Speaker 1: Bloomberg Audio Studios, podcasts, radio news from the heart of
Speaker 1: where innovation, money and power collide in Silicon Valley and beyond.
Speaker 1: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.
Speaker 2: Live from San Francisco.
Speaker 3: I'm Tim Stenebeck and this is Bloomberg Technology. Coming up
Speaker 3: today is Quantum Day at Nvidia GtC, and Ed Ludlow
Speaker 3: is there. We'll have the main takeaways from the conference
Speaker 3: so far and discuss what to expect from today. Plus,
Speaker 3: soft Bank is acquiring the chip designer Ampier in an
Speaker 3: all cash transaction died at six point five billion dollars.
Speaker 3: We'll sit down with Amper's CEO to learn more about
Speaker 3: the deal. And Campus, a for profit community college, has
Speaker 3: raised forty six million dollars from investors including Sam Altman,
Speaker 3: Peter Tiele's Founder Fund, and Joe Lonsdale's eight VC. The
Speaker 3: Founder and Joe Lonsdale join us on the future of
Speaker 3: ed tech. First though, a check of the markets, and
Speaker 3: we're seeing some green across the screen.
Speaker 2: Stocks opening higher.
Speaker 3: After yesterday's FED fueled rally or should say lower, but
Speaker 3: then it was the best FED day going.
Speaker 2: Back to July.
Speaker 3: Then about a half hour into the trading session, we
Speaker 3: got some surprisingly strong housing data which turned around the trade.
Speaker 3: At last check, about sixty five stocks in the Nasdaq
Speaker 3: one hundred moving higher right now, up about four tens
Speaker 3: of one percent off its best levels of the day
Speaker 3: so far, but still in the green. One of the
Speaker 3: stocks that's helping to push the Nasdaq one hundred higher
Speaker 3: is Meta Platforms, investors cheering the news that Meta will
Speaker 3: roll out Meta AI across forty one European countries this week.
Speaker 3: It's up right now by about four percent. Meta's intelligent
Speaker 3: chat function will also be rolled out across twenty one
Speaker 3: overseas territories and available in six European languages. The company
Speaker 3: said in a statement. It's going to be free too
Speaker 3: across its apps, including Facebook, Instagram, WhatsApp, and Messenger.
Speaker 4: Also watching.
Speaker 3: Shares of Intel down about seven tenths of one percent.
Speaker 3: It did fall by nearly seven percent yesterday after a
Speaker 3: TSMC board member dismissed report that the company has pitched
Speaker 3: a major US shipmakers about taking stakes in it JV
Speaker 3: to operate intels and factories. Shares we're bouncing back earlier,
Speaker 3: but lower now, and in Vidia is higher today as
Speaker 3: the company continues its GTCAI conference in San Jose today.
Speaker 3: Of course, Quantum day and video shares hired by one
Speaker 3: point three percent. And that's exactly where we go now
Speaker 3: live from the DCC event, our own ed Ludlow joining
Speaker 3: us at I want you to set the scene for us,
Speaker 3: but I also want you to clear something up for us,
Speaker 3: because there's lots of chatter this morning about in Nvidia
Speaker 3: in the context of money being spent in the US.
Speaker 5: What's going on, Yeah, it's based on an interview that
Speaker 5: Jensen Wong, the CEO, gave the Financial Times, and he
Speaker 5: quoted as saying is that in Vidia will procure half
Speaker 5: a trillion dollars worth of electronics in the next four
Speaker 5: or five years. But what he's not saying is that
Speaker 5: that is capital expenditures. Right, this is a company that
Speaker 5: has seventy percent market share in the market for AI accelerators,
Speaker 5: high performance GPUs that go into data centers. He spent
Speaker 5: a lot of time yesterday. We were with him for
Speaker 5: an hour explaining the mechanics of that. Right, when you
Speaker 5: build a data center from scratch or you upgrade its technology,
Speaker 5: that is a tens of billions of dollars or hundreds
Speaker 5: of billions of dollars project. If you have seventy percent
Speaker 5: market share for the brain that goes into it, Inevitably
Speaker 5: you're going to have to pay TSMC to manufacture the chips.
Speaker 5: You're going to work with Dell in HPE on the
Speaker 5: server IRAQ assembly and packaging. That's what he's referencing, essentially
Speaker 5: the cost of doing business. It's interesting because this is
Speaker 5: what Gensen one wants us to be talking about. He
Speaker 5: sees in video as foundational to all AI companies. In
Speaker 5: other words, companies are being created because of what in
Speaker 5: Video is doing. In the context of it calling itself
Speaker 5: an AI infrastructure company, an AI factory company.
Speaker 3: Okay AI infrastructure a AI factory today though is quantum
Speaker 3: day and in Nvidia doesn't actually make sure quantum computers
Speaker 3: what's going on?
Speaker 4: Correct?
Speaker 5: Yeah, so exactly the same point as with AAI data centers.
Speaker 5: In Vida does not make quantum computers. What it does
Speaker 5: is sell its existing technology to the quantum computing industry
Speaker 5: to help them make their own machines better. You can
Speaker 5: use an AI supercomputer for error correction and calibration of
Speaker 5: a quantum computer, but they're essentially two distinct field. Of course,
Speaker 5: quantum computers follow quantum mechanics and are coded in cubits,
Speaker 5: not in bits, ones and zeros. But we're all here
Speaker 5: today because what happened in January, right, Jensen one was
Speaker 5: asked basically at point blank, what do you think of
Speaker 5: quantum computers, and he said they're more than a decade
Speaker 5: away from being useful. The net result that day, January eighth,
Speaker 5: was the the publicly traded quantum computing stocks all sank
Speaker 5: thirty forty percent. And so we're all assembling today and
Speaker 5: Jensen's going to be on stage with all of the
Speaker 5: quantum computing CEOs who are basically his customers. He just
Speaker 5: sells the existing gear to them, and maybe we'll get
Speaker 5: an update on how Jensen feels on quantum computing. But
Speaker 5: from in Vidia's perspective, it's an arm of research, and
Speaker 5: it's where they sell existing tech GPUs principally to that industry.
Speaker 5: They do not make quantum computers.
Speaker 3: Bloomberg's Ed Ludlow ed at Invidio GtC ed, good to
Speaker 3: see you. We'll see you a little later too, Thanks
Speaker 3: so much. Stay with us, though, because Bloomberg this Afternoon
Speaker 3: has a special edition of Bloomberg Technology on quantum Computing.
