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Cristobal Valenzuela

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2023-02-09
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2023-02-09
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  1. There's a lot of creative coding communities and people from experimenting with COSAS are there's like a lot of conferences and these communities of people, baby castles in New York or Warhack or like Io or you have all this they're just like interesting just art it's just very very very highly creative and niche I think those folks will define a lot we'll see next in tech

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  2. Yeah, I mean, I'm biased because they've been part of this particular scene in New York, the media art scene that I particularly think will heavily influence a lot of these learnings in the stage. To your point, I think every art movement sits in a particular cultural context and historical context and futurism was like in particular moment in time about technology and also fascism was around. And there's a lot of things and you just look at the world in this particular way and you express in this particular way and there's an aesthetic and a line and a system that if you look back, it's like, oh, of course, like that, and cinema was the same. Like movies early on were a way of perceiving the world and expressing them because it was in a very contextual historical moment in time. I think for me, if you apply that same kind of principle now, I would tend to look a lot at the weirdos of tech, right? People who are at the fringes, people who have, we've been always considered like, oh, you're just toying around. This is like an experiment.

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  3. Have an intention and you want to express that intention in a very controllable way, right? These models that are yet not controllable, right? Not exactly as we would like them to be, right? And the reason why because of that is that we're super early. There's a lot that had to be invented to control them and have them be very expressive and have them work in the way that you really want them to work.

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  4. I think it's convenience and it needs to be accessible and useable and understandable by people. I think in the analogy of the paint tubes, we're not yet at the stage where you can just buy a paint tube and use it. We're still like in the stage where transitioning from this sophisticated pigments to some sort of a paint tube, right? But early gans and like Roby Barat, which I was thinking, I think is the artist you mentioned that was behind a lot of the early works on that auction. And 20, I think it was 2017, 2018. It was very hard to just get started with a model, right? It was very sophisticated process. And now you can just do it from your phone, right? You're coming closer to that. We're putting the cap on the painter, right? Almost there. I think we're just a rate of like the rate of progress and the expectation of it will become easier and better. And I would say two things. These models and the systems need to become really expressible and controllable, which is somehow the way I like to think about alignment. It's like, you

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  5. Because that's what really art is about. And these are just tools, right? It's hard to understand them first because you're just new. Like every new piece of technology is. And I think to your point, what are we going to be asking ourselves in like 10, 20 years, 30 years? I think it's the organization that will look back and we'll look at this moment as thinking like, yeah, I mean, it was a natural transition and we needed it. It allowed us to do so many things that we just couldn't thought of before. Great that we had it. And I think we're still early at realizing that.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  6. Relevant and like photography for me was the very similar one, right? And then cinema for sure, and then the digital world, the transition to film, to analyze digital is another one. And every single step of the way, you have artists experimenting with this technology and using them to put a perspective of the world. I think right now where we're seeing right now with AI, I like to think of two AI art waves. There was like the 2015 to 2022 where like the VQ gun and like the early GAN experiments and there was a lot of artists experimenting with it. And then now the diffusion kind of like and transformers kind of like world has enabled a whole new wave of people to expand with it. But both the first wave and now this particular wave, I think we're in the paint tubes moment, right? Where people are taking it and are using it to express something, right? To think of the world and then type that on the world and generate something, right? I think the artist still remains pretty much at the center.

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  7. That would allow was for a whole new generation of artists to look at art and be like, great, I want to take this painting. And there's some mountain that I really like there. I'm going to paint in plain air, which is a thing. You paint in plain air, right? You're painting in air in the wild, and you're able to look at the world and the sky, and you're able to quickly brush the light, right? And just being outside of the studio was just not physical. It was 10, like before that and then gave birth to Impressionism, right? And Impression was like a whole revolution. Like Impressionism was not really well received because it's like, hey, this is not art. These are just brushes of like things. Like they're not, I mean, no, right? And then impressionism really started to pick up. People started to really understand the medium. And then it evolved continuously evolve and evolve, right? And you find similar moments in time where the pain to metaphor becomes...

