# AI Infrastructure Demand, Chip Architecture, and Enterprise Adoption

**Podcast:** The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
**Published:** 2026-05-26

## Transcript

We can't build data centers fast enough to keep up with demand.
We have a $25 billion backlog.
If demand stays high, we're going to continue to see memory shortages for at least the next several years.
I think it has been NVIDIA's strategy to try and create competitors for the traditional hyperscalers.
I think they have funded and backstopped and over-allocated to the neoclouds.
They have created a dependence.
which is probably not healthy.
So over time, the history of our industry is a massive reduction in the cost per unit compute.
For hard problems, there is no upper bound to how much faster you want to be.
This is 20VC with me, Harry Stebbings, and I'm so excited to welcome a dear friend, Andrew Feldman, founder and CEO at Cerebrus.
Now, this show just makes me incredibly happy and proud to do because this is a true testament of resilience, of grit, of building really hard things.
And last week, Cerebrus went public, the largest semiconductor IPO ever.
The price went from $185 to $311.
They got over $5.5 billion.
It was an incredible day for an incredible team.
Today, we deep dive on the future of chips, the future of US-China relations, the future of data centers and energy.
This was an incredibly wide-ranging conversation, and I just want to say a huge thank you to Andrew for being a great friend to me over the years and for being a fantastic advisor to 20VC.
But before we dive into the show today...
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Andrew, dude, it is so lovely to have you on the show.
I have to say, I was quite emotional last week when I saw the IPO because you are one of the kindest, greatest people.
I love getting to know you.
I so appreciate our relationship.
And so to see that culminate last week with the IPO was really special.
So congratulations for last week, dude.
Thank you so much.
Those were really kind words.
And it was a really exciting day for the company and the team and the people who'd believed in us and who backed us for a decade.
It was great.
Thank you for saying those nice things.
Not at all.
And I was thinking in terms of this conversation, how I wanted to structure it.
And I always get back when I have amazing people like you on the show, which is Eleanor Roosevelt's kind of statement of not very intelligent people discuss other people, mediocre people kind of discuss current events, and then intelligent people discuss the future and ideas.
So I thought I'd grapple with my own ideas and wrestle with your incredible brain to help me understand where we're at and where we're going.
I want to start with, on the one hand, we look at the landscape stand, it's like, oh my gosh, an AI infrastructure bubble.
And then on the other hand, we look at, you know, Jensen Huang last night, he comes out and says, we're going to be spending three to four trillion on AI infrastructure by 2030.
How should I balance the, oh, there's an AI infrastructure bubble with this appreciation of three to four trillion dollars spent by 2030?
I've been thinking a lot about this.
I think when you look at other bubbles.
And you look at bubbles in the past.
And I was in one in the late 90s when we built out an enormous amount of fiber optics.
And you sometimes have economists who maybe think it's relevant to look at 1880s, the building out of rail.
I'm not sure that's relevant.
But what I see is that there was a pension to believe that if we built it, they would come.
The infrastructure build out was way ahead of demand.
And that was true in railroads.
That was true in fiber optic cabling.
And in a strange way, that is the exact opposite of where we are with AI.
The infrastructure build-out is behind demand.
We can't build data centers fast enough to keep up with demand.
We have a $25 billion backlog.
NVIDIA has a backlog.
AMD has a backlog.
Others have backlogs.
They have backlogs because we can't get data centers built fast enough.
And it's not that we're building on the come.
We're not building ahead of demand.
We're building behind demand.
That is a very different observation than those who say there's a bubble.
I don't think they've really gotten their head around the fact that we are trying to keep up with demand, not the other way around.
And I don't think that's a characteristic of a bubble.
When you are trying with your infrastructure to keep up with what people want today, not in the future, today, and their demands are growing over time.
Is it ultimately a good thing that we are metered in our ability to build out data centers because it almost tempers the demand?
If we were able, and Gavin Baker said, actually kind of the delays and the permitting and the challenges that are incurred today actually help because if you were able to have it all today, all of demand would be met with all of supply and that would actually be a challenge.
Sometimes the world is like...
I was in my 20s the first time I went to Vegas and went to the buffet, right?
You eat so much, you feel sick for days.
It's all in front of you, and you just gorge yourself.
I think the market can sometimes be that.
And I think Gavin is an extraordinarily thoughtful sort of guy about this.
I think we are being metered.
We also know that the reason you put meters on a freeway is because it makes the freeway traffic smoother.
It avoids hiccups.
That's exactly what metering is designed to do.
And so I think he used that analogy extremely thoughtfully.
One of the advantages that OpenAI has, and I think one of Sam's brilliances, was that he saw an exponential growth and he saw what that would mean in a year or two to the demand for compute, and he wasn't afraid by it.
He went out and took action.
And perhaps others couldn't believe it, or they were looking at the same demand, sort of steep exponential growth, and were like, well, we can't need that much.
You can't need tens of gigas.
My mind hurts if you do that.
Whereas what OpenAI did is they went out and they were like, we're going to contract for it here and here.
We're going to get power.
We're going to get data centers.
We're going to sign up for hardware and an ability to believe your data in an exponential growth environment.
out a year or two or three is a superpower.
Do you get rewarded for that insight if you can just buy it from Elon now on demand?
I don't think they can buy the same thing from Elon on demand.
They bought downrev gear.
I'm sorry.
I've learned from doing this show for a long time.
I can ask stupid questions.
They bought downrev gear?
What is that?
They got H100s.
They didn't get the B200s.
They didn't get the most current.
They are a generation and a half, maybe two generations behind.
This was not a great deal.
It was a good deal for Elon.
He had them sitting around.
But they were forced to take action in a deal that I think was not the ideal deal they wanted.
