overall capacity.
Speaker 3: Of the world.
Speaker 2: The demand is far out pacing this industry's ability to supply.
Speaker 2: When you go into an earnings how do you decide
Speaker 2: therefore the bar in terms of what is positive and
Speaker 2: what is negative. If you're in a supply constraint world.
Speaker 8: Well, I think you do want to see signs that
Speaker 8: they are monetizing it. Right, If you're in a supply
Speaker 8: constrained world, that demand should be moving earnings and you
Speaker 8: want to see some evidence of that. But of course,
Speaker 8: when we're talking about the supply constraint. We're also talking
Speaker 8: about supply constraint and areas that would infect the likes
Speaker 8: of n videos so memory checks, for example, And what
Speaker 8: does that mean for gross margins and how are they
Speaker 8: navigating that? I think those are important questions at the moment,
Speaker 8: but I think the bigger picture, and I caught that
Speaker 8: that interview yesterday. I think the bigger picture that Jensen
Speaker 8: Wong is pointing to is this massive supply and demand
Speaker 8: mismatch that we'll carry through not just this earnings report,
Speaker 8: but for several quarters years to come as this all
Speaker 8: plays out. So I really agree with his comment that
Speaker 8: this is inning one, Inning two on the AI build.
Speaker 3: Luckily we all call that into you. It was a
Speaker 3: great one with Ed and Mountain Norton. We so appreciate
Speaker 3: having you on the show today of Empower. Thank you
Speaker 3: for your time. Coming up a bitter feud, personal grievances,
Speaker 3: billions of dollars. The decision comes down to timing. We'll
Speaker 3: discuss the jury's rejection of El Musk's claims against his
Speaker 3: Open AI co founders, and what comes next the decision
Speaker 3: in that closely watched legal battle between Ela Musk and
Speaker 3: his open ai co founders came down to timing. A
Speaker 3: jury rule that Musk waited too long to sue of
Speaker 3: open AI's transition to a for profit business. Mugs Madelon
Speaker 3: and Macklburg has been following the case every step of
Speaker 3: the way. You join us now, Madeline. What did the
Speaker 3: jury decide? What didn't it decide on?
Speaker 6: Right?
Speaker 10: It was a bit of an anti climactic verdict, if
Speaker 10: I can say that, because the jury didn't actually make
Speaker 10: a decision on any of the claims that Elon Musk
Speaker 10: presented over the course of this lawsuit. What they said
Speaker 10: instead was that he had not proven his case within
Speaker 10: the statute of limitations set by law for the specific
Speaker 10: claims that he brought. So essentially, they found that he
Speaker 10: had concerns about this conduct and should have known about
Speaker 10: this conduct years before he actually filed his lawsuit, and
Speaker 10: so therefore the case that the jury was hearing should
Speaker 10: be tossed out, which is what happened.
Speaker 2: We're going to get an appeal, according to mister Mask,
Speaker 2: who posted on x that he would appeal. I believe
Speaker 2: like his legal team outside the courtroom said that we
Speaker 2: would appeal. If that's the case, what do we know
Speaker 2: about what that appeal would be based on From a
Speaker 2: legal perspective.
Speaker 10: Right, it should come as no surprise to anybody who
Speaker 10: follows Elon Musk as a litigant that he plans to
Speaker 10: appeal this and fight this vigorously. We saw him celebrating
Speaker 10: on X afterwards saying that, you know, just because they
Speaker 10: decided on the statute of limitations, they never actually touched
Speaker 10: the merits of the case. I think an appeal on
Speaker 10: this ground is a lot more narrow than if the
Speaker 10: jury had actually ruled on the.
Speaker 6: Merits of his claims.
Speaker 10: So I think a lot It still kind of remains
Speaker 10: to be seen of how this is going to play out,
Speaker 10: but it's going to be an issue that the Ninth
Speaker 10: Circuit Court of Appeals is going to have to sort
Speaker 10: through when he eventually files that.
Speaker 2: Bloomberg's Madeline Meckelberg, thank you very much. Let's dive more
Speaker 2: into the legal considerations. Dorothy Lund is with us, a
Speaker 2: professor at Columbia Law School focused on corporate law, governance
Speaker 2: and contracts, returning to the show and has been covering
Speaker 2: this trial with us. In our Bloomberg News story, we
Speaker 2: write that mister Musk was too late in his suit,
Speaker 2: and we later down in the story explain the idea
Speaker 2: that he had knowledge in twenty twenty four and so
Speaker 2: basically should have filed his suit sooner. But I've got
Speaker 2: a lot of sympathy with people around the world that
Speaker 2: don't understand the legal technicality of that. The Statute of
Speaker 2: limitations seems to play a role here. Is this codified
Speaker 2: or is this the jury's discretion in deciding that mister
Speaker 2: Musk ran out of time?
Speaker 6: Yeah, the jury.
Speaker 11: So the jury had to basically answer this question of
Speaker 11: whether or not the Statute of limitations applied to the
Speaker 11: two claims that were brought here. So the two claims
Speaker 11: is to remind everybody or there was a violation that
Speaker 11: open ai, Brockman and Altman violated a promise that was
Speaker 11: made to Musk that it would have a permanent charitable
Speaker 11: charitable mission to develop safe open source AI technology, and
Speaker 11: that they received undeserved benefits because of those broken promises.
