Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive
Speaker 1: from Coast to Code with Caroline Hide in New York
Speaker 1: and vl Loow in San Francisco.
Speaker 2: This is Bloomberg Tech coming up.
Speaker 3: Core.
Speaker 4: We've signed a deal to supply Meta with as much
Speaker 4: as fourteen point two billion dollars worth of computing power.
Speaker 5: Plus a change of leadership at Spotify, a CEO Daniel
Speaker 5: Ck stepping aside after almost two decades.
Speaker 4: And Anthropic releases a new AI model designed to code
Speaker 4: longer and more effectively than prior versions. We speak with Aropis,
Speaker 4: chief product officer, but.
Speaker 5: First ed we are both here in New York this
Speaker 5: week and checking out the markets that are just taking
Speaker 5: a pause amidst some macro focus. Of course, TENSI shutdown
Speaker 5: of the US government that's on every investor's mind. What
Speaker 5: does that mean in terms of data to what does
Speaker 5: it mean in terms of the future of rape policy
Speaker 5: the FED. We're currently completely flat, just pinching into the
Speaker 5: green on the Nastet one hundred, but it's way more
Speaker 5: interesting underneath the hood and you're looking at that.
Speaker 4: Yeah, our top story is Core, Weave and Meta. It's
Speaker 4: the latest Core Weave capacity deal fourteen point two billion dollars.
Speaker 4: The stock has been on a tear since it's listing
Speaker 4: in March right now trading at its highest level in
Speaker 4: around six weeks. Clearly that big game following the Bloomberg report,
Speaker 4: The market's kind of focused on this idea, that is
Speaker 4: evidence core weaves move beyond one single customer, which is Microsoft.
Speaker 4: But actually, as Brodie up Forward often says, carry the
Speaker 4: devil's in the detail on this one.
Speaker 5: Let's get that detail, Dy forward with us. You help
Speaker 5: break the story. Core weave has tripled since it's IPO.
Speaker 5: We're up another fifteen percent. What does it mean to
Speaker 5: be adding Meta to the fold as well as open
Speaker 5: Ai more recently of course in Microsoft O.
Speaker 6: Well, it means that core Weave isn't just a colonial
Speaker 6: state of Microsoft.
Speaker 7: Right.
Speaker 6: That was the concern for so long with these neo
Speaker 6: clouds that gosh, if their biggest customers are companies that
Speaker 6: also effectively compete with them, that seems like a pretty
Speaker 6: indefensible business. But you start getting companies like Meta and
Speaker 6: open Ai who are likely to be longer term buyers
Speaker 6: of this technology, and so I think folks are getting
Speaker 6: more comfort that Corewave and companies like it may have
Speaker 6: a more sustained place in this AI infrastructure build out.
Speaker 4: Fourteen point two billion dollars is a very large number, Brodie,
Speaker 4: But the terms of the contract extent of twenty thirty two.
Speaker 4: You know what I'm going to say, because we discussed
Speaker 4: it this morning. There is skepticism here because there are
Speaker 4: many unknowns. For example, does call We've actually have a
Speaker 4: data center somewhere that's built and operating that they can
Speaker 4: assign Meta's workloads too.
Speaker 2: Well.
Speaker 6: What the CEO told me is that they never sign
Speaker 6: a deal if they don't have the right power and
Speaker 6: data center allocation ready to go. I don't think there's
Speaker 6: a data center that they're just going to flip on
Speaker 6: and say, aren't Meta here you go. But you know,
Speaker 6: this contract goes till twenty thirty one. They're probably going
Speaker 6: to need to buy a bunch of chips, fill it
Speaker 6: up and hand it over to Meta. And what that
Speaker 6: also means is they're going to take out a lot
Speaker 6: more debt. I mean, Corewave is kind of famous at
Speaker 6: this point for levering itself up to a pretty incredible degree,
Speaker 6: and we'll probably see a little more of that.
Speaker 4: The role of debt in financing AI infrastructure. That's becoming
Speaker 4: a story of the year twenty twenty five, Blue Most
Speaker 4: Brady Ford with the core we've metastory.
Speaker 2: Thank you.
Speaker 4: Meanwhile, AI's boom is sending investors searching for trades in
Speaker 4: an overlooked group, suppliers of the gear used to make chips.
Speaker 4: Let's bring in Bloombos Tech equity reporter Ryan blaceelca lots
Speaker 4: of readership on this story and some names that have
Speaker 4: not been at the forefront of what's happened within the semispace.
Speaker 2: Give us your reporting.
Speaker 8: Hey, good morning, Thank you for having me so. Yeah,
Speaker 8: this is a trend that we have been seeing throughout
Speaker 8: twenty twenty five now that some of the more well
Speaker 8: known AI trade seems like maybe those are getting a
Speaker 8: little bit mature. Investors are looking elsewhere. We've seen it
Speaker 8: in storage companies, We've seen it in memory companies, So
Speaker 8: now we're seeing it in the semiconductor capital equipment companies
Speaker 8: named like LAMB Research, Applied Materials, KLA Core, Terradyne. These
Speaker 8: kinds of companies which make the equipment that is used
Speaker 8: for building the semiconductors. Building all this manufacturing out these
Speaker 8: are getting sort of a second derivative move. Given the
Speaker 8: sheer build out we're seeing all the chips that are
Speaker 8: required for AI, obviously it's going to mean higher demand
Speaker 8: for the chip for the machines that make those chips.
Speaker 5: We constantly question valuations, ran should we be worried about them
Speaker 5: for these names?