It was a deal that was available.
Going back to what we said about kind of the delay in data centers and data centers being a constraint, I just hear everyone say, well, memory, memory is the shortage too, Harry.
And that's why we're seeing an increase in cost, you know, 4, 5x in certain cases.
Is that true?
How should we think about memory being the shortage as well?
What's happening here is there is such extraordinary growth in demand that it is putting pressure on all parts of the supply chain.
Memory after TSMC, which is right after FabSpace, memory is number two item that's needed.
And what's happened is there are only three companies that make the memories GPU use.
We don't use that memory.
But that HBM is made by Samsung and Micron and Hynix.
They couldn't keep up.
And so the price is shot through the roof.
I mean, Micron...
producing numbers where they have 80, 85% gross margins.
I mean, they're getting software gross margins on making memory.
Yeah, I think it's extraordinary.
That is a limitation for all GPUs, but not us.
We don't use it.
Again, going back to my idea of what the future looks like, what should one expect from that?
Does it ease?
Does it ease over time?
What happens to the cost?
The challenge here is that these are extremely lumpy.
items, right?
You can't just add a little bit of manufacturing capacity at a fab.
You have to build a fab for $40 billion and it takes five years to build.
If you see demand explode, you cannot respond quickly.
All you can do is fill your factory.
Once your factory is filled, you got to build another factory, right?
It's a step function in your ability to meet that demand.
And the step is huge and takes years.
And so...
If demand stays high, we're going to continue to see memory shortages for at least the next several years.
Do you think we will see a peaking of demand?
You've seen so many different...
Not if AI continues to improve in usefulness.
I mean, what's happened here, and this is something that I haven't heard others sort of talk about, is that somewhere in 2025, the models got smart enough to be really useful.
Before that, Harry, these were sort of a novelty.
AI was like, cool, and then nobody used it.
Remember, we make AI with training and we use it with inference.
And so once the AI we made, 2025-ish, got smart, we began using it.
And this explosion in demand that Jensen described and that we very much agree with is happening.
That's because people are using it every day.
And they're using it on more and more problems.
They're using it on harder problems.
And it is sweeping through different demographic groups.
It's not just 28-year-olds in Silicon Valley.
It's my 85-year-old father, right?
My 11-year-old niece.
It is sweeping through demographic groups, and they're using it all the time.
That is what's driving this demand.
If we continue to find ways to make the AI, the frontier models, smarter and more useful, we'll keep using it.
The demand will continue on this sort of exponential curve.
You've compared past cycles before in this conversation.
Sarah Fry said about cloud providers can be similar into some perspective to what we're seeing today in terms of frontier models.
And she said that last night.
To what extent do you think you see the commoditization there?
And they essentially become utilities versus differentiated providers with meaningful modes.
I think it has been NVIDIA's strategy to try and create competitors for the traditional hyperscalers.
I think that has been a strategy of theirs.
I think they have funded and backstopped and over allocated to the neoclouds.
They have created a dependence, which is probably not healthy.
The truth is, is that what AWS and Azure offer is extremely useful for most enterprises.
They offer credibility and legitimacy.
They offer security.
They offer layers of different software for different parts of your organization.
If you'd like to enter in the AWS world, you can enter with Bedrock.
You can use tools like SageMaker.
You have a collection of different ways to enter.
And you can store your data there.
You have your S3 instance.
I mean, you can have an entire offering.
I think that is really valuable to a segment of the market.
I think there might be other segments of the market that are like, give me cheap compute.
I don't care about anything else.
In that case, your strength as a hyperscaler becomes your weakness.
You have the security, you have the other layers of software, and you have some of the costs that are associated with that.
And if people don't want that, if you don't care about leather seats and their leather seats in the truck, there's extra cost in the truck.
And when you buy the truck, you find somebody who's got a truck that's got naugahyde seats.
Our business, just because it's wrapped up in technology is no different than any other business.
It's segmented.
There's value.
That value comes at a cost.
You have to make that value.
The hyperscalers make the value.
They make the value through software, through security, through having rules about their data centers, about the security, physical security, the various security checks they put in.
Those are enormously valuable to most parts of the market, but not all.
You said about the costs there.
When we look forward, how do the costs of your business change significantly over time?
We spoke about the cost of memory going up 5x.
If we look at the cogs in five years' time, how do you think they will look most significantly different?
Well, look, the increase in memory has been very good for us because we don't suffer it, right?
This has given us opportunity.
We use SRAM and there's no shortage of SRAM.
The cost of SRAM hasn't changed.
And, you know, no SRAM maker, because TSMC etches it into your chip while they're making the logic.
There are no extra margins to pay the HBM maker.
And so we have been advantaged in this environment.
We have been advantaged by the fact that there are constraints on co-os at TSMC.
We don't use co-os.
We are advantaged by the fact that we're at 5 nanometer, and the 3 nanometer node is the most oversubscribed.
Our supply chain is advantaged on these dimensions.
And others are paying the price.
The price of GPUs has gone through the roof.
And so to my question on COGS, do we see like a plateauing of COGS in terms of it can't get cheaper and this is the stable state?
Do we see a meaningful reduction?
I think what happens over time, Harry, is all of us.
We improve our designs.
The designs deliver more tokens per unit time.
They deliver faster tokens.
We are 15x faster because of architectural reasons.
We will continue to improve over time.
Nvidia, they will continue to improve over time.
I believe the gap will widen between our performance and their performance.
But all of us, the whole industry, us, Nvidia, AMD, Qualcomm, ARM, everybody's chips will be better in three or four years than they are today.
They will produce more per unit power and they will produce more.
per dollar cost.
