Full Transcript for Inside fal’s $1.65B Series E & F Led by Sequoia & Bessemer

You guys have the coolest brand on Earth. You guys are growing really fast. You keep on raising more and more money. AI really has three product market fit. One of them, we believe, is generative media. Three years ago, no one really understood what that meant. Three years down the road, and it's a whole new industry. You sit down in front of a computer, and you generate videos all day.

And you spend $10,000, $20,000 a month. And we were like, OK, who the heck is going to pay all this money? Turns out there is essentially infinite demand. Every big company is going to be a compute company. Just the storefront is going to be different. Our storefront is unique and interesting. No one else has a storefront similar to us. Were you surprised by how much money there is behind this?

100%. Okay, cool. All right. Gurkem. Wow. You don't need to, you really don't need to. Gherkem. Yeah. Gherkem. Yeah. Wow. That was the last one. That was the last one? Yeah. Okay. Gherkem. Yeah. Gherkem. Now I'm just going to keep on saying it. Yeah. That's perfect. Teaching AI. Internet. You've been pronouncing Gorkum completely wrong. It's Gherkem.

AI, learn from the YouTube videos. We're kind? Yeah, perfect. You guys, this is great. You guys have the easiest names on earth. Easy. Welcome to Sorcery. Thank you so much. We're in a very special place, so do you want to maybe tell us where we are? Sure. Yeah. So we're at Dalida. Shout out to Sayat and Laura. Dalida is an Eastern Mediterranean restaurant with a lot of Turkish influence.

And fun fact, I got married here and Gerkem officiated it. Great wedding. Congratulations. Thank you. Amazing. Well, I'm excited. I can already smell the food. Everybody is eating it behind the scenes.

So, as much as this conversation is going to be rich and delicious, I'm sure the food is as well. It's amazing. Okay, so I think I've reached out to Michelle like a billion times because your name kept on popping up, you guys have the coolest brand on earth, like, you guys are growing really fast. Every single time, and it's about a round because we cover funding rounds, I'm like, I gotta get them the next time.

No. You guys already raised it. It's gone. It's over. The next one. Gone. Over. And I'm like, keep on trying to catch you guys, but you keep on raising more and more money. So, congratulations on the recent round. Thank you. Thank you so much. You did like couple back to backgrounds like any fast growing air company these days. But this last one is the biggest one yet.

So thank you so much. Congratulations. I think you've also hit the point where you don't want to do any media on it anymore. So you've passed the inflection point of like the hype cycle. And now you just have a humming business. Exactly. We rather focus on the business, the announcements. It gives some push in the beginning, but as you do more rounds, I think it's irrelevant.

It's the business that matters more. The adrenaline has worn off. Exactly. He's probably worked for hiring and that kind of stuff and customers, but he got to focus. Okay, so let's talk about the evolution of the business today. Generative media has taken off in AI. It's probably one of the coolest parts about AI, seeing all these videos being creative, all the creative stuff getting made.

And so... I don't know who wants to take it off, but feel free to just kind of like, where are we right now and why is this just kind of exploded? The way we talk about it, AI really has like three product market fits. One of them is search and like initial chat GPT consumer product and now Google and Gemini. The other really clear one that's growing really fast now is coding agents.

And the third one is, we believe, is generative media. And to put things in perspective, when we talk about it, with coding agents, an individual can go spend maybe $10,000, $20,000 a month on their cloud or open AI subscription. Generative media is the only other thing this exists. An individual, if this is your job, if you work at an AI-native studio or a real studio these days, you sit down in front of a computer and you generate videos all day and you spend $10,000, $20,000 a month.

This is the only other use case in AI that an individual can spend that much money. And search? is so big that it gets a pass and there is no other use case or part of the industry that has this dynamic. It's just coding and generating media. And that's why you are seeing all this growth because more people are adapting it and individually they are spending so much money on it.

I know this is kind of an elementary question, but were you surprised by how much money there is behind this? 100%. We were too. We were surprised all along the way. We were surprised how quickly we switched from image models to video models, where now we make, I would say, 50% of our revenue from video models. And then after that transition, we thought video was going to completely take over.

It was zero, and then it reached around 70% of our revenue. And then we thought image models are done, and it's like... It's not enough compute. It's a simple problem. And from now on, it's all going to be video. And then it turns out image editing models brought life back to image models. And then it's also useful for video models as well, because you can create different frames.