Speaker 3: Ed Lodlow will return live from in Video's GtC event
Speaker 3: starting at four to thirty pm Eastern Time. Four on
Speaker 3: the broader tech market and in Video, let's bring in
Speaker 3: Sylvia Jablonski, Defiance ETF's CEO.
Speaker 2: She joins us.
Speaker 3: Now, Sylvia, I'm wondering how you're watching everything happening at
Speaker 3: in Video GtC. You do argue that in Vidio is
Speaker 3: a buy right now off of its highs. How are
Speaker 3: you watching everything come out of San Jose this week?
Speaker 6: Yes, good morning, Thanks for having me here. I think
Speaker 6: it's all very exciting. You know, what we're what we've
Speaker 6: been seeing over the last.
Speaker 7: Year or two is just you know, so much news
Speaker 7: around the growth of AI, the potential for quantum computing,
Speaker 7: the buildout.
Speaker 6: Of six G.
Speaker 7: And you know who's the star of that show. It's
Speaker 7: it's Nvidia. And you're talking about a stock that you know,
Speaker 7: was trading up over above one forty pretty recently before
Speaker 7: this this pullback that.
Speaker 6: We see here at these levels.
Speaker 7: I mean, I love the stock, I love the company
Speaker 7: you're talking about potentially, you know, a fourth Industrial Revolution compounded.
Speaker 7: I know, growth rate themes, of AI and quantum and
Speaker 7: things like this of thirty five to forty percent per year.
Speaker 7: As an investor, I'm patient with technology. It takes time
Speaker 7: for things to play out, but I want to get
Speaker 7: in early. And this is still you know, first innings.
Speaker 7: A lot of people are saying that, but you know,
Speaker 7: we're seeing that it's it's it's true as we get
Speaker 7: more news from this conference.
Speaker 3: So do you think that in Nvidia investors right now
Speaker 3: have it wrong? Does the market have it wrong? To
Speaker 3: what extent do you think this stock is undervalued right now?
Speaker 7: Well, we can always say that the market is you know,
Speaker 7: the market's a little bit emotional, right, So I think
Speaker 7: that there are a lot of reactions in the market,
Speaker 7: and when the market becomes emotional and people panic, usually
Speaker 7: they sell the macseven or they sell kind of like
Speaker 7: the high flying names that have done well for that year.
Speaker 7: We've seen it happen with Tesla, we saw it happen
Speaker 7: with Apple during COVID, you know, all these different sorts
Speaker 7: of things. And then video is kind of the poster
Speaker 7: child of the market this year.
Speaker 6: So when we have fear.
Speaker 7: And panics about tariffs and things like this, people tend
Speaker 7: to run for the hills and sell you know, the
Speaker 7: most profitable stock. So I just think that there's a
Speaker 7: lot of liquidity on the sidelines. There's still this consumer
Speaker 7: consumer sentiment that is uneasy.
Speaker 6: But eventually, you know, when.
Speaker 7: Some of the tariff things shake out, and then we
Speaker 7: get you know, the tailwinds of lower regulation and tax policy,
Speaker 7: things that are favorable to the market.
Speaker 6: These are the names that also rally first.
Speaker 7: Right, It's kind of like the buy the dips and
Speaker 7: you know, sell the rips or hold on to the
Speaker 7: rip scenario.
Speaker 3: Here, well, we're still down on the NAZAC one hundred
Speaker 3: and ten percent, so officially in correction territory. You said,
Speaker 3: when we get the regulatory clarity, when we get tax cuts,
Speaker 3: when the tariff stuff shakes out, how are you so
Speaker 3: certain that stuff is going to shake out?
Speaker 7: Well, I think, you know, all of these things take time, right,
Speaker 7: and the only information we have is the information that
Speaker 7: we actually get from Washington, and that information seems to
Speaker 7: be that, you know, the tariff policy is inactive because
Speaker 7: of these fensanyl issues, immigration issues, cybersecurity, these other types
Speaker 7: of things that have to be sorted out. We have
Speaker 7: information that the president plans to you know, cut taxes
Speaker 7: to support your regulation and businesses. So I think to
Speaker 7: your point, it's a fair question, right, we actually have
Speaker 7: to see these things pan out. But even if nothing
Speaker 7: else happens, right, you have an economy that.
Speaker 6: Is still growing positive, you know, positive GDP.
Speaker 7: It's a little bit lower, but we're still above that
Speaker 7: two percent range. Jobs are fine, wages are fine. Corporate
Speaker 7: earnings are estimated to be in the high single digits,
Speaker 7: you know, even up to ten percent by some analyst estimates.
Speaker 6: The earning season was very good. There are still strong balance.
Speaker 7: Sheets, and you know what we're hearing out of corporate
Speaker 7: America is that it's you know, there's soll cap bax.
Speaker 8: Right.
Speaker 6: I don't see a recession either way. So maybe you
Speaker 6: don't get hyperbolic growth. But when you have these themes
Speaker 6: like quantum computing and.
Speaker 7: AI that are on sale, I think it's worth taking,
Speaker 7: potentially taking a risk for long term returns, regardless of
Speaker 7: what happens in the next year or so with policy.
Speaker 3: Hey, Sylvia, before we let you go, just twenty seconds
Speaker 3: on Broadcom another soccer bullet round, but down twenty percent
Speaker 3: from all time highs.
Speaker 7: Yeah, I mean I think Broadcom is going to be
Speaker 7: one of the leaders in AI and videos, the poster
Speaker 7: child there, but Broadcom should be a second winner there.
Speaker 6: You know, they're in software, they're in VM sales.
Speaker 7: They've had over fifty seven percent growth in AI revenue
Speaker 7: per the last earnings call. I just I think that
Speaker 7: this is a name that did sell off a little bit.
Speaker 7: It might be good to get in for the long run.
Speaker 3: Sylvia Jablonski of Defiance ETF's always good to see you, Sylvia,
Speaker 3: thanks so much for joining us. Well, coming up, we're
Speaker 3: going to talk about soft bank six point five billion
Speaker 3: dollar acquisition of Chip Designer and Peer Computing and Peer
Speaker 3: CEO Renee James joins us.
Speaker 8: Next.
Speaker 2: This is Bloomberg.