Speaker 11: And so then open ai said, well, you waited too
Speaker 11: long to sue. You know, you brought your case on
Speaker 11: August twenty twenty four, and the statute of limitations was
Speaker 11: only three It was three years, which meant the things
Speaker 11: that you're complaining about that took place in twenty eighteen,
Speaker 11: twenty nineteen, you're too late.
Speaker 7: Well, I think that is.
Speaker 2: Surely, did Elon Musk and his team of very expensive
Speaker 2: lawyers not understand the law or something when they followed
Speaker 2: the suit?
Speaker 6: Nosk?
Speaker 11: You know, so Musk of course had these fabulous lawyers,
Speaker 11: and you know that the statute of limitations is told
Speaker 11: if you've concealed, if harm has been concealed, or you
Speaker 11: haven't discovered the harm. And so his argument was, well,
Speaker 11: you know, Sam Altman and open Ai have been lying
Speaker 11: to me. They concealed that they were doing all this stuff.
Speaker 11: It wasn't until twenty twenty three that I really understood
Speaker 11: what was going on. And so this and this gets
Speaker 11: back to your original question, which is why did this
Speaker 11: go to a jury?
Speaker 7: Right?
Speaker 11: The jury had to sift through testimony from both parties,
Speaker 11: documents and to try to understand this timing question. Okay,
Speaker 11: so when was it that Musk knew or reasonably should
Speaker 11: have known about the harm that he was claiming happened.
Speaker 3: And instead we all get consumed with billionaire versus billionaire
Speaker 3: and how much equity they own in the underlying company
Speaker 3: and what they're like in terms of managers or how
Speaker 3: trustworthy they are at the end of the day, when
Speaker 3: we misguided to think that when they go back to
Speaker 3: an appeals court, will it be argued in a different way.
Speaker 11: Yeah, So it's a little disappointing that we didn't get
Speaker 11: an answer on the big question here, right, that the
Speaker 11: claims that I was telling you about just now are
Speaker 11: are unaddressed, and in this appeal we won't get any
Speaker 11: resolution on this either. So you know, this is going
Speaker 11: to be a narrow appeal on this decision of the
Speaker 11: statute of limitations. And because that statute of limitations question
Speaker 11: turned on a factual determination, you know that is going
Speaker 11: to be really hard to be overturned. Public courts rarely
Speaker 11: overturn a jury's fact intensive findings, especially in this case
Speaker 11: where the judge also reviewed the evidence and said I
Speaker 11: came to the same conclusion. And so the only path
Speaker 11: four from USK is going to be arguing a different
Speaker 11: set of things about you know, the argument would have
Speaker 11: to be some error that proud come here, improper instructions
Speaker 11: or improper evidentiary rulings.
Speaker 2: We're having some technical issues, or if you with your zoom.
Speaker 2: So give the Internet gremlins a second to reset. But
Speaker 2: my question to you is exactly that, I don't want
Speaker 2: you to speculate.
Speaker 4: But what options does mister.
Speaker 2: Musk have if he needs to go to the appeals
Speaker 2: court but argue something completely different to the original case.
Speaker 11: Yeah, his argument is going to have to be that
Speaker 11: there were significant legal or procedural errors that prejudice the outcome.
Speaker 11: You know that there the instructions to the jury were improper,
Speaker 11: their evidentiary rulings were wrongly decided. There won't be any
Speaker 11: discussion on the substance of this larger question of whether
Speaker 11: or not Opening I violated its charitable purpose when it
Speaker 11: restructured to create a for profit affiliate.
Speaker 3: Called a public opinion. Therefore, in many ways, Dorothy Lund,
Speaker 3: Professor at Columbia Law School, fantastic to have you. Thank you.
Speaker 3: Coming up, Parallel is moving past the era of flat
Speaker 3: f AI licensing deals. The CEO Arak Agrawal is me
Speaker 3: joining us. Next this is blue bag Tech.
Speaker 2: Parallel, a web API purpose built for AI and led
Speaker 2: by the FORMACYO of Twitter, is launching Index today, a
Speaker 2: new marketplace that pays publishers and data providers based on
Speaker 2: how much their content actually helps an AI agent completed task.
Speaker 2: Joining us is Parallel, founder and CEO Para Agrowl. So,
Speaker 2: in answer to the question what did you get done
Speaker 2: this week? You launched Index in this era of agentic right,
Speaker 2: the agents need the web data and the proprietary data sets.
Speaker 2: I guess saw a gap where the marketplace for that
Speaker 2: data doesn't exist. Then now you think it does.
Speaker 12: Yeah, we've been linked towards this content marketplace for the
Speaker 12: last two and a half years. We've started Parallel with
Speaker 12: the notion that agents will use all of the content
Speaker 12: on the web thousand x more than humans ever have.