And video models does such a better job interpolating between those frames. So image editing all of a sudden made image models come back. And now our revenue is 50-50. even that was surprising right like when we thought like a portion of our business was dying but it like made a huge comeback but yeah video models keep getting better yeah currently what we can do like the best video model maybe creates 10 to 12 seconds of video like the new ones are going to reach maybe like 30 seconds but until you can generate like real-time streaming very high definition video this is going to keep increasing and as you increase the resolution, as you increase the duration, the cost

increases exponentially because you have to have more attention during inference time, and the resolution increases the amount of pixels exponentially, so things are getting much more expensive. So now we have a framework to think about, okay, there's a lot more money to be made going forward because the video output we get is still very rudimentary.

There was also like a very interesting point sometime last year when VO2 came out.

I think at the time like Kling was probably one of the best video models and there was also like Minimax and the prices were like somewhat kind of going lower. I would say like they started at let's say 40 cents per five second video and then they sort of settled around there maybe like 30 cents for a five second like clip and then VO2 was very surprisingly it was like five dollars per five second video so it jumped like you know more than 10x and we were like okay like who the heck is gonna pay the pay all this money right like this is just another five second video turns out like there is essentially infinite demand so people people started using that model and then

even more expensive models came around And people started using those models. And what was really happening under the hood was we actually saw more and more professional use cases start happening for ads, real people who are in marketing and ads and actually movie production, they started using these models because the quality went so much higher and there was just more demand that other models weren't able to actually capture.

So it's like the usage is going up and then the capabilities are going up and then everything's getting more expensive over time. So essentially, yes, people ended up spending so much more money. And in terms of progress, it's still happening. We're nowhere near...

You know, with LLMs, I think people talk a lot about hitting a wall or like diminishing returns. I think in this side of the market, we're like nowhere near actually hitting like diminishing returns. I think there's just so much new stuff happening with like CDAS v2 and v2.5. It's just like the quality is going up, prices are going up, and people still want to use all these models.

For sure. I mean, do you guys remember Sora? Yeah. Feels like it was a lifetime ago. I mean, that was a really cool moment, but clearly too expensive. Yeah, it was too expensive. In fact, we also hosted Sora on our platform and we saw huge growth in the last three months before they decided to take it down. We were like, what's happening? There's infinite volume here, essentially.

But yeah, it turns out the rumor is there wasn't enough compute for everything else. And it's also expensive to run. So yeah, but I think it had a great future. Maybe it'll come back sometime. I mean, it's really interesting because earlier today we were down at Applovin and, you know, this will probably get released later than that. But I was talking to Adam, the CEO there, and Gio, their CTO, and we were kind of talking about how they've created their algorithms for all the ads and what works best.

And like the best ads are like actually 60 seconds long. And I was like, OK, well, are you thinking about using like a Higgs field or any of these other kind of companies out there? and offering that or acquiring any of these kinds of like generative ad platforms, because some of them just really I mean, most of these cases are ads and like it just it's just really not there yet.

It's like the best they can do is like five seconds. So it's like not every brand can do that in terms of where you guys came from and where it's going. Advertising is going to be the biggest use case, you think? I like ads as a business. Internet runs on it. And also, the content these models are able to make is perfect for these UGC style ads because the content is usually throw away.

If it doesn't work, make a new one. It works great. But also, the the quality like the the lighting nothing has to be perfect it needs to be almost looks needs to look homemade so it's like easier to do and you know yes the the best ad maybe 60 seconds but you don't have to do a continuous 60 second generation you can do fast small cuts which works maybe better in in certain cases and then what you can do is you get a lot of data back right that's I don't think anyone is particularly doing a good job at it.

But because you can post these ads and see how people are interacting with it, you can have like continuously improving or you can do small changes to what you are posting and just show more of the things that are performing well. And this can all happen automatically, right? So this is, I think it works great with video models. No one has done it perfectly, but...

We would love to be part of this automated ad story. I think it's going to be a great business. It was really funny. I was going to mention this in the interview, but then I realized it was probably kind of inappropriate. Like the example you just mentioned of like reinforced learning models on themselves and just kind of optimizing over and over again.

There was, and I don't know if you guys see this in your Instagram feed, but I do this because I make clips and I make like stuff for the internet. And they're like, one of the best hacks that I had was showing my armpits. Like I got so many more views from showing my armpits. As the hook, right? Literally, literally. It's like I got... 10x views just from like having my arms up and like and I was like what the hell yeah imagine like you can have yourself in 100 different positions let's go yeah I mean but 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 that kind of stuff because it works the algorithms differently exactly I think there's like really sophisticated users out there that are doing it like and 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 um and like we work with a few companies that actually do it but i think it's gonna get even more um available i would say because it's not it's not very straightforward i think to do the whole like reinforcement learning and all the technical stuff behind it.