Speaker 8: Well, I'd say if we were talking about this maybe
Speaker 8: a month or so ago, it would be a lot
Speaker 8: less of a ponent issue. But some of these companies
Speaker 8: have really seen very steep rises. They've really become momentum
Speaker 8: favorites over the past couple of weeks and months, and
Speaker 8: I think right now they are getting to a little
Speaker 8: bit more elevated levels. But certainly they are not sort
Speaker 8: of a nosebleed, real sort of bubble kind of valuation,
Speaker 8: but they certainly come up a lot from where they
Speaker 8: were earlier this year.
Speaker 4: Ryan, if you walk into a fab the clean room
Speaker 4: where semi condut is are manufactured, along the line is
Speaker 4: machines for lots of different companies. At the beginning of
Speaker 4: that line, you're probably likely to have one from LAMB Research.
Speaker 2: The chart that we took from your.
Speaker 4: Story shows LAMB being a real outperformer here.
Speaker 2: Is there anything more to know about that name.
Speaker 8: I think they are one that especially used with Micron,
Speaker 8: so the memory chips that has been another area of
Speaker 8: focus this year, so that high bandwidth memory. I believe
Speaker 8: that LAMB works on machines that are used in those
Speaker 8: I think that's probably certainly a component to their business there.
Speaker 5: Ran, So it's great to catch up with you, Ran, Plaselkah.
Speaker 9: We appreciate it.
Speaker 5: Meanwhile, sticking with chips at Taiwan's premiere, says that trade
Speaker 5: talks with the United States have ended, quote the crucial
Speaker 5: closing stages, indicating the global chiphub is finally nearing a
Speaker 5: deal with the Trump administration.
Speaker 10: Now.
Speaker 9: Investment in the US was.
Speaker 5: Among the issues discussed in Washington in recent days, according
Speaker 5: to a source, as well as lowering the twenty percent
Speaker 5: tariff imposed on the island ed.
Speaker 2: Yeah. Some other news we're tracking.
Speaker 4: Google's agreed to pay twenty four point five billion dollars
Speaker 4: to resolve Donald Trump's claims that being blocked from posting
Speaker 4: on his YouTube channel after the January sixth, twenty twenty
Speaker 4: one riot at the US Capitol amounted to illegal censorship.
Speaker 4: That's according to a court filing which also shows twenty
Speaker 4: two million dollars. We'll go toward construction of a new
Speaker 4: ballroom in the White House, a project near and dear
Speaker 4: to Trump, while the remainder will go to a handful
Speaker 4: of other plaintiffs who joined him in legal action. Okay,
Speaker 4: Coming up, and Thropic has a new AI model that
Speaker 4: codes on its own for up to thirty hours straight.
Speaker 4: No need to feel it soylent, no red bull, and
Speaker 4: Thropic chief product officer talks to us about Claude Sonnet
Speaker 4: four point five A conversations.
Speaker 2: Next, this is Bloomberg Tech.
Speaker 4: Deep Seak update is an experimental AI model, calling it
Speaker 4: a step toward next gen AI. The latest version introduces
Speaker 4: a new technique it calls deep Seek Sparse Attention or DSA,
Speaker 4: a mechanism designed to explore and optimize AI training and
Speaker 4: operation and improve efficiency when processing long tech sequences.
Speaker 5: Correct, let's stick on the models AI startup Anthropic is
Speaker 5: that with a new one Claudes on it four point five.
Speaker 5: The company says it can code longer, more effectively than
Speaker 5: prior versions. Let's get more with Anthropics chief product officer
Speaker 5: Mike Kreger.
Speaker 9: Mike, it's wonderful.
Speaker 2: How to have you on.
Speaker 5: Thirty hours straight is how long then it can code
Speaker 5: on its own? What are the technical feats needed to
Speaker 5: be able to go that long where humans can well
Speaker 5: definitely not survive that unless as a whole load of
Speaker 5: caffeine involved.
Speaker 11: Good morning.
Speaker 12: I think one of the main advancements we made was
Speaker 12: around memory and what we call context management.
Speaker 11: So if you think.
Speaker 12: About how you human works for longer periods of time,
Speaker 12: you're writing things down, You're making sure you can always
Speaker 12: pick up where you're left off if you're coming back
Speaker 12: the next day. So with cloud sign It four point five,
Speaker 12: we did a lot of work on that memory management.
Speaker 12: So the model, if you think about it, sort of
Speaker 12: writes down what it's doing, keeps track of its state,
Speaker 12: and then if it needs to sort of backtrack a
Speaker 12: table to then keep going. And that's how it's able
Speaker 12: to stay coherent for a much longer period of time
Speaker 12: than any other of our models.
Speaker 5: How much you've managed to lower therefore those ideas of
Speaker 5: inaccuracies or more broadly, that well that they're making things up.
Speaker 5: Hallucination has always been the key issue. Heren't been something
Speaker 5: that's limited edgentic AI adoption.
Speaker 12: Yeah, this is the model that we have that is
Speaker 12: also besides being our most powerful, is also are safest
Speaker 12: and most coherent, so as the lowest hallucination rate, and
Speaker 12: is the least susceptible to things like jail breaks.
Speaker 11: And I think that matters a lot. I think I
Speaker 11: tell my product.
Speaker 12: Team all the time, it's no use going for twenty
Speaker 12: thirty hours if you're making mistakes along the way, and
Speaker 12: so having it be both accurate producing good code that's
Speaker 12: the prerequisite, and then you can focus on scaling up
Speaker 12: on the time horizon.