Speaker 12: And when that happens, the technology that we've built over
Speaker 12: the last couple of decades isn't enough. But the business
Speaker 12: models also break down. Adds, subscriptions, these business models no
Speaker 12: longer work, and that I think is the opportunity for
Speaker 12: us to figure out how to align the interests of
Speaker 12: AI agents doing real work along with the content owners
Speaker 12: who are creating valuable content that feeds these agents.
Speaker 7: And that's what Index is all about.
Speaker 2: To help the Boomberg Tech audience out. The question what
Speaker 2: did you get done this week? Was posed to you
Speaker 2: by mister musk just before you left Twitter. How do
Speaker 2: you assign a value then to the data? You've called
Speaker 2: this index very interesting. Right on the one side you
Speaker 2: have the agent or the entity the agent is acting.
Speaker 4: On behalf of.
Speaker 2: And then on the other side you have the source
Speaker 2: of the data who sets up price or value.
Speaker 12: Yeah, So if you think about other deals that are
Speaker 12: being done, these deals are typically between a large lab
Speaker 12: or a hyperscaler or Google alongside a large publishing house.
Speaker 12: And these are flat feed deals where over time, I
Speaker 12: don't believe content owners get to participate in the growing
Speaker 12: economy of agents. Now, what's really happening with agents is
Speaker 12: they are starting to do real work, real knowledge work
Speaker 12: in the enterprise. So if you think about our customers,
Speaker 12: our customers span people building AI scientists. Our customers are
Speaker 12: building air lawyers, customers are building for finance using agents,
Speaker 12: and all of these agents that our customers built are
Speaker 12: doing real work when they produce value. Content owners don't
Speaker 12: get to participate in that economy of the value being.
Speaker 7: Created with index.
Speaker 12: What we're trying to do is buil a system where
Speaker 12: if very valuable work is done using somebody's data, they
Speaker 12: get more money. If someone has very high quality data,
Speaker 12: they get paid more. And we've built a model to
Speaker 12: figure out what this value is, what this marginal contribution is,
Speaker 12: and it draws from this game theorty concept called Shapi values.
Speaker 3: Let's talk about the shapely value. It's contribution to the
Speaker 3: work performed by an AI agent. So basically, instead of
Speaker 3: content access crawls or citations, you consider the value. I mean,
Speaker 3: but where's the monetary number coming from? What are you
Speaker 3: pegging it against? And how how do you work out what?
Speaker 3: Then ADII agent has eventually learned itself.
Speaker 7: Off for well.
Speaker 12: Shappie values has been my obsession for the last three
Speaker 12: years as we've been working on this. So just in
Speaker 12: a sentence, what shappily values is is about like if
Speaker 12: a few people decide to collaborate on building something in
Speaker 12: a positive some way where the whole is bigger than
Speaker 12: the sum of parts. The question is how do you
Speaker 12: divide up this value? And schappely value is the concept
Speaker 12: that tells us the way to divide this value so
Speaker 12: that everyone is incentivized to participate. The net outcome of
Speaker 12: using this concept two reward content owners. It creates three
Speaker 12: really nice properties. One high quality content gets paid more.
Speaker 12: Number two, content that gets used in high value work
Speaker 12: gets paid more. And most importantly, as agents do more
Speaker 12: work and create more value, content owners grow alongside them,
Speaker 12: which we believe allows content creation on the web to
Speaker 12: be sustainable.
Speaker 3: There are a lot of content creators out there right now,
Speaker 3: So how do they sign up to INEX? How do
Speaker 3: you make sure that it's not just quite large either?
Speaker 6: Individuals who are.
Speaker 3: Writing I think of alex Etho is actually those that
Speaker 3: have got a minor substack, but with really valuable content
Speaker 3: that somehow the agent has managed to access.
Speaker 6: How do they access that?
Speaker 7: Yeah?
Speaker 12: With Index Today we're announcing collection of launch partners. These
Speaker 12: span premium news publishers like The Atlantic and Fortune to
Speaker 12: really raw, factual, amazing content from the pr Newswire, business
Speaker 12: intelligence and data providers like pitch Bork and Traction and
Speaker 12: zoom Info, as well as independent creators like Alex Heath,
Speaker 12: Azimazer as several others. The really interesting part about this
Speaker 12: is that we want everyone, all content owners big and small,
Speaker 12: to be able to participate in this economy, and we
Speaker 12: want all agents, not just once built by large providers,
Speaker 12: to be able to get access to all of this
Speaker 12: amazing content.
Speaker 2: Correct, We just have sixty seconds, but can ask you
Speaker 2: about x the platform known as Twitter. Of course, still
Speaker 2: using it, your view of it and as part of
Speaker 2: XAI is part of SpaceX.
Speaker 7: I'm still using it. I'm still calling it Twitter.
Speaker 12: I think we built a product over a decade that
Speaker 12: I was there which endures in value forever, and I'm
Speaker 12: really proud of the platform that we created.
Speaker 7: It allows the theme of.
Speaker 12: Content access and democratization out in the open versus and
Speaker 12: permission groups, and that theme is what carries forward into
Speaker 12: my current company, Parallel, where the goal is to have
Speaker 12: as much content as possible out in the open, for
Speaker 12: everyone to have access to, everyone's agent to have access
Speaker 12: to instead of just the.
