Andrew Feldman on Building a Chip 58x Larger Than Nvidia's

0:00The demand for AI has outpaced everybody's expectations, everybody's forecasts. And so everybody's chasing. They're chasing chips, they're chasing memory, they're chasing data centers. OpenAI, we announced in January a huge partnership, one of the biggest deals done in Silicon Valley history. We'll be doing more than$20 billion of hardware for them over the next several years. I'm concerned that there are ways frequently for NVIDIA to exercise market strength. There are ways for Enzidia to use their balance sheet to limit competition. We have a chance for our children or the next generation, not only to not die from cancer, but to not know anybody who died from cancer.

0:49Andrew Feldman, welcome to Sorcery. Well, thank you so much for having me. We are out here in Paris at Ray's. pretty okay huh it's pretty okay i also heard you're one of the most popular people here that would be first in my life so it's nice to nice of you to say a big theme though is and we were we were talking about this just off camera is hardware is cool semiconductors are cool everything is in fashion now we are in fashion we're in demand we're hard to get it's a big change. I think what's happened is the demand for AI has sort of outpaced everybody's expectation, everybody's forecast. And so everybody's chasing.

1:35They're chasing chips, they're chasing memory, they're chasing data centers. There's an opportunity to invent new things, different architectures. It's really a time of sort of a Cambrian explosion of ideas. and that's really fun. So you were at Ray's last year. I remember this because I think you had the biggest booth here. There was a fence around it. Yeah. And a lot of people. What is the biggest difference between last year and this year? Oh, I think last year was their first year, right? And I think there are more people here. There are more participants. So there are more attendees. There are more companies participating.

2:16I think people are participating in a bigger way. I think the dinner last night at the... Secret location. Secret location called Versailles was sort of awesome. You know, we spent a lot of time in the digital world. And the people, we talk about AI. To go look at something that illiterate masons made 400 years ago, right? And to sit in it and to enjoy the grandeur is extraordinary, right? This wasn't AI. this wasn't eda design or cat or these were guys with pen and paper communicating with you know masons and and other tradesmen who couldn't read and they built something unbelievably beautiful and that was really fun and so you're going to be on stage this year what are you mainly i'm on stage with uh satchin from openai um you know we we announced in january a huge partnership one of the biggest deals done in Silicon Valley history.

3:16We'll be doing more than$20 billion of hardware for them over the next several years. We'll talk a little bit about deploying hardware and fast AI and how important fast inference is in the emerging inference AI landscape. Inference is a hot topic. Everyone loves inference. Yeah, we make AI with training, right? And we use AI with inference. and so as the the the models and as the AI we made becomes useful everybody wants to use it and and inference is the mechanism through which we use it and so now we have smart smart AI people want to use it and when they want to use it they want to use it and they want to be fast and that's sort of where we come in and where the fast is not by a little bit but by 20x And so everybody's using their AI.

4:09They're trying new things. They're deploying, you know, GPT or Cloud Code or one of these supermodels. And it's sort of an explosion of building, of trying new things, of a new way to work. It's pretty fun. So we're nearly two months after your IPO. and there was one post that I thought was really cool. You posted that you had a very large chip on your shoulder. It was quite literal and physical. I hope that now that we're running a public company that I wouldn't lose sort of the self-deprecating humor whatever that I enjoy, the sort of tone in my social posts. And so we put a giant chip. We put this sort of on my shoulder like this, and we built a harness for it.

5:10Yeah, that was a fun one. You know, I think that people assume that as a CEO or of any size or an entrepreneur, that it's sort of always peaches and cream. And it's just not the case. There's an enormous amount of hard work. There's sacrifice that you make and that your family makes. They see you less. It's not for a little bit. It's not like a weekend or two weeks in a row you work hard. It's for years. And so sharing that a little bit is something I thought would be well received. So what's been the biggest difference for you post-IPO? the number of people who want something really yeah has exploded um of one form or another and uh we get a little better at at triaging those um between my my executive assistant and chief of staff and just if you get 80 emails a day of of different people asking you for something that's not work that that's just sort of this range of of people who want something of one form another to meet you your time for you to present for you to donate to their cause for you to whoa that was a little unexpected your last company you helped create 100 millionaires this company you have I don't know countless more but maybe a thousand maybe a thousand maybe the future a thousand?