Speaker 4: Mike, can we talk a bit about the audience for
Speaker 4: claudes on at four point five. The real emphasis from
Speaker 4: Entropic from the early days was enterprise customer as opposed
Speaker 4: to a sort of direct consumer. But this field of
Speaker 4: tools for the developer is expanding. It's probably more competitive.
Speaker 4: Who are you hoping uses this?
Speaker 12: It's really we've taken a business focus, but that also
Speaker 12: manifests kind of in the prosumer space, and so we
Speaker 12: have a lot of what we call power users who
Speaker 12: might be developers or might just be early adopters who
Speaker 12: want to bring AI to their work. So one of
Speaker 12: the things that SIGNUT four point five can do, along
Speaker 12: with writing code, is also creating really professional looking word
Speaker 12: and PowerPoint and Excel documents. It actually uses the same
Speaker 12: coding capabilities under the hood, but not to write code,
Speaker 12: but instead to produce documents. And that sort of capability
Speaker 12: means that we're starting to see adoption in the enterprise
Speaker 12: as well.
Speaker 4: Mike, you and I have discussed this in the past.
Speaker 4: We know Mike Krieger as Mike Krieger CTO Instagram, And
Speaker 4: what I'm seeing right now in the field of your
Speaker 4: peers is the reports on open Ai and what Meta
Speaker 4: is doing in social media and video. Is that a
Speaker 4: direction you want the product team to take, claud.
Speaker 12: In, We're focused much more on the productivity use case,
Speaker 12: and so when I think about our roadmap, it's very
Speaker 12: much how do we take workoff people's hands, or how
Speaker 12: do we accelerate folks and make them, you know, the
Speaker 12: work the best that it can be. How do we
Speaker 12: automate your work in the browser? So much more on
Speaker 12: that productivity side of things, and I don't think you'll
Speaker 12: see us play very much in that entertainment space.
Speaker 5: Might productivity perspective. It's come under some concerns recently. Think
Speaker 5: about the MIT report everyone's suddenly talking about this only
Speaker 5: well ninety five percent of the tests were basically failing
Speaker 5: out there in the wild. How are you making sure
Speaker 5: that enterprises adopt your products but actually see the productivity
Speaker 5: gains from them.
Speaker 12: I think this is really important, where if you know,
Speaker 12: AI gets brought into the workplace without the right either
Speaker 12: tools around it or enablement, what you end up with
Speaker 12: is this disillusionment a couple of months later around while
Speaker 12: folks aren't adopting it, or yeah, it helped me a
Speaker 12: little bit, but not enough. And so we have a
Speaker 12: lot of emphasis on let's.
Speaker 11: Make sure the work is actually good.
Speaker 12: You know, you might hear this word online like slop,
Speaker 12: where AI is creating work that actually just is not
Speaker 12: very good. And I think of us, we're trying to
Speaker 12: produce the anti slop work that actually, you know, maybe
Speaker 12: gets you eighty percent of the way there, but it's
Speaker 12: eighty percent that then lets you complete the work in
Speaker 12: a way that you're proud of, rather than you know,
Speaker 12: opes it did something, but now I feel like I
Speaker 12: have to start over because it didn't really help. So
Speaker 12: I think that's the really key piece for enterprise adoption.
Speaker 5: And therefore, does it remove the need for so many
Speaker 5: people or ultimately there's still this argument this can all meant,
Speaker 5: but will it start to replace?
Speaker 12: Mike, we think a lot about what, you know, the
Speaker 12: comparative advantages are of people, you know, as relates to AI.
Speaker 12: There's a lot of still relationship building and trust, critical
Speaker 12: analysis and strategy that really comes on the human side
Speaker 12: of things, and so we really try to design tools
Speaker 12: that as much as possible play up those parts of
Speaker 12: that human AI interaction, knowing that you know there will
Speaker 12: be you know, laborships that are almost inevitable, but if
Speaker 12: we can design our products along the way to maximize
Speaker 12: both people's understanding of AI but also their use in
Speaker 12: a complementary way.
Speaker 4: Mike, open a eyes holding dev day next Monday. It's
Speaker 4: probably on your calendar for peripheral awareness. But I'm very
Speaker 4: conscious that you're kind of speaking to us twenty four
Speaker 4: hours after the news of clots on four point five
Speaker 4: km out. Have you any data on the sort of
Speaker 4: reaction to it, early demand and where that's coming from.
Speaker 12: It's been really interesting how quick people are to adopt
Speaker 12: a new model. So by I think about one pm yesterday,
Speaker 12: we already had more usage of clouds on at four
Speaker 12: point five than all of our other models combined, which
Speaker 12: really speaks to the eagerness of a lot of these
Speaker 12: startups that are building on top of our models, as
Speaker 12: well as early adopters to on day one you saw
Speaker 12: GitHub and Cursor and Windsurf and many of these products
Speaker 12: that build on top of our models want to incorporate
Speaker 12: clouds on at four point five, and so we had
Speaker 12: this really early crossover moment as well.
Speaker 2: That is interesting data.
Speaker 4: Correct me if I'm wrong, But this model is running
Speaker 4: on Project Rainier, right, is that sort of operationally and
Speaker 4: infrastructure wise where the training and now inference of it
Speaker 4: is being done.
Speaker 12: So we do our both training and inference across You know,
Speaker 12: we have partnerships with Google and Amazon, but we have
Speaker 12: a significant part of this model being served now from
Speaker 12: Amazon as well, and we're seeing a lot of growth
Speaker 12: on a tobospedrock as well.
Speaker 5: Just going to that infrastructure layer. You're obviously the product
Speaker 5: visionary here, but you need to have the energy the
Speaker 5: compute to bring your products to life. Many worrying that
Speaker 5: we're in some sort of bubble cycle around AI. How
Speaker 5: do you think about that as you drive this business forward?