Speaker 3: Few, and be compensated Paral Else, CEO Aragagowel is great
Speaker 3: to have some time with you. Thank you for coming on.
Speaker 6: Now.
Speaker 3: Coming out, we dive into metas mega data center plans
Speaker 3: in Louisiana and some the hiccups along the way from
Speaker 3: New York from San Francisco, there's a Bluema.
Speaker 4: Tech welcome back to Bloomberg Tech.
Speaker 2: There's still a semiconductor story in financial markets and looking
Speaker 2: at the socks or the Philadelphia Semiconductor index. We're down
Speaker 2: for a third straight day.
Speaker 4: A part of this is.
Speaker 2: Kind of a breather after what we were calling the
Speaker 2: melt up. The performance in chip stocks since the end
Speaker 2: of March was astonishing. But there's also this element that
Speaker 2: we are really close to correction territory in three days.
Speaker 2: At one point in the session, we were down almost
Speaker 2: ten percent. Its karra Of pointed out earlier. In Vidia
Speaker 2: is a part of it, right, and the idea that
Speaker 2: posts President Trump's visit to China. We don't really have
Speaker 2: a net conclusion of what's going on, but we get
Speaker 2: in Video earnings on Wednesday, so fresh off his trip
Speaker 2: to Beijing and Video CEO Jensen Wong says he's confident
Speaker 2: the Chinese market will eventually open back up.
Speaker 4: To his company.
Speaker 2: Delceo and Michael Dell shared that optimism for economic collaboration
Speaker 2: as well. Here's what both leaders told me at Del
Speaker 2: World in Las Vegas yesterday.
Speaker 9: The President once America the wind everywhere right. The President
Speaker 9: wants America to lead the Ai revolution, and so h
Speaker 9: two hundreds are licensed to sell to China.
Speaker 7: The Chinese. The Chinese government.
Speaker 9: Has to decide how much of their local market do
Speaker 9: they want to protect and how much of their local
Speaker 9: market do they want to expand with more a more
Speaker 9: AI capacity. My sense is that the demand in China
Speaker 9: is so incredible, just like it is here. Agentic Ai
Speaker 9: is also making enormous progress there. My sense is that
Speaker 9: over time the market will open. President she was very
Speaker 9: clear that he wants China to be an even wider
Speaker 9: open market. Premier Lee Chang was very straightforward and to
Speaker 9: explain very eloquently that that China will be an open market.
Speaker 7: So I'm looking forward to China be in a more.
Speaker 2: Open clarified as you were able to meet with those
Speaker 2: officials directly to discuss whether or not you can sell
Speaker 2: to those Chinese tech companies.
Speaker 7: I did.
Speaker 9: I didn't discuss directly with them about age two hundred, right.
Speaker 9: I was there to represent the United States and I
Speaker 9: was honored to do so. I was there to support
Speaker 9: President Trump and.
Speaker 7: Really glad to do so.
Speaker 9: But that was really the focus of my trip. President
Speaker 9: Trump had some conversations with the leaders, and I'm looking
Speaker 9: forward to what they decided.
Speaker 2: Michael, you did not go to China, but I think
Speaker 2: what's interesting is you are a member of the President's
Speaker 2: Council advises for science and technology, as is Jensen, your
Speaker 2: net conclusion on whether or not China will become open
Speaker 2: to American technology companies to do business there.
Speaker 4: You know, we have a bus in China.
Speaker 13: Obviously we comply with all the restrictions and you know,
Speaker 13: various controls that are in place.
Speaker 4: But I hope that there's.
Speaker 13: More economic collaboration between the United States and China that
Speaker 13: ultimately is will lead to greater outcomes and prosperity for everyone.
Speaker 13: And you know, a greater likely heard of a successful
Speaker 13: relationship between the countries and around the world.
Speaker 3: Dell CEO Michael Dale, of course, and Video CEO Jensen,
Speaker 3: And I'm speaking there with Ed yesterday. And let's just
Speaker 3: revisit today's big number with Meta reassigning seven thousand workers
Speaker 3: to new jobs. Of course they're related to AI. An
Speaker 3: internal memo from Chief people Officer Janelle Gale, viewed by Bloomberg,
Speaker 3: Reveal's employees will move into one of several new groups
Speaker 3: focused on AI related products, including agents and apps. The
Speaker 3: new corporate structure will quote be flatter and have smaller teams.
Speaker 3: Now this comes as the company is getting ready, of course,
Speaker 3: to cup ten percent of its staff this week as
Speaker 3: part of an effort to, as they say, improve efficiency ed.
Speaker 1: Yeah.
Speaker 2: Sticking with Meta's big AI plans, Mark Zuckerberg's plan to
Speaker 2: build the world's biggest AI facility has enmeshed his company
Speaker 2: deeply in Louisiana's politics and economy, the projects providing an
Speaker 2: economic boost to one of the nation's poorest regions, but
Speaker 2: also bringing a host of growing Bloomberg's Riley Griffin joins
Speaker 2: us more with the big take, and there's big readership
Speaker 2: on this, a lot of interest. You did what every
Speaker 2: good Beat reporter does. You go there, you see what's
Speaker 2: happening on the ground. The headline is two hundred billion dollars, right,
Speaker 2: that's the commitment. What is happening with Meta in Louisiana.