It's not fully there yet, but I think in a few years, this is gonna become the norm. 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 how have you completely embraced this new category? 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, OK, there is, 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. So in order to build the next generation of 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 SQL, basically like what Snowflake did and what Databricks did to a certain extent was like enabling SQL to run on Python.

you know, in the cloud and they own the compute and they let you scale the compute elastically. So we thought Python is going to 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, Um, some insane things happened in the market. I think from a technology point of view, like we had a massive breakthrough with chat GPT and in our space, stable diffusion and, and Dali. So we kind of have like, uh, we kind of had a choice at that point. Like we can either stick to our, like, you know, data infrastructure, um, your 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. The trend still holds. Where the trend still holds is let's focus on image models. Because there's something interesting happening there as well. There was no site of video models. No one even talked about it, I think, back then. But we thought that we could take image models and make them run a lot faster in the cloud on the same infrastructure that we built.

And so we did that. So we had a very technical team. We thought we could do a really good job running these models faster. I don't think we had a very formed thesis on where those models are going to go. So we kept doing it.

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 revenues 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 useful for very different things than what LLMs are helping with. We thought it'll help with ads and marketing. We thought the buyers are going to be completely different. So we decided to call it something else, to 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, follow 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, yeah, 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.

and people want to make feature films out of it. Exactly, yes, yes. I don't think, I think like when you first play with the first Dali, like you would never think, okay, like we could make movies with this. But it took only like... It came here very, very fast. Yeah, we came here really fast. It only took like 18 months that people started thinking, oh, like this could actually make feature films.

So we're in San Francisco. People here are super nerdy. Maybe you guys are too, but like, well, 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?

In the beginning, we were extremely involved, obviously. 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 super power to ask their opinion what they think about like what's coming new what they pay attention to and A lot of the information I get these days is from from that team I'm also very curious to read everything but I get I learn more from the leadership team than than the internet these days Oh, that's pretty

good What about you? Yeah, I think just echo what Gerkam said it is 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 recruiting the earlier team. I think one of the things we did there, so I joined Coinbase 2016, team was almost 100 people maybe, very early days, similar to our size now.

We're like 150 people today. 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 your 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 with someone on the team. How crypto-filled are you? I think this was a very key factor to Coinbase's success in the long term, because you really want these fanatics about the space so that they can keep things going.

you know, most of the time, like the whole job becomes about, it becomes like staying up to date, right? 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-pilled or gen media-pilled. 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. The companies building what's next from Vercel, OpenAI, Anthropic, Granola, and Deepgram all made the same call.

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So where are you hiring people from? Like what were their roles? Because this is all, again, this is all very new. This is a common question I ask in these conversations because it's like to remind people like none of this really existed like three or four years ago. So how many people are trained? Even in the beginning, it was an overlooked market because it happened at the same time with the LLM growth.

Like maybe if it happened by itself, it would have been the hottest thing, but it was like the second hottest thing. It's also hard because it's the creative industry. It's kind of at odds with technology to some degree. It's like... There is a lot of technology involvement in creative industries, right? Like even an IMAX camera is like, you know, size of that table over there.

Like there is technology involved and in different parts of like animation, filmmaking, bigger parts, and then it plateaus. And maybe we are going through one of those times where in the next five to 10 years, it's going to have another outsized impact on the creative industries. But yeah, like AWS, AMD, they have massive media businesses where they sell to studios and media companies.

So this is just the next wave of it. Yeah, I think I was listening to something on Christopher Nolan and his infrastructure.

Where he's keeping all that IMAX film. Yeah, 900 pounds. So heavy. Which is funny. Okay, so let's talk a little bit about the team and how you guys all gathered together. So you came from Coinbase. You came from Amazon. Amazon, yeah. Yeah. So how did you guys meet and what was kind of like the early culminations of gathering together a group? You go.

So we are both Turkish, but we didn't know each other back home. We met in San Francisco when I first moved here. 2014 is immediately I met him. We were both working at different companies and doing, you know, minding our own business. And it was actually during COVID time.

We've told this story a couple more times before, but We ran into the house in Palm Springs and that's when we first thought, okay, maybe there's like a working chemistry between us. And then it took us maybe another year to start the company. But that's how we met. We were longtime friends for over 10 years and never worked together until that COVID Palm Springs house.

And here we are. We've been building the company for five, six years now. And you've been pulling people from Coinbase, from Amazon. Coinbase and Amazon. It's funny. It's like from both places. Exactly. And so what were you like looking for in the early days? What were the types of hires?

I would say just really good people in many ways. I think one is obviously they have to be excellent technically. I think early on we...

we definitely had to get the technical part right, because we were just doing a lot of deep technical work. We still are, but at that time, that was our differentiator.

