20VC: Cerebras CEO on the Future of Data Centres, Token Costs and Memory | We are Not in an Infra Bubble & Dario Got a Bad Deal with Elon for Compute | Should US Companies Sell to China & Why Most Layoffs are AI Washed with Andrew Feldman

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 in video strategy to try and create competitors for the traditional hyperscalers. I think they have funded and backstopped and overallocated 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. Pretty in a compute. For hard problems, there is no upper bound how much faster you want to be. This is 20VC with me Harry Stebings and I'm so excited to welcome a dear friend Andrew Feldman, found and see you at Sir Ebrace. 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, Sir Ebrace went public. The largest semi-conductor IPO ever. The price went from $185 to $301.00. 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 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, you have the idea but often with AI tools, you hit a wall. Well, Base 44 is where that friction disappears, turning how you talk into how you build. Full stack, web and mobile apps, sites or autonomous super agents all built in minutes, not weekend spent on damn configuration. Base 44 ships it all out of the box, the back end, the database, the authentication, and the hosting. It handles the heavy lifting so you can just stay in the flow. It doesn't just replace the busy work, it multiplies you. 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To see they culminate last week with the IPO, it was really special. Congratulations for last week, dude. Thank you so much. Those are really kind words. It was a really exciting day for the company and the team and the people who believed in us and who backed us for a decade. It was great. Thank you for saying those nice things. Not at all. I was thinking in terms of this conversation, how I wanted to structure it. I always get back when I have amazing people like you on the show, which is Alan and Rose Valtz statement of not very intelligent people discuss other people, mediocre people discuss current events and then intelligent people discuss the future and ideas. I thought I would grapple with my own ideas and wrestle with your incredible brain to help me understand where we are and where we are going. I want to start with, on the one hand, we look at the landscape stand and say, "Oh my gosh, an AI infrastructure bubble." Then on the other hand, we look at, you know, Eurides and Hwang and 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, right? The infrastructure build out was way ahead of demand. 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. InVidia has a backlog. AMD has a backlog. Others have backlogs. They have backlogs because we can't get data centers built fast enough. 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. 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 meted 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. 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 we're like, "Well, we can't need that much. You can't need tons of gago. 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, how to 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 now on demand. They bought down rev gear. I'm sorry, I've learned from doing this show for a long time. I can ask you the question, they put down rev 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. It was a deal that was available. Going back to what we said about the delay in data centers and data centers being in constraint. I just hear everyone say, "Well, memory is the shortage too, Harry." And that's why we're seeing an increase in cost for 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 and demand that it is putting pressure on all parts of the supply chain. Memory after TSMC, which is right after FabSpace, memory is a 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 get 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 go back to my idea of what the future looks like. What's your wanting to 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 dollars and 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 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 to sort of talk about. 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 right 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 to 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 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 that has been a strategy there. I think they have funded and backstopped and overallocated to the Neoclubz. They have created a dependence which is probably not healthy. The truth is is that what 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. They're like you meet your computer. 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 naga hide seats. Our business just because it's wrapped up in technologies 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 cost 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 five X. 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 is 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 five nanometer and the three nanometer node is the most over subscribed. Our supply chain is advantaged on these dimensions and others are paying the price. The price of 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. In video, they'll 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 in video, 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's 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 costability? There are pros and cons of that strategy. The 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 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 cerebral risk 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 a video. 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 that you're actually overvading when you look at it in that case or are we running the others? I think CoreWeve has been an extraordinarily innovative company. I think they've solved a series of financial challenges with really innovative 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 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 for 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 Kimmy 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 I 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 it. You're lucky, 80% of your portfolio where you were dead wrong. You should do it if you're doing it right. Yeah, I agree with that. How important was that for you? 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. 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 egentic flows. It's true in every part of the AI landscape. Let me just ask you this question. How big is the market for a slow search? It really is zero. How big is the market for dial up for slow internet? How much would I have to pay you? Let's try to turn it around and say there's a negative market here. If I gave you a thousand dollars a month to have slow internet in your home, you wouldn't take it. A thousand dollars 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? When you power code acts and you're able to be so much faster. If you're a crook, you're not like, "Ah, bugger." They are. You have to be. Are you able to sell to them also? Again, please tell me to sort of. 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, hurry, give me a break. I've just signed a 20 billion dollar deal. You want more?" While we were on the road, some investors would ask, "Oh, you're heavily concentrated. You have a big portion of your business with opening." We say, "I talked to you a year ago when I had a billion dollar deal with G42." You said, "You're heavily concentrated. You have a billion dollar deal." I come back to you in a year with a 20 plus billion dollar deal. You tell me the same thing. But with a different customer as well. With a different customer. 