Andrew Feldman | How Cerebras Built the "Impossible" AI Chip Now Challenging NVIDIA

Today we have the pleasure of speaking with Andrew Feldman, founder and CEO of Cerebras Systems, the company behind the largest chip ever built and the fastest AI inference engine in history. Led by a veteran team of infrastructure builders, Cerebras is redefining what's possible in high-performance compute, quietly becoming one of the most technically ambitious and resilient companies in the world. Andrew, thank you so much for spending time, man. I know you're extremely busy. You're probably one of the hardest working AI founders I know, or any founder I know. Like, I don't know how you stay married or stay sane.

I think I got lucky with a wife.

You must have. Welcome to the club.

Thank you.

There are so many wack things about Cerebras that I love because as you know, when you find a company that has a story that's just like totally surprising, then you have to, you want to tell that story. The stories of like, like, you know, all the usual suspect OpenAIs and all these other guys, drama or no drama, they're fairly linear. Like Anthropic's linear, OpenAI's sort of linear, Cerebro's not linear. And so I thought what we would do today is talk about your journey because it's such an unlikely story. I mean, you know, starting with the fact that you started this company 10 years ago before anybody knew what the fuck AI was gonna even be. I mean, we already knew what AI was, but they all thought about it as Big Blue and—

Like chess, finding a cat.

Exactly. So let's get into it, man. I wanna, what I would love to do is talk to you, uh, start with like, you know, who you are. Of course, I've known you for 20 years. I hired you forever ago for you know who, and I've always thought the world of you. But what I'd love for you to do is share with the audience just a little bit about who you, who you, who are you, what your little bit about like your upbringing and any meaningful moments or, or, or, uh, vignettes or mentors or, life experiences that led you to where you are today, which is doing probably one of the hardest things in the entire AI ecosystem that is imaginable, which is a gigantic GPU kicking NVIDIA's ass.

It's not easy.

So yeah, man, tell us about you.

So I, I was born and raised on the Stanford campus, and so my parents were professors. And I, I, I think one of the things that, that really teaches you is that the world isn't gonna get going to get a whole lot smarter than your first grade class, right? First grade, we had only faculty children were in that class. And we grew up in an environment where ideas were the currency, not money. And where, you know, my dad had a tennis match every weekend. There were 6 of them who played tennis in rotation and 4 ended up with Nobel Prizes and one with a Fields Medal.

Wow.

You, you learn what brilliance is and you, you, you learn that it's not arrogance. If you brought them a question in their field after tennis, they, they'd explain to you how, how something worked and they were willing to teach. And when you stopped by when you were 8 doing a, a readathon, when your school was raising money for books, they would sign up for you. And years later, you, you know, you, you, you read their definitive work in their field.

So you, this early experience bred a deep curiosity, a deep intellectual curiosity. Is that what you're saying?

Yeah, it, it, it bred, it bred real curiosity and, and curiosity without sort of absurd arrogance, without sort of it being attached to wealth. Two doors down, our neighbor had two Nobel Prizes. Two, right? And what we knew growing up was his wife gave, gave full-size Three Musketeers bars at Halloween. That, that's what we knew.

You know, we have another founder, this woman who's the founder of Vanta, did a podcast with her. Christina, and she, you know, her parents were college professors. And I thought what was interesting about her journey was going from this deeply academic environment to this just this raw, you know, entrepreneurial company building, capitalistic sort of environment. Tell us about that transition. So you go from this academic heavy, brilliant Nobel Prize. How'd you start thinking about, hey, I wanna go out and do something in the business world? 'Cause you've done like 4 or 5 startups now, and you've been a, a company builder for decades.

I was always somebody who, who was an entrepreneur. And in high school I had a t-shirt company and Nordstrom's was carrying our label. I've always enjoyed finding things that people want or need and trying to build them and sell them. That was a passion from, from the get-go. You know, my brothers are doctors and I never had any interest, never in, in, in that. I, I was always interested in working with, with, with people who could build things and finding customers who could use them and getting sort of a high from watching your customers really enjoy something you built. And if, if, if you don't like that, that then this is the wrong thing for you. You need to really love watching your customers enjoy a product or a service that, that, that you invented. And that, that I knew early, early on. I took great pride when I'd walk around campus and I'd see people with t-shirts that I'd designed or that, that we'd made. One of the companies I was a part of was one of the first to build hardware-based switches and routers. We took great pride in being part of a movement that made IP networking free. We didn't know anything about WhatsApp. We, that wasn't our thing. We didn't know about Viber or any of these different techniques. But what we knew was that if you could make, if you can make networking approximately free, other people could build amazing things on your stuff. And the world would move forward. And so that's always been a passion. And I, I think that's what led me to infrastructure. To do infrastructure, Andy, you have to love building roads and you have to really take great pride in what other people drive to cool locations on the road you built.

Well, you know, it's funny 'cause you and I grew up at the same time, as you know, professionally speaking. And I remember graduating from school in the early '90s and being like, what's this internet thing all about? Like we had CompuServe, we had AOL and Prodigy. And they were all closed. There was no Mosaic, there was no Netscape, there was no anything. There was no Yahoo. And I had to actually set up my first modem, and that took me like 3 days to figure out how to program a modem.

Yeah, yeah, yeah.

And then, so, they like, we remember we called it the information superhighway. We were building the information superhighway.

Yeah, now maybe it's building us, right?

I know, exactly.

It's incredible.

So, so you started in this transformative world where you're building the on-ramps to the internet.

Okay.