Speaker 14: Yeah, A really important point here is that two hundred
Speaker 14: billion dollars spend that Meta is thinking about with Richland
Speaker 14: Parish and its data center.
Speaker 6: There is largely about the chips.
Speaker 14: This is going to be a five gigawatt of compute
Speaker 14: capacity data center, another two point five gigawatts to support
Speaker 14: the broader campus, which is spanning nearly four thousand acres.
Speaker 14: President Donald Trump has said that this is going to
Speaker 14: be a Manhattan sized project after speaking with Mark Zuckerberg.
Speaker 14: But a lot of that spend isn't going directly into
Speaker 14: the community. It's going into the chips inside the facilities.
Speaker 14: And we still have to ask the question, what does
Speaker 14: this mean for the people of Richland Parish in the
Speaker 14: Louisiana Delta, a region that has struggled for decades and
Speaker 14: where farmers are really losing four hundred dollars on every
Speaker 14: acre of cotton they sell.
Speaker 3: Right now, Well, let's go to Dustin Morris, because you
Speaker 3: paint a picture of how his economic reality is currently.
Speaker 3: He's a soybean, a corn farmer, and he's flying around
Speaker 3: his own land trying to work out whether it's the
Speaker 3: right time to be selling out right.
Speaker 14: Yeah, it's a story of expected land rush right as
Speaker 14: with all of the data center stories of this size
Speaker 14: around the United States, many of them shifting into rural regions,
Speaker 14: particularly in the South, and people are looking around and wondering,
Speaker 14: you know, do I trade this history, Do I trade
Speaker 14: this land? Do I trade this crop for a data center?
Speaker 14: And it was I mean, it was really an honor
Speaker 14: to be able to go multiple times to Richland Parish
Speaker 14: and hear their concerns and think about the way they're
Speaker 14: looking at Meta as a lifeline, and I over.
Speaker 2: Was jumping what a Meta saying about that? Like was
Speaker 2: Meta's response to it? And what do people genuinely feel
Speaker 2: about the company even where it's made a building there.
Speaker 6: Well, it took some time.
Speaker 14: Meta hashed out this deal over the course of a
Speaker 14: year in private. Meta is certainly saying they want to
Speaker 14: be there in the thick of it with the community.
Speaker 14: They're investing in the schools. There's actually a school at
Speaker 14: the corner of the data center. There are discussions about
Speaker 14: whether it should be moved. I have heard that Meta
Speaker 14: is reviewing plans, so they're in the trenches. But notably,
Speaker 14: Meta is only bringing five hundred jobs. This is a
Speaker 14: community that's looked for five thousand over the years from
Speaker 14: an auto manufacturer and have been unable to court that.
Speaker 14: So will five hundred jobs be enough to provide that
Speaker 14: economic lifeline long term?
Speaker 6: I'm not sure.
Speaker 2: To the's Riley Griffin with the big take top of
Speaker 2: the website and the Bloomberg terminal carry there's plenty more
Speaker 2: news out there today.
Speaker 3: There is It's time now for talking tech ed and
Speaker 3: first up Chinese AI pioneer Moonshot is restructuring to secure
Speaker 3: its path to public markets now. The developer of the
Speaker 3: popular kidney chatbot has informed investors it will revamp its
Speaker 3: corporate structure to comply with Beijing's rules and pave the
Speaker 3: way for a highly anticipated Hong Kong ipo. Speaking of which,
Speaker 3: Chinese robotics Unicorn Lingobot is exploring a Hong Kong ipo
Speaker 3: that could launch as early as this year, and the
Speaker 3: maker of highly dexterous robotic hands is targeting a six
Speaker 3: billion dollar evaluation and counts Samsung ten Cent among its clients.
Speaker 3: And China's demographic time clock is triggering an unprecedented automation boom.
Speaker 3: A new report from Barkley's shows humanoid robots could offset
Speaker 3: as much as sixty percent of that labor decline by
Speaker 3: twenty thirty five, turning.
Speaker 6: What is a structural crisis into a hardware gold rush.
Speaker 2: Ed Coming up, we're going to go live from the
Speaker 2: JP Morgan Tech Media and Communications Conference, and we'll hear
Speaker 2: from Lori Beer, JP Morgan Global c Io that conversation.
Speaker 4: Next this is Bloomberg Tech.
Speaker 2: Let's get out to the JP Morgan Tech Media and
Speaker 2: Communication Conference in Boston. Where Bloomberg Surveillance co host Lisa
Speaker 2: Vonovitz is standing by Lisa.
Speaker 6: Thank you so much. Ed.
Speaker 15: I am here at a JP Morgan conference at four Technology,
Speaker 15: Media and Communications, and I'm here with Lori Beer, the
Speaker 15: chief information officer for JP Morgan.
Speaker 6: Laurie, wonderful to speak with you. In many ways, you
Speaker 6: are the woman of the moment.
Speaker 15: Because you have to understand how to oversee change that
Speaker 15: seems to be happening at an accelerating pace. Can you
Speaker 15: give a sense of just how quickly it has accelerated
Speaker 15: from say, six months ago, a year ago to right now.
