# Runway’s founders treated early AI as a creative medium

Markdown copy of https://realalpha.app/s/runways-founders-treated-early-ai-as-a-creative-medium/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Cristóbal Valenzuela](https://realalpha.app/builders/cristobal-valenzuela/) · Cristóbal Valenzuela is co-founder and CEO of Runway. · Co-founded Runway, an applied AI research company whose creative suite has more than 30 AI-powered tools.
- Host: [Alex Konrad](https://realalpha.app/people/alex-konrad/) · Founder & editor, Upstarts Media · Ran Forbes' Midas List for ten years and co-created its Cloud 100 list; founded Upstarts in 2025.
- Show: Upstarts
- Episode: [Runway’s Cris Valenzuela: Building The Hollywood-Friendly Video AI That OpenAI Couldn’t](https://realalpha.app/v/hBT2oKYGcKU/), May 1, 2026
- Moment: 6:11 to 12:59 of the episode (7 min), playing on https://realalpha.app/s/runways-founders-treated-early-ai-as-a-creative-medium/; the episode from there: https://realalpha.app/v/hBT2oKYGcKU/?t=371

## Quote

> “it's really important to have an open mind and be kind of **less obsessed with what you know** and more of what you can discover.”
> — [Cristóbal Valenzuela](https://realalpha.app/builders/cristobal-valenzuela/) at [9:59](https://realalpha.app/v/hBT2oKYGcKU/?t=599) · Upstarts

## Takeaways

1. Runway’s three founders met at NYU’s art-and-engineering program.
2. Early AI could identify cats and dogs, but creative uses were still open.
3. Exploration helped reveal uses the founders had not anticipated.

## About this segment

Cristóbal Valenzuela traces Runway to an NYU program blending art and engineering, where early AI experiments revealed new creative possibilities. The founders explored what the technology could do before settling on a product.

From “Runway’s Cris Valenzuela: Building The Hollywood-Friendly Video AI That OpenAI Couldn’t”, May 1, 2026. [Watch the full episode](https://realalpha.app/v/hBT2oKYGcKU/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[6:20](https://realalpha.app/v/hBT2oKYGcKU/?t=380) like art projects and technology. Can you talk a little bit about sort of what you were doing there and how deliberate versus accidental, you know, developing runway was there? Yeah, that's a good question. So, yeah, we've the three founders met at ITP. So ITP, the best way to think about it is it's art school for engineers or engineering school for artists, which is another way of saying that it's a way to explore like the reasonably possible, the things that are adjacently like or new in terms of technology and like possibilities from a technical standpoint.

[6:54](https://realalpha.app/v/hBT2oKYGcKU/?t=414) At the time when we started kind of working on first ABS of runway, the deep learning revolution that we're in was kind of beginning to take shape and form. It was 2015, 2016, 2017. And a lot of what we're trying to do at the time was really understand what was possible. Because we need to remember that in 2018, the state of the art, and I think we suffer from collective amnesia because we forget this.

[7:19](https://realalpha.app/v/hBT2oKYGcKU/?t=439) The state-of-the-art AI models, the thing that people were freaking out about was a model that could distinguish a cat from a dog. That was revolutionary at the time. To be honest, it was, because you never reliably could do it with any other process or technique. But suddenly now you can go from identifying objects to identifying different kinds of breeds of dogs, which also at the time was fascinating.

[7:43](https://realalpha.app/v/hBT2oKYGcKU/?t=463) And so the applications of AI and deep learning back then were very boring, if that's a good way of saying it. People were thinking about classification or financial systems or security or organizing data. And for a minute, I thought there was like maybe something else that was more interesting coming from a mix of both engineering and kind of art background where you can see this technology basically as a tool to express or to create or to imagine things.

[8:14](https://realalpha.app/v/hBT2oKYGcKU/?t=494) And so really what we tried to do really early on, once we start training early models, both on kind of computer vision and then on like generative side, was to just build things, prototypes. A couple of things we built back then was we built this film kind of recommendation system or think about it more as a search engine that you can search for visually for shots. So I remember I went to like New York, to a street in New York.