And like, that's where you and I met is when the equipment just wasn't there. We had the Mays, May West, May East, they had these concentrated, as you know, data center equivalents with lots of networking gear. Yep. And then it grew out of DARPA and became the backbone of the internet. And so you're building that key contributor to major companies that ended up going public and some of them just became, you know, uh, big acquisitions. But effectively they were really difficult products to build. And as you recall, ASICs, application-specific integrated circuits, were getting more and more dense and the kind of these were, these were like optical transport networks and what have you. And speed was always like the thing you were trying to push for, right? You just, it was the need for speed, density, I/O, speed. Do you think that that early experience 10 years ago, which is a freaking century ago in this world, led you to the aha moment that AI was going to be ultimately about speed? Like, tell the audience about your aha moment where you were like, hey, I'm going to do this wafer scale. Intel chip and all this crazy, you know, absurd Ferrari speed.

One of the things the internet taught you is that if you can make infrastructure fast, you can unlock new business models, right? When the internet was slow, Netflix was sending DVDs in the mail. And when the internet is fast, Netflix is a movie studio. Right, right.

Great example.

There was no reason for that to happen except that the internet got so fast that delivery became made it dead simple for them such that they, they could bypass all the delivery mechanisms, right? All the other studios who had been in the way. And we believe that. We, we believe that when you make communication blisteringly fast, all sorts of new business models emerge.

Absolutely. Well, wouldn't it then, then can you tell me when the fuck we're gonna get 5G actually working? Just kidding. We'll talk about 5G some other time.

Go to Beijing. I mean, it, it's, oh, it's shocking. It's shocking. Our, totally, our toku infrastructure is disappointing. Uh, our, our, our, our roads, bridges, trains, our, our physical infrastructure is really, uh, lagging.

It's embarrassing.

It's embarrassing. A few weeks ago I was in, uh, Riyadh, Abu Dhabi, and JFK, and JFK looked like third world airport compared to the others. And, and there's no reason for that. I mean, th—

th—

this is New York, right?

Well, We know the reasons, we just don't, it's uncomfortable to discuss them.

To discuss them. And there's no reason why our airports should be falling apart and our other nations who we think of as behind us in some sort of developmental hierarchy are building way better things than we are. And so that was disappointing. But I think to your point, the first thing is we know and we've seen it in compute, we've seen it in the internet. We knew going in That if you could make training faster, if you could make inference faster, the world would do all sorts of interesting things with it.

All right, but let's back up for a second. It's 2015, you know, and we're removed from the '20s, you know, the Lehman crazy, you know, financial collapse, right? Like we're removed from that, but it's not 2018. It's not exciting. It's not like a lot of capital's flowing. One of the things you'll find if you read it, if you see any of my other podcasts, which I don't, you know, recommend you do. Some of them are more interesting than others, but they're—

I'll only watch the boring ones, Andy. Just send me the list of the really boring ones.

I'll watch them. You got it.

Watch those.

Yeah, well, I'll just try to make this one less boring. But here's the funny thing, man. You know what they all have in common is that the people I like to interview like to grind. Oh, because I look at this world today and I'm like, okay, all these AI startups, they're so cool though. Oh my God, that's so great. You look at these blistering fast growth companies, you're like, that thing could vaporize tomorrow. It's like watching an F1 car driving down a country highway with, you know, no pavement, it's like gravel. And you're like, that's not gonna— that might not end well. It might be really exciting for a bit, but it might not end well. So I really appreciate people that grind and they really, uh, know what it takes to actually like dig out a success story. So I'm curious, in 2015, nobody knows what the hell AI is doing. Everybody's doing this cloud application service providers are moving to cloud. Amazon's launching AWS around that time, maybe a couple years later, but like, you know, the whole world that we know now did not exist. And so what were you and your founders thinking about when you decided to build Cerebras and go after a wafer-scale chip when the world had forgotten about semi, all the fabs moved from Arizona and Santa Clara and Milpitas to, you know, Taipei.

Yep.

So like, what, what was in your head? And you have obviously a few founders that had to believe the same thing you believed. Tell us about that.

And the, the state of AI was pathetic. I mean, guys like Kwok Lee, who was finishing his doctorate at Stanford, were identifying cats out of images, right? I mean, this was the most rudimentary stuff. We were identifying numbers, right? Handwritten numbers was a big thing.

So why bother?

We came to believe that the trajectory they're on, when you bet on the future, you, you're really betting on a trajectory, right? You're, you're, you're betting on an accretion of small gains that, that quickly add up to, to meaningful gains. And, and we saw this on the horizon. And what we saw was that this type of compute could produce profoundly different results that what it was trying to do was solve problems that CPUs and GPUs were really bad at, that our traditional compute infrastructure was terrible at. Traditionally, our compute infrastructure was bad at understanding images. It was terrible. We could store them, we could retrieve them, we could replicate them, but we couldn't understand them.

Yeah, we had no context.

That's right. We had no context that, that we weren't very good with language. Again, we could store, we could type, we could, but what we couldn't do is understand the meaning of what was being said. And there were a few sort of madmen out there. I mean, we met in 2015 or early 2016 with Sam Altman and Ilya Sutskever and Greg Brockman and Scott Gray. And you know, they're doing this, telling me how, you know, we're just a few years away from AGI and how they have a plan and that, you know, we're gonna build superintelligence. And you're thinking to yourself, holy shit. I can't get my head around that.

You might have thought they were like microdosing or something.

