00:12:28 · Molly O'Shea, Burkay Gür
[00:12:28] S0: Yeah, I mean, that's like a thing. It's like, the thumbnail is always testing. I mean, for like YouTube, for us, it's like, you gotta test thumbnail, you gotta test the title, you gotta test like the copy, all of that kind of stuff because it works the algorithms differently. [00:12:42] S2: Exactly. I think there's, like, really sophisticated users out there that are doing it, like, at, like, smaller scale, maybe they're, like, a creator, but also, like, large companies is doing it right now. I don't think it's, like, super spread out yet, but, like, it's out there for sure. And, like, we work with a few companies that actually do it, but I think it's gonna get even more available, I would say, because it's not very straightforward, I think, to do the whole reinforcement learning and all technical stuff behind it. It's not fully there yet, but I think in a few years, this is going to become the norm. [00:13:19] S0: So let's talk about the engine behind fall, and then we can kind of get into how your culture is keeping up with the growth because it's crazy. So you were saying you started off with compute, you started off as a compute company, you found your way into this area space. What was that evolution like for you and like how have you completely embraced this new category?
00:13:42 · Burkay Gür
[00:13:42] S2: Right, yeah. So we started in compute but like a pre AI era, let's call it, right? So we started in 2021 and the whole thesis was like, okay, there's, you know, this previous data infrastructure wave led to some amazing companies like Snowflake, Databricks and what do they have in common? They own compute, you know. So, in order to build the next generation of like the data infrastructure company, we also have to focus on compute. That was the initial thesis and we thought the next big thing is going to be Python. So, basically like what Snowflake did and what Databricks did to a certain extent was like enabling SQL to run on, you know, in the cloud. And they own the compute and they let you scale the compute elastically. So, we thought Python is going be the next thing because AI is the next big thing. So, we ended up working with some really awesome teams like trying to bring their data science and machine learning, old terms, like workloads into the cloud. So, that was like our initial starting point. And then, soon after we started, some insane things happened in the market. I think from a technology point of view, like we had a massive breakthrough with ChatGPT and in our space, stable diffusion and DALL E. So, we kind of had a choice at that point. Like, we can either stick to our like, you know, data infrastructure, you know, initial idea or we could go into this like new world of AI. And there was language models and at the time, I think people were very excited about a bunch of open source models. If you remember, like Llama came out shortly after and there was this like huge price race at the bottom and we just thought, okay, we're like five, six people right now. We don't have that much money in the bank. We're a pretty early company and we can't really go and sell tokens at a negative margin. And let's do something more interesting. Trend still holds. Where the trend still holds is let's focus on image models because like there's something interesting happening there as well. There was no sight of video models. Like, no one even talked about it, I think, back then. But we thought that like we could take image models and make them run a lot faster in the cloud on the same infrastructure that we built. And so, did that. So, we had a very technical team. We thought like we could do a really good job running these models faster.
00:16:15 · Burkay Gür, Molly O'Shea
I don't think we had a very formed thesis on like where those models are going to go. So we kept like, we kept doing it and that got a lot of attention from like very early customers and we thought, okay, you know what, like with this other business, we ran it for a year, we didn't make a single dollar. With this one, our revenue's starting to go like this. There's clearly something here so we decided to focus on the image model space there. And three to six months later roughly, we actually realized that like this trend is probably much bigger and we thought that these models are like useful for very different things than what LLMs are helping with. You know, we thought it'll help with ads and marketing. We thought it's gonna be, the buyers are gonna be completely different. So we decided to call it something else, to like just be able to tell the story to people. So we actually came up with this word generative media and we slapped it on our website and we said, Fal, the generative media company. And we always have to explain what it is because I think, you know, three years ago, no one really understood what that meant. So, that's kind of like how we got into it and how we sort of found our, like, niche, which, you know, three years down the road, it's more well established and it's a whole, like, new industry, so. [00:17:42] S0: And people want to make feature films out of it. [00:17:45] S2: Exactly. Yes, yes. I think, like, when you first play with the first DALL-E, like, you would never think, okay, like, we could make movies with this. But it took only, like
00:17:45 · Burkay Gür, Gorkem Yurtseven, Molly O'Shea
[00:17:45] S2: Exactly. Yes, yes. I think, like, when you first play with the first DALL-E, like, you would never think, okay, like, we could make movies with this. But it took only, like [00:17:54] S1: Came here very, very fast. [00:17:55] S2: Yeah. We came here really fast. It only took, like, eighteen months that people started thinking, oh, like, this could actually make feature films. [00:18:02] S0: So we're in San Francisco. People here are super nerdy. Maybe you guys are too, but as you're growing super fast in this inflection period, how are you keeping ahead of research? Like, are you paying attention to research? Like, what are you how are you learning as you go? [00:18:22] S1: The beginning, we were extremely involved, obviously, like we had a very small team and we had to be part of every single little edge we can make. And then nowadays we have a really talented leadership team that most of them we worked with before in different companies. So I would say that's the best part of our job, that we can rely on these leaders and that's a superpower to ask their opinion, what they think about what's coming new, what they pay attention to, and a lot of the information I get these days is from that team. I'm also very curious to read everything, but I learn more from the leadership team than the internet these days. [00:19:05] S0: Oh, that's pretty good. What about you?
00:19:05 · Molly O'Shea, Burkay Gür, Gorkem Yurtseven
[00:19:05] S0: Oh, that's pretty good. What about you? [00:19:11] S2: Yeah, I think just to echo what Gorkem said, it's very important like how you build this team. I think I got a lot of inspiration from my days at Coinbase in terms of like recruiting the earlier team. I think one of the things we did there so I joined Coinbase 2016. Team was like almost 100 people, maybe, like very early days, similar to like our size now. We're like 150 people today. And one of the things they did was like they had this like crypto quiz that they posted on Reddit, right? And one of the things they assessed for was like, literally like your knowledge about crypto. Like, how much do you know about it? You know, a bunch of technical terms. Also, pre AI, like, you know, it was hard to find the answers to these questions. But, like, there was literally a quiz, and you had to pass this quiz to, like, actually get on a phone call [00:20:08] S1: with someone on the team. How crypto filled are you? Was You can't remember.
00:20:08 · Gorkem Yurtseven, Burkay Gür
[00:20:08] S1: with someone on the team. How crypto filled are you? Was You can't remember. [00:20:12] S2: So, this was like I think this was like a very key factor to, like, you know, Coinbase's success in the long term because, like, you really want, like, these, like, fanatics about the space so that, like, they can keep things going because, like, you know, most of the time, like, the whole job becomes about it becomes, like, staying up to date, So like how do you stay at the forefront? One, like you could collect really great people and, you know, get them on your team and hopefully they'll feel motivated or you can get people who are like already motivated. This is all they can think about. This is the thing that they're, like, most excited about today. If you didn't hire them, they would be doing this anyways. So, like, that was literally like and it still is. This is kind of the criteria we have for bringing in the early hires because, like, it helps with just naturally, like, we're up to date all the time. And I think it helps with people being just, like, constantly motivated about, like, what they're working on. So, like, you know, you don't have to try to do that. People are already like AI built or gen media built.