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