Well, you're right. You might have been. The problem with vision is that it's real visionaries are very close to madmen. And you look at the great science fiction, 20,000 Leagues Below the Sea, Around the World in 80 Days, these great sort of acts of science fiction, of creativity turned out to be underestimates. Of where the world ended up. And clearly Sam and Ilya and Greg, they were profoundly visionary. And what we took away from this was that this work was coming. I didn't know how long it would take. I didn't know how fast it would get here, but that it would require a very different type of compute and that CPUs weren't the answer. And that we thought the way they were building GPUs wasn't the answer. And then in particular, there were two things that would be very different about this type of compute. Number one, you'd have to move a lot of information. And traditionally, when you go to a processor, you don't move information. You bring it in, you work on it, it leaves. That's not what happens with AI. In AI, you, you bring in information, you work on it, you get to an, an intermediate result, you move it somewhere else, more work is done on it, you move it somewhere else. This movement of information is problematic to traditional architectures. And we thought to ourselves, We need a solution for that. The second thing we saw was that this work, particularly in inference, required a different pattern of going to and from memory. That to generate inference tokens, you had to bang on memory, and it was unlike any other problem we'd seen. And that the type of memory that, that was being used by GPUs, HBM, would be insufficient and would end up being a massive constraint.

Yeah.

What, what happened very interestingly is we were right on both fronts on those. I mean, we, we were wrong on a lot of other things, but on the big ones we were right. One, NVIDIA also came to realize that you were gonna have to move information a lot, so they bought Mellanox. They bought the, the, the thing to tie together little chips so that you can move information.

All right. But wasn't Mellanox all about I/O and I/O speed and interconnects?

An interconnect switch. That's exactly right. So they could tie together lots of little chips. All right, so they could move information.

To build clusters.

That's right. Now when you build clusters, you use a great deal of power and you move information very slowly because you have to go off the chip onto a motherboard, off a NIC, into a switch, maybe through another switch, back onto a motherboard. You use a ton of power because those are lasers, extremely power hungry, very slow. We thought to ourselves, if we built a bigger chip, we could move information less often. We could store more information on the chip. We could keep it in this super fast, extremely low power domain on a chip, and we would be faster and use less power. And that if we stuffed this giant chip to the gills with SRAM, all right, we would be able to overcome SRAM's traditional limitations. There are two types of memory. There's DRAM and HBM, which, which GPUs use as a type of DRAM. And it is extremely high capacity. It can hold a lot of stuff. But it's dead-ass slow. Moving information onto and off of it is unbelievably painful. SRAM is the exact opposite. Can't hold very much, but you can move information onto and off of it unbelievably quickly. And so what we thought was that if we built a giant chip and stuffed it to the gills with SRAM, we could use enough SRAM on that chip, 44 gigabytes of SRAM, such that we overcame SRAM's limitation of capacity and we're left with this blazing— Yeah. And as a result, we're 40, 50 times faster than NVIDIA in inference today. We're the fastest in the world on every inference workload.

Let's talk about this for a second. I actually started my career working in, believe it or not, semiconductors for guys like Wolf Corrigan and TJ, all these legendary—

Easy dudes to work for is what I hear.

Oh my God, they were brutal. But honestly, I've learned so much from them and I feel like we all stand on their shoulders and that they're forgotten heroes of tech. I mean, the people that built the semiconductor industry in the '60s and '70s, like Fairchild and all the Hogan's Heroes and all these people, maybe 1% of technology people even know who these people are. And so as you know, it is extraordinarily difficult to tape out any chip that has any kind of complexity to it. Remember when we had, you struggled with the taping out of the ASICs at Force 10, for example, because they were like the biggest ASICs that anybody had ever seen in the networking industry. And that was sort of the basis of the company. But, you know, if you think about wafer scale, that is like a gigantic atom splitting likely to fail thing. So that's 2015. You guys go, okay, we're going to do wafer scale, we're going to jam this. Oh, it's SRAM. I don't know, I'm sorry, DRAM, right?

SRAM. We're going to build a bigger chip. We're going to build a chip 56 times larger than anybody else in history.

How the hell did you get anybody to back this idea? Like, you know how high stakes this is. We're talking about tens upon tens of millions per attempt. I mean, this is why the semiconductor industry from a venture capital perspective died in like 1999. I mean, I don't think anybody funded anything past like Bellio or something. But selling it to the VC community, like who was your first VC? Was it Vitria?

Uh, we took it to Benchmark and we took it to Foundation Capital. We, we took it to Eclipse. We took it to 6 or 8 others and, and we, we did 8 meetings and got 8 term sheets.

Those 3 are still super active and super helpful, are they not?

They are super active and super helpful and I couldn't ask for better investors.

The best in the world. But it's not like those guys are huge funds or like they've got, they're not an Insight where they can go, ah, let's write another billion dollar check to Cerebras. Like, no. How did that work? And this risky as hell for their partnership.

It was. I, I think we also had, we sort of ran the table on the absolutely most knowledgeable people in chips. Andy Bechtolsheim backed us, Pradeep Sindhu backed us, Atiq Raza backed us. I mean, every single person was a legend.

Those three are as good as it gets.

Yeah, that's right. That, that's the best in the world. They knew the power of the idea. Now they, they, they weren't sure we could do it. It was hard and it involved, uh, building a partnership with TSMC, convincing TSMC to modify some of the steps in the lithographic process. It involved inventing packaging techniques. It involved— from the get-go, we knew we were going to be a system company. We weren't going to do a PCIe board. We were going to build a whole system. 7 years later, AMD says, you know, we should probably be a system company, and they buy ZTEK for $5 billion. We knew this going in. We knew this was not going to be a low-cost project. And our investors have been along with us for the ride. After A, Coatue joined us, VY, Altimeter. We have had extraordinary investors. They've been wise. When you do fundamental work, there are months and months where your shit does not work, where you cannot figure out how to solve the problem and you're spending millions of dollars a month and you go into your board meetings, it's not working yet. It's not working yet. And, you know, to their great credit, these were really seasoned investors and they asked about the methodology we're using and we were using good engineering methodology and we were solving a problem that nobody had ever solved. Gene Amdahl had failed at it. IBM had failed at it, right? TI had failed at it. The NSA had tried it and failed at it. Elon Musk recently gave up on it after trying to buy us in 2018. He started Dojo, just gave up on it.