So people who are really good at, very good technically, I would say also people who are just people that we get along with. I think early team chemistry is really, really important, I think if you can like figuring out like product market fit is probably the most challenging thing for a startup. Right. So like you have to in our mind, I think you have to keep a pretty small team and that can work really, really well together that can stick together and just have a really great way of.

experimenting with ideas and then like throwing things that don't work and just like keep moving and keep looking for... I think this is one of the biggest advantages of starting a company in your mid-thirties because you have your whole working life, people you worked with, you trusted, you didn't trust that you can bring in together and as soon as, you know, you reach out to people.

If you have something worthwhile, they come and join you and they want to be part of the story. And if you are like younger, you unfortunately don't have that. And you have to just go on your own and try to hire people and get trust. But here we build trust with so many people that early engineering team was almost all people like we knew before and worked with and trusted.

help navigating the problems so much easier. What are your views on scaling up or keeping flat?

So culture-wise, our company, I would say, is flatter than your run-off-the-mill startup. I think the deepest level we have is two.

levels of reporting. And yeah, I think that's by design, I would say. We really believe in this like super ICs. I think it's becoming more popular. Now it has a name. I don't think we had a name. Really? Yeah. It's a super IC? It's a super IC. So we have four deployed... Deployed agents, not agents. Is it agents? No, we need agents soon. Forward deployed engineers.

I know Palantir quite well. So we have forward deployed engineers and now we have super ICs. Super ICs are, I think now it's becoming a more common term. Basically, you want your management layer to be super ICs. So people who are just so epic at their job, they can actually do hands-on work and then they can also lead teams.

I think we have a very similar, without like calling it this way, we always had the structure

in a way that like essentially like we don't have pure managers. We don't plan on having pure managers. Yeah. And we can gather the team around like these really magnetic like people within the team that are just like really freaking good. And that's just like a very... I don't know, natural way of building leadership within the team. So that's kind of how we've been building it out.

We just add really good people, and then we see leaders emerge, and we gather the teams around them. But how long can you go this way? I think there is a limit, right? So you start hitting... I think like some communication bottlenecks. Right. And I think that's part of the scaling challenge. Right. Like you have to kind of think about like like we think a lot about like how do you how do we communicate with the team broadly? How do we keep everyone like aligned? I think those are like, you know, as as you grow, those start becoming the challenges.

And so far, like We just try to have many check-ins with the team. I think we're still keeping everything flat and see when things break. And then we would throw maybe more management layers. But essentially, we're really focused on this super IC strategy. And in a way, our growth was timed perfectly with how coding agents and NLMs became a huge part of software engineering.

I think forever we can keep this as long as agents and coding models improve at this pace. You just need really talented leaders that super ICs to manage, maybe be the leader of I don't know, five to 10 engineers and you rely on coding agents to do most of the work. And I think we can keep up like this to have like maybe just two levels of hierarchy and that's it.

I mean, look, Applovin does multi-billion dollars in revenue. They have like 400 employees and 100 people on their engineering team. Yeah. Yeah. Big fan of Adam. Big fan. Big fan. I mean, I was there today.

It's crazy. I mean, like their market cap peaked at like 250 billion. Now they're at like 130, 150. But I mean it's like he is such a proponent of what you're just saying like his whole thing is built on individual contributors and like people not just because now we have access to coding agents like What about the other side of the brain? What about the like, you know the human personal things? Yeah, also holding the business weight of it and making business decisions, but like having you know the team effort around it so I think that is like a It's kind of a structural component that's just fundamentally changing.

It's like, you can't just be a 10X engineer. You have to be a lot more. I think other CEOs are also talking about it. Brian Armstrong from Coinbase, he recently talked about it. Literally describes a blueprint. This is how we're building the company going forward. I think Elon is a very big proponent of this, for better or for worse. He talks about this a lot.

Yeah, I think it's really picking up, especially among, I think it's harder to do at non-tech companies because there's so much hierarchy, but I think tech companies particularly are very, they still need to, I think, go out of their comfort zone, but at least they're better suited to be able to pull this off. But it is something I think a lot of people are talking about.

So what are the key traits that you guys look for?

Agency is one thing that we talk about in the office. I think everyone would want people with agency, but you just mentioned software engineers even making business decisions. I think it's unheard of in a big company like Amazon, Coinbase, whatever, software engineers do software engineering, but because the market is moving so fast, the customers are you know, emerging, changing between different models so fast that a lot of the times we want our software engineers to make business decisions or work with customers, therefore have to make business decisions around them.

So that's the hardest type of engineer to find. And I think you look for agency. If you think this person can act independently, take responsibility and own the decisions, then the other things we want just comes naturally with it. hard to test for it. I think the best way to know it is if you work with him before or her, that's the best way to know it.

But that's something we care about a lot. Yeah, I think we also look for maybe maybe correlates a little bit, but like hunger, I think is something that's like very, very important because like I think you need to be you need to be able to like really push in this market like to to actually win. So you have to like just really want to you know, win and build a big company.