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  8. Mixturing them and then you store them in this sophisticated bladders and you seal them and it was incredible complex and expensive process. And then someone was like, hey, we should just build a tube and then like have this and carry it around, right? And maybe it's easier. And it was. And it was a very radical innovation, very simple at the time. It's very simple for us now.

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  9. Previous moments in times were technical revolutions enabled people to look at their world in very different ways and then express those views of the world in very different ways to whether it was visible at the time or possible at the time. And an example I go back to often is this idea of in the 1700s, like before even painting was a massive thing that you can do in any condition, situation, or location, painting was the realm of these very sophisticated painters that were painting in studios, right? Painting was the realm of people who can afford and were able to understand and master the techniques of the masters, right? And more importantly from a tools perspective, it was really hard to get pigments, right? It's a very practical thing. But like you couldn't just pigments didn't exist, right? You could just go to a store and get red white yellow and open something and have a canvas. The way you mix pigments was this very sophisticated thing where you had to hire a master that knew like this obscure techniques and you were like

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  10. Yeah, I like to think a lot about what I guess previous moments in history and time as you were referring before that has taught us something about how to both understand art and like look at the tools that we use for art. For me, art is a way of looking at the world and expressing that view of the world in a particular way. And an artist's role, I think, should be to explore and experiment with different mediums that would allow you to express that in the best way you think possible, right? And so people experiment with different techniques and different systems and different like.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  11. No, it was an abstract painting. He generated something that was very abstract, right? And then he painted a canvas and then he used like mixed techniques to just like improve sometimes and like change some colors. It was very new and novel at the time. It was like, wow, that's just, I don't know, interesting and fascinating

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  12. Like everything was just basically people making things and then sharing them online. I think that really drives, I would say, the relationship of, okay, we're into something. Like people are using this. Every day they're coming and they're sharing with their friends and they're thinking about it every day and they're like, I remember an artist and a person who early runway adopter was just falling so in love with the product. He sent me like, he painted a picture and he just sent me the picture to my home. Just once you have the first piece I ever made with AI. And that was like 2018.

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  13. Taking existing images and you're pasting them together, right? I'm just like, no, this is, you're generating them. This model has learned patterns around for sure a data set and you're then generating them on the fly, but these images don't really exist, just don't then exist. And so there's a lot of, I think, mental models that need to be adjusted to really understand it. And we've been adjusting that those mental models. And from a product perspective and from a product microfeed perspective, I think there's the right moment for the market to use technology. And I think that moment has matured. And we've seen it more as more people have been exposed to genetic models and the potential of them. And for us, it's still, there's a lot to build and to develop and to kind of like improve. But a few realizations where like when people were starting using runway as a verb, right, you just run with that. That means something. Then you start seeing people just like creating tutorials and speaking about the product online, right? For a long time never had a marketing team or a content strategy team.

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  14. I really like it, but at the same time, I remember showing it to advertisers, and I went to this save you meeting at this top agency in New York. And it was like, here, guys, here's the thing you will be using to work, right? And they were like, Chris, this is a toy. Like, great. I mean, fascinating technology, whatever. But like, we have work to do. Come on, like, move on, right? And I think the main mistake for me was like you're looking at this singular moment in time of that technology. You should really be looking at the rate of progress, right? Thing that I can type a word and send an image wasn't feasible a year ago. Just it didn't exist, right? Now we have this. So just compound and try to imagine where we'll be in like four or five, six years, right? But the thing is, it's really hard because you can't imagine it. And I remember people at the time, like when I show some of those demos, specifically for genetic models is people were asking me like, hey, Chris, how you're collaging these images, right?