Okay, so you're grinding, grinding, grinding, grinding. And by the way, I ran, you and I have a mutual friend who we won't name here. And I was at a dinner party with him because his mother-in-law is one of our dear friends that was our neighbor and blah, blah, blah. And he was telling me about you and I had lost track of you. And he was like, God, man, Feldman's trying to do this like really crazy AI thing. And I was like, oh, I kind of see this company in the press, but like, whatever, this is, you know, years, 5 years ago or something. And he kept telling me, he's like, I think Andrew's gonna, gonna go crazy. He's worried about your sanity because he was like, every time I talk to him, he thinks he's under existential threat and he's going to be out of business like tomorrow. So you're going grinding through the desert.

Okay.

You got no water. You got no compass. You know, you, you've, you got nothing but, but, but continuous failure. And yet you guys stuck together. Did you just know you could get there?

No, you, what you do have is colleagues who care about you and who you have profound trust in. And what, what, what you do have is a methodology. You have a belief that an engineering methodology where each time you fail, you do a failure analysis, you figure out what you got better at from the previous failure, why this one failed, and you move, you do it again.

And that's why your investors clued in on that as their measuring stick.

That, that's right. I, I think it's no different than, than pitchers, right? You know, it's, you gotta work on the process. Sometimes they're gonna hit a good curveball, but more likely they're not. And so you, you, you dial into the process, you dial into extraordinary colleagues, you, you work closely with them. You, these are people, some of them on the, on the hardware side who were with me since '96. I mean, we have people, uh, in fact, our whole hardware team was with me, uh, at Yago, uh, at, uh, all the way through Riverstone and, and have been with us for decades. and I, I have such profound faith in them. There was never a minute I, I doubted them. I doubted myself, um, that I was leading them on the right path, but I never doubted their ability to, to execute.

So, okay, let— when did you GA?

Right at the end of 20— 2019, beginning of 2020.

Wow. Okay. Okay. From that day to current day.

And Andy, look, we had failed.

We had failed for, for 5 years.

Years. In making it work. I mean, it wasn't like the market said no. The market's like, when can we have our part? And we're like, we can't get it to work. And one day, you know, after failure after failure, it worked. And the founders stood there in the lab and we were in a tiny little building in Los Altos, not meant for hardware. We drilled a hole in the wall to put in a chiller. We had the windows open. You know, there was nothing about this building that was right for hardware. And the system began running. The founders stood there and we couldn't speak for half an hour. I mean, that every other team that had ever tried this had failed and we were watching it succeed. And, and it was one of the greatest minutes of my life.

Describe that feeling for a second.

You know, obviously have, having kids and there, there are lots of things that, that you, you love in your life with every ounce of your soul. This was our idea working and the, the fruit of, of our thinking. And in 70 years of history, starting with Johnny von Neumann, all the way up to the greats in, in the industry, this had been tried again and again, again, and we were the only ones who ever made it work. Nobody could speak. We just stood there and would, I mean, and watching a computer run is about as interesting as watching paint dry on a wall. We're just watching it and the monitor's ripping. So we're watching to make sure that the calculate— it was one of the greatest minutes of my life.

I mean, I can't even imagine. Okay. So it's, I mean, just real quick, this is kind of funny. In 1981, my dad brought home an Apple II Plus. My brother and I were like, I was maybe 10, he was 12. We plugged into the TV and I never forget. I was like, this is the most crazy thing that I've ever contemplated. I was young, so I didn't contemplate at all.

Apple II Plus is a cool machine. That was my first machine.

Great. We were writing video games. That was terrible.

You probably remember playing Pong on Atari.

It was incredible.

If that's where you grew up with, I mean, there are a lot of games that are just fine now.

But so, so you're watching this thing spin and you're saying, oh my God, our, our vision was right, but it's still 2019. OpenAI is nascent and it's open source and there's no Anthropic. There's like—

the business was nowhere, but the technology was solved. We, we had come up with a recipe that allowed us to solve a problem that nobody else has solved.

And that maybe at the time very few people cared about.

I think very few people did care about, but I, I think when you do deep research, when you do deep innovation, you are by definition ahead of where most people care, right? That's what it means. You're ahead of your vendors, right? When you do pioneering work, it's not like you can go to a catalog and get a heat sink for, for a part that had never been invented before. And so what we had to do is we had to meet with vendors and say, look, this is what we've achieved. We ended up inspiring many of our vendors who were like, holy crap, we want to be a part of this. And that's something that I underestimated profoundly, was that you can inspire your vendors and your partners with the power of your vision as well.

Do they want to be part of the innovation?

They want to be a part of the innovation too. And one of the field engineers from one of our vendors said, you know, working with you is why I became an engineer. I mean, this is what I came an engineer to do. I didn't become an engineer to do a little bit a little bit better than the last time, it was projects like this. And so when you can inspire people, we had many vendors who did heroic things for us. And now, you know, 6 or 7 years later, we've got 3 factories working. We've got yields higher than NVIDIA on our wafer-scale part. We are ripping our quality, delivered quality is better than the DGX.

Fastest inference in history of humankind by far.

Fastest inference in the history of humankind by a lot.