So over time, the history of our industry is a massive reduction in the cost per unit compute.
I was chatting to a friend who is a phenomenal mind, and he said that Google will become the lowest cost producer of tokens because they own the full stack from TPUs, data centers, networking, power procurement.
Do you think that's right, that that full stack ownership will lead to their highest margin, lowest cost ability?
There are pros and cons of that strategy.
pro is you have everything from the ground, land, all the way up to tokens.
The downside, you can only sell your TPU to yourself.
And historically, volume mattered a lot.
And so your market is constrained by your own demand.
Whereas if you were able to sell to the whole market, you might have more demand and be able to drive down the cost.
It's an open question.
Google is threatening that argument.
I think your friend's argument is reasonable, but there has historically been a challenge if you only have one customer yourself for your hardware.
That has historically limited the size of the opportunity landscape for you.
Do you think they should sell to external customers?
I think you are already seeing them step outside of their own data centers for this exact reason.
What it says in your friend's construction is our ability to sell hardware is constrained by our ability to build data centers.
One can imagine a world where you don't want that constraint.
You would like to be able to sell hardware to anybody's data center.
These arguments are extremely complicated, rarely unfold in a simple form.
But it is true that when Google or when Cerebris puts our equipment in our own data center, we have a significant advantage over a neocloud.
Because NeoClouds are buying hardware with gross margins of 70, 80% for NVIDIA.
So the hardware in those data centers, and then they have to make their margin.
That's not what Google's doing.
That's not what we're doing.
Does that mean they're dramatically over-vindied when you look at an Abias or a CoreWeave or any of the others?
I think CoreWeave has been an extraordinarily innovative company.
I think they've solved a series of financial challenges with really innovative sort of financial engineering.
They were the first to use debt in a very innovative way.
They get enormous credit for that.
They have been extremely good at sort of rapid deployment, which itself is a really important skill in this environment.
I don't know about the others, but all of us have challenges as our business grows.
I think they have produced really interesting things through creativity.
Now, it's different creativity than what I have, but they've gotten paid for real innovation in financial thinking.
Speaking of real innovation, I saw the post about you running Kimi K2.6, 6.7x faster than the next fastest GPU cloud.
We posted it while one bozo at an analyst firm was on TV saying we couldn't do it.
I mean, if ever there was an example of being empirically proven dead wrong, to have these numbers posted while you are on TV saying, They can never do it.
It was perfect.
I enjoyed that.
I'm a collector of examples of people being dead wrong.
My wife has a list of when I'm dead wrong.
So I've sort of embraced this and collected.
You should be a venture investor, my friend, with a portfolio of 30.
You'll be dead wrong a lot.
You have, if you're lucky, 80% of your portfolio where you were dead wrong.
You should do if you're doing it right.
Yeah, I agree with that.
How important was that for you?
And is there a stage where actually...
It doesn't matter being that increment more important.
Like 6.7 times.
This is so much more important.
It's not 20% more important.
That's right.
I think for hard problems, there is no upper bound how much faster you want to be, nor the value of speed.
I think that if in three minutes we can solve problems.
that take others 20 minutes, then think of all the extra problems we get solved.
Think of if I'm your competitor and I'm solving your hard problems in three minutes and you're taking 20.
Imagine over a day or a week.
I mean, you get smoked.
You will be smoked in this example.
That is the way this is going.
Speed is of the essence.
And it's true in coding.
It's true in agentic flows.
It's true in every part.
of the AI landscape.
I mean, let me just ask you this question.
How big is the market for a slow search?
Really, it's zero.
How big is the market for dial-up, for slow internet?
How much would I have to pay you?
Let's turn it around and say, there's a negative market here.
If I gave you $1,000 a month to have slow internet in your home, you wouldn't take it.
$1,000 a month.
That's how impossible it is to engage with an important technology slowly.
Why do we believe that inference will be any different?
I am kind of pushing them when you power codecs and you're able to be so much faster.
If you're claw code, are you not like, ah, bugger?
They are.
I think you have to be.
You have to be.
Are you able to sell to them also?
Again, please tell me to sort off.
Oh, no, no, no.
Look, right now we are digesting one of the largest deals in the history of Silicon Valley.
You're like, for fuck's sake, Harry, give me a break.
I've just signed a $20 billion deal.
You want more?
While we were on the road, some investors would ask, they say, oh, you're heavily concentrated.
You have a big portion of your business with OpenAI.
And we say, I talked to you a year ago when I had a billion dollar deal with G42.
And you said, you're heavily concentrated.
You have a billion dollar deal.
I said, I come back to you in a year with a 20 plus billion dollar deal.
And you tell me the same thing.
But with a different customer as well.
With a different customer.
With a different customer.
And I tell everybody that the way you get good.
And the way you have succeed with many customers of size is first you win one.
The way to catch big customers is first catch one and learn, build the muscle, change your supply chain, learn how to work with a large customer.
Then you're in a position when the next one comes to have a chance to win.
And what's more, chance to keep them happy once you won.
And then once you have that muscle, you're in a position to go out and win the next one.
It is a huge deal.
What are the biggest challenges in fulfilling it?
With the greatest of respect, you go to sleep at night going, oh, that is quite a lot.
Look, I think what has happened, and Sam said this, he said the first time people use GPT, I think it was what, four something, they said, oh, this is amazing.
And the next day they're like, how come it's not faster?
The rate at which you get accustomed to something and then want better is amazing in our industry.
And it used to be the case that 20 megawatts was a lot, and then 100 megawatts was a lot, and then a gigawatt was a lot.
And now we're running around looking for multi-gigawatt facilities.
And that's, in any other time, 750 megawatts would have been a mind-boggling amount.
And now we're like, yeah, we got that.