So we try to test for that, which is very hard to test. But I think like you can kind of get a sense when you like sit down and talk to a candidate. We do a little bit of like reverse selling. I think that helps maybe to identify hunger. Like, hey, like it's a lot of work. We don't like believe in, I don't think we believe in like I don't know, toxic work hours or things like that.

We go home during weekends, for example. Really? Yeah. What? Imagine that. This is the first I've heard of that. So, nothing to, I think, brag about, like, you know, like, nothing to brag about, about not going home. You go home during weekends and you're still successful. Yes, imagine. Crazy. But I think, like, there is a certain baseline, I think, that we try to be realistic about, like, what to expect.

And so that's part of the reverse sell, I think.

there can be a lot of time crunch where we really push and we have to spend a lot of time working and 60 hours and 80 hours. And I think that filters out maybe certain people. So I think looking for hunger is very important. And then I think culturally, I would say anyone who interacted with our team on the customer side, they would probably attest to this is our team is pretty low ego, pretty easy to work with.

I think we look for humility in general. They got to be really talented, but at the same time, not be a jerk about it. I think that's pretty unique to find. And I think anyone who's interacted with our team probably knows that. And that's, I think, why they really like us. People are really easy to work with and really friendly. I think you can have both at the same time.

So we try to, I think, filter for humility as well. What have been the biggest surprise challenges that you guys have come across? And not just like the standard stuff, but it could just be like something you had no idea you were going to expect. I'd say being at the forefront as a company is pretty hard. I think one, you have to really want it.

You have to want to build a big company. And two, you have to keep up with it, which requires a lot of effort. I think in order to build a big startup, you really have to just be very committed. and be very hungry. And I think like that's, you know, that definitely, that's a lot of work, you know, that takes a toll on you. I think Adam would say this probably,

you know, but yeah, it just requires a lot of hard work. I don't know. I asked him what he's most excited about. He says he doesn't feel excitement. So he's beyond that point. You're going to get there one day. No emotions. Our industry is incredibly dynamic, right? When there's no good model for a month, everyone starts panicking. Oh my God, it's been one month.

Nothing new has happened. But the answer is just wait another month and something incredible is going to happen. It's been true since we started and that keeps excitement going and that keeps people very encouraged that, okay, there's going to be the next model that's going to unlock these other use cases, which is going to unlock these other types of customers.

And that has brought so much growth to our business. And so far, it just keeps happening for us. Where have you been seeing some of the best models come from? Do they just come out sporadically? Is there any consistent theme between all of them? so right now we we play a bigger role in the ecosystem because we are an infrastructure partner for the model providers but we are also the the api partner for the application layer or studios people who are consuming the models so we got a good sense of supply on demand on both sides and we are in such a compute constraint moment right now that And if you are coming up with a new model, you really have to plan ahead of time.

You have to make sure you have enough compute to run inference. If you are successful, you are likely not going to be able to procure it on your own. So it's usually a good idea to partner up with an inference provider like us to do your launch. So we work very intimate with the model providers. And for customers, they usually use multiple models at the same time, but they really care about model releases because they usually tie their product releases with model releases as well.

So we keep in very close communication with them as well. And then we have to sometimes anticipate how much growth is going to come on the model side to procure our own compute to maybe do some investment on our side to enable the whole space. And someone really has to do that because otherwise all the compute is going to go to coding agents or whoever is doing the bigger investment.

planning ahead and investing on compute a little bit, we can enable both the model providers and the applications being built on it. So that has become our responsibility in the ecosystem these couple months because compute is so hard to come by. I'll add a few more points. I think generative media is very unique in the sense that, in two ways.

One, I think there's just more modalities. I think when people think of gen media, maybe they only think of video. But you would have to think about text-to-image, image editing, video, 3D, text-to-speech, speech-to-text. I don't know if I said 3D, like for gaming use cases, whatever. 3D, 4D, 5D. Exactly, all of these. So there's actually like many modalities within generative media.

So like, and there's like, I don't know, five to 10 companies in each of these sort of sub categories within gen media. So that's like one interesting aspect. So there's just like a lot more happening. There's more fragmentation. And then the other is going back to what I said about like, diminishing returns I think it's still like so early in the space that there's actually a lot more leapfrogging happening between more players because like we're not at like the 98 point whatever percent we're only at like I don't know 50 percent of like you know, where we're ultimately going to go.

So there's actually more people leapfrogging. There's more diversity in like the number of labs. So it's not just like open AI anthropic, open AI anthropic, you know, it's more like there's like eight, you know, players and they're all like leapfrogging each other. like one big reason is you're not running out of data there is like so much video data out there and so much new video data is being produced every day that no one has no one claims to train all of that data right they have to pick the hard problem with training a video model is actually you have to filter out the interesting video data so that you make a good model.