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  15. Exactly. I was actually, I remember we had a version of very early gun system that did text to image translation. We actually still have the demo online. And the output was like this 120 pixels, like exactly you're saying images that were just blurry. It looked like abstract paintings, right? I mean, you typed, I don't know, a blue ocean and we get like a blue form with something. So if you close your eyes like 10 meters away, maybe.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  16. Yeah, I like to think of product market feed as a spectrum of you have either really strong product market feed or weak product market fit. And as you build new products and new research, you're always seeking to be very on the strong side of things, of course. I think for us, there are a few factors that we've kind of like realized that what we were building was beyond just a niche. Because I think we started with a very niche audience and everyone dismissed a little bit of what we were doing as toys. She's just sort of like art students building like some toys. And I think you shouldn't dismiss toys. Toys are very interesting to learn a lot. And I've learned that over time. But by the time when you're building those, of course, it's just like you're focusing on the output and they're glitchy and they're like abstract and it's just weird and can make sense of it.

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  17. Yeah, and you always integrate, there's ways of combining existing tools, right? So for produce company, for example, you can get 80% there. And then if your professional filmmaker working on Nuke or Flame, you can do the 20% in that stack, right? But you still save yourself days of work, right? So it's still better than anything you were using before, right? So it really depends a lot. And I think over time, more models will get to higher numbers and we'll have higher outputs. There's a lot yet to be developed and I think we're still scratching the surface of what's coming.

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  18. Have humans coming up with great ideas and they want to express those ideas. How do you build systems that will help them get there really quick? And sometimes what you need is to get 80% there, 90% there. And in research going from 80% to 100% is really hard. I think that you'll be seeing that in autonomous vehicles where like it's always like two years ahead and always 80% but like that 20-10% is just really hard. But it's really hard in that domain because if there's a one percent failure, someone might die, right? In creative domains, it's not the case. Even if you're 80% there, the 20%, like sure, I mean, you could worry about it, I can improve it, I can like find ways of work with that, but you've made incredible progress, right? From that perspective.

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  19. Exactly. And now he's telling me, like, now I can do the three, right? You can just see the three and pick the one that I like the most, right? I'm not constrained by the time and the cost. I'm constrained by whatever idea I think works the best.

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  20. He was like, we should just runway that, right? Just run away the thing that you want to do. And before runwaying something, they had to marry themselves or like just log one specific idea, right? Because if we try to do two other things, it's going to take us too much time and we just don't kind of afford that. Like every creative is always in a deadline.

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  21. Yeah, I think the realization for us is like what the goal is. If you're trying to automate the entire process of like the whole end-to-end system of making a movie, yeah, like we're not there, right? We're very far from that. There's a lot of things to be that have to be developed, that have to be research and kind of understood and tested. But going back to the green screen, if you look into the processes and the nuances of how video is created and you look at the inefficiencies of how people are doing it right now and you offer these people even like 10% or 20% or like whatever percentage of like speed and cost reduction is just so radically better, right? And it's radically better for two reasons. Of course, it has helped reduce the cost of like you can do things faster, so it's just easier. At the same time, you can explore creatively more, right? And this happens a lot. I was speaking with this director who is working on a film and was

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  22. Devoted to like storytelling and creative exploration and ideation. And that's a widespread spectrum of people who are you can consider work in the storytelling business, right? On the one hand, you have professional, really professional people that have been doing this for years, right? Folks working in post-production agencies, BFX agencies, broadcasting companies that are creating video as their main business. Like this is basically what you do, right? It's entertainment, it's sometimes sports.

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  23. And that helps the product itself because people were using that model in that particular way. And that really decision was, I would say, like a combination of different things. It was some research knowledge and understanding of what was feasible. Can you build that sanitation model? What data sets? And what do you need to do it? Who would be using it for? How are we going to test if it works? And the first version of green screen was working at like four frames per second, right? It was like incredibly slow. It was like not as good as the one we have now, which is incredible, but it didn't matter. It was significantly better than anything else that was at the time, right? And people were like scrambling to use it just because it proved to be a percentage amount better than anything out there, right? And people were hacking things and were trying to like incorporate it. It's like, great. That means that you hit something and then we start iterating a lot. And so we keep iterating a lot on it, but the fundamental piece of how we build product is still pretty much similar to that.