6:47No. At IPO, it was more. It was about a thousand. Would that be investors and employees? Yeah, as employees. Really? Current and former. Okay. Wow. And so what lesson do you learn from that as a CEO? What is in your mind? I think a couple of things. I think to do the job you got to love to build, I think making money is really great and making money for people you care about is really, really great. and when you get a chance to deliver for people who bet on you, who bet chunks of their career. Your investors, it's great to deliver for them. They bet on you, but they're diversified. They bet on you and 20 other companies.

7:30When someone bets five or seven years of their career, and a career is 30 years, they're betting a sixth of their professional career. And when you get to deliver for them and they get to achieve the financial goals that they wanted. That's a great feeling and I'm proud of every day. It's a very selfless position on that. I mean, it's really interesting because today, I mean, in the backdrop, we are in a hyper super cycle, whatever you want to call it, of AI. And so these companies that are coming up, whether they're in semiconductors or they're in, I don't know, models or coding agents. There's a lot of companies that are rising up really fast and hitting that billion-dollar mark.

8:17Some are having liquidity events like OpenAI and Anthropic to come, but others are getting that paper markup and they're seeing that kind of wealth creation event. How do you maintain a healthy mindset around that? I think you bring it. it's not a change right for

8:43the type of people I love working with they like building stuff and they like building hard stuff when it paid a little when it was out of fashion when hardware was uncool they were still building hardware because that's what they like to build and now that it's in fashion they like to build hardware and they're sort of even keeled about that, that their passion is the building And I think in Silicon Valley, which sort of is what I know, that chasing money is not the path to money. The path to happiness is working on projects you like with colleagues that are interesting for people with integrity.

9:21And if you do that, the money will come. But even more importantly, you'll work on things you like. And you'll work with people you learn a little something from and you can teach a little something from. And if that's the way you said about pursuing your career, I think when things are really bad, you're on an even keel. And when things are really good, you're on an even keel because you're enjoying what you're doing. This episode is brought to you by Brex, my favorite. You become what you spend on. And I refuse to spend my time on work that shouldn't exist. Expense reports, receipt chasing, and manual closes.

9:58the companies building what's next from Vercel, OpenAI, Anthropic, Granola, and Deepgram all made the same call. They all run on Brex. Brex is the intelligent finance platform that combines cards, expenses, and banking into a single stack with agentic finance built in. AI agents that handle expenses automatically, enforce policy before spend happens, and close your books in minutes. That's why Sorcery runs on Brex, so I can spend time on building and not busy work. It's time to get Brex AF. Learn more at brex.com slash sorcery. That's B-R-E-X dot com slash S-O-U-R-C-E-R-Y. Bye. So looking forward, I'm sure this is also just a mark in your journey because you're a builder.

10:51So what are you most looking forward to over the next couple months? as we said across this year? Getting to an IPO is not the end of a journey. It's sort of a plateau. It's sort of the arrival at corporate adulthood. It is the achieving one plateau so that you can climb others. And our opportunity has gotten bigger. We have more resources. We're better recognized. We can reach more people. and we can sort of prosecute our vision and our ambitions with more fuel. And so that's what we're excited about every day. You know, building more chips, building more data centers, inventing technology that moves the industry forward.

11:42That's what drives us and gets us out of bed every day. I think I was listening to a Harry Stebbings episode that you did and talking about data centers and the demand for them and how we're actually not trying to meet future demand. We're actually just really behind. We are behind. On where we are. So could you explain where we are with the data center build out? Right. So what happened is data centers had historically moved at sort of the speed of real estate, right? Somebody would decide to build a building, and two years later, after permits, and they poured concrete, and the building would go up.

12:17And two years ago, nobody cared about AI. All right, two years ago, we were at the beginning of this. And the AI explosions happen so quickly. There's so much demand for compute. We've outstripped the demand for compute, for memory. And where do these things go? They go to these buildings. And we haven't made them fast enough. And so people are chasing data centers around the world. And that's what's happening. And so it is a major limitation for everybody right now. We just had Tony Kim on, and we were talking about the new architecture of data centers. So how are you working with other companies, whether it's through your build-outs, creating the right stack and architecture?