Okay, so, but here's one for you. Okay, here, this is fun. So now you're starting to roll and you're starting to get some early adopter customers. These are the kind of wild scientific lab type peoples, right? And then you all of a sudden the B2B world starts going, eh, maybe one server versus, uh, 40 is probably a good idea.

Might be.

Maybe it's a good idea. Maybe I don't want to have racks that are 40 feet high full of a bunch of interconnects and cables and crap like that. That's kind of a 1999 thing. So you do something crazy and you go to the Middle East. I was watching at that point, 'cause Vishri and I do a lot of company building together. I mean, he does all the hard work. I just sort of try to be useful here and there. And you were one of the companies that would come up every once in a while and I'd be like, God, you know, Feldman, man, he's just, he's seems like he's got it. And then you do something crazy. You go to the Middle East and people at the time were always like, oh, Middle East, it's just about Saudi Arabia and it's maybe UAE or whatever. And all of a sudden today, I was told, I don't know if this is current data, that it's still by far the number 2 market in the world after the United States. Is that correct?

True.

Middle East.

Okay.

So what made you do something that's like, I heard you were on a plane like once a week back to the Middle East. I don't envy that at all. But what was driving that decision? Because that's another completely whacked, nonlinear, non-traditional thought process.

Well, first, Emirates flies an A300 out of San Francisco. It's 16 hours. It's a beautiful plane.

It is a nice plane.

Beautiful plane. If you can fly on that, I highly recommend that. Agree. I did it once a month for more than a year.

Whoa.

And look, I met the CEO of G42. His name is Peng.

Yeah, but why'd you go in there in the first place? I guess that's what I'm looking for. Like, what were you thinking?

We were looking around the world for people who were working on interesting AI problems. And we, we knew that there was a project in the UAE, uh, to train in Arabic.

Hmm.

Arabic, like many other languages, we, we call under-resourced, which means that if you scrape the internet, which is what the big US players did, you don't come up with a lot of Arabic. And that means that, that you don't have a lot of tokens. You don't have a lot of data on which to train your models. And we, we, we heard they had a program. We reached out. I met the, the, the CEO Pang, and I flew out to meet him. And I, I found a kindred spirit. I found somebody who had a, a monstrous vision. I had a, I was honored to meet his chairman, Sheikh Tahnoon. And I, I found in a nation, I, I found the largest and most compelling and sort of coherent AI vision that I'd ever seen. And we began working with them and showing them how our products could solve problems that were of interest to them. They had a problem that they'd been working on for quite some time. We solved it in a few days and we started a partnership that is now sort of fundamental and strategic, a cornerstone of our work. And through this partnership, we have delivered hundreds and hundreds of millions of dollars worth of equipment. We've trained the leading models in Arabic, we've trained genetic models for them, we have collaborated with them on a range of different projects. Uh, it has been one of the most productive and rewarding partnerships that, that one could have imagined. And, you know, I didn't know anything about the UAE.

I love Europe, obviously we're of European descent, many of us in the United States, and who doesn't love to go to Europe? But if you think about the Middle East leapfrogging Europe in a lot of areas of innovation using products like this. By far. You could see a sea change in industries because as you know, they need to diversify from energy-centric, resource-centric, like yesterday.

They are, they have a 5 and 10 and 20-year plan and their plan is to reduce their dependence on petroleum. The nations are clean and safe. I mean, in the UAE, unlike any other place in the world, sitting in the lobby of the hotel, I got up, left my computer and my bag, went to the restroom, came back and had no fear that my shit would be stolen. I tried that in New York. No fear. I think they are, they have their shit together.

Let's be honest. They have their shit together and it's like, they do pay attention to what's happening. You say whatever you want about, people can say whatever they want about politics or how they operate and this or that or the other thing, but I will say that I am blown away by what I'm seeing and hearing coming from that region and obviously cautiously optimistic that it changes the whole construct.

I'm very optimistic. I mean, I went to—

Very bullish.

I was in the UAE. I went to synagogue in the UAE. They, in the, the Abrahamic Center, they have a center that was built with the Abrahamic Accord. They built a church and a synagogue and a working mosque. In an area for peace, it took my breath away. To me, it gave me, uh, it was a profoundly moving experience. It gave me a sense that there's hope, that there are leaders in the Middle East who want peace like I do.

Well, I mean, if you look at the Abraham Accords and you think about what it could have been had it not been for— let's just be, I'm going to be really open— freaking Iran throwing a hand grenade literally into the entire set up.

Agreed.

Uh, and Israel's having to clean it up, but, you know, it's like that vision is something that's lost a lot of humans. Like, people don't realize how many people in the Middle East are peace-loving, want to innovate.

Right now, I was invited to give a talk in Riyadh, and I'm standing in front of an audience of, of 1,000 people, right? A Jewish guy. And I'm thinking to myself, 10 years ago, I wasn't allowed in the country. And right now everybody's too busy to hate. Everybody's so focused on AI. Everybody's so busy trying to build cool stuff that we, you could put aside all the other garbage and we could just be people.

Yeah. Be, that was one of the questions I, I was proud of that.

And, and I, that meant a lot to me.

How they received you so quickly, even with the name of Feldman, which isn't exactly a, a Gaelic.

We're not hiding it. No, no, no. That's who I am. Yeah, I think what we've seen is that the rewards to this type of thinking is enormous. I mean, compared—

Do you think Europe's going to wake up and realize they're about to get their ass smoked by the Middle East, which is going to be extremely embarrassing to them?

I think that in some senses they have been. I mean, there are people all over the world who would rather go to Dubai than French Riviera, who would rather go to Dubai than the Amalfi Coast, right? Who would rather go to—

Lindsay Lohan moved to Dubai.