Speaker 16: Yeah, I think it's an amazing moment, first of all,
Speaker 16: to be in technology and to be in financial services.
Speaker 6: And we definitely saw the.
Speaker 16: Gen one tools come out a couple of years ago.
Speaker 16: The last six months have rapidly accelerated, not only new
Speaker 16: models getting created, but how we're able to apply them.
Speaker 6: And so it really ties back to how.
Speaker 16: Do we think about driving and adapting.
Speaker 6: Change so quickly?
Speaker 15: Yeah, one thing is wered a lot of nervousness, a
Speaker 15: lot of anxiety. There was a story that was out
Speaker 15: this morning about Standard Charter CEO coming out and saying
Speaker 15: they was going to cut fifty percent of staff support
Speaker 15: staff and removing lower value human capital and replacing it
Speaker 15: with AI tools and investment in AI. What's real what's
Speaker 15: not when it comes to sort of the mass job
Speaker 15: cause what's been your experience?
Speaker 16: Yeah, So overall we've seen definitely productivity opportunities.
Speaker 6: So even when we.
Speaker 16: Think about technology, we've seen ten to twenty to thirty
Speaker 16: percent improvement just from the initial generation one tools. As
Speaker 16: you look to agentic you're going to see even more.
Speaker 6: But there's a huge demand.
Speaker 16: There's a huge demand to create new products and services
Speaker 16: and experiences for our customers. We're using AI to figure
Speaker 16: out new products to offer and frankly, when you think
Speaker 16: about the other side of it, the AI is also
Speaker 16: creating increased cybersecurity risks. So how do we think about
Speaker 16: also the accelerating the investments to protect our customers and
Speaker 16: client too. So the demand remains large, you know, significant,
Speaker 16: and we're able to get a lot more done than
Speaker 16: we have historically. How's very is mythos so with mythos
Speaker 16: AI in general, but it's really good on both sides
Speaker 16: of the equation. One to understand vulnerabilities and so the
Speaker 16: key with that and any other AI is how do
Speaker 16: we capture those, how do we clearing house those, how
Speaker 16: do we update those in.
Speaker 6: A safe and secure way. But on the other.
Speaker 16: Side of this, as you apply these models into the
Speaker 16: software development process, we're going to have safer and more
Speaker 16: secure software.
Speaker 6: On the flip side, or cyber.
Speaker 16: Teams can use the power of these models to be
Speaker 16: able to protect, defend, identify fraud, identify.
Speaker 6: Issues more quickly.
Speaker 16: So there's really two sides of this equation to think about.
Speaker 15: Based on how quickly you see technology shifting and what
Speaker 15: tools are really coming to the fore, how does the
Speaker 15: mindset have to shift of the people who work for you.
Speaker 16: Yeah, I think it's a great question. The technology is amazing.
Speaker 16: I think this is truly a shift, a transformational shift
Speaker 16: in technology where this is getting embedded and horizontally across
Speaker 16: all layers of the stack. The harder part is the
Speaker 16: change management in the leadership, and I think really thinking
Speaker 16: about where are things going. We don't know all the answers,
Speaker 16: so how do you navigate change in an uncertainty? It's
Speaker 16: still very early innings, so it's really had to shift
Speaker 16: from how do we help guide our teams, how do
Speaker 16: we make sure our software engineers understand what's coming.
Speaker 6: My management team.
Speaker 16: Spends a lot of time on the weekends building their
Speaker 16: own apps, pick your favorite coding adentic coding tool, but
Speaker 16: it helps them understand what's coming. And I think this
Speaker 16: is a moment where leaders, in addition to software engineers
Speaker 16: truly have to understand the change. And we have to
Speaker 16: understand how do we actually create an environment that allows
Speaker 16: us to pivot and navigate when times are uncertain and
Speaker 16: really make sure don't lose track.
Speaker 6: Of what's really important.
Speaker 16: How do we deliver products and services and experience.
Speaker 6: From our customers and clients.
Speaker 15: Howty balance innovation with risk and the idea of the
Speaker 15: tried and true you need to do this project versus
Speaker 15: moonshot projects.
Speaker 16: Yeah, you know, I think this is one of the
Speaker 16: most interesting times when you have to think about the
Speaker 16: balance of innovation and risk taking. We wouldn't be in
Speaker 16: business as long as we have been if we haven't
Speaker 16: driven a lot of innovation historically. But we're also in
Speaker 16: the business of managing risk, and so I think in
Speaker 16: this moment you have to really think about going at
Speaker 16: the appropriate speed of innovation. Some of these moonshots are
Speaker 16: becoming real and so you have to move aggressively at
Speaker 16: the innovation front.
Speaker 6: But we obviously are a.
Speaker 16: Business of trust, and we have to make sure our
Speaker 16: customers are clients, the bank is protected every day, and
Speaker 16: so finding this balance and actually again using these capabilities
Speaker 16: to also protect ourselves.
Speaker 6: And so it's this really interesting time while along with
Speaker 6: that you don't necessarily know who's going to win in
Speaker 6: the end, and.