Speaker 12: Might I think there's this combined need to both scale
Speaker 12: up for the training side, but also on inference. And
Speaker 12: as we've scaled, especially with our business arrangements and the
Speaker 12: companies building on top of son it, I think we
Speaker 12: now have a sort of forward looking perspective on what
Speaker 12: our inference needs will be, and I think that'll let
Speaker 12: us go out and also secure the kinds of compute
Speaker 12: deals that we need to both feel the training but
Speaker 12: also have that sort of revenue generating inference side as well.
Speaker 5: And we get so focused on the compute needs of
Speaker 5: the United States, but we've been talking a lot about
Speaker 5: that in Europe. How it's scaling in the UK. From
Speaker 5: your adoption, how are you seeing things different globally MIC,
Speaker 5: Because those that are actually deploying what's happening with Sonnet
Speaker 5: four point five in the latest models, we see this
Speaker 5: a lot.
Speaker 11: In terms of our global footprint.
Speaker 12: There's something we started expanding earlier this year, and so
Speaker 12: for our rollout of Trainium too, which is the chip
Speaker 12: that Amazon has built for a WS that we use
Speaker 12: pretty extensively for our cloud models. A lot of that
Speaker 12: deployment is actually international, and when I go to Europe,
Speaker 12: for example, I hear a lot of questions about data
Speaker 12: locality and making sure that inference is happening in local
Speaker 12: data centers.
Speaker 11: And the only way we're going to be.
Speaker 12: Able to do that is to have that international footprint
Speaker 12: of these chips.
Speaker 11: And so you've seen the same in APEC.
Speaker 2: Mike.
Speaker 4: We are going to ask you a question about talent wars,
Speaker 4: but I'm just going to make an appeal to you
Speaker 4: to just be honest with me on this. How big
Speaker 4: a factor it is or isn't for you right now?
Speaker 4: In the product team at Anthropic in particular, I'm looking
Speaker 4: at the pace at which open ai is putting stuff out,
Speaker 4: Meta is putting stuff out. Just through your experience, what's
Speaker 4: the talent situation right now?
Speaker 12: I'm seeing much more of that talent sort of you know,
Speaker 12: back and forth happen within the research site in general,
Speaker 12: a little bit less on the product. I think there's
Speaker 12: some key hires where that's been the case. One thing
Speaker 12: that's been a positive sort of maybe surprise or just
Speaker 12: outcome of how mission oriented a lot of Anthropic, a
Speaker 12: lot of the Entropic team really is has been. It's
Speaker 12: affected us very minimally in terms of that back and
Speaker 12: forth that you're seeing maybe among some of the other
Speaker 12: frontier labs, which.
Speaker 11: Is very encouraging.
Speaker 12: Of course, you have to continue to make sure we
Speaker 12: build a great culture and maintain that mission alignment.
Speaker 11: But so far it's it's been minimally affecting us.
Speaker 4: If we take so on it. Four point five is
Speaker 4: the case study. What were the types of roles that
Speaker 4: you needed to bring in to roll out the release.
Speaker 12: I think people think of, you know, research and model
Speaker 12: science as being fairly cut and dry. I actually think
Speaker 12: that there's a lot of art and taste to it
Speaker 12: as well. You are making a lot of decisions from
Speaker 12: a research engineering perspective around what are the task the
Speaker 12: model needs to improve on, how will it improve on that,
Speaker 12: how will we know that it's improving on that? And
Speaker 12: so a lot of that reinforcement learning post training piece
Speaker 12: is the key shape of what we really thought about.
Speaker 11: And son at four point five.
Speaker 4: My creagain andthropic chief product off. So it was a
Speaker 4: real deep dive into Sonnet four point five. Thank you
Speaker 4: so much for joining us. Back on Bloombo Tech, I've
Speaker 4: coming up on the show Door Dash has a new
Speaker 4: autonomous robot.
Speaker 2: Meet Dot, Hi Dot.
Speaker 4: We'll talk to the VP of door Dash Labs about
Speaker 4: what this robot delivers.
Speaker 2: In terms of its capabilities. That's next. This is Bloomberg tech.
Speaker 4: Delivery company door Dash is unveiling a new autonomous delivery
Speaker 4: robot called Dot. The company says Dot is the first
Speaker 4: commercial delivery bot to seamlessly navigate bike lanes, roads and sidewalks.
Speaker 4: His stirs more actually read vice president of door Dash Labs.
Speaker 4: This robotics experience includes work with zooks and video, but
Speaker 4: the real terms parameters for deployment, which cities, how many
Speaker 4: deliveries when.
Speaker 3: So, we have been focusing on the greater Phoenix area
Speaker 3: and that's our focus for this year. We are hoping
Speaker 3: to address about one point five million customers by the
Speaker 3: end of this year, and then you know, as we progress,
Speaker 3: we'll see what happens. DoD likes to travel though, so
Speaker 3: hopefully we can expand to more cities.
Speaker 4: Team, let's bring up some pictures of Dot again. I
Speaker 4: mean to me assue you that this looks kind of
Speaker 4: the design like a bit like a stroller or a
Speaker 4: pram as we might have said in the United Kingdom.
Speaker 4: Could you just talk us through the design of it
Speaker 4: and how this is what you arrived at.
Speaker 11: Sure.