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  24. Central object or two, let's say Just a few minutes of chatting with a professional filmmaker, you'll probably discover that that's rarely the case because the shots, the scenes, and the compositions and the camera angles really depend. If you have a shot of 10 people, you might want to rotoscope the one on the left. Depending on your idea, right? It's a creative tool, right? So it should be general. And so what we did was instead of like relying on fully automatic systems, we embedded a human in the loop kind of like component in it, right? And we thought it would be great if before you start doing that, you can guide the model. Like you can tell what kind of selections or areas of the video, then you can zoom in and define you want, right? And that also really help us train the model because we train a model on, we build a probabilistic model of like human simulated, like human clicks on a mask and the model will strain on that knowledge, right? From the very bare bones.

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  25. Click solution for grid screen, right? If you ask people what they wanted, they wanted a better alternative that was faster to create masks from their current stack, right? And they're probably using something like Rotobrush 2, right? So whoa, what I really like will be like a better brush to just brush over my frames, right? And I think customers and people are really good at telling you what their problems are. They're really hard at verbalizing solutions. And so you aggregate that amount of data. You see what's possible for research. You see, you chat more with people and you start prototyping a lot. And then we came to the realization that we could build and we have the expertise to build a system that will help you automate that, right? And most literature around video objects segmentation, which is that in filmmaking is basically known as rotoscoping or green screen, right, was around like fully automated systems, right? You fit in a video and the video automatically understands subjects and then rotoscopes or segments, right? One specific

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  26. Yeah, I think that green screen is a great example of how to build and how to deploy useful AI products at scale. When we were building that model directory and we're just like early stages of understanding limitations and capacities and directions, we quickly realized a type of user that was coming for segmentation models. And at the time, we didn't have a green screen tool. It was just like an image segmentation model. Those folks were coming from a specific domain and they were actually applying a model that was image based into a video task. And so they were like exporting themselves with FFMP, creating this sequences of images to then render them back in video. And there was like, why are you doing that? Why are you, what's going on? And the thing is like image models don't really work really well with like video. And so we started interviewing them and we got to a point where I was like, wait, it seems like this could be something where we could improve and we're bringing our research team. So we started like iterating more on that. But no one ever asked for.

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  27. Yeah, we're a small team. We've been consistently and historically small team. And until two weeks ago, we didn't have a And I think that drives a lot of fundamentals of truly understanding the things that need to be explored. We've iterated a lot on building squads or building teams or having more autonomy. I think it really depends. I think you tend to have a different company every like four or five, six months if you've successfully built stuff. It's a continuous process. And the thing that worked when we were like five people sitting at a table, it's not going to really work when you're like 20 and you have new technologies and system things available. And so I don't think there's one answer in particular. I think we're pretty much with how we think about product, we like Twitter a lot. Right now, we're working a lot with squats. And so we've come to a kind of like a place in time where the organization can have a bit more of like domain expertise and like instead of having like very generalized engineers, we tend to more specialize a little bit more. So you can still jump and be and collaborate, but you tend to have a bit of a focus of area. And we're iterating with that and seeing how that works.

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  28. Specialize on vector graphics, and you have a tool that specialized on motion graphics, which is different from video editing, which is different from compositing, which you have all this very sophisticated software stacks. And I think that the very interesting aspect of what it would like to see and what we'll probably see more with multimodal systems is that you're able to merge all of those. And what I really find interesting about that is that's how we humans think, right? You don't go to a movie and watch the video first and then you stop and you hear the audio and you stop and you read the subtitles. It's a combination of all of those things, right? And our art director thinks in all of those things at a certain time as well, right? So having systems that can translate ideas and text descriptions into videos and then having a conversation with what's the input of those videos into like audio and then I think that's the kind of like creativity and set of tools that I'm really excited to discover and build.