Speaker 3: Soft bank six point five billion dollar acquisition of Chip
Speaker 3: Designer and Peer Computing is highlighting how the increasing demand
Speaker 3: for compute is crashing up against infrastructure constraints. Renee James,
Speaker 3: founder and CEO of and Pierre joins us to talk
Speaker 3: more about this deal. Renee, good to see you, congratulations
Speaker 3: on this.
Speaker 9: Thank you.
Speaker 2: I just want to know how are you feeling this morning.
Speaker 9: I'm feeling I think it hasn't sunk in.
Speaker 10: I'm of course thrilled with this outcome for you know,
Speaker 10: my employees, my investors, and most importantly, we're a group
Speaker 10: of inventors and innovators who are very excited about the
Speaker 10: vision that Masa has for AI and our ability to
Speaker 10: continue innovation as part of SoftBank.
Speaker 2: What is that vision?
Speaker 3: Because Ampier will operate as this wholly owned subsidiary of
Speaker 3: soft Bank, of course it is a majority owner of ARM.
Speaker 3: How do you fit into that vision? What is that vision?
Speaker 10: You know, Massa has talked a lot, even the Stargate
Speaker 10: announcement that was recently done in the White House, about
Speaker 10: AI and the the role AI will play in everybody's
Speaker 10: lives and building super chips, and he's talked a lot
Speaker 10: about that.
Speaker 9: So I think our role is to make that come
Speaker 9: to life.
Speaker 10: We are the leading supplier of high performance, very power
Speaker 10: efficient processors for data centers on the our architecture, so
Speaker 10: it's a very synergistic for us to join into the
Speaker 10: SoftBank family and continue working on the Silicon roadmap that
Speaker 10: we have which includes AI acceleration, and now we'll have
Speaker 10: a broader mandate.
Speaker 9: So I'm very excited about that.
Speaker 3: What happens to your existing customers and your existing product
Speaker 3: line when this deal does close in the second half
Speaker 3: of the year.
Speaker 9: Yeah, we continue as is.
Speaker 10: We continue with the product line that we've worked on
Speaker 10: for the last eight years are very low power, high
Speaker 10: efficiency microprocessors, and now we've announced that we have AI
Speaker 10: acceleration in our products. So I think that's the future
Speaker 10: of where we're going in the data center. We're going
Speaker 10: to see compute and AI start to come together, especially
Speaker 10: as inference becomes the larger part of the market, and
Speaker 10: so our customers continue with us and hopefully we'll be
Speaker 10: excited about a broader set of products from us.
Speaker 3: Well, Y, you recognize something really early on that there's
Speaker 3: this need and there's going to be this need, and
Speaker 3: indeed we're seeing it right now for super high performance
Speaker 3: that required lower power. When you look across the landscape
Speaker 3: right now and where we are in AI, what do
Speaker 3: you see that perhaps other people don't see right now.
Speaker 9: Well, as you know, Tim, I've been doing this a
Speaker 9: long time.
Speaker 10: I've been in semis a long time, and power is
Speaker 10: always been a variable in semiconductors for how you get
Speaker 10: performance or a limited performance. And so one of the
Speaker 10: things that I didn't get to work on in my
Speaker 10: long career at Intel was working on how to do
Speaker 10: the highest performance possible in the most constrained power envelope.
Speaker 10: That was a portion of the spectrum of computing that
Speaker 10: we didn't really work on. And the reason the thesis
Speaker 10: was we knew that power would be the biggest limited
Speaker 10: to growth long term.
Speaker 9: There wouldn't be enough of it. You need increasing amounts
Speaker 9: of compute.
Speaker 10: We've talked a lot about AI, especially with GtC this week,
Speaker 10: taking nothing away from that, we're also having a massive
Speaker 10: growth in compute. It's going alongside this massive growth in
Speaker 10: AI AI compute.
Speaker 9: So those two things.
Speaker 10: Are just taking you know, a tremendous amount of growth
Speaker 10: and power and AIS a ten x.
Speaker 9: You know, if you.
Speaker 10: Will a function growth in power required and I think
Speaker 10: we knew that you could know that from the workloads,
Speaker 10: and we decided that, you know, one of the things
Speaker 10: we should go pioneer is is this sufficiency. Our architecture
Speaker 10: is very efficient and we preserve that efficiency, but we
Speaker 10: used our experience in high performance and building high performance
Speaker 10: microprocessors to really, you know, get us to this level.
Speaker 3: You know, we've heard a lot from Jensen this week
Speaker 3: about physical A and I'm wondering from your perspective. When
Speaker 3: you think about the compute that will be needed in
Speaker 3: the years to come, what does that world actually look
Speaker 3: like for the normal person. What are the products and
Speaker 3: services and tools that we are all going to be
Speaker 3: using that will require this compute.
Speaker 6: You know, I used to think this is funny.
Speaker 10: You know, every wave of computing, whether it was the
Speaker 10: wave of PCs, the waves of mobile phones and laptops,
Speaker 10: we thought, this is it. We're going to have computers
Speaker 10: that you know here, you have a computer in your pocket,
Speaker 10: You're going to have a computer here at computer. I
Speaker 10: think that in this next phase, you know, as was
Speaker 10: discussed at GtC, we begin to really crest over into
Speaker 10: integrated computing and everything.
Speaker 9: And it really is transparent.
Speaker 10: It's a background activity that happens in your life that's
Speaker 10: assistive in different ways.
Speaker 9: Whether it's robotic or not.
Speaker 10: All of your appliances are smart now, all of your
Speaker 10: homes have become smart, your.
Speaker 9: Car is smart.
Speaker 10: So the experience of computing that used to be isolated
Speaker 10: to your computer or your phone or what have you,
Speaker 10: is now integrated into your life and you have I think,
Speaker 10: you know what we'll see. This is why I'm very
Speaker 10: positive on semi conductors.
Speaker 9: Semiconductors have fueled every single.
Speaker 10: One of these waves of growth, and the base technology
Speaker 10: to go into any kind of AI is basic computational semiconductors.
Speaker 10: That's why, despite you know semis are always cyclical, we
Speaker 10: do see this, we see these downturns. I'm very confident
Speaker 10: that we have another growth cycle ahead of us in
Speaker 10: semis and.
Speaker 3: Peter founder and CEO Renee James Renee, thanks so much
Speaker 3: for joining us on what is certainly a really big day.
Speaker 2: I really appreciate it.
Speaker 3: Deep Seeks Innovation made ripples across the AI industry when
Speaker 3: it announced that it's models performed as well or better
Speaker 3: than its American counterparts and at a cheaper price.