Speaker 16: So making sure we're not locking ourselves in to one
Speaker 16: provider or one scenario and we're constantly sandboxing what's on
Speaker 16: the horizon in the future.
Speaker 15: Does it change your decision whether to build or buy
Speaker 15: in terms of different software solutions.
Speaker 16: You know, it's been interesting because over the last several
Speaker 16: years we've made sure that we're really focusing our engineering community,
Speaker 16: and we have a large engineering community on building the
Speaker 16: things that are competitively differentiating and great value for our
Speaker 16: customers and clients. And over time you have to balance
Speaker 16: where that still makes a lot of sense and where
Speaker 16: we focus our energy on those unique products and services
Speaker 16: for our customers and clients. And so when you think
Speaker 16: about the balance of trade and the fact that software
Speaker 16: engineering overall is increasing in speed and it is more
Speaker 16: cost effective when you look at the end to end
Speaker 16: product development life cycle. You know, there are different trade
Speaker 16: offs you would consider in making those build versus buy decisions,
Speaker 16: but you're always going to have some of those, you know,
Speaker 16: enterprise software solutions frankly that aren't competitively differentiated that sort
Speaker 16: of help us run the bank without delivering those unique
Speaker 16: products and services.
Speaker 6: Just twenty seconds.
Speaker 15: Do you think that we're going to be able to
Speaker 15: recognize what banking looks like, say, in ten years.
Speaker 6: I think we're.
Speaker 16: Watching it transform as we speak right now. At the
Speaker 16: end of the day, we have to maintain that trust
Speaker 16: with customers and clients and we have to make sure
Speaker 16: that their unique needs are served across the over one
Speaker 16: hundred countries we operate in. But how we do it
Speaker 16: and the products and services will absolutely evolve over the
Speaker 16: next several years.
Speaker 15: Caroline, that is Lori Beer, the chief information officer at
Speaker 15: GENP Market.
Speaker 6: I'll set it back to you.
Speaker 3: What a great day, what a great set of interviews.
Speaker 3: Thank you New Mexsavana's co hosting ROUMWA. It's there, and
Speaker 3: we've got some bocking news in the meantime.
Speaker 2: Yeah, it's some breaking news on the tunnel about Apple.
Speaker 2: Apple chief hardware Officer Johnny Shreuji, reorganizing hardware development and
Speaker 2: shifting oversight of key functions such as product design partner
Speaker 2: effort to speed up work on future devices. Sources say
Speaker 2: the hardware shakeup is also meant to better integrate teams
Speaker 2: working on in house silicon with those that are creating products.
Speaker 2: And of course Bloomberg's Mark Gum and the one carrier
Speaker 2: that broke the story some other detailed Shelly Goldberg Dave
Speaker 2: Pecula are now going to oversee product design. Maybe not
Speaker 2: names as familiar to the Bloomberg Tech audience, but in
Speaker 2: this new era for Apple, a lot of focus on
Speaker 2: who's right at the top and running the show.
Speaker 3: It will become known ed thanks mean while coming up, Look,
Speaker 3: we're going to be speaking with Armada CEO Dan Wright
Speaker 3: as the company raises to one of thirty million dollars
Speaker 3: in a series be funding boosting his valuation to two
Speaker 3: billion dollars, and some new strategic investors and big projects
Speaker 3: for the hyperscaler for the Edge as a Bloomberg Tech.
Speaker 4: Some more breaking news crossing the Blue terminal.
Speaker 2: Open AI founding member Andre Carpaty says he's joined rival
Speaker 2: and Thropic. In a post on x Carpappy says he
Speaker 2: will be working on R and D with Anthropic and
Speaker 2: be focused on helping train new AI models. Cope previously
Speaker 2: helped lead the team behind Tesla's autopilot system before then
Speaker 2: returning to Open Ai. He left the chat gp maker
Speaker 2: for a second time last year and had launched a
Speaker 2: startup focused on AI and education. In that post, carry
Speaker 2: he says that he's still passionate about education plans to
Speaker 2: resume his work on that, but in the market of
Speaker 2: AI talent, this is a bit of a wow. This
Speaker 2: is a big story that I didn't see coming breaking
Speaker 2: this morning.
Speaker 3: It certainly is. The wows keep coming. Meanwhile, let's talk
Speaker 3: about a fundraise now. Amada has just raised two hundred
Speaker 3: thirty million dollars in an oversubscribed Series B round, bosting
Speaker 3: the company's valuation to a call two billion dollars. But
Speaker 3: the company is also announcing a partnership with Johnson Controls
Speaker 3: to produce modular data centers and they're at scale joining
Speaker 3: us now. I'm oada CEO Dan Wright alsome modular data center?
Speaker 3: How are we going to be making it?
Speaker 4: Ye?
Speaker 17: So much for having me on a modular data center
Speaker 17: is a full stack AI factory that you can deploy anywhere,
Speaker 17: and we can do it with the three s's. We
Speaker 17: call it speed, scale, and sovereignty. You can deploy these
Speaker 17: within weeks. You can scale up with demand versus traditional
Speaker 17: data center sometimes you end up overbuilding or building the
Speaker 17: wrong thing. And then modular data centers also have the
Speaker 17: benefit that you can get sovereignty down to the site level.