Right. And Dubai's a great example. You know, was it in 2005, it had the same GDP as Gaza. Yeah. And now it's one of the most interesting places in the world.

I have to ask you a question, totally off topic. Have you seen the camel racing?

I have.

Was it awesome?

It was awesome. It was awesome with robots on them. Yeah. Camel racing with robots on them was awesome. Awesome. Everyone should see that. No, no, no. Camel racing with robot jockeys is phenomenal. But I think what's happening is that right now there are returns to vision. There are returns to putting big bets behind vision. There's opportunity for countries with vision and capabilities and resources to have a global impact. And I think that's what you're seeing coming out of Abu Dhabi, which, which is the space I know best, and with, through their national champion G42.

So it was pretty ballsy move, cuz you knew that after all these years of all your investors putting all this money into a science project that effectively now worked and was, you know, has a chance to change the world. I believe it.

It is. We're getting there.

That's why I'm so excited to talk about Cerebras. But if you think about, you know, the, the, the, all the optics and it was all over the press, okay, well we have to delay the IPO till we get clearance. That was ballsy too. You had to go, okay, this is where the innovation's going. We're gonna have to delay our, you know, you, you don't appear to have ever been motivated by making the billions of dollars and whatever. You seem to be motivated by driving the innovation that your company unlocks. Did you run any, any interference on going that route knowing that that would delay the opportunity to take this thing public?

You know, it's actually really interesting in, In 2024, in the first part, people were saying, well, who's the UAE and who's G42? And now everybody who needs big amounts of money for investment is visiting the UAE.

Oh yeah.

Everybody in the world knows who G42 is in our industry.

Right.

We were early and there were a lot of people who were saying, who are they? And there were a lot of people throwing stones in Congress. Who just didn't know better, who didn't know better.

It was just ignorance.

Just ignorance.

Yeah.

And instead we got to know the people. And when you get to know the people, when you get to know Pang and Kirill, who runs Core42, and the people they surround themselves with, like Marty Edelman and this collection of others, these are world-class people. They have a vision for how their small nation can play a bigger role in the world. And can play a leading role in AI and they're executing on it. And I, I think right now nobody asks me, who are they? Right? They're first, they're, they're our strategic partner, but nobody says, you know, who's G4? Everybody knows. And I, I think we're not just leaders or innovators on the technical front. We're looking for interesting business models. We're looking for partners who are doing interesting things. We are looking for other visionaries because at the end of the day, that's the shit that's fun. Right? Love it.

Oh, here's a question for you. So everybody in the world's like, ah, NVIDIA, $4 trillion market cap. Jensen's such a rockstar. And honestly, I got the chance to meet him when he was doing graphics chips, battling with shitty ATI, which AMD bought, as you remember, like back in the '90s. And he was such a sweetheart then. He was like such a gentleman and pretty humble. And So you can't really hate Jensen. I just, I can't.

I don't, I disagree with him on some of his China policy, but I think, you know, what you have to say is that over the last 15 years, there are no better CEOs than Lisa, Jensen, and Hock Tan, right?

I mean, there you go.

I mean, like, you know, so that is the pantheon in the last decade and a half of the best.

You're competing with arguably, with arguably one of the best 10 CEOs in the history of tech, maybe top 5.

Of late, and it may be the history of capitalism.

Graphics chips, crypto, and then crypto implodes. So what does he do? Pivot to AI, and next thing you know, the crypto comes back. Like, it's just unstoppable. So how do you get up every morning being like, I'm going and battling? This is literally a David and Goliath story, except Goliath is not 10 feet tall, he's, well, 100 feet tall.

Andy, you know, and it's not just me, but professional entrepreneurs are professional Davids. This is what we do.

Absolutely.

This is, this is who we are, right? We, we are not people who get up and root for the Yankees. I cannot stand the Yankees and can't stand them not because we don't like the team or the— we don't like the fact that you're trying to win by buying it, by, by being the biggest and the richest. I hate that.

Yeah.

We are people who, who root for the underdogs, right? We're people who are like, okay, see, that's all right to win the, the, the NBA championships, right? Nobody put them in the top, right?

Well, that's one of the reasons why you and I loved Force 10, because it was— we've thought we were gonna go kick Juniper and Cisco's ass. Like, that was so exciting.

And I, I think, you know, that is something you have to love.

Yeah.

And that has to be deep in your soul that, that you have to enjoy competing and you have to know that, that every $100 million you take from them or every $100 million you win is $100 million that they would have gotten had you not been alive.

Right.

It would've just defaulted to them. Right? They, they just have to show up by the, the— it used to be the fax and now it's, you know, the email, and they get the business.

But don't they need you for antitrust? Like, remember Intel needed AMD for all those decades and AMD just ended up smoking Intel, to your point, which we all love.

Intel sort of smoked itself. I mean, yeah, they did. Lisa, under some, some good decision-making between about 2014 and 2020, They made, by Jim Keller, they made better and better parts. It really helped that Intel stumbled and fumbled by far.

But doesn't Nvidia kind of need you?

I think if you were to ask them, they'd say, we certainly don't need Andrew Feldman. They might even say, who? They don't. I think what, what a healthy ecosystem needs is choice. And what a healthy ecosystem needs is Lots of different ways to skin a cat because there will be some, some cats that can only be skinned a few ways. If you want to do fast coding, there are no choices other than Cerebras. You could do slow coding with lots of choices, but if you want to code fast with an IDE, there's only one choice. If you want to do deep research fast, if you want blazing fast inference, there are no choices besides Cerebras. Now there are other parts of the market if you want to generate data, if you want to do Patchwork. There are lots of choices you can go to, but for this type of work, we are alone at the apex of performance.