13:11Sure. So the interesting thing about data centers hadn't changed a lot in 20 years. and a lot of the infrastructure in them hadn't changed. I mean, the generators that we use for backup have been unchanged for about 20 years, the type of batteries we use for backup, the chillers and the CDUs, and suddenly there's this sort of intense demand and sort of people are looking to innovate and they're using fuel cells and guys are using jet engines, like boom to generate power for these data centers and the turbines are being rethought of. And so there's sort of an innovative push in the data center.

13:56For us, while we build this sort of super big chip, the chip that's like 58 times larger than any other chip, it goes in a server. It goes in a metal enclosure that's about the size of a fridge for a dorm room, a little fridge. and we put a couple of those in a standard rack. And so the physical requirements weren't very different from if you're going to deploy a competitor's product. What Tony's really talking about is sort of these buildings were sort of unimproved for a generation and now they're part of a factory that makes AI. and people are trying to optimize every part of that factory yeah and now they're also putting them in space yeah well they're talking about putting them in space i think like a lot of technology you talk about it for a long time before it happens do you have plans um you know i'm we we are really good for space because one of the hardest problems in space is getting all these little chips to talk to each other and because we're a big chip we don't have that that problem um i don't think we're in danger in the near term of having a data center in space uh i i think it's more than five years away five years five years okay and that's a long time in our world right i mean three years ago nobody was using ai right and so that i think we got a lot of work in building data centers on earth before we actually have big production data centers in space.

15:37I'd love to talk about how chip design has changed. Sure. Co-design has become an important part of how do you create that kind of platform for the next three years because you're building for the next three years. So how do you think about that and how do you go about chip design? Well, I think historically you made chips and you ran software on them. And there wasn't surprisingly a close interaction because there was a layer called an operating system that lived between the chip and the software. And so, you know, Intel and AMD made chips and people wrote software for the operating system or for the chip.

16:28But AI has gotten so large and speed is so important that what they're doing is they're thinking about sort of the design together. What changes could we make in software that would advantage the hardware or as we're designing the hardware, what changes could we make that would make the software easier to run? And so they're being designed sort of at the same time. And like anything, when you sort of design things together, the advantages are enormous. And so this is something that's really taken shape right now. One of the advantages of our relationship with OpenAI is we get to see exactly where the frontier is going and we get a chance to roll that into our designs.

17:17One of the advantages Google has is that their TPU can be designed in collaboration with the team building Gemini team of deep mind and so they can they can inform their choices back and forth and that's an enormously powerful thing that is surprisingly relatively new in our space do you think that the biggest misconception with that process is and the challenges are well i think that the misconception is that it's easy and all you need to do is get in the room and um it's a uh it's a very hard problem. You know the the software guys think one way, the hardware guys think a slightly different way.

18:02You know anything you do to make it easier to write the software makes it harder to do the hardware, right? And these are really hard trade-offs and so bringing them together and means these sort of compromises where it will be harder here to make it easier here. And that means somebody's schedule is going to be impacted. Somebody's got to add resources. Those discussions are enormously difficult. I'm really curious because I come from an outside perspective. You have an inside perspective. There's a lot of big deals that are being thrown around left and right. And I don't know what's actually under the headline.

18:42So when SpaceX comes out and they say they now have multi-billion dollar deals with Google and also with reflection like what does that actually mean like what are they selling them it's tough to tell no it's tough to tell inside as well really yeah I think um they've been announced some sort of deals that didn't have teeth deals that could have teeth later. I think X had available capacity. And you've got to ask why they had available capacity. They had available capacity because the Grok model wasn't used very much. So they had these GPUs that were sitting around, and that's a bad idea. and so they sold a whole block of them or leased a whole block of them to Anthropics and they looked up and said, whoa, that's a pretty good idea, right?