It is the change in mentality over the last year or two for everybody in our industry has been sort of extraordinary.
Five years ago, if you'd have said, we're engaged in a multi-gigawatt build-out, or you'd think about what Crusoe is doing, or think about some of the other cool companies, what SoftBank Power is doing, what some of these groups are doing, and you'd say, that would be delusional five years ago.
And right now, it's like, oh, another one?
Yeah, that makes sense.
I mean, we should try and get our UAE Stargate at five gigawatts.
Oh, yeah, yeah, no problem.
That seems reasonable.
That's what's happened.
It's this extraordinary sort of change in thinking.
If we are nonchalant to multi-gigawatt build-outs today, what are we in five years' time?
It's difficult to imagine.
And by the way, that is exactly where I think Sam is the best in the world, maybe Elon, is where everybody else's brain shuts down, right?
When you're trying to think about 100 gigawatts or 500 gigawatts.
Those guys, they have sort of this ability to not be constrained by the way the world has always been.
And that is such an extraordinary power.
When you have such scale as the multi-gigawatt, you mentioned that the 500 gigawatt, does energy not just become the core crux and bottleneck that enables winners and losers?
I certainly think that people like Sam and Elon and others have said that's what they believe.
that at the end, we're in the business of turning electricity into intelligence.
Therefore, the limiting factor is electricity.
I don't know if I agree with that, but that is certainly a very reasonable view from where we are.
What's the bad case against that?
What's the alternative argument?
It doesn't have to be yours, but it happens.
No, no, that you bump into something else.
That what happens, in fact, is our models can't.
keep getting smarter.
That you hit something that has an assumption built in that the models keep getting smarter and you keep feeding them more energy.
And at the end of the day, the models are either smart enough or keep getting smarter so that it makes sense to keep feeding them energy.
That might be true.
I don't know.
Do you think we'll be able to build out data centers in the way that we need to and build out capacity in the way that we need to when we see that 40 out of 100 data centers are now not being built out, even post-approval because of local municipalities permitting, disruption?
AI is not popular.
Harry, I think it's hilarious.
People say, oh, my God, the data centers are late.
Oh, my God, they're delays.
Have you built a kitchen?
Your contractor was late.
Pick a little tiny project in your home.
Was it built on time and on budget?
No.
Now imagine building something the size of 50 football fields and requiring interaction with local municipalities and power companies and regulated industries.
These things aren't going to be delivered on time historically.
People's mind explodes and they never think about their own experience in their own homes.
Does your contractor show up every day?
No.
Does he do exactly what he says he's going to do?
Rarely.
Do the materials, the tiles or whatever you selected for your home, do they sometimes delayed?
Yes.
All that same thing happens when you build a data center.
The generators, sometimes they're late.
Sometimes they fall off a truck, literally.
They fall off a truck and damage is done to them.
Are the transformers late?
Sometimes the transformers.
I mean, everybody suddenly...
sort of throws their arms up and says, oh, everything's late, or they have to deal with localities.
Anybody who's built anything big knows this is par for the course.
This is what building is.
So you're not concerned then about bluntly local neighborhoods seeing data centers as a symbol of...
I think our industry did a shitty job of engaging the community properly.
And I think Brad Smith put out a post a while ago that should have been the way we all work from the get-go.
And it was, these can be clean, they can make jobs, they can be good for communities.
We can do this thoughtfully.
These create thousands of local jobs.
And thousands of local jobs mean restaurants and lunches and hotels.
And the way they were done was, I don't know if sneaky is the right word, but sort of shielded and wasn't open.
And they weren't good neighbors.
Now, there is no reason why we can't be good neighbors.
There's no reason why we can't.
add these to communities and have the community benefit from it.
And we have to do some thinking, right?
We have all the heavy equipment out there.
Build a football field for the local school.
Build a school.
Add a church or a synagogue to the community, right?
We can be good neighbors at very, very low cost.
We can pay our own way.
Don't try and use sort of loopholes in the way power companies.
have historically amortized the cost of new power lines over 30 years and push that on the community.
That's BS.
We ought to pay our own way.
We ought to look after our neighbors.
When we do that, I think that the neighborhoods that embrace this will benefit enormously.
But we didn't do a great job.
I mean, we didn't do a great job as an industry at all.
It feels like kind of the cartels in Columbia, they were, it's like they built the churches and they built the schools and they had such good businesses and such high margins that they could kind of get away with it because of that.
And hey, great.
I don't think that's right.
I think these localities have a resource that isn't being used.
They have power.
Many of these land is cheap because nobody wants it.
We are not going to parts of Metro New York.
Everybody wants that chunk of land.
You're going to places where the price of land is depressed.
You are near power resources.
And my position is that we ought to be good neighbors and we ought to be transparent.
We ought to pay our own way.
Now, this seems not to be very controversial in my mind.
I think the best and most concise description is what Microsoft has put forward.
And we should have been doing that from the get-go.
Most communities are comfortable when their neighbors pay all their own way.
And it's only when groups tried to shift costs or not pay for the full resources they're using.
Our data centers don't need to use a ton of water.
They can recycle it.
You can have a closed loop.
We can pay our own way.
We can upgrade substations.
We can upgrade grids and pay for it in its entirety.
We shouldn't be pawning that off on local communities.
Do you worry about like AI as a brand?
You see Meta lay off a huge amount of people today and it's challenging to see 4am emails from Zerk and jobs being lost.
Yeah, I do worry about it.
Those are people and they have families.
And I think there are sort of two views, Harry.
I think to date, most of the layoffs were AI washed.
They were because we did boneheaded hiring during COVID.
It is actually because a great deal of productivity gains have occurred over the years that we're just now harvesting.