So if you need to put more data into the model, there is abundance. And it's seemingly free. There's enough free video out there that it works very well. But also, the problem space is bigger, right? You are trying to reason around the whole world, physics, everything. So it's not as specific as coding or as specific as certain LLMs are trying to optimize around.

So there's a lot more angles people can take to create a more interesting and appealing model. And it's been happening every other month almost. I think that's where the naming comes in too. There you go. You have to differentiate with your naming. I mean, they've got some funny names. Yeah. Happy Horse, Nana Banana. What do you like? There's Happy Oyster.

It's like a game model. There's Minimax. Sea Dance and Sea Dream. Sea Dance, Sea Dream. I think those are... I think when Nano Banana had like its moment and everyone was talking about Nano Banana for like three days. Even my dad was talking about Nano Banana. I was like, what the hell is going on here? I think the backstory is that it was an anonymous model.

So people do these cloaked releases where they will release a model, they won't actually disclose who it is. It's a code name. Get people excited about it because it ranks highly. And I think somehow they used that nano banana as a placeholder name, code name. And then it just stuck. So it became the original name. If you guys were a model, what would your model name be?

Sorbet. Sorbet. This is Gerken's favorite word. I don't know why. I wanted to rename the company once to Sorbet. Sorbet? He likes Sorbet a lot. Yeah. I also have this, I think about names, like I also want like these exotic colors, like burgundy, turquoise, you know, like I think that would be a good series for model names. That is a good name, I guess.

What about you? I don't know. Sorbet could be a color apparently too. It's like the peach color associated with sorbet. I like... We can do birds. There's so many birds. Birds! Do you have a favorite bird? I'm asking for a name. You can even do owls. There's so many owls. You can literally just do different owls. I like owls.

You can do insects. I don't know. Nature, I think, would be my theme. Well, how did you come up with the name Fall? Let's talk about this. We have a longer name, features and labels. It's a double entrant there. It's the initials of features and labels. It's not fal, it's fal. It's fal.

Yeah, it's features and labels, which if you're a real OG, you would know those two terms. It's like from the machine learning world. It's like very old, like pre-AI.

And so it's the initials for that. But also it's, I don't know, have you had Turkish coffee? Yeah, I have. Okay, so have you been like told your fortune from like the coffee grounds? No. All right, so that's foul. It's like your fortune told by the coffee grounds. You should get it done. We'll do it sometime. Okay, let's do it. So, you know, it's like your future prediction.

Someone looks at like when you finish the coffee, looks at what's remaining. Are you guys trained in that? Can you tell fortunes? You know, everyone is trained in Turkey. Everyone has done it before. Yeah. Should we do it right now? We could try. Yeah, we'll get some coffee. I think they have Turkish coffee here. Oh, my gosh. That's fun. Do you think the open source, closed source debate is still going to be going on in two to four months, six months? How long do you think that's going to keep on going? I think so, because anyone who's falling behind a little bit,

open sourcing their model is an incredible marketing tactic. And the whole world starts talking about you if you open source your model. And there are real advantages.

If you talk to anyone, any of these studios in Hollywood, they want to be able to fine-tune the model. They want to be able to apply different Laura's filters to change the lighting, to be able to use their unreleased characters, their unreleased... styles on the models. And the only way to do that is open source. So there are real technical advantages to it.

Also, it's an incredible marketing tactic. So people are just going to keep doing it. Someone's going to create a frontier model. People who are falling behind is going to open source it. And the pendulum is going to keep swinging. We thought this was a bigger threat to our business in the beginning because we were running mostly open source.

And then we started partnering up with closed source models and running inference for them as well. So it's a win-win situation for us, but open source makes it a more interesting ecosystem. And I think it's good for the industry in general. So we always welcome more open source models and we support as much as we can the community. I think the fact that people want to protect their IP and that's going to continue, right? Not just for media, but also you want to protect your source code, you want to protect your customer lists, whatever, right? All of that, that's always going to be a thing.

So I think, yeah, if you have something local, you don't have to worry about it. So I think it's always going to be there, this debate. When we talk to our customers, if they know the model is run on our GPUs, they trust the whole process so much more. Open or closed, this works the same. But that has been a big differentiation for our business.

And obviously, when it's open, they know for sure that they can even self-host, but they trust us because we can do it better than them. But trust is really important with customers. video models especially because people don't want their unreleased content to leak and it's usually an input to the video model when these creatives work with it.

So we've been really pushing on that with the enterprise customers and it resonates. How good is AI at real professional work? Mercore's AI Productivity Index, or APEX, tracks it with every major frontier model release. Filled with partners like Harvey and Cognition, see where the frontier actually stands at mercore.com.