19:41We had all these GPUs. Our model wasn't a success, but whoa, we can have a great business by sort of stepping into what is a constrained market, very hard to get lots of GPUs and lease these and then they looked around and said, well, what else can we, who else can we lease to? And so that's how it started. And now the specifics of those deals I'm not super familiar with. Are you concerned at all about the circular deals that are going on? I'm concerned that there are ways frequently for NVIDIA to exercise market strength. There are ways for NVIDIA to use their balance sheet to limit competition.

20:33If they invest in a NeoCloud, the NeoCloud is less likely to use a non-NVIDIA chip. if they invest in a model builder. There's pressure not to use other people's chips. That's what I'm more worried about. Yeah. This is happening in the token world with all the free tokens that are being offered to these startups. That's exactly right. I think these are drug pushers. Here, little girl, try a little bit, just a little bit. And I think what the startup should do is, you know, they should take it and then never be dependent. Take some from AMD and come to us and see if we can get you some as well and avoid dependence.

21:25That never ends well. If you're building what's next in AI, you need to know MongoDB, the database platform developers love and built for the agents you're running. MongoDB stores, searches, and reasons over your data in real time. with vector search and embeddings from Voyage AI all in the same system. No separate pipelines, no stitching together 10 different tools. It's why 75 % of the Fortune 100 and leading AI-native startups run on MongoDB. Build and scale from your first user to billions of vectors. Go to mongodb.com slash AI to learn more. That's mongodb.com slash AI to learn more. Bye.

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22:46That's assemblyai.com slash S-O-U-R-C-E-R-Y. I mean, this is actually a good transition into something that Karp said not too long ago on CNBC. He was pretty much talking about sovereign AI and how every company should own the full stack. and so whether it's their data for their products and everything in between and models too because you don't want to sell that then the models will recreate it and then about a new Figma how do you feel about sovereign AI in this like the shift over to owning the full stack well I think the notion of not being dependent I mean you shouldn't be dependent on on Nvidia you shouldn't be depend on one model maker.

23:32I think that that rarely works out well. What you'd like to be as a nation or as a big company is you'd like to have choices. And I don't know if you need to own all the stack but you like choices at each layer of the stack. I think a different way to think about what Alex said is you You want to think about where your advantage is, right? If you're really, you have unique data, be sure you don't give that away, right? Be sure you have multiple choices in different parts of the stack, but you get the credit for your data. And it doesn't help make somebody else's model better. As we look forward, I guess more on the macro lens, the proliferation of AI and everything that we're able to now create and build and do, what are you excited about on the externalities that come with all of this?

24:34I think that we have a chance for our children or the next generation not only to not die from cancer, but to not know anybody who died from cancer. I think that is a real achievable goal in 25 years. Wouldn't that be something? it. You know, when we think about what AI can do, writing better code is cool. And there's a huge market for that. But I think what it can do to better humanity is rid us of the number one killer of adults. And I think, you know, that's when I think of what we're all doing this for it's an outcome like that you know pancreatic cancer had a huge breakthrough recently i i think they're uh the opportunity for for breakthroughs right now is has never been better and ai is a an extraordinary tool in in pursuit of of of knocking down um major major human killers right i mean if you think if you if you took out cancer and you took out automobile accidents.

25:54You're taking out huge numbers of deaths a year. And you say to yourself, well, that's a lot of good that we did. And I think, you know, self-driving, humans are terrible drivers. Horrible. Horrible drivers. It's not just when we're 16 or 18 or when we're not paying attention or our parents in their 80s or, you know, it's, we don't pay attention we're on the phone we're talking to our wife we're worried about work whether that's even before people drink or do all sorts of things they're obviously bad but we're just not good drivers and machines can drive better than we can today and so that's the number one killer of people whatever 15 to 40 is car accidents you take that out through self-driving you take out a major killer like like cancer going whoa that's a pretty good 20-year run of technology Are you a peptide fan?

26:50I'm a peptide fan. You are? Yeah. I think not in the specifics of there is a peptide, but rather in that our opportunity to advance our knowledge about the biology of our bodies and how to achieve performance and how to achieve longevity. We're just beginning. Yeah. And we're going to make some big strides, whether it's with peptides or something else or, you know, the next GLP-1 inhibitor or whatever. We're going to make giant strides. Yeah, it's been really cool to see all the new drug discoveries and new drug discovery companies. Brian Armstrong just came out with this company called New Limit.