Speaker 2: That was back in January.
Speaker 3: Since then, China and many other companies have been raising
Speaker 3: to integrate that model throughout the country. Bloomberg's Daviting glaz
Speaker 3: sat down with one AI c Kaifu Lead to discuss
Speaker 3: their adoption of Deep Seek.
Speaker 11: Well, I think China had its Chatgibet moment when Deep
Speaker 11: Seak came out. We can call it deep Seek moment.
Speaker 11: Everyone's aware of it over the Chinese holidays, everyone's talking
Speaker 11: about it, and the CEOs came back to work saying,
Speaker 11: put put deep Seek to work and my company, and
Speaker 11: what they found out was deep Seek is a fantastic model,
Speaker 11: amazing AI, but it doesn't have the middleware and the
Speaker 11: user interface that it takes to connect to corporate databases
Speaker 11: to build applications to make it useful for HR finance
Speaker 11: and customer service.
Speaker 4: So what zero one Dot.
Speaker 11: Day I did was we saw deep Seak has been
Speaker 11: making great momentum, and we decided to really bet on
Speaker 11: deep Seek and build a missing middleware and UI so
Speaker 11: that deep Sea can be made.
Speaker 8: Useful in corporations.
Speaker 11: That's the product we announced this Monday, and we're getting
Speaker 11: fantastic reception in China and.
Speaker 8: Also in Hong Kong.
Speaker 9: Tell us more about that launch.
Speaker 11: What we talked about was many of you have deep
Speaker 11: Seak now you love to use it. In fact, one
Speaker 11: CEO friend of mine asked his employees what do you
Speaker 11: use it for?
Speaker 4: And good question and the answer was fortune telling.
Speaker 11: By the way, that's a great thing to try for you,
Speaker 11: but it's not very deep into the industry the company.
Speaker 11: You know, every company has ERP and the CRM databases,
Speaker 11: they have employee records, they have their internal information, and
Speaker 11: they want the model to be more a generalist. They
Speaker 11: wanted to be knowledgeable. Bloomberg would want a finance knowledgeable model,
Speaker 11: right Ping I would want an insurance knowledgeable model. So
Speaker 11: our job is to really build that layer for that purpose,
Speaker 11: sort of like if I gave a If I gave
Speaker 11: you a Windows kernel that is the core operating system,
Speaker 11: you wouldn't know what to do with it. You need
Speaker 11: all the Windows layer, the application interfaces, so that the
Speaker 11: Windows kernel can be useful. And we like to think
Speaker 11: that zero one dot AI is providing that layer for deepseak,
Speaker 11: which is the underlying model in technology.
Speaker 3: K That was Kai fu Lee. There's you know, Innovation
Speaker 3: Ventures and also one AI. Meanwhile, with the advent of
Speaker 3: the AI boom, many of the manufacturers involved are becoming
Speaker 3: amopolistic and only ever growing companies such as Nvidia and
Speaker 3: it's partners who make the semiconductors just keep getting richer
Speaker 3: every time you use your favorite chatbot. That's the story
Speaker 3: in today's quick Take, and Bloomberg's Peter Elstrom joins us
Speaker 3: now Peter the team over a quick take, writing that
Speaker 3: every time we use chat GBT or Claude or Lama.
Speaker 3: We're making a handful of companies wealthier take us through it.
Speaker 12: That's right, or even deep Seek for that matter, they
Speaker 12: also use this supply chain. So we took a look
Speaker 12: at is this really unusual dominance that we've seen in
Speaker 12: the supply chain of AI technologies. It begins with the
Speaker 12: in Nvidia, which is probably the highest profile player here
Speaker 12: in the supply chain, but it's also TSMC, the company
Speaker 12: that makes the chips, s Kehaynix, which makes the high
Speaker 12: bandwidth memory that is paired with invidious chips, and then ASML,
Speaker 12: the maker of these lithography machines that are really the
Speaker 12: necessary to be able to make the highest end chips
Speaker 12: in the business.
Speaker 8: So what we've seen is this really.
Speaker 12: Consolidation of power in the AI supply chain with these
Speaker 12: four companies where they wield tremendous power over how companies
Speaker 12: are able to get these technologies and then deploy them.
Speaker 12: That's true for all the hyperscalers, Meta, Microsoft, Open Ai, etc.
Speaker 12: But also the companies in China have been trying to
Speaker 12: buy these Now there are limitations on which chips Chinese
Speaker 12: companies are able to buy, and deep Seek and even
Speaker 12: Kaifu les zero.
Speaker 4: One Dot AI.
Speaker 12: But they want to be able to get those Nvidia
Speaker 12: chips and the rest of the technologies from these companies
Speaker 12: to be able to build the AI models that are
Speaker 12: now going to be marketed to companies and to individuals.
Speaker 3: What is the moat that these companies have, Peter, Because
Speaker 3: typically when we think about innovation and technology such as this,
Speaker 3: we think about it from the perspective of, Okay, if
Speaker 3: these companies are making money, a rush of competitors are
Speaker 3: going to come in and they're going to try to
Speaker 3: do the same thing.
Speaker 2: What's the moat that these companies have.
Speaker 12: Yeah, that's a very important question. And just to take
Speaker 12: a step back, I'd say that when you look at
Speaker 12: monopolies over time, especially monopolies in tech, they tend to
Speaker 12: last for quite a while. We saw it with Windows
Speaker 12: and Intel in the PC era. Before that, we saw
Speaker 12: it with IBM, which got sued three different times for
Speaker 12: and I trust allegations. But they tend to last for
Speaker 12: a very long period of time, and they tend to
Speaker 12: fade not just because of competition, but because of government
Speaker 12: intervention too. Now, these AI dominating players, let's call monopolies
Speaker 12: for now, four players that are effectively monopolies in their categories.
Speaker 12: They've only been in place for a very short period
Speaker 12: of time at this point. When it comes to Nvidia,
Speaker 12: they have lots of competition. TSMC and ASML have quite
Speaker 12: a bit less.
Speaker 3: Bloomberg's Peter Elstrom joining us from London today. Welcome back
Speaker 3: to Bloomberg Technology. I'm Tim Seneveek in San Francisco. Let's
Speaker 3: get a quick check of the markets. We do see
Speaker 3: stocks off their best levels of the day. We did
Speaker 3: see a lower open, but then we got some surprisingly
Speaker 3: strong housing data which turned around the trade. Our last
Speaker 3: check just about sixty five stocks in the Nasdaq one hundred.