[8:39](https://realalpha.app/v/hBT2oKYGcKU/?t=519) I recorded a bunch of people walking and then I put it to our system. and then the system returned me like seven films in which like the same type of shot was like in a scene. And so I can remember Children of Man, it was like the same shot, but like way nicer done. And so you got all those like kind of opportunities of, oh, you couldn't do that before. Now you have the system that can do it. What does it mean?

[9:02](https://realalpha.app/v/hBT2oKYGcKU/?t=542) I don't know. We're just building, experimenting and one experimentation led to the other, led to the other, led to the other. And then eventually we're like, oh, we should take this more seriously and start building a product around it and a company around it. Did you have a good sense of who your ideal customer or power user would be then? And has it played out the way you maybe initially anticipated?

[9:20](https://realalpha.app/v/hBT2oKYGcKU/?t=560) No, I think to be honest, when we started, it was too early. I think we were building something that wasn't a comparison, there wasn't a reference point. So it was hard to wrap your hand around as to why this will ever exist. And again, this is why we sometimes have collective short-term inertia because now there are a lot of things that are obvious. But a couple of years ago, a lot of things weren't these obvious.

[9:44](https://realalpha.app/v/hBT2oKYGcKU/?t=584) And so the use cases of other models, mostly because in a way the models weren't working as well. So you were like, why would I ever use this? And I think a lot of what I had to do was prove that you can get better models by improving both data and algorithms and training and everything else. Once you cross that threshold, you start kind of realizing more of the use cases more early on. But I would say that early on, if you're doing kind of research and discovering new things, it's really important to have an open mind and be kind of less obsessed with what you know and more of what you can discover.

[10:16](https://realalpha.app/v/hBT2oKYGcKU/?t=616) And that has allowed us to understand how the models can be used for things that I could never imagine for, which is exciting. And from a business perspective, what I like thinking about the most is instead of like a company winning a market or like being good in solving specific like need. It's more about creating a net new market. You created something that didn't have a name and you help people do things they never thought they could.

[10:39](https://realalpha.app/v/hBT2oKYGcKU/?t=639) And that becomes the new standard. That's how I like to think about what we're doing. What was your sense of how artists and sort of the film industry would react to a tool like this? Was this something that you felt they should be supporting and excited about or feel challenged by? I know you've said in the past that you think maybe the next great filmmaker doesn't come from L.A. and Hollywood anyway.

[10:59](https://realalpha.app/v/hBT2oKYGcKU/?t=659) So what was kind of your feeling about that relationship? So, you know, back then I don't think there was a sentiment or a point of view in terms of how you should feel about it. I think it was, at the most, it was just very exciting. Like you were able to do things you couldn't do before. I remember we trained this model that you could write. This is like before Transformers, anything else. But it was a website.

[11:24](https://realalpha.app/v/hBT2oKYGcKU/?t=684) It was a web editor. and i trained it on like a couple of authors that i like so it was bolano and like jane austen and a few other folks and you could write something and you could get a completion of a sentence kind of as if that person was being your editor or was like helping you and it was kind of cool it was it was using like lstms and it worked in the browser in real time so it's like a cursor for coding from like 10 years ago and when i share with people and with writers i think people just got excited it's like oh this is this is very cool and i could think about all the things i could use it for and of course it wasn't as good as the stuff we have right now but i think the excitement when you show people projects like that and ideas like that is it begins to open their minds into what else can they do and i think that was at least my perspective on like the the whole

[12:11](https://realalpha.app/v/hBT2oKYGcKU/?t=731) field was like this is a whole new medium it's a whole new way of thinking about our relationship with technology and if we really need to think about them from a creative standpoint then what we need to really think about this is how do we get creative minds to be part of the process? Because one thing that becomes clear, maybe. Kind of touching back on what we just spoke, is that if you design the systems in isolated ways with one particular point of view of the world, then you're not going to get the kind of things that you can do in runway and kind of models and stuff, because you need to have more of a creative, artistic point of view and actually create tools for them.

[12:45](https://realalpha.app/v/hBT2oKYGcKU/?t=765) And so I think we've always thought about it that way. And the excitement that we had back then, I think we still have it today.