The ability to gather information from across the organization, to synthesize it and put it in one place, is now changing what it means to be middle management.
The role of information gatherers and presenters is being eliminated.
The ability for us to automate roles.
None of this is AI yet.
That is really...
90%, 95% of what the, in my view, what the terminations have been about.
It's easy to put them under the umbrella of AI.
Now, AI is starting just now to have meaningful enterprise impact.
But if you are an engineering organization that can't see how to take advantage of vastly more productive engineers, I don't think you're long for this world.
I mean, the list of things I want our engineers to do is 50 times as much as we have engineers.
As we get more productive, we do more things.
We're going to hire more engineers.
We're not going to hire less engineers.
Can I ask you, we saw Benioff say that he spends 300 million a year on Anthropic, which equates to about 3.8% of developer salaries on Anthropic.
To make it justify the valuations that we're seeing for these companies, it needs to be 20%.
Do you have any concern in that movement from 3.8% to 20%?
No.
I mean, I think if you look at, and I've never done this in any detail, but.
If you look at what we pay hardware engineers and you look at what the tools, the EDA tools they use, I bet you're much closer to 15 or 20 percent than 2 or 3 percent.
What's happened is historically software engineers use very low cost tools and hardware engineers used extremely expensive EDA tools.
And so that's interesting, isn't it?
I mean, the cost of bugs in hardware is so high that we became accustomed to using many expensive tools.
In software, we threw people at the problem rather than tools.
As AI becomes more productive, I certainly don't see a problem where software engineers are using 50 or 100,000 a year each in tokens.
There are 47 million software engineers in the world.
I mean, that's $5 trillion just in software engineering token use.
We mentioned hardware engineers, we mentioned software engineers.
What role does not exist today that you think will be incredibly commonplace in three to five years?
I've been a part of, over the past 25, 30 years, several technical transformations that produced jobs in companies that didn't exist.
Prior to the mid-90s, the role of CIO didn't exist.
CIO arose as a role with Cisco, with their sort of rise to dominance.
Prior to the mid-90s, the amount of enterprise networking was de minimis.
There was a role that was often VP of telco infrastructure.
That job is gone.
We don't have a phone system.
In fact, we don't have phones on people's desk.
Call me on my cell phone.
That job disappeared completely.
Gone.
And companies that built the PBXs like Rome and all these other, that business has shrunk to nothing.
Now, later.
What happened in the 2000s with the rise of Palo Alto networks and these other security, the role of CSO never existed prior to that.
And what you're going to see is the rise of roles that reflect the governance of AI in companies.
Some companies have chief AI officers.
I don't know if that's what it is.
But as these technologies become important in companies' life, new jobs emerge, jobs that never existed before.
New organizations exist where there were none.
Previous ones disappear.
I think the role of HR changes fundamentally.
The part of HR that answered questions, that provided information about benefits, that disappears.
AIs can answer all your questions.
They can provide better answers, faster answers, more thoughtful answers.
It becomes something different.
The management of people becomes something different.
I think there are all sorts of other parts of organizations that have fundamental changes.
Because AI can answer the questions that they used to answer.
Do you agree the biggest inhibitor to enterprise adoption of AI is data structure and data clanniness preventing?
No, no.
The biggest are lawyers.
No, really.
I think the security apparatus and the lawyers who, when they don't understand the technology, say, no, we can't do it.
They're in the saying no business.
Entrepreneurs are in the getting it done business.
There's a reason for this, that your security apparatus and your lawyers, I mean, they're in jobs that everyone just blames them.
No credit, no credit, failure, blame.
No credit, no credit, failure, blame.
I mean, that's their life, and it's brutal.
It's brutal.
You're selling it so well for any aspiring lawyer.
Go into being a CISO.
It's brutally hard.
We had a year where nothing happened.
Well done.
That is their dream.
I mean, every day their phone doesn't ring.
It's like, oh, made it to another day.
But when confronted with new technology, because their payoff structure is such that they're in the business of trying to avoid risk, they are a drag on adoption of new things.
And you see this across the board.
Lawyers don't know how to contract for it.
There's no precedent.
That's in a business of backward-looking precedent.
You want to make a lawyer uncomfortable?
I know your girlfriend's a lawyer.
Ask her to work in an area with no precedent.
They don't know what to do.
Their whole training is about what has everybody else done before?
How do we synthesize this?
How do we work within those rules?
I think the wide-scale adoption and use of AI in organizations is today limited by security and legal.
Once they agree, we need to do this, here are the rules we will use, there's a huge amount of productivity to be gained.
Then you are immediately constrained by the way you chose to husband and marshal data.
the way you chose to organize data over years.
And so companies like organizations like Mayo Clinic that have been on a 30-year quest to organize data, they are at a huge advantage.
Same with companies like GlaxoSmithKline and other companies who haven't perhaps been as disciplined, as thoughtful about the organization of their data.
are at a disadvantage.
On the security and the provisioning side, do you think we will see industries tip like legal has done where the biggest firms in the world are now going, oh, shit, we need AI.
Our clients are saying we need AI.
Harvey or Lagora.
I'm not going to get into which one, but there's two options.
Boom.
Do you think all industries will follow the tipping or do you think most will follow the slow agreement that it's the new normal?
What's happening is the leaders are tipping, right?
And I think even Jensen told a story that he was battling with his own internal lawyers around the use of, I think it was cursor.
And finally, he just decreed, we're going to do it.
I think at some point, leaders weigh the productivity gains against the unseen boogeyman of Brisk.
And the problem with unseen boogeyman is sometimes they're actually real.
Not often, but sometimes.
That's the problem.
What does he call him in John Wick?
Baba Yaga?