Speaker 2: We're moving higher. A couple of.
Speaker 3: Individual equities I do want to check in on. Check
Speaker 3: out what's going on with pdd Hired by about two
Speaker 3: percent right now. These are shares listed in the US.
Speaker 3: They erased that earlier decline, this coming after the company
Speaker 3: reported fourth quarter results. Sales did misestimates for a third consecutive.
Speaker 2: Quarter, but earnings were better than expected.
Speaker 3: And look at Tesla down about eight tenths of one percent.
Speaker 3: The company is recalling all cyber trucks produced and sold
Speaker 3: in the US over the past fifteen months. This due
Speaker 3: to a safety issue with steel trim pieces that can
Speaker 3: detach from the vehicle. The company's recalling them all, but
Speaker 3: it estimates that only about one percent of the recalled
Speaker 3: vehicles have the defect. It can actually create a road
Speaker 3: hazard and increase the risk of injury or collision. Now,
Speaker 3: let's head back to in video GtC where Bloomberg's Ed
Speaker 3: Ludlow is standing back.
Speaker 5: Hey, Ed, Yeah, there's just such a large volume of
Speaker 5: news and data about in video out GtC. If you
Speaker 5: look at the stock over the first four days of
Speaker 5: this week. There's also skepticism in the market about the
Speaker 5: understanding for demand long term. That's all many care about.
Speaker 5: And I've got a brilliant guest to unpick it with me.
Speaker 5: Flad Galibov is research director at Omdia. Stick that caught
Speaker 5: my eye is that compute demand, particularly from agentic and reasoning,
Speaker 5: is one hundred x today one hundred x what it
Speaker 5: was one year ago. And to many people that doesn't
Speaker 5: actually mean anything. But the way that it was explained
Speaker 5: to me by in video is that they just counted
Speaker 5: all the tokens.
Speaker 2: Right.
Speaker 5: In a tokenization context, you basically take a token three
Speaker 5: bytes of data and you say, okay, what our companies
Speaker 5: beyond the hyperscalers doing right now today it's one hundred
Speaker 5: x more than it was a year ago.
Speaker 4: How do you model that?
Speaker 5: I mean, it's a very very difficult forward looking metric.
Speaker 8: So there's two ways to do that.
Speaker 13: So and by the way, there is a misunderstanding and
Speaker 13: because it's complex, right, that's why people struggle. So one
Speaker 13: part of my team tests models. So you know, what
Speaker 13: they tried to find out is how good a model
Speaker 13: can behave and they found out there is any models
Speaker 13: behave better. The reason why they behave better is that
Speaker 13: extra tokens is the extra computing. By being able to
Speaker 13: in essence think, they actually end up getting a better result.
Speaker 13: So my team got very excellent results from that. But
Speaker 13: I have a different part of my team that actually
Speaker 13: tries to understand exactly how many GPUs the different companies bought.
Speaker 13: So my team in China was able.
Speaker 5: To you're going to bring us to deep Sea, can't you?
Speaker 8: Yes, I'll bring it to.
Speaker 13: Deep Sek because my team in China found out that
Speaker 13: Deep Seek bought a huge amount of GPUs. So imagine
Speaker 13: then they release we have given that information to our
Speaker 13: clients they release their paper, and in the paper they say,
Speaker 13: we don't use many GPUs for training. So my clients
Speaker 13: immediately came in they said, why did you tell us
Speaker 13: they bought so many GPUs And.
Speaker 8: I said, well, they did.
Speaker 13: I have the receipts, and we know now that they
Speaker 13: bought them because their inference is so compute intensive, because
Speaker 13: their infance uses, as you said, one hundred x small
Speaker 13: tokens than a traditional knowledge model. But that's a good
Speaker 13: thing for us. It's actually better for us to train
Speaker 13: quickly and simply and have a better out put through
Speaker 13: more tokens, through more reasoning. People are, especially the environmentally
Speaker 13: conscious people, which we all should be, are very concerned
Speaker 13: about that extra tokenization during the inference stage. But actually,
Speaker 13: if you can get the right answer once with one question,
Speaker 13: that stops you from having to prompt many times. You
Speaker 13: might have got a good answer from CHGBT, but you
Speaker 13: would have needed to ask it one hundred questions, so
Speaker 13: you're doing the reasoning for it now. If you use
Speaker 13: a reasoning model with you know, what they call a
Speaker 13: gender GAI, you end up having the right answers traded.
Speaker 5: This is the core of Jensen Wong's argument right. If
Speaker 5: you were at GtC in twenty twenty two, twenty twenty three,
Speaker 5: twenty twenty four, maybe the fixation was on H one
Speaker 5: hundred and training the next frontier model. But the world's
Speaker 5: very different now. I think in videos really focus on
Speaker 5: its enterprise customers. What Gensen one did outline was a
Speaker 5: roadmap four years and four generations worth of hardware. Electronics
Speaker 5: company the consumer electronics technology companies they don't do that.
Speaker 5: They don't say here's what I'm doing this year all
Speaker 5: the way through to twenty twenty seven. What did you
Speaker 5: make of that?
Speaker 13: So I disagree that electronics companies don't share their roadmap,
Speaker 13: I'll be honest, because I think if you look at AMD,
Speaker 13: they share their roadmap pretty broadly.
Speaker 8: I think this is very transparent.
Speaker 13: You know, I come from Intel and Intel we've always
Speaker 13: shared a roadmap pretty broadly.
Speaker 8: Well maybe not in the le nasty this have been
Speaker 8: a bit shick.
Speaker 5: Well, there's a difference between sharing a roadmap and executing
Speaker 5: on it.
Speaker 8: It is very big difference.
Speaker 13: I think what's amazing about Nvidia is an extreme laser
Speaker 13: focus in this incredible culture, and they understand, they understand
Speaker 13: the hardware stack. They understand their software stack, they understand
Speaker 13: the services, they have a strategy, and they understand that
Speaker 13: the world is getting tokenized, so they're focused on that.
Speaker 13: Their laser focused on how do we make the most
Speaker 13: efficient token processing engine.
Speaker 5: The analogy that gents one gave was Louis Vuitton bagged.