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  29. Yeah, for sure. I think, I mean, everything we've seen on the explosion of deep fishing has been just so exciting to see. I think I'm particularly excited about multimodalities and like combining different input or outputs in ways that are yet to be explored. I think we're moving away from very siloed domains, so like someone who could be an NLP researcher and computer vision researcher, right? I think we're starting to see them gradually converge and mix. And so building a diverse team that can understand those multi-domains is really interesting. And I'm excited to see how that's going to play out in video and in images. And I like to think also of how you translate again and go back to product, a bit of product obsess, but how you translate that into products that are useful, right? I think a common natural evolution of just the creative stack or the creative software solutions out there, they tend to be very specific to domains of content. So you have a tool that's specialized on like image editing. And then you have a tool.

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  30. Product perspective is always just a good, and releasing and working with real people as fast as you can. I think that's just key. I think a lot of researchers just assume how people work and how creatives work and say, oh, we'll just do that. But the realities might be very different. And so having tools being used by people is, I think, the best way of learning how to develop products.

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  31. Yeah, I think it's just phenomenal to see that progression of more researchers that being perhaps in academia for too long progressing or moving into the operational world, like building products, I think it's a great realization of you working or something for six, eight months a year, but you see something else in the world of someone using something very similar to what you just built and impacting the world in very meaningful ways. I think that's great to see people transitioning more. I think we need more of that. I still think that there's a lot to be learned around the difference between a model and a product. And again, there's a lot of back and forth of how you embed models into usable products. And so coming up with training a model or improving some sort of quality of benchmark in some particular way, even if you have a very cool demo, it's a long way to go to like actually build a business and a reliable system that will continuously iterate over that. And so I think having that more.

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  32. You figure something out, it's a lot of learning and a lot of processes and like frameworks of how you make decisions, how you understand what's really possible versus what's visible. And there's a lot of just nuances of how to do that.

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  33. Went back to the world analogy. And so in one single table, you can have a PhD scientist that's been contributing to fundamental research on the space, working really closely with someone who's working on video for 20 years, right? Who's been editing and post-producing films or content? And the things they learn from each other is just so unique. It's so radically different. And it helps inform how we build products, right? And so we don't treat research as a standalone kind of like department that comes every six months, but here's a paper and just do something with it. We see it as an apply thing. It's like it's at the core of who we are and how we drive the product forward. And it helps just drive the product in a different way. I think that the only thing I've learned is that building that muscle takes time, right? It's not that something you can just like, I'm going to hire a bunch of creatives and a bunch of researchers and just put them in a room and like.

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  34. That there's a breakthrough somewhere else, you need to react really fast, right? And you need to be able to incorporate that. And if you're just relying on third parties or some other solutions, then it might be very hard, right? And so for us, it was a survival realization that if we really want to make and move the standard of creative tools in the ways and vision that we had, we had to own our stack. And so we started building this research team, right? And this research team has very deep understandings and knowledges and perspectives on how to build models and we've done this and we've collaborated and contributed to breakthrough moments in like the creative AI space. But most importantly, we have these researchers working really closely with creatives. Half of our team have arts backgrounds, right? Which is very unique. And we put a lot of emphasis on finding those very unique, they're very hard to find folks that can speak both worlds.

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  35. Yeah, I guess going back to that set of learnings early on, I think one thing that we realized is models on their own are not products. A model is a research component. And taking a model and productionizing that model, it's a different problem that actually building one single model, right? Or one single task or problem or improving a metric in a specific kind of direction. There's a lot of nuances of how that model get deployed. It will get built, how users will interact with it. The unique economics of running this kind of systems as well is very important, right? So they have all these complexities. And as we started leveraging perhaps open source solutions at a time or trying to build our own, we quickly realized that having control is like key. Like you need to be sure that you can understand your stack and you can understand and know how to fix your stack, right? Because if things are changing really fast and you think about going in one particular direction, but it then happens to be the case.