John Wick is the guy you send to kill Baba Yaga.
I'm just, you know, I think for me, I'm not that young anymore, but I'm definitely capable of exuberance.
You look good.
I know you're in your 60s, but you look good.
Yeah, and it's the facial moisturizing routine.
We mentioned security, permissioning, legal, everything in between.
They get even more freaking nervous when it's open source.
They shit the bed.
How do you think about that?
I see more and more companies, especially in the Valley, really push the boundaries with Frontier and then try and get as close as possible with open source, given the cost advantages.
Is that the future?
And what does that mean?
Look, I think we as an ecosystem have made real progress in sort of the legal gunk.
around open source, but the result has been a complexity that hurts your head.
If you ever want to dive down a rat hole that has no bottom, begin a discussion with lawyers about open source software.
And there's no end to the depth and the boredom which you will suffer as you head down this hole.
This is made doubly worse by some of the best open source models were made by Chinese companies.
And they are exceptionally good models.
Kimi K2, DeepSeek, Quen, GLM, these are extraordinarily good models.
They're not quite as good as the closed source models, but they're exceptionally good models.
And I think that is a case of people trying to decide whether it makes sense to save money.
They have been easy for us to adopt, to demonstrate extraordinary speed on.
It's a hard problem.
I mean, I don't envy the legal team and the security groups that are thinking about these things.
The truth is the tidal wave is so big and the demand is so high, they often just get washed over.
Do you think we should be selling chips to China as a result?
No.
I think let's remove all of us that are self-interested, even though I'm arguing against my self-interest, right?
If you remove me and you remove Jensen, you remove Lisa, you remove everybody in the chip industry.
And you say, if we sell to somebody in the security business, and you ask this question.
If we sell leading edge technology to China, will their military use it?
Everybody says yes.
There is no debate on that point.
Their military will use it.
You ask a second question, which is, if you sell our leading edge technology, will their government use it through their industry to compete with us in an advantaged way?
The answer is also yes.
That's where I stop.
There's complete agreement that those two things are true by everybody in the security business and outside of the chip business.
Now, you can say that keeping them in our ecosystem is the best way to manage that problem.
That's one argument.
And there's some merit to that.
There is keeping them from building their own ecosystem is something that's in our interest.
There's real merit in that.
I don't agree with either of those arguments, but they're real arguments and they have real merit.
They are, at least today, our industrial adversary.
As you travel the world and you see the results of some of their industrial policy, for example, the driving down the cost of solar, driving down the cost of lithium batteries, the results it's had in their auto industry, and the fact that you travel the world and you see Chinese cars and fewer and fewer American cars, they're an industrial adversary.
I don't love that.
I, for years, did business with extraordinary entrepreneurs there at Baidu and at Tencent and Didi and all these companies.
They're every bit as good as anybody in Silicon Valley.
And I would love a world in which they weren't an industrial adversary.
And instead, we were working together to solve real problems.
The state of the world is the state of the world.
For me, if it's an industry, as American industry, we sold fewer chips and we didn't sell them to China, I'm just fine with that.
People would argue back and say exactly as you said that if we don't sell to them, they'll build their own capabilities and they'll get very good at it.
And then we won't control it.
Why do you not think that's a credible argument?
I think the chip industry requires you to go through TSMC, and TSMC requires you to go through ASML or Samsung.
There are reasonable choke points to manage those challenges.
I think the strategy in any case is, even those I think who disagree with me would suggest that you don't want to sell them your cutting-edge technology.
You want to keep them down rev.
I'd like to keep...
My industrial adversary is more than downroth.
With that, how important is it that we onshore TSMC-like capabilities in companies given Taiwan's vulnerability to China?
We have problems in the US in long-range policy.
Policy that endures more than a single administration.
We have problems building infrastructure that is clearly needed and crosses municipality lines.
Let's look at things China has done extremely well.
Their power infrastructure is extraordinary.
And in the U.S., we are a patchwork of 1950s technology, if we're lucky.
And that's really bad.
There are things we don't do well.
One of them is thinking about long-term consequences of decisions like not investing in fabs in the U.S.
We didn't just lose the fabs.
We lost the surrounding ecosystem.
We lost the packaging expertise.
We lost a whole set of surrounding strategic jobs and industry, and it is extraordinarily important we get it back.
And I've been saying that for a decade and a half, that not the CHIPS Act, not subsidizing Intel.
It's important that we have cutting-edge fabs in the U.S.
and that we surround them with cutting-edge packaging technologies.
These are a strategic asset.
If I said that you have one policy change that you could usher through with no resistance, what would it be?
I would allow TSMC and Samsung to a 20-year period free from all local ordinances, all of them, to build fabs in their desired location in the U.S.
If that's Arizona, that's great.
If that's Texas, that's great.
20 years, no local rules.
Allow them to build fabs.
And I would say that use the same rules you use in Taiwan.
Don't build garbage.
Use exactly the same construction techniques and rules, et cetera, that you've built fabs successfully elsewhere in the world.
But local ordinances are disastrous and not intended to cover pyramids, right?
Fabs are modern pyramids, Harry.
They are the greatest things humans make in the manufacturing world by far, by far.
Nothing's closed.
Can I ask, Andrew, I sit here in London.
Should I be worried?
And you have the best frontier labs in the US.
You have amazing open source and amazing manufacturing capabilities in China.
What does Europe really have?
We've kind of failed on the model front.
Mistral, it's the leader, but sadly nowhere near others.
Should I be worried?
You should be worried at the pattern.
The pattern of sort of lack of success across a range.
of technologies.
It's not just that the leading AI companies are ...
most of them are in the US, but the leading chip companies, but the leading software companies.