Speaker 5: So for what it's worth, you argued, Louis Vuitton comes
Speaker 5: out of this twenty five bag. But at the same day,
Speaker 5: it doesn't tell you what it's going to be doing
Speaker 5: in twenty twenty eight or twenty twenty nine. Whether you
Speaker 5: agree with that that analogy or not remains to be seen.
Speaker 5: What is different is you get a sense then videos
Speaker 5: move beyond the hyperscalers the demand side of that equation.
Speaker 5: What do you see?
Speaker 13: So I do think that let me just kind of
Speaker 13: just touch on enterprises in the world for a second.
Speaker 13: Enterprises need predictability and they like it so and actually
Speaker 13: they've been looking ever since Intel stop delivering, they've been
Speaker 13: looking for more partners to be honest, to give them
Speaker 13: a roadmap, to explain things and to then deliver. So
Speaker 13: I think it's actually the best way to address the enterprise.
Speaker 5: Does it protect the enterprise's ability to commit spending if
Speaker 5: they know what employer signed the technology bar it does.
Speaker 13: In my discussion with Jensen, that's exactly what we got
Speaker 13: into this protection of enterprise spend, this guarantee because the
Speaker 13: investments these days are huge. But it also helps to
Speaker 13: create an ecosystem. So what you need to make it
Speaker 13: in the enterprise is you need an ecosystem. So over
Speaker 13: seventy percent of it is purchased through partners, through channel partners,
Speaker 13: but in the enterprise, if you zoom into just the enterprise,
Speaker 13: it's virtually every transaction, So you really need to have
Speaker 13: trust in partners. You need to have trust that you
Speaker 13: know there'll be people who will help you to have
Speaker 13: a hard ar ecosystem.
Speaker 8: And video.
Speaker 13: May make a GPU, but they work with the cooling
Speaker 13: vendors on this exact specification of how the codeplate that
Speaker 13: will cool it will look like.
Speaker 8: That's very impressive, right.
Speaker 13: So then when you go to the software layer, you
Speaker 13: want to get the developers behind you. And on top
Speaker 13: of developers, you want to also users that might.
Speaker 8: Not be experts.
Speaker 13: So by having both you know, a language, by having
Speaker 13: a platform, by having models, that means that the different
Speaker 13: level of skills you know, people can work with you,
Speaker 13: and then you need to have a services prior enterprises.
Speaker 13: Some enterprises like to do stuff in house. Other enterprises
Speaker 13: like to have a partner.
Speaker 5: And we were short on time, and I've got to
Speaker 5: mention quantum day. That's why we're here in this room.
Speaker 5: And Video does not make quantum computers. Yes, we're having
Speaker 5: quantum day. How do you approach it?
Speaker 13: So I think you know, big speculation of quantum computing.
Speaker 8: When is it coming?
Speaker 13: So I'll just tell you one very quick story. Arm
Speaker 13: CPUs Right, arm CPUs are now a really big part
Speaker 13: of the ecosystem. We use it, and Video has them,
Speaker 13: Amazon has them, many people have them.
Speaker 8: But when it was.
Speaker 13: When the first kind of data center ARMCPU was launched
Speaker 13: in about twenty eleven twenty thirteen. You know, I was
Speaker 13: at Intel when we were very worried about it. But
Speaker 13: at the time it lacked performance, so it took another
Speaker 13: five years for performance to happen. But then it lacked
Speaker 13: software ecosystem, it lacked programmability, it lacked libraries, and it
Speaker 13: lacked you know, being able to use enterprise software out
Speaker 13: of the box. So it took another five years. Huge
Speaker 13: investment from Amazon. Actually, if we're honest for codes to
Speaker 13: be rewritten to work. So we're now in the place
Speaker 13: where Armor was in twenty eleven. So I think that
Speaker 13: we need at least another five years for the hardware
Speaker 13: to get to a place where it's highly reliable. But
Speaker 13: then the programmability of it, how easy it can be popularized,
Speaker 13: that's the difficulty. So in many ways there might be
Speaker 13: true behind truth behind everyone sayings. Pad Guessinger thinks it's
Speaker 13: going to take five years for the hardware, yes, but
Speaker 13: I think Jensen thinks about it very practically. It takes
Speaker 13: longer for the programma BOS.
Speaker 5: System, and Nvidia's argument would be their AI supercomputer separate
Speaker 5: technology can help in the development. Flag Alobov of Ondia
Speaker 5: really great to catch up here in San Jose.
Speaker 3: Turn back to UNSF no great stuff, big thank you
Speaker 3: to add lod though out there in San Jose. Tune
Speaker 3: in at four thirty pm Eastern today for a special
Speaker 3: edition of Bloomberg Technology, hosted by our very own the
Speaker 3: Live from Videos GtC.
Speaker 2: Now coming up, investor.
Speaker 3: Joe Lonsdale and Campus CEO today O Rende are going
Speaker 3: to join us to discuss the startup Series B funding
Speaker 3: round and changes to higher ed.
Speaker 2: This is Bloomberg, a tech startup.
Speaker 3: Campus has just raised forty three million dollars in a
Speaker 3: Series B funding round. The company aims to give students
Speaker 3: a more affordable path to a college degree. Bloomberg Beta,
Speaker 3: the venture capital arm of Bloomberg LP, is one of
Speaker 3: Campus's five largest shareholders. We should note joining us now
Speaker 3: is campus CEO Toddy o ya Rende and one of
Speaker 3: its investors, Joe Lonsdale. Toddy, I want to start with
Speaker 3: you because you studied aerospace engineering in the UK and
Speaker 3: at Embry Riddle in Florida. Was it your experience with
Speaker 3: education that led you to start this company?
Speaker 14: Hey, Tim, thanks for having me. Hey Joe, definitely, I
Speaker 14: mean before college, I was homeschooled until high school. My
Speaker 14: paternal grandfather was a college dean. My paternal grandfather was
Speaker 14: a high school principal. My mother is a college dean.
Speaker 14: My older sister is a professor. So probably I was
Speaker 14: brainwashed from birth to get really excited about education.
Speaker 3: Well, a school's reputation when it comes to academics is everything.
Speaker 3: How do you build that reputation today from the ground up,
Speaker 3: especially in the early years and when for profit schools
Speaker 3: have had such a checkered past.