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Talking macro, what do you think the biggest question is that people aren't asking right now? Not exactly that, but if you listen to any Hollywood podcaster or look at the news about Hollywood, they always have this angle of AI is going to kill Hollywood. And we are really...

In this business, we talk to these people all the time. So far, I would say I had zero impact on anything in Hollywood. It's just like people are projecting to the future a little bit. The business we get from Hollywood has been increasing in the last six months. I think it reached a meaningful percentage of our revenue. But... I would say it had zero impact on the labor.

It barely made any content that's worthwhile in Hollywood. It's gonna happen, there are signs of it, but we've been talking about it for four years and it's always been fear mongering and nothing real. I think that's the thing that people don't realize from a distance. Yeah, most of LA, that's where this is happening. It's really regulatory and what they're doing there with different laws.

Exactly. It really has nothing. And that's been the reason the adoption has been slow because it's not only the quality of the models, the lawyers of the companies need to be okay with it as well. But finally, slowly, we are seeing that everyone is going full force at it. What do you think people should be asking? What's going on out there? I think people are asking everything.

They're asking too much. They're asking too much. Yeah, I don't know. There's a lot of skepticism, I think, about use cases. Again, just speaking more broadly about AI, there's this certain skepticism about, oh, all of this CapEx investment, where is that going to go? And is AI actually useful?

But I think, I'm more on the optimistic side. I don't think, a lot of the people who are making these claims, I don't think they really actually understand what's going on, how AI is actually being used at companies. I think gen media is still very early. If anything, it's just starting. It's just gonna, I think ads, we're starting to see it.

Hollywood, social, whatever, we're starting to see it. I think there's real value. We were just estimating how much faster we're going. Our software engineering team is moving. And I estimated somewhere between 3 to 4x. Pre-AI, we would literally need four times the people to go at the same speed. And we're definitely paying less than that.

So there's clear ROI for us. So yeah, I think if you...

If you really go deep into the ROI for the companies who are using AI, if you really go deep and actually try to measure it, not read it from a bunch of reports or non-technical people, I think you'll see a different picture. so yeah i'm very in favor like very uh long compute as as they say yeah like we talk about it every big company is going to be a compute company just the storefront is going to be different our storefront is unique and interesting like no one else has a storefront similar to us some has coding agents if you go to a neo cloud there is no storefront If you go to Databricks, whatever, it's about data.

Everyone has a different story and different way to talk about it. But behind the scenes, it's who's running the most compute. That brings the revenue. And yeah, we have a unique, interesting storefront and it keeps growing. Yeah. And there's not enough of it.

All the numbers you hear, you know, like 200 billion and, you know, CapEx and whatever, like a lot of that stuff is like not built yet. So, like it's very slow, right? Like building these things takes a lot of time and there's not enough compute right now. So I have two final questions and then I'm going to ask you what your hot take is. I'm letting you know that now so you can get it prepped.

Think about it. This was a hot take. Don't let it catch you. You guys have been crushing it. You have great answers and they're quite opinionated, so it's awesome. But before we get there, what are you most looking forward to in the next 12 months? I'm looking forward to the first timeless AI content. And the way I define this is

you and i we are going to watch this and it's going to be a year later we're going to watch it again and we are still going to like it the same way we like it today so far ai content has been about capabilities it's been about oh look this is possible to do with a video model or that's possible to do with like an image model but we need to reach that point where Things look fresh all the time.

And I'm looking forward to that. I think we are in the next year. There's going to be a widely accepted, maybe a short movie, maybe animation that people are going to look back at it in a couple of years. And they're still going to enjoy it the same way they're enjoying it today. It's pretty good.

Evergreen content. Yeah. It's very important. I try to do that, but... There you go. Like, people say Toy Story is that for computer graphics. Like, that was the first time. It came out in 1996, something like that. Isn't it crazy how long ago that was created? You know, we can just go watch it and it's going to be good. Yeah. I'm going to enjoy it.

Did you like the Odyssey in that way? I haven't seen it yet. You haven't seen it? All you've been doing is talking about Christopher Nolan. You haven't seen it? I'm waiting for the IMAX, the big IMAX stand. I couldn't get a ticket yet. Go to the Spear. Do they show it there? I don't know. It's too big. Not as Nolan intended. For me, I would say like world models.

We haven't spent too much time talking about them. I think... they're super exciting. I was very skeptical even three months ago. So world models are these models you can actually play around and move around. It kind of looks like a game. And you can actually put in actions with your keyboard, and you can navigate the world. But seeing what I've seen recently, it's pretty incredible.

I actually started feeling very bullish about it.