Speaker 17: People used to talk about data sovereignty in terms of countries,
Speaker 17: but with increasingly sophisticated cyber attacks, now you want data
Speaker 17: sovereignty at the site level.
Speaker 2: This is all about speed, movement, building funding. This has
Speaker 2: helps you move even quicker or what's the plan here?
Speaker 17: Yeah, So this round was led by co ed by
Speaker 17: Overmatch eighty ninety industries as well as black Rock, and
Speaker 17: really what it allows us to do is scale up
Speaker 17: to accelerate deployment of the USAI stack. As part of this,
Speaker 17: we're also announcing a global agreement with John's Controls, where
Speaker 17: starting with Galleon Forge one in Arizona, we're going to
Speaker 17: do continuous manufacturing of these modular data centers. And if
Speaker 17: you look at them, they kind of look like shipping containers,
Speaker 17: so they're easily transportable anywhere in the world. You can
Speaker 17: deploy them whereever you want. And the nice thing is
Speaker 17: you can use any source of power, and that's obviously important.
Speaker 17: Power is a big concerned when it comes to data centers.
Speaker 17: Energy is distributed. We're saying compute should also be distributed.
Speaker 3: Where's the demand coming from? Exactly who wants these?
Speaker 17: Yeah, so energy companies. We're working with many of the
Speaker 17: largest energy companies in the world. All of them have
Speaker 17: a hard segregation between IT and OT, meaning that the
Speaker 17: only way to do anything with AI is to deploy
Speaker 17: the infrastructure on the rigs, on the refineries and run
Speaker 17: those models behind the firewall at the edge. We're enabling that.
Speaker 17: They're all trying to be fully autonomous over the next
Speaker 17: few years. You need compute locally in order to enable that.
Speaker 17: And then also defense is a huge driver for us.
Speaker 17: For example, with the conflict in the Middle East. We
Speaker 17: got a call from an ally. They said, hey, we
Speaker 17: need one of these like immediately. We were able to
Speaker 17: deploy within days. They called back said we need more.
Speaker 7: We were able to share more.
Speaker 3: Out and who your partners within this data center? I
Speaker 3: can understand that you're helping with the construction of it all,
Speaker 3: but still you need the chips from.
Speaker 7: Someone, you need the service of someone.
Speaker 3: How are you bringing this all together and how open
Speaker 3: are you to different types of partners?
Speaker 17: Well, well, I think that's actually part of the magic
Speaker 17: of Armada is that we built this ecosystem of amazing
Speaker 17: partners and it's kind of like, actually, what the hyperscalers did.
Speaker 7: You know twenty years ago?
Speaker 17: Is you're bringing all of these different services and you're
Speaker 17: making them accessible to more people. That's what Armada is
Speaker 17: doing for the edge is the Hyperscaler for the edge.
Speaker 17: And a good example of this we just announced a
Speaker 17: partnership recently with Microsoft to bring Foundry, bring Azure Local,
Speaker 17: allow them to run these customers to run services that
Speaker 17: they love from Microsoft models that they run from Microsoft
Speaker 17: at the edge air Gap.
Speaker 7: Same thing.
Speaker 17: We announced a partnership with Opening Eye. We announced on
Speaker 17: with Nvidia, Dell as well as Pallenteer bringing all those capabilities.
Speaker 7: To the edge.
Speaker 2: So Dan real quick. I was with Michael Dell and
Speaker 2: jensmong yesterday. The bigger theme is on prem people want
Speaker 2: at the edge facility close to them. Is that an
Speaker 2: addressable market for you. We just have thirty seconds.
Speaker 7: Yeah, absolutely.
Speaker 17: I mean that's what I believe is going to happen,
Speaker 17: is you're going to have sovereign AI factories. And really
Speaker 17: what that means is that every country and every company
Speaker 17: is going to have its own AI factory. And I
Speaker 17: know that Michael and Jensen would agree with me on
Speaker 17: that because they've been saying that publicly. And in order
Speaker 17: to do that, you need both the chips, you need
Speaker 17: the servers, and then you also need the infrastructure, and
Speaker 17: that's what are enabling as the hyperscaler.
Speaker 7: For the edge.
Speaker 2: Then right, I'm out a CEO back on Bloomberg Tech
Speaker 2: after a big fundraise. Great to have you back. Thank
Speaker 2: you very much. That does it for this edition of
Speaker 2: Bloomberg Tech Carrot.
Speaker 3: Yeah, you don't want to forget to check out this podcast.
Speaker 6: What a rich podcast.
Speaker 3: We're going to be having all eyes as we build
Speaker 3: up towards the videos earnings after the bal tomorrow.
Speaker 7: You can find it on.
Speaker 3: The terminal as well as online on Apple, Spotify and
Speaker 3: iHeart ed still a phenomenal interview from yesterday as well.
Speaker 2: Yeah, and you know the market is waiting anticipation for
Speaker 2: the Nvidia Print Wednesday night post melt up in chip stocks.
Speaker 4: Wow, this is Bloomberg Tech. H