Speaker 3: So there were three sort of key pillars for us
Speaker 3: when we looked into the line of Dot. The first
Speaker 3: one was product market fit, so we wanted to make
Speaker 3: sure that Dot would have the right cargo capacity and
Speaker 3: the payload that it can carry up to thirty pounds
Speaker 3: fits a vast amount of the door dash deliveries that
Speaker 3: we do today. The other big part was it had
Speaker 3: to be going at speeds that allowed us to do
Speaker 3: a big chunk of deliveries in the three to mile range,
Speaker 3: and that's why the design point was it needs to
Speaker 3: be able to go on bike lanes, on roads, on sidewalks.
Speaker 3: But the other key part is the pickup and drop
Speaker 3: off for deliveries, which makes it very different from right hail.
Speaker 3: And one of the key feedbacks we had gotten from
Speaker 3: merchants was it is absolutely imperative to have the robot
Speaker 3: come as close as possible to the merchant, right next
Speaker 3: to the doorstep, which is what Dot does, and so
Speaker 3: that was a key design feature, was that it could
Speaker 3: go on sidewalks and be sort of narrow enough to
Speaker 3: navigate sidewalks.
Speaker 5: And pretty well that what our shoe currently isn't on
Speaker 5: the market because you're already using Coco Robotics spat by
Speaker 5: some aaltman. There are others on the market. Isn't just
Speaker 5: the speed the pace that they can't meet.
Speaker 3: Yeah, So we actually also announced as the key product
Speaker 3: called the Autonomous Delivery Platform, which we actually in which
Speaker 3: all our partners, including Coco and our drone partners and
Speaker 3: other robots including Dot can participate. And the idea is
Speaker 3: that as the demand for delivery is growing, we have
Speaker 3: an all of the above approach, which is there'll be dashers,
Speaker 3: they'll be drones, they'll be Dot and so we are
Speaker 3: looking to work with all of our partners to enable
Speaker 3: this different modalities. So we believe the future will be
Speaker 3: multi modal for our delivery. And that's this is the
Speaker 3: first step towards.
Speaker 5: That I cycle every day, I navigate dashes. How will
Speaker 5: how many dashes will I be navigating in the future?
Speaker 5: Is this going to replace careers in the long term?
Speaker 5: How haven't much of a percentage do you want delivered
Speaker 5: by Dot?
Speaker 3: Well, we don't look at this as a percentage. We
Speaker 3: look at it as just a growing pie. So if
Speaker 3: you think about the just over the last few years, DoorDash,
Speaker 3: the demand for delivery has been growing significant a year
Speaker 3: over year. So we think of this as like I
Speaker 3: said before, it's just going to be multimodel. There are
Speaker 3: going to be many, many different forms of delivery. And
Speaker 3: you look at the range of deliveries we do. If
Speaker 3: you just look back to you in five years ago,
Speaker 3: we were doing mostly restaurants. Now DoorDash does groceries, It
Speaker 3: does household items like you know, toothpaste or diapers, even
Speaker 3: home electronics.
Speaker 11: You can buy a.
Speaker 3: Complete laptop on door Dash and have it delivered to
Speaker 3: your door step. So we expect all kinds of deliveries
Speaker 3: to be happening on our platform. And this ADP that
Speaker 3: we announced yesterday is the first step towards at.
Speaker 4: Ashu who is going to manufacture dot and where will
Speaker 4: they manufacture dot?
Speaker 3: So at this point we are you know, going through
Speaker 3: that process of figuring out all the all of the
Speaker 3: pieces of where the manifest actually is going to be
Speaker 3: and where you know, all the components, et cetera.
Speaker 2: So it's not decided, it's still.
Speaker 3: Being discussed internally as to how we will end up doing.
Speaker 5: This is the aim to have it largely us.
Speaker 3: Made, so we you know, a big the technology that
Speaker 3: we have developed here is all built here in the
Speaker 3: US in Indoor Dash Labs, so it's pretty much purpose built,
Speaker 3: homegrown robot, you know, and it uses a state of
Speaker 3: the art technology, again developed by the engineer's at door Dash.
Speaker 3: It is fully LPHO autonomous system, so it, you know,
Speaker 3: as you can see, navigates through all of the various
Speaker 3: situations that can encounter, whether it is pedestrians or cars,
Speaker 3: and again going up in sidewalks, going up to your doorsteps,
Speaker 3: lots of pedestrian and what are called vr US vulnerable
Speaker 3: road users which means kids, pets, and so on. So
Speaker 3: all of that technology was developed in DoorDash Labs.
Speaker 5: So motoring along at twenty miles an hour next to
Speaker 5: me on the cycle lane, so surely I'm sure she
Speaker 5: thanks so much for joining us. Shue Reggae, vice president
Speaker 5: of door Dash Labs at door Dash and coming up
Speaker 5: AI chip startup Cerebras Systems. Well, it's closed a new
Speaker 5: funding round an over eight billion dollar valuation. We're going
Speaker 5: to talk to the CEO Andrew Folman, because remember this
Speaker 5: is a company that actually wanted to IPO. Does that
Speaker 5: delay that inevitable? We could talk the ambitions next and
Speaker 5: what are you looking.
Speaker 4: At to private markets, conversation, in equity markets and technology,
Speaker 4: there is some stuff going on. I mean the broad
Speaker 4: story is that we are basically flatten the now's like
Speaker 4: one hundred traders are in weight and see mode.
Speaker 2: Will we get some economic data? Will we not?
Speaker 4: But we know the big story out there on the
Speaker 4: single mover side is core weave up thirteen percent, highest
Speaker 4: level than six weeks on a fourteen point two billion
Speaker 4: dollar compute deal with Meadow, which is down one and
Speaker 4: a half percent. So much more to come on the show,
Speaker 4: stay with us. This is Bloomberg Tech.