So who's like— can Weighted First Skills— you guys have a bunch of patents, obviously.

A huge number of patents. It's got—

it's probably a 4-digit number, 5. Who do you worry about? Like, who's behind you? Not just Jensen, but who's the guy that thinks you're Goliath?

The thing about Jensen, And I think people need to sort of contemplate that is for 10 years he didn't run a good company. Look at the stock price between 2004 and 2014.

They were in the desert.

In the desert. It was flat. And that guy, the market kind of sucked in that timeframe too. It did. But he fought and fought and I mean, that's stuff to admire. Yeah.

Yeah.

When things are ripping, everybody says, oh, everybody jumps.

Wants a hero. Yeah.

Everybody jumps in. It's, these are fair weather fans. But for those of us who, who, who watch CEOs and try and learn from other CEOs, it was when it was shit that, that you learned the most from it. And he was relentless over that, those 10 years where things were brutal and he was trading at cash or cash plus a little bit. That's where those of us who are professional Davids, that's when those of us who are students of CEO-dom, we go, whoa, that guy, he has fortitude. Right.

You are worried there are people crazier than you and your co-founders trying to do something bigger than Wafer Scale? Like, of course people have got to be trying, but I don't see a lot of capital flowing to chip companies.

We hope. We love this industry, Andy. We hope people are doing cool shit that's not us. We hope people are inventing things that we hadn't thought of. We make no bones about having some sort of monopoly on big ideas, on interesting ideas. We're pretty good at bringing big ideas to practice. We're pretty good at building companies to support them and raising the type of money you need. But I hope there's a generation of young entrepreneurs who are building amazing things behind us and who'll give us a run for our money as part of the sort of community we love. We love the fact that it generates interesting ideas.

Does it piss you off as much as it pisses me off to see all these AI startup founders bail on their investors and their employees and take billion-dollar offers to Google while guys like you are grinding through the snowstorm for 10 years, 15 years. And you don't seem to be tired either, by the way. You seem like you're just like in the middle part of your journey getting going here. That's the energy I'm getting. How do you feel about like the backdrop of all this AI insanity while you guys are grinding through just trying to solve incredibly hard problems? It seems like there's this mercenary mindset around AI that really infuriates me.

There is, uh, I saw your, I saw your LinkedIn post about that. We have more than 80 people here who've worked for me across multiple companies. That is because they know I would not do that. When the S-1 is written, when the details are written, right, they will never find me in front of them doing trades to make, to aggrandize myself or to enrich myself. You will find neither me nor our founders ever doing that shit.

And why, why is that?

Those aren't my values.

It's just because of how you were raised.

The world is really simple, right? I, I, I think we, we, we make it complicated. Like, would Shirley Feldman, my mother, be proud if I described that, yeah, what I did is I hired all these guys and left them behind to take a big payday somewhere else. My mother would look at me and say, Andrew, I'm disappointed in you. And I, I think it is, you could just use that, you know, would your mom be proud?

If I did that, my dad would've literally beaten me in his 80s with a 2x4. And I don't know what it'd been like. He's doing me a favor.

I also wanna say, I don't know the situations and there's lots of things happening, but for me, the reason the team stay with me is because there's sort of a deal. And the deal is, is that I find interesting work for them. I pay them fairly. I do everything I can to look after them and their families. All right. And in return, they give me They give us balls-out effort, world-class effort.

And you think, like, Cerberus doesn't have a lot of drama, at least I don't see any. And do you think that's because everybody in the building is just fueled by this passion about problem solving and engineering challenges? Is that what it really comes down to?

I, I think we have our share of disagreements, but I think the disagreements are about the best way to solve the and I don't—

It's unemotional.

That's why I don't for a minute sort of brook discussions about self-aggrandizement or politics or doesn't matter how good you are. You can't work for me if you're interested in you. We are in one boat. We're gonna try and do this together. And I have no patience whatsoever for some of the stuff that infects larger companies where there's empire building and there's, you know, I'm not working on it, but I don't want you to work on it in case it works out well. We have not one minute of time for that sort of garbage. Good. But that doesn't mean that passionate people don't have disagreement on the best way to solve a problem. And I, we love that passion. We feed on that passion. But when they're done, you can go out and have a snack, have a slice of pie together because it was not personal. It's, we, I've made a slightly different set of trade-offs in my mind about how this should be built and they made a different set and those conflict. But when you're fighting over the product and how to make the customer happy and how to invent things that haven't been invented before, those aren't damaging discussions. Those are productive discussions even when they're passionate.

Okay. So over the long haul in AI, you and I are old enough. I'm 54 now and I look back at all these companies that where people grinded and they built something that's lasting and durable. And that's what I really, really, really get inspired by durable companies. When you think about the AI landscape, I know for 24-year-old founders that have like half a billion dollar companies in 2 years, unbelievable. But you kind of worry, like I said, these are F1 cars driving on an old dirt road in Southern Baja, Mexico, right? Like you just don't know what the fuck is going to happen with these things. What advice would you pass off to them in order to keep the thing on the rails, and be a long-term company. And you guys are going to be a billion-dollar company before we know it. And you'll be public one of these days. And you're going to be this iconic thing. I believe that in my soul. Because you split the atom. And that's something that's hard to replicate. And I believe that your core mission and the things you guys are doing are all correct. But what would you pass on to younger entrepreneurs who figure out at some point, maybe the hard way, if they don't take the billion-dollar acquihire offer from fucking Google, What would you tell them so that they can build durable companies too? What are like the 3 things that they need to do? I know it's 3,000.