Speaker 14: Look, it's about elite education for all and so that's
Speaker 14: what we're doing at Campus. We're sort of rethinking the
Speaker 14: first two years of college. We're building a new kind
Speaker 14: of two year college where students get to learned from
Speaker 14: a the best professors from the top schools in the
Speaker 14: country Princeton, Stanford, UCLA knock out the first years of
Speaker 14: college with us, and there not just learning theoretical nonsense,
Speaker 14: learning like really useful skills. And then they transferred to
Speaker 14: the four year school of their dreams to complete their
Speaker 14: bachelors with no debt. And I think that's the key.
Speaker 8: No debt.
Speaker 14: Student loan debt's about to pass two trillion dollars in
Speaker 14: this country. We were hearing crazy stories students taking out
Speaker 14: one hundred thousand dollars two hundred thousand dollar loans that
Speaker 14: are graduating. They can't even get jobs. It makes no sense.
Speaker 14: It's got to stop. But now there's actually a better way.
Speaker 3: Hey, well, speaking of that, I want to bring in
Speaker 3: Joe to this conversation.
Speaker 2: Joe Lonsdale.
Speaker 3: Look, you've already invested in Campus, but this isn't your
Speaker 3: first foray into education. You co founded the University of
Speaker 3: Boston a few years ago. What in your view is
Speaker 3: wrong with higher education? You went to Stanford, you seem
Speaker 3: to be doing pretty well.
Speaker 4: Well.
Speaker 15: Of course, there's a lot of issues with the very
Speaker 15: top of our education, which is what the University of
Speaker 15: Austin's focus on. But you know, I'd argue that our
Speaker 15: community college is unfortunately, are even more troubled in this country.
Speaker 15: There are many have very low graduation rates. A lot
Speaker 15: of them also are focused more on ideology than skills, sadly.
Speaker 15: And so what today and campus represents to me, It
Speaker 15: represents excellence, it represents merit. And you know, our economy
Speaker 15: is changing drastically ais you guys are talking about on
Speaker 15: other segments today. You know, it's changing everything how it's
Speaker 15: going to work, and we need to get the right
Speaker 15: skills and the right frameworks, you know, to millions of
Speaker 15: young adults. And you know, I'm hoping Todd I could
Speaker 15: scale this to a million students, kepture timers, sent the community,
Speaker 15: call colledge market and really help all of those live
Speaker 15: better lives and succeed more on the economy that it's coming.
Speaker 3: Let's go, well, Joe, what's your input on the curriculum,
Speaker 3: because You're hiring a lot of folks, your portfolio companies
Speaker 3: are hiring a lot of folks who have diverse backgrounds,
Speaker 3: who have skills that are arguably not necessarily taught in
Speaker 3: some schools and universities. What's the input that we're getting
Speaker 3: him on the curriculum?
Speaker 15: You know, my push from my side is let's do
Speaker 15: let's add some in more, some more courses in that
Speaker 15: reflect what you need to know for AI.
Speaker 4: You know, there's people like Sam Altman involved.
Speaker 15: As well, who build open AI of course, and others
Speaker 15: who are invested here. And the idea is, how can
Speaker 15: we help hundreds of thousands, millions of young Americans, you know,
Speaker 15: obtain the skills necessary to work in an economy where
Speaker 15: AI is going to be involved in a lot more So,
Speaker 15: that's not the immediate focus today. The immediate focus today
Speaker 15: is on a lot of basic skills needed in today's economy.
Speaker 15: But what's really fun is today's talking a lot and
Speaker 15: thinking a lot about what else can we add in
Speaker 15: here to really make sure we get people ready for
Speaker 15: the twenty thirties.
Speaker 3: Well, Toddy, you were talking about the cost of college
Speaker 3: getting out of control. You were sharing some pretty staggering
Speaker 3: statistics about the trillions of dollars of student loan debt
Speaker 3: that exists in this country. Nobody argues with that. How
Speaker 3: do you make the economics of campus work though, when
Speaker 3: other colleges and other even junior colleges community colleges.
Speaker 2: Are more expensive.
Speaker 14: Yeah, I think the key is, like the completion rates
Speaker 14: actually have to go up for the economics to work.
Speaker 14: So the traditional community college has an average completion rate
Speaker 14: of about twenty seven percent graduation rate, and so when
Speaker 14: you lose students when they drop out, you actually earn
Speaker 14: less tuition revenue per student. So if you actually it's
Speaker 14: sort of paradoxical. But if you actually keep students longer
Speaker 14: because you help them graduate, then guess what, you earn
Speaker 14: more tuition revenue, which makes the economics more healthy. And
Speaker 14: so that's like the sort of the beautiful symmetry in
Speaker 14: terms of what's best for the student, what's best for campus,
Speaker 14: and what's best for our country. Driving up graduation rates
Speaker 14: is actually how you make the economics work.
Speaker 3: Joe, come on in here, because I'm curious about your
Speaker 3: view of the federal government's involvement in education. The government
Speaker 3: is frozen, suspended, or cut more than a billion dollars
Speaker 3: from universities In a recent week, we're talking about reports
Speaker 3: from Columbia, Johns Hopkins ten and more. And I'm wondering,
Speaker 3: as an entrepreneur, as somebody who's hired a lot of
Speaker 3: folks who founded successful companies, somebody who has founded successful companies,
Speaker 3: are you concerned about the American talent pipeline being cut
Speaker 3: off as a result of these cuts?
Speaker 15: You know, I'm more concerned about making sure we spend
Speaker 15: money effectively and efficiently, and so I really like what
Speaker 15: Toddy is doing along those lines. A lot of the
Speaker 15: policy I'm pushing, you know, coming from my side of things,
Speaker 15: is how do we make this spend accountable. So, for example,
Speaker 15: if you're going to do vocational education, Unfortunately, just like
Speaker 15: our community colleges, a lot of the vocational programs, low
Speaker 15: graduation rates, wrong skills, not helpful if you can spend
Speaker 15: the money effectively, if you say these money is going
Speaker 15: to be tied to results. For example, when you tie
Speaker 15: the money to the salaries of students coming out.
Speaker 4: Of vocational schools, it doubles those results.
Speaker 15: Those are types of policies I think be popular on
Speaker 15: both the left and the right, And what I love
Speaker 15: about what today is doing is it's not really playing
Speaker 15: the ideological games.
Speaker 4: There's people of all backgrounds.
Speaker 15: There's people involved from the left, from the right, black, white, Hispanic, everything,
Speaker 15: and it's just about merit and excellence and getting good
Speaker 15: results for very small spend. So I think this is
Speaker 15: this sort of thing that is going to remain popular
Speaker 15: with everyone, regardless of some of the other fights going on.