It's a matter of, I think, the quality going up and then the speed getting so much better. And I think there's new architectures now that people are able to actually have more persistent worlds. Before, you used to look this way, see the flower, look away, come back, it's gone. So they're able to persist things now. And you'll be able to actually build a game with a prompt.

But I think that space is like... just going to blow up. So again, the big challenge there is compute. But I actually think that because you need like a GPU running at all times to actually like play that game. But I think the quality of the games itself is going to go a lot better. And I think it's going to be probably yet another product market fit like gaming with AI.

That's not like a thing yet. I actually think there's a big chance that may happen and it might be like this fourth category maybe. Very expensive. Yeah.

Damn. Okay, so we have one more question until the hot take. Okay. I'm just letting you know again. I'm warning you. Okay, so Sorcery is very proud to be sponsored by Brex. I don't know if you know what Brex is. Of course. Brex knows where you are. Proud users.

So they're all about spending smarter, moving faster, performance, a performance corporate card. I like to take this question in the personal bend to things. I mean, you guys have worked for legends, whether it's Brian Armstrong, Jeff Bezos. I mean, you like chips, so you might like Jensen Wong. I don't know. And then you also like Christopher Nolan.

So I'm curious, who are some figures that really inspire you and keep you motivated? Who keeps you like running at it?

Great question. To be your dog. I don't know.

Of the previous generation of founders, I think Jack Dorsey is very underrated. I think he has...

more range than than anyone else and and then like now he's he's like maybe maybe coming back I think watching his his journey with Twitter and then Square I never got to work close to with him but that that's a like inspiring figure when I was younger in Silicon Valley I always like look up to what he was doing yeah

I wouldn't say it keeps me going level, but I really like Ali Ghotzi. I think he's transformed this company many times over time. I think I like to think... He keeps reinventing. He keeps reinventing, and I think that's very important. I think that's a secret to building a long-lasting company. and navigating through like all these changes that are happening.

So yeah, really great leader, I think. The time has come. What is your hottest take right now? Do you have it? No. There's so much pressure.

Well, we can take our time. Yeah, let's take our time. You can cut it. Cut it. And then it's like dark outside. Should we prompt you with some? No,

no. Let's do it. I have a good one. It could be on like IPOs. It could be on like companies disappearing. It could be on fake GPUs that people sell from. Oh, wow. I don't know where they get them. Could be.

Yeah. I had a hot take a year ago, the OpenAI meta merger. Yes. Ooh. Could still happen. It could still happen. They're not doing too great. I think it makes sense. My hot take would be bad for the whole industry. Sure, sure. OK. So I guess not too spicy or anything, but I think it makes a lot of sense. OpenAI was known for this consumer edge, right? right, like that was their whole thing, right? Oh, like OpenAI is winning in consumer, therefore they're going to win because, like, consumer is so much harder to win.

And then Anthropic sort of came with, you know, their enterprise thing. And, you know, and then Google started adding, made their own consumer move. And so I see, like, OpenAI not necessarily, like, winning very strongly in either enterprise or consumer.

And then Meta, on the other hand, I think is in a similar situation where like they need something. And I thought, what if they like combine their forces? That would be really cool. So, like they can really just like really start winning consumer. So, I thought it made sense. But again, I have no information about any of this. So, I'm completely speculating, but I thought it would be a good move.

That is very interesting. Another one. This is a common hot take. I'll do it for both of us.

I have more now. The consensus view was there's going to be more margin in the application layer. And I think it's completely reversed. Margins are close to zero in the application layer. There's so much competition. People need to spend so much money for marketing. You can only create margin if you are in the compute path and you can innovate in that path.

That's the only way you can create margin. which wasn't the case when we started the company four or five years ago everyone thought like the the infra layer is going to end up with price going to the bottom and application is going to have margins looking around application layer doesn't have any margin today as well so wake up we cease it's a good one yeah yeah we talked to tony kim about this that raise and he was like

The chips have much better margins than all these other companies. They're the only ones with margins right now. I have another one. This is a very recent one. I've been kind of toying with this. I think coding is part of genmedia. Really? Yes. Well, it's also part of genmedia. It's its own thing, but at the same time, we're seeing so many developers building richer applications that are not just like a website.

Like they can be, you know, programmable video, right? Like content, like maybe you've seen these websites that like look more like a video. Like there's, I think coding is becoming more and more like a very key part of what the developers on file are using. So I think we're going to have to invest in it because there's just so much demand from our own customers.

Everything is a computer. Everything is a computer. Everything is computer. That's the hot take. That is the hot take. Well, that's a great place to end. Thank you guys so much. I'm very excited for dinner and... And the coffee. And the coffee. I can't wait to know what my fortune is. There you go. Cool. Thank you. Thank you, Molly.