Speaker 5: Welcome back to Bloomberg Tech. Let's check in on these
Speaker 5: markets because on the surface some calm, we're currently off
Speaker 5: by just a quarter percent, and then adds that one
Speaker 5: hundred anxiety about a potential government shut down here in
Speaker 5: the US. What does that mean for key data in
Speaker 5: the jobs market, particularly on Friday? What does it mean
Speaker 5: for the federal Reserve? We stampat in terms of big tech,
Speaker 5: but underneath the hood, let's look at individual movers because
Speaker 5: there are some big deals being done.
Speaker 9: Once again in the spectrum space.
Speaker 5: We are having the best month for EchoStar on record,
Speaker 5: at more than twenty percent because it keeps on selling
Speaker 5: Spectrum this time we understand it's likely to be selling
Speaker 5: to Verizon. There's talks of Plum and the moment for
Speaker 5: AWS three licenses. Already they've been selling to AT and
Speaker 5: T and SpaceX. Let's have a little look at what's
Speaker 5: also on the move. Big deals being done in AI compute.
Speaker 5: We're going to delve into that throughout this section. We're
Speaker 5: up twelve thirteen percent on Core. Weave fourteen billion dollar
Speaker 5: deal to Meta Yet more GPU access, more compute, but
Speaker 5: we've got plenty more when it comes to the world
Speaker 5: of AI infrastructure.
Speaker 11: ED.
Speaker 4: Yeah, a lot more happening in technology in private market.
Speaker 4: It's AICHIP making startups. Rebrest Systems Is is a one
Speaker 4: point one billion dollar funding round Cerebras, which aims to
Speaker 4: rival and Video Now, has a post money valuation of
Speaker 4: eight point one billion dollars. The company's CEO, Andrew Feldman,
Speaker 4: joins us for more. Andrew, good morning, Welcome to Bloomberg TEG.
Speaker 4: You know, my assessment with cerebras is is that you
Speaker 4: claim that the technology is as competitive or better than
Speaker 4: what in Vidia's systems offer, and you are aggressively building
Speaker 4: out that infrastructure, and you are doing deals with end
Speaker 4: customers in the context of this funding round, what's your
Speaker 4: priority here?
Speaker 10: Sure, I think it's not just what we think. Every
Speaker 10: third party benchmark has shown that we are ordered twenty
Speaker 10: times faster than in video GPUs AT for inference work.
Speaker 10: So that's for the using of AI. And so this
Speaker 10: is the largest and sort of fastest growing part of
Speaker 10: the market. So we wanted to fuel our continued extraordinary growth.
Speaker 10: And so we're going to use this money to double
Speaker 10: our manufacturing capacity. We manufacture in the US, and we're
Speaker 10: going to double in the US, to extend our footprint
Speaker 10: more data centers so we can support more customers and
Speaker 10: those are in the US as well, okay, and to
Speaker 10: continue to invest behind our pioneering technology which has sort
Speaker 10: of solved problems that were open for seventy five years
Speaker 10: in the compute.
Speaker 4: Industry andrew to what extent you supply constrained? In other words,
Speaker 4: you have all of these customers, are you having to
Speaker 4: choose who gets first DIBs when some capacity comes online?
Speaker 10: Right now, one of the most challenging components is to
Speaker 10: get access to data centers, and those are some of
Speaker 10: the massive contracts you discussed in your previous segment with
Speaker 10: Core that they're providing to the like of Meta. Meta
Speaker 10: is also one of our customers. But the ability to
Speaker 10: stand up and deliver data centers filled with our gear
Speaker 10: so that our customers can enjoy the benefit of the
Speaker 10: fastest inference through the cloud is one of the limiting factors.
Speaker 2: Right now.
Speaker 5: You've got what five new data centers just in the
Speaker 5: course of twenty twenty five. Looking at Dallas, Oklahoma City,
Speaker 5: look at Santa Clara. What's really interesting, Andrew is that
Speaker 5: where are you building? Are you literally going out there building?
Speaker 5: Are you just trying to win future relationships with a
Speaker 5: Core weave so that they take your compute rather than
Speaker 5: of Nvidia.
Speaker 10: Well, I think we are renters of data centers. We
Speaker 10: are not builders of data centers, and so we partner
Speaker 10: with those who own the real estate and those who
Speaker 10: stand up the facility. We fill the facility, We rent
Speaker 10: the facility, and then fill it with our infrastructure. Infrastructure
Speaker 10: is then used by customers around the world, either by
Speaker 10: the by the day, by the month, by the token
Speaker 10: to get their fast AI and so I think that's
Speaker 10: the way we think about it.
Speaker 5: Caroly Andrew, we think about your customers and you're mentioning
Speaker 5: the likes of Meta. I'm interested in also where the
Speaker 5: money has been coming from for this round, because I
Speaker 5: noticed that one of your key backers of the past
Speaker 5: isn't on the list, seems G forty two key investor
Speaker 5: in previous and of course Middle East and based relationships
Speaker 5: potentially CEO with China, and that's been an issue for
Speaker 5: Syphius in particular, if you wanted to IPO, have you
Speaker 5: decided not to take money from them this time?
Speaker 10: No, that wasn't That wasn't the situation at all. I
Speaker 10: think it is very common in your dash to get
Speaker 10: to being public to raise raise a late stage round
Speaker 10: from public market investors. Around was led by Fidelity in
Speaker 10: a treatise. It included Tiger Global Valor seventeen eighty nine,
Speaker 10: It included Alpha Wave, all of whom have large and
Speaker 10: predominant public market practices, and so I think this was
Speaker 10: a round that was aimed at a different class of investor.