Of course, there's some examples, SAP and some others, but there has emerged in Europe a sort of be afraid of it, then regulate it, tax it.
sort of mentality that works against entrepreneurship.
And I think Europe, this isn't true across the board.
And clearly there are pockets outside of Cambridge and in London and Stockholm, where the guys at Lovable are doing really interesting stuff.
And there are all sorts of counter examples.
But on the whole, given its population, the opportunity to do vastly better on the innovation front across industries is sitting there, unexercised.
That, I think, is a worry.
How much of your business do you think will be in Europe in five years' time?
I think along with this, they have been slow to adopt new technologies.
Not only have they been sort of slower to invent new technologies, but they've been slower to adopt new technologies.
I think the fastest adoption will not be in Europe, but in the two and a half to three to five year range, it will be a meaningful portion.
Is that in line with your experience?
I mean, my experience is from a long way away and from visiting regularly and talking to customers.
Is that your experience?
Application layer, no, I think we have some of the world's best companies, whether you're Eleven Labs or your Synthesia or your DeepMind, I think 100% on the infrastructure, on the chip side, on the model side, unwaveringly so.
So yes, in large part, with a little bit of nuance, which you, to be fair, added there with Lovable and Hotspots.
So I think we're totally aligned there.
respect.
I think you've done real work to argue against that and hats off to you and the others in the venture community.
I think capital plays an important role.
I think a culture in which it's okay to fail plays a role that is not traditionally in Europe.
Careers are at one company and are long and that breeds a conservatism.
I think one of the most powerful parts about Silicon Valley is the absence of a stigma.
If you try to do something extraordinary, crash and burn, VCs don't hold it against you.
They ask you what you learned, and often it's great experience and a credit to you.
I think that is something that I don't understand its history, but it's clearly present.
Can I ask you, before we do a quick fight, we mentioned the IPO at the start.
You timed the IPO with the greatest of respects, in my mind, to absolute perfection.
before a SpaceX IPO, before Anthropic or OpenAI.
Was that strategic and deliberate with the greatest of respects, or was it relative luck?
No, let me share.
It was 100% deliberate.
We tried to go public a year and a half earlier, and we couldn't get it done because we bumped into CFIUS.
We're 10 years old.
We tried to get public for years.
It was 100% luck and grit, sort of a relentlessness and an unwillingness to fail.
But did you have in your mind the other IPOs and when liquidity would be best, excitement would be highest?
Did we know when we set the date that chips would be on a run and that it was impossible for XAI and OpenAI and et cetera to get public before?
We didn't know any of that when we set the date.
But what we did know was that we had a chance to be the first and only AI peer play in the entire market.
There's only one, and that's us.
We had a chance to bring an extraordinary growth story to public market investors who had been shut out.
And that we tried again and again.
And that's how you get lucky, Harry, is smart, hardworking people, relentless work.
They get lucky and occasionally they find the perfect time.
Should you be investing in companies building on top of you?
You said about trying and trying again.
Jensen said before that he wishes there were companies he had invested in and about investing in the ecosystem around NVIDIA.
Do you think Cerebra should be investing more aggressively in the application layer built on top of you?
I think that's an opportunity that is newly available to us.
Probably not with venture dollars or traditional venture dollars, right?
I think you have to think very carefully about your investors.
When you're using venture dollars, the question is, should we be investing in them or should our venture partners be investing in them?
With public dollars, the mandate is different and your investors have different access.
And so the opportunity for us to do really interesting things with our customers and our partners grows.
That includes acquiring companies.
That includes investing in companies.
That includes different structures of partnerships.
And we have to explore them all.
You mentioned the multiple times trying to go public and the persistence.
What do you know now about going public that you wish you'd known when you were trying multiple times?
Is it what you thought it would be?
No, look, I think what happened was we bumped into a CFIUS challenge that was sort of obstructionist.
There were unnamed concerns that never got articulated.
that sort of lived in the ether about some of our large customers.
And then we got a new government.
Those concerns disappeared.
And we were able to move through it really quickly and thoughtfully with a really fair resolution.
And by the way, a resolution that we had proposed a year earlier.
Is the Trump administration unwaveringly better for business?
Again, I sit here on the UK.
Unwaveringly better for business.
There are things I agree with.
There are things I disagree with in this administration, but unwaveringly better for business.
You got to be at bat taking swings and you've got to be building every day.
When we got public, we were a much stronger company.
We had larger sales.
We were further down our roadmap.
We had better customers.
You sort of have to separate.
We didn't get public because of CFS, but we kept building the business.
The business got better and better and better.
And that gave us the opportunity to try again.
That's, I think, the message to your builders, to your audience who builds companies is a lot of stuff will happen that is not in your control, right?
There will be bad times.
There'll be, you know, I was raising money in the summer of 2008.
Yeah, that's right.
That look on your face is exactly right.
Summer 2008, Bear Stearns falls apart in March.
Lehman Brothers is exploding in September.
VCs didn't want to put money to work.
And you know what the only thing we could do?
We could keep trying and keep building.
I was 11.
I was playing Pokemon, dude.
When you were out of nappies, we were out raising money.
And what you can do is run with the things you can control.
You are always stronger if you keep building.
Always.
And if you keep adding customers and you keep moving your technology forward, adding space between you and your competitors, that's what you can control.
Good times, bad times, that's what you're in charge of.
I have to move into a quick fog.
Number one, Dave.
What have you changed your mind on most in the last 12 months?
I think there are a lot of things that sort of...
As you prepare to go public, the number of people who call you and try and sell you stuff is insane.
Suddenly, developing a presentation, which should cost $20,000 to $200,000 project.
Suddenly, you get 20 emails a week about wealth management.
Suddenly, you get just the garbage.