Speaker 3: Well, today, how do you watch what's happening in the
Speaker 3: federal government because Predesident Trump today is expected to sign
Speaker 3: an executive action that formally asked officials to take steps
Speaker 3: to dismantle the Department of Education. According to our reporting,
Speaker 3: what happens to your business then, because forty percent of
Speaker 3: your students qualify for pelgrants and those are administered by
Speaker 3: the Department of Education.
Speaker 14: Yeah, Look, the vast and jort of our students use
Speaker 14: PEL grants to cover their twition and so they don't
Speaker 14: have to pay anything out of pocket for twition expenses.
Speaker 14: Paul Grant is not going away. Even if the Department
Speaker 14: of Education is dismantled, some of these key programs that
Speaker 14: are mandated by Congress are going to be split across.
Speaker 14: You know, maybe Treasury or the IRS or other organizations.
Speaker 14: The way I look at what's happening in Washington right
Speaker 14: now is, hey, look, obviously everyone's looking at this and saying,
Speaker 14: we need to be more accountable. As show talked about,
Speaker 14: we definitely need to be more efficient with taxpayer dollars.
Speaker 14: It's really early days. Secaturmic Man's been in there for
Speaker 14: less than three weeks. I think you know we're watching
Speaker 14: it closely, but we're going to have to let this
Speaker 14: one play out.
Speaker 3: Hey, Joe, last one to you, speaking of efficiencies in
Speaker 3: the federal government, You've been supportive of Dog this week,
Speaker 3: though a federal judge ruled that Elon Musk's actions to
Speaker 3: shut down USAID violated likely violated the Constitution in multiple ways.
Speaker 3: Are you concerned that the courts are going to prevent
Speaker 3: Elon from being able to do the cuts that you
Speaker 3: want to see him?
Speaker 15: Do you know that particular ruling. I'm glad you mentioned
Speaker 15: it because it was so ridiculous. So actually the ruling
Speaker 15: was so misguided that it thought Congress had created USA,
Speaker 15: which is not correct. It was actually created by executive
Speaker 15: action the USA. It is just such a great example
Speaker 15: of just complete waste, right they're just all sorts of
Speaker 15: scams and fraud that we've uncovered. I think no matter
Speaker 15: what your party background, if you look at the details,
Speaker 15: you'll agree this should have been turned off.
Speaker 4: And there are.
Speaker 15: Activist judges they are going to try to slow it down.
Speaker 15: I personally hope the Supreme Court is going to step
Speaker 15: in and make some sound rulings here and stop activist
Speaker 15: judges from violating the Constitution by their interference. And it
Speaker 15: is going to be a big issue.
Speaker 3: So what have you spoken to Elon about this? Have
Speaker 3: you spoken to Elon since he's been a doge.
Speaker 15: He's a friend and I am in touch, and he's
Speaker 15: working really hard with a lot of smart people. They're
Speaker 15: being very aggressive. A lot of my friends are involved
Speaker 15: in DOGE and listen, there's there's I think. I don't
Speaker 15: think everything they're doing is going to always be perfect,
Speaker 15: but there's so many crazy things that have to be
Speaker 15: turned off and have to be confronted that overall, I'm
Speaker 15: very very happy for the work they're doing, and I
Speaker 15: think they're kind of shocked about some of the ridiculous
Speaker 15: things they're finding as well as they're publishing all right.
Speaker 3: Well, really appreciate both of you guys joining us. That's
Speaker 3: Joe Lonsdale from a VC also campus CEO today. Oh
Speaker 3: Yareen Day, thanks so much for joining us. If you
Speaker 3: wanted to grind the world to a complete hall, you
Speaker 3: could achieve.
Speaker 2: That by removing magnets.
Speaker 3: They're crucial to basically all tech, including EVS and the
Speaker 3: next nuclear breakthrough fusion Energy Primer or the latest Bloomberg
Speaker 3: original series takes a deep dive into all of this.
Speaker 16: It takes a lot of work to build something big.
Speaker 16: You also gets very expensive, like the amount of money
Speaker 16: you need to spend on something to get just the
Speaker 16: first one can get very very expensive.
Speaker 17: That's exactly what's happening with ETA, a giant fusion reactor
Speaker 17: currently under construction in France that uses super conducting magnets.
Speaker 17: Look at this thing. It's huge and as a result,
Speaker 17: it's projected to cost as much as sixty five billion dollars.
Speaker 17: So to make fusion smaller, cheaper and more practical, Commonwealth's
Speaker 17: founders needed a whole new kind of magnet.
Speaker 16: The question was like would that material ever happen? And
Speaker 16: it wasn't until the early two thousands we could really
Speaker 16: see that that material was going to happen that there
Speaker 16: would be a new type of superconductor. And it's a
Speaker 16: weird it's not a wire, it's a weird thing. It's
Speaker 16: a film and it won the Nobel Prize like months
Speaker 16: after it was discovered.
Speaker 18: So this is a material called HTS or high temperature superconductor.
Speaker 18: Is it is Literally it comes down a tape. It's
Speaker 18: probably kind of hard to see on the camera. It's
Speaker 18: very thin. It's actually mostly copper and steel, but there's
Speaker 18: a very very very thin layer inside of this that
Speaker 18: is high temperature superconducting material.
Speaker 17: High temperature in this case is still wildly cold, but
Speaker 17: not quite out of space cold. And that was the
Speaker 17: breakthrough that Commonwealth needed. Magnets made with this material can
Speaker 17: create a stronger magnetic field, so they don't have to
Speaker 17: be so massive.
Speaker 18: You can shrink the size of the device by a
Speaker 18: factor of ten. Basically allows us to make things smaller,
Speaker 18: which makes things cheaper and makes things faster to get
Speaker 18: fusion to a spot where we can make energy from it.
Speaker 3: And that was the voice of Caroline High. Tune into
Speaker 3: the first episode of Primer tonight on a Bloomberg TV
Speaker 3: at six pm Eastern time. That is going to do
Speaker 3: it for Bloomberg Technology. Tune in later today at four
Speaker 3: thirty pm Eastern one thirty pm Pacific for a special
Speaker 3: edition of Bloomberg Technology Live from Nvidia's GtC event.
Speaker 2: Also check out our podcast.
Speaker 3: You can do that on the terminal, as well as
Speaker 3: online at Apple, Spotify, and iHeart This is Bloomberg.