It's not 3,000. You have to love the work.

Could be 30,000.

You have to love the work. Yeah. And I think the people who I've watched over 20 years jump to try to make money, jump from company to company, they've not been the happiest. And in fact, they haven't been the richest either. If you love the work and you find really interesting colleagues, people you can trust, whether they're your co-founders or people who work with you for years at a time and who inspire you. I've got engineers who are so good, they inspire me and who are so fast and the caliber of what they deliver is so high that I get fired up, all right, after a review with them. Good people, interesting work, and if you can really aim it at something that, that you believe benefits society, a group of customers deeply, I, I think you will have a very rewarding career and the money will come.

When you look at hiring, you know, you've gone through different types of hiring prototype. What do you attribute to your relatively low turnover? And like, what would you tell people they should be thinking about? Or how do they operate? Should they interview people 10 times? What, what are the tricks to the trade? On keeping a stable organization?

I have a very cynical view of interviewing.

It is hard.

And it is really hard. And what you, you're gonna, you're gonna learn in an hour whether this person, when they're tired, can work really hard and can, has grit. How are you gonna learn that in an hour? What you're gonna learn is whether they're smart. And smart is a necessary but not sufficient condition, right? And what you can't learn is whether they can work with others, whether they have grit, whether they're the type of person who, you know, at the end of a company picnic stays 5 extra minutes to help clean up. And that, that person is the same person who takes 10 extra minutes to review somebody else's code, even when they, they didn't need to and, and makes a, a positive suggestion, right? These are things that are really hard. And that's why at first most of us build a nucleus around people we've worked for before, because where these things are hard to to ascertain in an hour or two, they're very easy in 60 days. In 60 days, you know a great deal about the engineer you're working with, right? Read 3 emails. Were they tight and thoughtful and organized and clear and concise? That's the way they're going to write code. Did they solve problems neatly and generally, or do they solve them for a very narrow case that was the current bug that has been opened?

Well, I saw you, I saw you hire a couple of extremely senior people as you know, pretty recently.

We have.

And I didn't see you do 1-hour interviews. I thought you met each one of them about 4 or 5 times, maybe 6.

I think you, you can't do that when you're hiring 200 a quarter. Right. I mean, there's just not enough hours. But, you know, as you hire more senior people or people who are more important to your company, uh, you, you have to find ways to understand who they are as people. You have to understand their values. There, there are all sorts of techniques, you know, over-the-shoulder cold coding or coding together. Or problem solving with them. We have some examples where we bring real problems that we're having to, to leaders and, and sit with them and say, well, how, how she wouldn't go about thinking, how would you go about thinking about this problem?

But in the end, when you're about to make an offer, it sounds to me like you really want people leaning into the actual work. You show some real, like, primal level passion.

Don't come to us for money.

Yeah, exactly.

That, that is the worst. That is the worst. Reason to come. I think you come for the work, you come for the colleagues, you come for the fact that you have a chance to work on extraordinary things.

You might actually change the world. I mean, I know people say that, but there aren't that many companies where you can actually change the world. I mean, you know, Meta would say they change the world. I'd say that they fuck it up. But at the same time, like changing the world in a constructive way, those companies are really hard to find.

They're hard to find. And I think in the Valley, it is easier to find money than extraordinarily interesting projects with good colleagues.

Right.

And so the rare thing you should be looking for are people who want interesting problems, challenging problems, problems they can sink their teeth into, problems they can make a difference on. And those are the people we look for. And my job is to to build a company that returns and rewards them for that effort financially.

Andrew, I can't thank you enough for the time you spent this morning. I truly am inspired. I really mean this, man. I've known you for a long time. I just keep watching what you guys are doing. Me, like, what? It's incredible. I'm proud of you. I can't say proud. Proud is the wrong word because I didn't have anything to do with your success. But I am very grateful to the work you guys are doing. Every single person And anybody at Cerberus who, you know, sees this podcast, just want to express my gratitude. I think what you guys are doing is important. I think how you're doing it is incredibly inspirational. And I hope people learn from this podcast that, you know what, life is a grind, but as long as it's worth, you know, worthwhile, it doesn't feel like a grind. Like, you don't seem like a guy who's grinding. I know you're grinding, but you seem like a guy who's just like, I'm going to get this done.

You know, there's I forget who said it and it certainly wasn't me, but for some of us, happiness is sort of earned satisfaction, right? That it's when you've accomplished something to be proud of. That's sort of what happiness is, is that when you've done really hard work and you get to a point, you can look back and say, I'm a little proud I did that.

I mean, I totally agree with you. You know, you even talk to young people and they would care, well, do you have any life advice for them? I was like, get shit done. And they go, what do you mean? I'm like, your self-esteem will very likely be tied to achievement, no matter what you think. Maybe somebody gives you money, maybe your company goes public, maybe you win a lottery ticket. That's going to make you happy. A new Mercedes is going to make you happy. A new house, a plane. It's not going to— maybe for a second, but the achievement orientation is what to me fuels happiness that's not fleeting.

That's right.

It's actually like sticky. It sticks, stays with you.

There's something durable about, about having that in your pocket that you achieved something over a long period of time that was worth being proud of.

Well, you certainly are on your way to doing that, sir, and I applaud you and I salute you and I genuinely thank you for the wisdom and the story that you shared this morning. Is there anything else you want to pass on to other entrepreneurs?

No, we appreciate it. We use your firm, as you know, to recruit for some of our leadership and we appreciate the good work you did for us. And thank you for having me on your podcast.

I'd sweep the floors for you, brother. Call me anytime.

All right. Floors are dirty, man. Beep me well.

Be right there.