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. What's more, a 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 and I go, "Oh, it's quite a lot." I think what has happened, Sam said this. He said, "The first time people use GPPT, I think it was for 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 it 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 had said, "We're engaged in a multi-gigawatt buildout." Think about what Crusoe is doing or think about some of the other cool companies, what SoftBand Power is doing, what some of these groups are doing. And you say, "That would be delusional five years ago." And right now it's like, "Oh, another one? That makes sense." I mean, we should try and get our UAE stargated five giga. Oh, yeah, no problem. That's interreasonable. That's what's happened. It's an extraordinary sort of change in thinking. If we are nonchalant to multi-gigawatt buildouts today, what are we in five years' time? It's difficult to imagine. And right away, 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 back case against that? What's the alternative argument it does not have to be yours, but how? I don't know. 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 the 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 the 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. I, I, I, it's not popular area. 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, right? 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 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 shop 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 are late. Sometimes they fall off a truck literally. They fall off a truck and the damages 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 for the local school. Build a school at a church or synagogue to the community right. 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. It feels like kind of the call towels and Columbia they were slightly and they built the church 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 have a resource that that isn't being used to 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, your near power resources. And my position is that we ought to be good neighbors and we ought to be transparent. We have 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 for this. 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 is a brand? And you see Matt and Leo a huge amount of people today is challenging to see 4 a.m. emails from Zuck and you know, jobs being lost. Yeah. I do worry about it. Those are people. 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 has been, have occurred over the years that were 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. And then now 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 onto 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 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 think if you look at, I'd never done this in a detail, but if you look at what we pay hardware engineers and you look at what the tools, which the EDA tools they use, I bet you're much closer to 15 or 20% than 2 or 3%. What's happened is historically software engineers used very low cost tools. And hardware engineers used extremely expensive EDA tools. That's interesting, isn't it? The cost of bugs in hardware is so high that we became accustomed to using many expensive tools. In software, we threw people with problems rather than tools. As AI becomes more productive, I certainly don't see a problem where software engineers using 50 or 100,000 a year each in tokens. We have 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 Nalt exist today that you think will be incredibly commonplace in 3 to 5 years? I've been a part of over the past 25 or 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 to Minimus. There was a role that was often VP at telco infrastructure. That job is gone. We don't have a phone system. In fact, we don't have phones on people's desk. They call me on my cell phone. That job disappeared completely gone. And companies that built the PBX's like role and all these other, that business is 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 cheap 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. AI's 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 also other parts of organizations that have fundamental changes because they can answer the questions that they used to answer. Do you agree that biggest inhibitors to enterprise adoption of AI is data structure and data clandiness preventing? 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, they're in jobs that everyone just blames them. No credit, no credit, failure, blame. That's their life and it's brutal. It's brutal. You're selling it so well for any of your foreign lawyers. What are you listening? Going to being a CISO. It's really hard. We had a year when nothing happened. Well done. That is their dream. I mean, every day their phone doesn't ring, they're like, "Ha, made it through another day." Like, 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 have a 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. What a 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 illegal. Once they agree, we need to do this. Here are the rules we will use. There's a huge amount of productivity to begin. 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 a huge advantage. Same with companies like Galaxos Smith-Kline. And other companies who haven't perhaps been as disciplined as thoughtful about the organization of their data are to disadvantage. On the security and the provisioning side, do you think we will see industries tip like legal has done? Wow, the biggest firms in the world are now going, oh shit, we need AI. Our clients say we need AI, Harvey or LaGoura. I'm not going to get into which one, but there's two options, boom. Do you think all industries will follow the tipping? What do you think most will follow the slow agreement that it's in you normal? What's happening is the leaders are tipping, right? And I think even Janssen told the 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 boogie man, Obris. And the problem with unseen boogie man is sometimes they're actually real, right? Yeah, 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 a capable of using you. You're good. I know you're in your 60s, but you look good. Now, and it's the facial moisturizing routine. We mentioned security, permissioning, legal, everything between. They get even more fricking nervous when it's open source. They shit the bet. How do you think about that? I see more and more companies, especially in the valley, really push the boundaries on with frontier and then try and get as close as possible with open source, given the cost of farmstures. Is that the future? And what does that mean? OK, 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 sort of 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 may doubly worse by some of the best open source models were made by Chinese companies. And they are exceptionally good models. Kimi K2, deep seek, Quentin, GLM, these are extraordinarily good models. They're not quite as good as the close 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 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 myself interest, right? If you remove me and you remove Jensen, you remove Lisa and 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 there be a 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, well, 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 are an industrial adversary. I don't love that. I, for years, did business with extraordinary entrepreneurs there at Baidu and at Tencent and D.D. and all these companies. They're everybody as good as anybody in Silicon Valley. I would love it 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 solved fewer chips and we didn't sell them in 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 case booths. He's not going to forget today's and then we won't control it. Why do you not think that that's a credible argument? I think the chip industry requires you to go through TSMC and TSMC requires you to go through ASMR 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 rough. I'd like to keep my industrial adversaries more than down rough. With that, how important is it that we on short TSMC like capabilities and 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. In the US, we are a patchwork of 1950s technology if we're lucky. 