Speaker 10: We are continuing to collaborate with G forty two. They
Speaker 10: are our strategic partner. We are building enormous clusters in
Speaker 10: the US for them. We are training models, We are
Speaker 10: serving models, including one that they built in partnership with
Speaker 10: their leading university in the UA, nbz UAI, so that
Speaker 10: partnership remains rock solid.
Speaker 2: Andrew quickly.
Speaker 4: Then the obvious question is does your ongoing association with
Speaker 4: G forty two preclude you from pushing forward within investment
Speaker 4: based on the history of the Syphius review.
Speaker 10: Well, not at all, not at all. I think each
Speaker 10: investor has their their own appetite by stage, and what
Speaker 10: we found in this round was that the lead investors
Speaker 10: had a very large appetite and so we were able
Speaker 10: to meet that appetite. We cleared Syphius in March, and
Speaker 10: so there is nothing blocking the IPO.
Speaker 5: So when, Andrew, when in mid March we cleared when
Speaker 5: will you IPO?
Speaker 9: Dare we ask?
Speaker 10: Yeah, that's the big question. I appreciate you asking, and
Speaker 10: as you also know, I'm unable to tell you with
Speaker 10: S one on file, but I appreciate it.
Speaker 5: We keep the dance going, Andrew Fellman, it's so good
Speaker 5: to have you Ceo Cerebra systance. We appreciate it.
Speaker 1: Lott.
Speaker 5: We go stick with AI infrastructure now, because spending has
Speaker 5: been dominant theme inequities ever since CHATCHYBT ten. Everyone's attention
Speaker 5: to the technology, and of course it's compute needs. But
Speaker 5: the proliferation of data centers across the United States is
Speaker 5: putting pressure on energy supply and sending wholesale electricity costs
Speaker 5: a sawing for you for customers paying their bills. It's
Speaker 5: more on this with the big take. Let's bring in
Speaker 5: Bloombog pot Power reporter Josh saul Sot of Bloomberg Data
Speaker 5: is reporter Leo Nicoletti, and I start with you, Josh,
Speaker 5: the compute You go down to the individuals this is
Speaker 5: affecting you, particularly go to Baltimore. Can you tell us
Speaker 5: a little bit about how you found these individuals and
Speaker 5: what the effect on them is of Well, basically all
Speaker 5: the data center is being built pretty close to.
Speaker 11: Them, right.
Speaker 7: So the headline here is that data centers and their
Speaker 7: massive power demands are driving up power bills for everyone.
Speaker 7: The people that we spoke to in Baltimore are some
Speaker 7: we found because they had testified in a city council
Speaker 7: meeting about their bills. Some we found because they were
Speaker 7: eating eggs next to us at a diner. We talked
Speaker 7: to a lot of people and everyone's really upset and
Speaker 7: having a hard time paying their power bills because of
Speaker 7: this effect.
Speaker 2: Leo.
Speaker 4: This is the latest in a series really of pieces
Speaker 4: of data journalism from this newsroom about the impact of
Speaker 4: the buildout in data centers. Just explain methodology and the
Speaker 4: data set that we arrived at that gave us that headline.
Speaker 13: Yeah, so, you know, essentially, we dove into very granular
Speaker 13: data on wholesale power prices, which is an important component
Speaker 13: of what then makes up power bills, and we looked
Speaker 13: at locations tens of thousands of locations throughout the country
Speaker 13: and we kind of related it to the location of
Speaker 13: data centers. And what we found essentially is that areas
Speaker 13: located closer to data center activity are much more likely
Speaker 13: to experience price increases than areas located far from data centers.
Speaker 5: That's what's so interesting about data center ali in the
Speaker 5: Virginia region, and this is why you go to Baltimore.
Speaker 9: Can you, therefore, just break.
Speaker 5: Down us in New York are we going to be
Speaker 5: feeling the impact? How are you going to start seeing
Speaker 5: people built up and affected by region that they live,
Speaker 5: and how certain local government is going to have to
Speaker 5: stand in and help in some way.
Speaker 7: Data centers affect power prices and your power bills in
Speaker 7: two main ways. One, they just use up so much
Speaker 7: power that economics one O one it makes power more
Speaker 7: expensive for everyone else. And two they require so much infrastructure,
Speaker 7: you know, new transmission lines, new power plants. The way
Speaker 7: utilities work is those costs are spread out among everyone.
Speaker 7: The reason this might matter for some of your some
Speaker 7: of our some of our listeners here, maybe they pay
Speaker 7: their their like I pay my power bill, fine, that's okay,
Speaker 7: and some poor people have a hard time paying theirs.
Speaker 2: Okay.
Speaker 7: But it can really affect these companies because if data
Speaker 7: center developers, big tech firms have a harder time connecting
Speaker 7: to the grid, or if that's slowed down because of
Speaker 7: public anger, that slows down some of these AI plays
Speaker 7: like we're just listening to. And it can also hurt
Speaker 7: utilities if they're if regulators tell them that they that
Speaker 7: they need to do something differently, that can affect everything
Speaker 7: from their share price to their future planning.
Speaker 2: LEO.
Speaker 4: You know, data analysis can take you in lots of
Speaker 4: different directions. So the headline is up to two hundred
Speaker 4: and sixty seven percent more. But were we able to rank,
Speaker 4: you know, in which geographies regions this this gain in
Speaker 4: price is most present and what are the factors behind it.
