Venture with Grace
00:26:38 · Grace Gong, Jerry Tworek
[00:26:38] S1: We only got interrupted sometimes. Sorry. Okay. So... That's that's okay. Yeah. The Parag. The rack. [00:26:45] S2: It was like per per rack. Yeah. Per rack billing model where, like, you basically buy your own hardware Mhmm. With your own capacity. It is only serving for you. And because the model is customized, that rack has a memory. And that memory integrates the data from your business. And it's used for your usage. And you know that your data doesn't leave your systems. It is not something that goes to some other company that you never heard of and it's hard to trust. So I think it's a good business model of the future. In the end, compute drives it. And we want to be kind of like an extra layer on top of NVIDIA chips that's help you achieve your business goals. [00:27:26] S1: Let's talk about NVIDIA. You guys have a great relationship with NVIDIA, apparently. So some people are both investor and client at the same time. So how how do you kind of, like, think about the NVIDIA layer? So obviously, there are a few people on our podcast also are building NVIDIA's layer. Obviously, NVIDIA is still one of the biggest provider in the market. So what's your thought process on these other kind of players in the industry, their approach to GPUs? And how do you think about maybe expanding the solution to different things as well?
00:27:26 · Grace Gong, Jerry Tworek
[00:27:26] S1: Let's talk about NVIDIA. You guys have a great relationship with NVIDIA, apparently. So some people are both investor and client at the same time. So how how do you kind of, like, think about the NVIDIA layer? So obviously, there are a few people on our podcast also are building NVIDIA's layer. Obviously, NVIDIA is still one of the biggest provider in the market. So what's your thought process on these other kind of players in the industry, their approach to GPUs? And how do you think about maybe expanding the solution to different things as well? [00:28:11] S2: Yeah, yeah. That's a great question. First and foremost, at least today, NVIDIA builds just the best training chips in the market, and that's why we are very happy to be working with them. There are many companies trying to compete in a hardware market. And it's hard for me to say much about how that will play out. I'm just not an expert in the hardware market. I'm always very happy to be using the best hardware of the day and make sure our models will be running very well in there. There a reason why we didn't choose to build our own hardware. We are willing to devise and develop all of the deep learning stack and all of the ways of training models. But the hardware layer is where we are starting. So we take the existing chips. And our goal is try to figure out how to develop the best model with the maximum amount of learning capabilities on the existing hardware, which largely is built to execute matrix multiplications very, very fast.
00:28:11 · Jerry Tworek, Grace Gong
[00:28:11] S2: Yeah, yeah. That's a great question. First and foremost, at least today, NVIDIA builds just the best training chips in the market, and that's why we are very happy to be working with them. There are many companies trying to compete in a hardware market. And it's hard for me to say much about how that will play out. I'm just not an expert in the hardware market. I'm always very happy to be using the best hardware of the day and make sure our models will be running very well in there. There a reason why we didn't choose to build our own hardware. We are willing to devise and develop all of the deep learning stack and all of the ways of training models. But the hardware layer is where we are starting. So we take the existing chips. And our goal is try to figure out how to develop the best model with the maximum amount of learning capabilities on the existing hardware, which largely is built to execute matrix multiplications very, very fast. [00:29:12] S1: Mhmm. Thinking about, I guess, like, your day to day as a CEO, what's the difference between, like, being the researcher yourself to, like, running a company? Because I I would assume, like, seems like you would enjoy research.
00:29:30 · Jerry Tworek
[00:29:30] S2: I do enjoy research a lot. It's one of my favorite things to do, obviously, being a CEO and building your own company. It does require a of other things. Like, one thing is you need to secure funding for a company. You need to be somewhat external facing. And you need to be able to tell your story and explain to all of other people that AI companies of the day that don't really exist in a vacuum. How do you fit into the ecosystem and how you relate to other companies is also very important. And there are also a lot of operational things that you need to do in some way when you are a CEO of a company. Everything is your problem, everything is your responsibility, not just research. Research is probably one of the things I care about the most, but I have a lot of other headaches and a lot of other things I need to worry about every day that are just beyond research. But in some way, it is an extremely enabling thing to do, to try to design something that you want to be built, which is this new type of model, and then try to bring it to the world. The reality we live in is that starting a new company is one of the best ways to achieve certain technological goals. And then companies are not just models, not just training, but everything that needs to come together, it's an organism. That needs to function very well. And that's what we are doing.
00:30:57 · Grace Gong, Jerry Tworek
[00:30:57] S1: What motivates you? Since you want to I don't know, I don't think... I mean, I listened to a bunch of your podcasts, but I didn't know if you ever shared the story of coming from Poland. And is there how you grew up and then how you kind of... Do you always know that you wanna become an entrepreneur? Or obviously, it seems like you have a you know, great, like, trading career and to, like, you know, riding the wave of AI. But what kind of, like, you know, is something that you enjoy doing? And then what do you identify as your, like, unfair advantage as a as a founder? [00:31:30] S2: Yeah. Yeah. Like, think what mostly drives me, in many ways, is I just like building technology. This is, to me, what makes me get out of bed and what makes me wanna do things. I think building specifically new solutions to our products. I'm not AI. But I very much, very much enjoy building things and solving problems using science and engineering. And that's kind of what I just like doing and what I wanna be spending my days. And the rest of the question is how in which configuration for the rest of the world I want to be doing that. I have thought about being an entrepreneur on and off throughout my life. It's usually question. Is it the right time? Do I have the right idea? Is the world ready for what I'm trying to do? [00:32:17] S1: The world is not ready. Will be ready soon.
00:32:17 · Grace Gong, Jerry Tworek
[00:32:17] S1: The world is not ready. Will be ready soon. [00:32:21] S2: Exactly, exactly. There are doors. I think we have an idea for a company starting in college, which I don't think it was a very good company because it was mostly meant to be a company making personalized and interactive study materials for mathematics. Was my first You're [00:32:37] S1: newest company. Interactive mathematic... That sounds like ChatGPT. [00:32:40] S2: Exactly. In some way, working on AI and ChatGPT helped me realize that, and I think that is that is pretty nice. I I think I think back in the day, there wasn't really a good time, and there wasn't really a very good very good moment for this idea. These days, a few hours of byte coding, and you already can have a prototype of exactly [00:33:00] S1: You were just like ten year earlier. [00:33:02] S2: Exactly. Timing is very hard, and one of the most important things in starting a company. The question is, is this the right time to build a company I want to build? It's extremely, extremely critical. And you don't wanna be too early and you don't wanna be too late. [00:33:17] S1: Like, are you in the right time? [00:33:19] S2: I I assume so. That's why that's why I decided [00:33:21] S1: to do it now.