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  36. You need to build to really aim to solve the things that you want to solve. But yeah, it's a fast growing space. So there are a lot of things that are changing.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  37. Move you away from a more consistent long term plan. I think for us, was that reason of those kind of things? And then the third one I would say is the third component of how we think about that stack is really understanding our users, right? Who are we building for? And so early on, it was more technical product. So you had to know CUDA and Docker containers and managing your Docker Nvidia GPU cards. And like you had all these sophistication that I think it's in some part natural when things are so early because just the only way of making sense and also you have to build more things. But for us, we've always been thinking about artists and filmmakers and creatives hard and really those things don't really matter that much. What matters is like your idea and how you execute that idea. And so from the stack perspective, we've iterate a lot on the kind of like back-end side of things. But from a user perspective, we iterate even more on how to present those things and what abstractions are metaphor.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  38. Really fast, right? And so if you're thinking about building a long term business and a long term product, which we are, you always kept the desire of like, okay, what are long-term birds versus short-term beds? And I think a lot of building and software engineering and developing products is just saying no to a lot of things. Customers might want to ask you to build something and could sound good. It could bring you actually revenue and some growth, but it actually might

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  39. No, that's a great question. Something actually we think a lot about when you think about product sequencing and roadmap, which is just, I would say, one of the most important aspects of product building. It's like how do you sequence everything you have to do? And specifically an infrastructure, like what makes the most sense and how do you spend time every single day means a lot in a startup? I think for us a few realizations, to be honest. One is that the moment something gets released, like let's say transformers or a particular piece of technology that you think would be interesting could be worth experimenting with, I think it takes a collective set of months, like 12, 24 months sometimes, to understand the implications of that, right? And we've seen this with like language models. GPT-3 has been around for some time, but it took like a collective 24 months of just thinkering and experimenting to truly understand like, okay, where can you go and what can you build and what's possible? So I think that we embedded that and we always keep that in mind. The second thing I would say is things are changing.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  40. Interesting layers of applications that, to be honest, for us, was just a way of learning and learning a lot about the space and a lot about what was visible, what was possible, who was kind of like interesting in building more of this. And from there on, we kind of continuously iterating. We've learned a lot from that model registry or like model hub. We still use a lot of those in our infrastructure kind of like parts on the app, but also we gathered a lot of insights on how to build this kind of systems in scalable ways.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  41. Target an aim that's creatives, right? And so if you're a designer, a filmmaker, an art director, a copywriter, you might want to tap into some of these things. So you want to experiment with them, but they're just very hard to get started with. So we build at the time was a model directory. It's an app store of models, right? We had around at some point like 400 different models. It was one of the first, like, I would say model hats. I think there are a few out there now that you can tap into and use them. This was very, very early. And we built a whole system around it. We built an SDK. We build systems for deploying those models into real-time applications. So we built a RESTful API system where you can use a model, train a model, and then deploy that model. And so people were building web apps and interactive GPT-1. Someone was training a model and like fine-tuning a GPT-2 model on a specific corpus of data and then creating an API to build a text generation app. And we had all this like very.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  42. Actually, it means right? What do you mean by how do you experiment with this sophisticated algorithms that were very early, that had all this obscure CUDA dependencies and C++ libraries that were just very research centric because they were basically research, like core research? But it was just fascinating by the outputs of the research elements. And at the same time, everything I would say that we consider like a baseline today wasn't really there yet at the time. Things have progressed radically. The space has been growing exponentially, but systems and like software and abstractions to tap into that potential wasn't really there. So our first intuition and our first kind of like product experimentation was let's build like thin layer, right? Basically, let's take this research set of models and the amount of models that are coming up. It's just like so interesting. Let's add a thin layer of accessibility to those models.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  43. Yeah, totally. A lot has happened, I would say, over the last decade or so. When I started building runway, it was perhaps like the Alex net image net kind of like moment. There was image classification was the big thing and the breakthrough. And a lot of interesting applications were coming out of that time. It was still very early. TensorFlow was just perhaps a year old. Pythorge might not even have been released at the time. I think PyTorch was 2016. Guns were just like very early, early, early, like inception time. But what I kept seeing was there's this neural aesthetic, this neural capabilities that are impacting not just the visual world or like perhaps industries and markets that are using a lot of this technologies and hardware. But the outputs are very interesting from a visual perspective, right? It seems to be a correlation and approximation towards the visual domain. And so I started just experimenting with what...