Speaker 13: Yeah, so we looked at data, like I said, all
Speaker 13: over the country, tens of thousands of locations, and of
Speaker 13: course there are areas in the country that are more
Speaker 13: effected than others, especially on the east coast, the northeast,
Speaker 13: the PJM grid in Northern Virginia. But also interesting Baltimore,
Speaker 13: which doesn't have data centers immediately nearby, but it is
Speaker 13: actually very close to Northern Virginia that is Data Center Alley.
Speaker 13: And what we found is people and locations in the
Speaker 13: Baltimore area were experiencing some of the highest increases, sometimes
Speaker 13: three times as much since twenty twenty in twenty twenty
Speaker 13: five than other parts of the country.
Speaker 4: It is today's Bloomberg Big Take the impact of AI
Speaker 4: data centers on boosting the cost of electricity consumers. Check
Speaker 4: it out Bloomberg. Joshul Elia Nicoletti, thank you very much.
Speaker 4: Now coming up. Shares of Spotify and lower today as
Speaker 4: the company announces changes in the C suite with the
Speaker 4: departure of CEO Daniel k And it is moving the
Speaker 4: stock a little bit lower. We'll have more next, This
Speaker 4: is Bloomberg Tech. Big changes over at Spotify. CEO Daniel
Speaker 4: k is stepping aside after almost two decades, leaving the
Speaker 4: leadership in the hands of Chief Products and Technology Officer
Speaker 4: good Stuff Pseudostrom and Chief Business Officer Alex Norstrom starting
Speaker 4: January first. The two officers have been co president since
Speaker 4: twenty twenty three and have been largely leading strategic and
Speaker 4: operational development. Bloomberg's Spotify reporter actually, Carmen, it's with us
Speaker 4: on set.
Speaker 2: You know, the stock tells a story.
Speaker 4: It's down more than five percent on the news, but
Speaker 4: we gave the context. After two decades, Daniel k is
Speaker 4: passing on.
Speaker 14: The torch right and a founder, So that's obviously always
Speaker 14: going to be big news, and investors always have strong
Speaker 14: feelings about that. But the way they're portraying this is
Speaker 14: that kind of status quo. They're saying Alex and Gustav
Speaker 14: have been doing this work essentially since they took over
Speaker 14: as co presidents, and that Daniel's kind of the visionary
Speaker 14: and he's still going to be very hands on.
Speaker 9: That's what they're telling everybody.
Speaker 5: But what's not status quo is the world of music
Speaker 5: and the way in which Spotify is trying to identify
Speaker 5: new ways of doing audio books and trying to galvanize
Speaker 5: people perhaps around AI development of music and whether or
Speaker 5: not they want to be paying actual musicians royalties. How
Speaker 5: will these two leaders navigate that?
Speaker 14: That's the big question. I mean, they're portraying this as
Speaker 14: a huge opportunity, right, AI music, huge new frontier to
Speaker 14: do markets that have never really adopted streaming or haven't
Speaker 14: in the same amount that the US and Europe have.
Speaker 9: But these are also the big challenges.
Speaker 14: I mean, there's a world in which if everyone can
Speaker 14: create their own music, do they need to have a
Speaker 14: streaming service? So these are the big questions that Spotify
Speaker 14: and alex Obusep are going to have to answer. Can
Speaker 14: they actually bring the value of AI, get these emerging
Speaker 14: markets to pay more, and then from a video front,
Speaker 14: compete with YouTube.
Speaker 4: I think it's worth a health check on Spotify generally,
Speaker 4: Like at the end of twenty twenty two, this was
Speaker 4: a seventy five eighty dollars stock It's now six hundred
Speaker 4: and eighty nine dollars, Like, clearly something's going right there.
Speaker 4: I spend quite a lot of time on Spotify. I
Speaker 4: know carrots too. They're still dominant in certain categories like
Speaker 4: how do you see them as the beat reporter?
Speaker 14: Yeah, no, they absolutely are the biggest music streaming service,
Speaker 14: so they have owned that category completely. Part of the
Speaker 14: reason the stock was down at that time was because
Speaker 14: they had been investing so much money in podcasting.
Speaker 9: Yeah, and the investors didn't like that.
Speaker 14: Now in this past year, I mean they switched to
Speaker 14: a loss now, but they were profitable for a full year.
Speaker 9: They showed they can do this.
Speaker 14: Investors loved that, and I think they just have this
Speaker 14: new confidence that they're going to spend their money more
Speaker 14: wisely and if necessarily, flip the switch to turn to profitability.
Speaker 5: Now. That was a big message for met himself. I
Speaker 5: leave it in profitable hands. I leave it on a high. Basically,
Speaker 5: what's he leaving to do because he's staying on as chair,
Speaker 5: is going to be there for strategy. But he has
Speaker 5: been active in founderland, building new companies and new ventures
Speaker 5: and backing defense ones, health ones exactly.
Speaker 14: So he didn't really speak about that. He really kept
Speaker 14: to focus on Spotify. But it does seem like he's
Speaker 14: going to spend more of his time in his investments,
Speaker 14: probably focusing.
Speaker 9: On what they're up to.
Speaker 14: But he is again really saying he's going to be
Speaker 14: involved in the day to day with Spotify. He's going
Speaker 14: to be sharing his office as he does with Alex
Speaker 14: and Gustav as well.
Speaker 5: Actually common of Bloomberg, So appreciate the time on little
Speaker 5: things Spotify. Meanwhile, coming up, we speak the Microsoft Security
Speaker 5: Corporate VP A Sir Jacka, as the company unveils Microsoft
Speaker 5: Sentinel or improvements to it, about a unified focus on security.
Speaker 9: This is a Bloomberg Tech