27:34That's one of them. I think their goal is to eradicate all diseases. Yeah. It's a good one. Right. I mean, even if that's a little hubris, I mean, it wasn't even hubris that was thinkable a decade ago. Yeah. Right. I mean, we're now in a realm where, wow, that is sort of crazy big, but not insane. Right. I mean, how cool is that? Yeah. I mean, well, a lot of people like to talk about the doomerism of AI, but I think we're entering a new mix of talking about the actual outcomes with it. And so to your point of what you're talking about, whether it's with AVs or drug discovery, it's really good.

28:14I think the problem with the doomers is they're only looking at one side of the ledger. I think to look at this with clear eyes, you've got to look at both sides of the ledger. You've got to say, look, we're going to use a lot of power. It's true. And AI has some real risks. It's true. And on the other side of the ledger, here's some things it can do really differently. and here's some things it can do. Take education. We've known for 2 ,000 years the right way to educate children and we never do it. Ever. I mean, we knew that the right way to educate Alexander the Great was to have a tutor and the smartest tutor, Aristotle, was and that you teach each child differently and you think about their way of learning and we never do that.

29:01You throw them in a classroom, You teach to some sort of middle level. Each child does not get sort of any different teaching for their different way of learning. With AI, we can do that. We can get you a tutor that's right for you. And what's more, the tutor can be running in the background saying, look, 3 % of students make this type of error, and the best way to teach them to overcome this weakness is with this approach. How cool is that? I mean, we've been screwing this up for 2 ,000 years. and now we can bring it to every child. Put it on the positive side of the ledger. And look at clear eyes at both the negative and the positive and see if we're doing right by society.

29:45So one of our sponsors is Brex. And I bring this up because our questions around performance, they are all about spending smart and moving faster. But performance in terms of like for your finances, I ask this question in terms of your personal side of things. I do believe that performance for individuals is kind of who you surround yourself with or who you're inspired by or mentored by. You've had a great run at building companies and have had great success. So I'm really curious who those people are for you. There are a couple of mentors. There was a venture capitalist named Pierre Lamont, and he's now in his 90s.

30:23He invested in us at Cerebris when he was in the ripe age of 84. Oh, my gosh. And was on our board, and he's forgotten more about making chips than I'll ever know. There was a CEO, a former CEO named Mark Leslie. He was CEO of Veritas. They invented the file system. And these were sort of wise people. And they had extraordinarily high standards. and they taught me a lot about being a leader, about demanding a great deal from myself and from others. They were people who were exceptional. I think sort of on a day-to-day basis, sort of my co-founders, there are five of us. Five is, in almost every case, too many founders.

31:21They all worked. We all worked together in my last company. I've learned an enormous amount from them. They challenge me and I'm excited to think with them. And that's an okay way to go into work every day. It's amazing. Well, thank you so much, Andrew. It's a pleasure to have time. I know we covered a lot of ground with this conversation. We covered a lot of ground. It's so many topics. I didn't think we were going to get to peptides, I'm going to be honest. I just had to ask. Well, thank you for having me on your show. I really appreciate it. Thank you. Huge thank you to the entire RAISE team for an incredible event.

32:04And thank you to Brex, MongoDB, and Assembly AI for making this trip and series possible. If you enjoyed this conversation, you're going to love the rest of the RAISE series with Tony Kim from BlackRock, Scott Wu from Cognition, Andrew Feldman from Cerebris, Rodrigo Liang from Salmanova, Michael Hurlston from Lumentum, cj desai from mongo db and many many more like our hot takes that we did at a secret location that you can find on x youtube and instagram subscribe to sorcery on youtube for more conversations with the people shaping ai and join the free newsletter you can also do paid at sorcery.vc for weekly insights on ai robotics enterprise software consumer semiconductors Did I say AI?

32:50AI again. And everything that's coming next, like funding announcements and all big things in tech. Thank you. Bye.