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  44. Systems that help you do that. So we have tools like GreenScreen, for example, which a lot of And we also have tools that help you ideate and design and craft. And we have a set of suites for generative image editing, for generative video editing. So it's the best way perhaps to think about it is it's a creative collection of tools and systems that just help you augment your creativity in any way you want.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  45. Yeah, totally. Also, happy to set a bit of context of the company itself. So I think that better helps contextualize the product itself. The best way of describing runaway, I would say, is to think about it as I'd apply a research company. We do core fundamental research on neural networks for both content creation and video automation and journey models. We then transfer those models into an infrastructure, a system to deploy those algorithms and systems in safe ways and in ways that will make us build products that are useful for people, right? And those products can take different shapes and forms. We have around 35 different, what we call AI power tools or magic tools. And those tools help serve a wide spectrum of creative tasks from traditional editing, editing videos or just audio or images has been a very expensive, time-consuming and sophisticated process. And so we build

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  46. Both my career, but also in runway as a whole, that we look at things, we try to look at things with very fresh eyes and pretty much with our first principles kind of like mentalities to it is like, okay, why are we doing this? But really why? And they go to the basic aspects of it. And then innovate, I think that's a lot of innovation comes basically from that way, looking at the world.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  47. Yeah, I agree. And for me, as always, Vianna's a bit new, like I've been in New York like six years and I run away now. It's going to turn four years. And I was also new to just the tech world and SF, like I've never been to SF like three years ago, right? So I'm relatively new to the space. But I think how we approach it was with that semi-level of curiosity of like, I'm going to figure out, I'm going to learn about it. And I think that there's two sides of that. The one is that it takes time for you to adapt to that because it's just new. Like everything else, you just, you need to understand it. You need to understand the patterns of that subject, that domain, that area, right? But at the same time, looking at it with fresh eyes, with things that perhaps the ecosystem itself has considered like norms that I don't consider them norms. I've just like, when I'm not trying new things, right? And I think that opens the door, again, to do new things and experiment with new things. And that has, I think, been a consistent path.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  48. And I think that's how I like to leave off the world. It's just the same world. You can apply different points of views and perspective on that. We build arbitrarily definitions of like, this is hard. And that's design and that's econ and that's business. But I think true creativity and curiosity comes from just like looking at it as a whole and taking things that weren't supposed to be part of one thing and then adapting them. And sometimes it's hard because you need to learn things that you've never done before and it's uncomfortable. And it's perhaps you feel like an imposter, like you shouldn't be doing this. I've learned not to care, to be honest. I just like just drive out curiosity. Like you'll figure something out and I really like that.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  49. Media arts probably is the best way of describing it. I think for me, Metearts is a way of expressing a worldview using technology, like any other form of art, like you just kind of like experimenting and reflecting and expressing a worldview using a piece of like a tool. And in this case, it happens to be that we like to express it via computers and software and writing softwares that form of art and making hardware is also a form of art. One thing I've remember early on in my career when I was doubling between like art and business, I met this very famous Chilean artist, the sea's a photographer, and he was just like mentoring me and like we were chatting and he was speaking to me. He was like, Chris, this is the same world. We all live in the same world, right? It's the same, right? We just build like silos and like arbitrary definitions of what is what. I think he just said it. I really like stuck.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source

  50. Experimenting with early computer vision models in 2016, 15, and then went into Rabbit Hole, apply and got a scholarship at NYU, and then spent like two years in art school, ITP, that's the name of the program. It's a very unique program for me, though it's very fundamental kind of like piece in my career of understanding how to bridge business design, art, and technology in a cohesive way.

    2023-02-09 · No Priors · What does AI-powered content creation look like? with Runway ML’s Cristobal Valenzuela · IDENTIFIED FROM THE TRANSCRIPT · source