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 US. 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. It is extraordinarily important that we get it back. I've been saying that for decade and a half, that not the chips act, not subsidizing until it's important that we have cutting edge fabs in the US 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 TSNC and Samsung to a 20-year period free from all local ordinances, all of them, to build fabs in their desired location in the US. 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, etc. That you build fabs successfully elsewhere in the world. But local ordinances are disastrous and not intended to cover pyramids. Right? Fabs are modern pyramids. They are the greatest things humans make in the manufacturing world by far. By far, nothing's close. 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 to Mr. Al. It's the leader, but it's 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. Right? 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 London and Stockholm, where the guys at Loveable are doing really interesting stuff. And they're 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 slow 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, I know. I think we have some of the world's best companies, whether you're 11 labs or you're synth easier or you're deep-mind. I think 100% on the infrastructure, on the chip side, on the model side, unwavering me so. So yes, in large part, with a little bit of nuance, which you, to be fair, they're with Loveable and so hot hotspots. So I think we're totally aligned there and in 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 it 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've not understand it, it's 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 space ace IPO, before Anthropic or OpenAI, was that strategic and deliberate with the greatest of respects? 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 Syfias. 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 a setter to get public before it? 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. Here it is. Smart, hard working 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 at Janssen said before that he wishes there were companies he had invested in and about investing in the ecosystem around Nvidia. Do you think the cerebrus should be investing more aggressively in the application by a 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. 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? The 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 syphias 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. 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 it Trump administration unwaveringly bad off of business? Again, I say here in the UK. Unwaveringly bad off of business. They're things I agree with. They're things I disagree with in this administration, but unwaveringly bad off of 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 had we're further down our road map. 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. There will be bad times. There will be, I was raising money in the summer 2008. Yeah, that's right. That look on your face is exactly right. Summer 2008, Bear Stearns falls apart in March. Laman 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 a lavern. I was playing Pokemon, dude. Yeah. When you were out in 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. That's what you're in charge of. I have to move into a great fight. Number one, dude. What if you change 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 or $200,000 project. Suddenly you get 20 emails a week about wealth management. Suddenly you get. I 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 and then you'll call it a wedding? Three times as much. Same for a caterer. Same for everything. Why? Because you can't put a price on love. Let me carry it in maybe a while. It's not the same reason. No, because they can. And that's something that I didn't expect and is 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, as you touched on Europe from an American's perspective, if I touched on a 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, the. Oh, it's like. 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 looked back and four ended up with no well prizes and one had a field's medal. [laughs] Right? You know, 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-sized candy bars. That was what we thought about his 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 a hundred millionaires. What made me proud in this company so far is we 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-period to their career with us. Right? I mean, maybe you get 35 years as a 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 offered a quote 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 a public and you're a 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 or 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. 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. Then 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. 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 scream of debits against your relationship. I know one thing you did. What's the kindest thing anyone's done for you? We see a lot of, whether it's your investors publishing on your IPO day and oh, I met Andrew once at a coffee shop. We, you know, oh, I opened the door famed once. That was part of cerebrus. 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 for 18 months and we couldn't solve the technical problems. You know, it's like to have a board meeting every six or eight weeks and come back and say, "No, I can't do it. Still can't do it." Did you tell 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 it at an hour. Each time we did a full failure analysis, each time in 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 assaulted. 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 lights. 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 way with questions from Paul and Shukri. No, you're interesting. I think Harry, you're an extraordinarily good interviewer. You can cut that part if you want. No, I love to. That's fantastic. I had just been, we're going to start. The teaser is Harry. You're going to show it to me. Thank you. Very good. Do I really get it here? But before we leave you today, you have the idea, but often with AI tools, you hit a wall. Full stack, web, and mobile apps, sites, or autonomous super agents all built in minutes, not weekend spent on damn configuration. Base 44 ships it all out of the box. The back end, the database, the authentication, and the hosting. It handles the heavy lifting. So you can just stay in the flow. It doesn't just replace the busy work. It multiplies you. 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