It's like when you get married, Harry, it's the same.
You want a photographer to do a corporate event, $3,000.
You want a photographer to do the exact same thing, only you call it a wedding, three times as much.
Same for a caterer.
Same for everything.
Why?
Because he can't put a price on love?
That's the same reason.
No, because they can.
And that's something that I didn't expect.
And it's sort of uncomfortable.
The number of people trying to take a little nibble of your IPO and get paid on it.
That was a surprise to me.
I didn't really think carefully about that prior to getting out the door.
I mean, you touched on Europe from an American's perspective.
If I touch on America from a European's perspective, there's always a take.
It's always about the money in America, the transaction, the money, the money.
We have a problem with that in our society.
I think that's right.
It is both the source of some of the drive and the entrepreneurship.
and some of the source of the uncomfortableness.
How did money change you as an entrepreneur?
It changed me as an investor.
I go for way bigger upside.
I'm not so fearful of losing money.
I grew up on the Stanford campus, and the only currency was intellectual horsepower.
My dad's tennis match, he played doubles every Saturday and Sunday.
And they were like six or eight guys in rotation.
I look back and four ended up with Nobel Prizes and one had a Fields Medal.
Right?
William Shockley lived next door to us.
Dude invented the transistor.
And what we knew about him growing up was on Halloween, he gave full-size candy bars.
That was what we thought about as kids.
After I sold my last company, nothing changed.
Nothing's changing now.
I think what's made me proud, what made me proud in my last company is we made 100 millionaires.
What made me proud in this company so far is we've made 800 millionaires.
800.
If you don't like doing that, you have no business being CEO.
If you don't like delivering for your team, you're not a real leader.
That feels good every day here.
800 millionaires.
800 millionaires.
Yeah, that must feel pretty great.
Well done.
And these are people who bet, many of them bet long periods of their career with us, right?
I mean, maybe you get 35 years of the career as a top working engineer.
And many of these guys have been with me for three or four companies.
Some of them have been here eight, nine.
nine and a half years.
We've spoken before and off record about personal lives.
I'm intrigued.
When you are a public company CEO and you're going public, the world wants a piece of you.
You're public now, you're public.
Any advice on how to sustain an amazing marriage and an amazing relationship while also being a public company CEO and going through that process?
Pick a wife with patience.
Pick a partner, a husband or a wife, partner, who understands what it is to be an entrepreneur.
I don't think, and I look at my co-founders and our leaders every day when you're a leader of a startup, a pressure test on your soul, every single day.
If you're a real leader, when you are 30 people, a little company picnic, you look out what you see, your mortgage payments and braces that need to be done that you're responsible for.
And that doesn't change.
If you really believe that and you hold that in your heart every day, you carry real weight with you.
You have to share that with your partner so they understand.
It's really hard if they don't.
I think almost everybody, and maybe your partner has felt this, and every CEO I know has told the story of their partner telling them that they're more lonely when you're sitting next to them thinking about work.
Your mind is just ripping on work than they were when you weren't in the house.
I think that what we do is a family thing.
There's a price to be paid and how often you see your wife.
I mean, I'm on the road three weeks a month.
Put it this way.
Emirates airline sends me a Christmas basket.
This is an Arab airline sending a Jewish guy a Christmas basket.
You know how frequently you have to fly for that to happen?
It takes a toll.
And I think you have to think really hard about how to put some credits back because otherwise they're just a stream of debits against your relationship.
Final one for you, dude.
What's the kindest thing anyone's done for you?
You know, we see a lot of, whether it's your investors publishing on the IPO day and, oh, I met Andrew once at a coffee shop.
Oh, I opened the door for him once.
I was part of Cerebris.
What's the kindest thing?
I think, and this is for you, Harry, and the VCs, is to have empathy for how hard our job is.
I think one of the things that I was really lucky with was we had a board that understood they didn't need to put more pressure on us.
That if the pressure doesn't come from within, all right, they bet on the wrong people.
You know, hardware is extraordinarily difficult.
And we had and we attacked a problem that had never been solved.
And we had an 18-month period where we were spending $8 million a month and we couldn't build it.
Yeah.
$8 million a month we were burning.
18 months and we couldn't solve the technical problems.
You know what it's like to have a board meeting every six or eight weeks and come back and say, nah, I can't do it.
Still can't do it.
Did you doubt yourself at that point?
18 months?
Of course.
I think there's this myth that CEOs don't doubt themselves.
It's not driven by relentless fear of failure.
Of course.
Of course you do.
But I believed in the methodology we were using.
I believed that each time we failed, we learned a little bit.
And we didn't fail the same way again.
Where it started, we failed in the first two seconds.
And then a year later, we were failing at an hour.
Each time, we did a full failure analysis.
Each time, I mean, every single one we failed at for 18 months.
That's some of the proudest work of my career.
It was that problem.
Nobody else to this day has solved it.
Nobody else knows how.
I think you can imagine, getting back to your previous question, I wasn't a peach at home.
Right?
I wasn't chipper.
I wasn't light.
I wasn't happy.
I was failing every day at work, every single day for a long time.
And I think if you want to attack hard problems, you have to come to grips with that.
You have to learn to manage it.
You have to surround yourself by people who you believe in, who you want in the boat when the hardest problems are present.
And I had all of those things.
And my wife was an extraordinary partner.
Dude, listen, I so appreciate you.
I so appreciate you putting up with my incredibly wayward questions from partnership.
No, they're interesting.
I think, Harry, you're an extraordinarily good interviewer.
You can cut that part if you want.
No, I loved it.
That's fantastic.
Trust me, we're going to start.
The teaser is, Harry, you're an extraordinarily good interviewer.
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