00:07:46 · Anastasis Germanidis
[00:07:46] S2: Yeah. So when we started, generative AI wasn't a term. Like, we were trying to figure out what the term... The right term was to describe what we're doing. We were coming up with, you know, synthetic media and, like, trying to figure out how to describe this thing. So we started out... Really we started collaborating with each other around 2016 when we all were in the same kind of art school. And we're initially just making... You know, at that point there were some early very interesting demos of applying deep learning in creative ways. But it was very, very difficult to use those models for if you were an artist and a filmmaker. And so the initial goal was let's let's make those models very easy to use in an interface that feels like a creative tool, but it's actually powered by those new kind of early image and video generation models. We quickly realized that in order to advance those models, in order to give them the control that's needed, we needed to build a research team in house and build a research organization but yeah it took quite a long time before you know we got anywhere close to results that were kind of usable in a production setting It took maybe from like, you know, twenty twenty eighteen when we started to 2022 or 2023. So it was it was kind of a long process of really having conviction that video generation, we we get there. And a lot of it was just driven by just seeing the improvement of those models every year. So you had like... You started from, you know, the early... What was called the generative adversarial networks was one of the earliest kind of neural network architecture for image and video generation. And you could see... You started from, like, 32 by 32 pixel images. And every year, you have, like, resolution, you know, double fidelity and quality improve predictably. And so you could see that if you extrapolate from that, we'd get to the point where you can make really compelling, like, realistic outputs, but it took it took it took a while to get there.
00:09:54 · Adam Miller, Anastasis Germanidis
[00:09:54] S0: Mhmm. And fast forward from when you started in 2018 to where we are now, eight years later, Runway isn't just being used by individual creators. You've got film studios, ad agencies, indie studios using these tools. How would you describe what people are actually using Runway for nowadays? [00:10:12] S2: Yeah. Runway has been useful for all the things that you mentioned and many more. So we think of the tool as being a very general purpose tool. Right? You can create images and videos for any kind of purpose. A big set of use cases in... Are in media entertainment. So we have all the major film studios using Runway as part of basically every part of the workflow. So you have, like, from preproduction to production to postproduction. So you might use Runway for concepting and storyboarding for essentially kind of blocking out, like, what the... Your short or your ad looks like to... Increasingly, we're seeing runway being used for the final frame as well. So the thing that you generate in runway actually being used for, you know, the the thing that you distribute and share it with the world. And then a lot of use cases in post production. So in, like, VFX work and editing and background removal and, like, all those things that are very time consuming but very... Part of every... Basically, every VFX workflow. So, yeah, Runway is being used in in film. It's being used in, in marketing and and advertising. It's being used in, in games, in architecture. A big part of our thesis is that video models are very general, and they can be used in all those industries.
00:11:35 · Sachin, Anastasis Germanidis
[00:11:35] S1: There's a lot of discourse about the way Hollywood is reacting to how quickly these models are getting better. And as people on both sides, you know, I've I've read a lot about how actually way more people in Hollywood are using these things than they than they let out. How do you think about the creators that will say that these models getting better is like an existential threat to their jobs and their livelihoods and the kind of, you know, craftsmanship in the work that they create? [00:12:01] S2: Yeah. So I think the the easiest way to answer that question is just by pointing examples in history where it seemed like this new technology would completely eliminate the role of the artist and the creative and it turned out that it kind of multiplied and it and there were as a result of those technologies there were more and more artists and creatives than ever before so you can see the same thing with you know like Photoshop and like the with and even even before that with you know the invention photography and how that you know, essentially created modern art as we know it. So I think there's always this, like, like, you know, the history of art and the history of technology have always been very intertwined and every change in technology does does change the, you know, the roles and the kind of job descriptions, ultimately it expands and, like, grows the the number of people that can now be part of, you know, can can be artists, can be creatives.
00:12:01 · Anastasis Germanidis, Adam Miller
[00:12:01] S2: Yeah. So I think the the easiest way to answer that question is just by pointing examples in history where it seemed like this new technology would completely eliminate the role of the artist and the creative and it turned out that it kind of multiplied and it and there were as a result of those technologies there were more and more artists and creatives than ever before so you can see the same thing with you know like Photoshop and like the with and even even before that with you know the invention photography and how that you know, essentially created modern art as we know it. So I think there's always this, like, like, you know, the history of art and the history of technology have always been very intertwined and every change in technology does does change the, you know, the roles and the kind of job descriptions, ultimately it expands and, like, grows the the number of people that can now be part of, you know, can can be artists, can be creatives. [00:13:00] S0: And for the future vision, do you see a world in maybe a few years' time, five years' time, where people will be making major movies just with products like Runway, doing all the scripting in there and having all the generation of many different frames in there, doing the post in there and we'll be able to go to the cinema and watch a movie made on Runway.
00:13:00 · Adam Miller, Anastasis Germanidis
[00:13:00] S0: And for the future vision, do you see a world in maybe a few years' time, five years' time, where people will be making major movies just with products like Runway, doing all the scripting in there and having all the generation of many different frames in there, doing the post in there and we'll be able to go to the cinema and watch a movie made on Runway. [00:13:19] S2: I hope so. Think that's definitely like I don't see any reason why it won't happen like if you look at the improvement of the models and the ability to generate kind of longer and longer sequences the ability to keep consistency of, you know, character settings, environments, I think the... It's it's very likely that, you know, you'd be able to... And you... Already, we have a large community of of filmmakers that are that are using Runway to make to make films, less so feature length films at this point, but there is no fundamental reason where the models are not gonna improve and get there. [00:13:55] S0: And under that world, if we are making fully AI generated films, those films aren't going to need, you know, the hundreds, sometimes thousands of people which are needed to make films now, so do you think what will offset that is that we'll just be making far more films into the future so that there'll be so many more creators, more films being made, and on net, we just have more artists.
00:13:55 · Adam Miller, Anastasis Germanidis, Sachin
[00:13:55] S0: And under that world, if we are making fully AI generated films, those films aren't going to need, you know, the hundreds, sometimes thousands of people which are needed to make films now, so do you think what will offset that is that we'll just be making far more films into the future so that there'll be so many more creators, more films being made, and on net, we just have more artists. [00:14:14] S2: There are roughly, like, thousands of films being released every year and millions of books being published. Like, why does that gap exist? Because it's so hard and so, you know, resource intensive to make a film. So it's exactly what you said that the the number of... We're we're more bottlenecked by supply than demand. There is, I think, a lot more latent demand to watch amazing stories that are not being told. And so I think that's what we're gonna see, that we're gonna see way more way more films in the in the world and then way more new kinds of experiences that are powered by those models. [00:14:47] S1: At the kind of deepest level, I'm sure there's been many times over the last few years where it felt impossible or it felt like you may not get there. What is the thing that has kept you going? Like, what is the world you wanna see with Runway that has kept you going? Because it seems like you're quite a philosophical person. So, know, what what is that kind of vision?