How Colab Hackers Sparked the Text-to-Image Boom (Full Transcript)

[00:00:00] Speaker 1: And then while we're doing this, we noticed this really interesting community of people who were building models, what they were doing, what they were doing, I think they were trying to replicate, it's where the word comes from actually, we want to make research reproducible, they were trying to replicate DALI and to do that, they were taking CLIP, which was a model that's opening at open sourced, and they would smushing it together with a GAN to try and create images, which looked like a piece of text and what was really interesting about this community is they were doing it all in Colabs, which was very different to the research community, they were much more like open-source hackers. So they were just tinkering around Colabs, sharing them on Twitter, sharing them on Reddit, sharing them on Discord, and then riffing off each other's ideas to like, oh, what if I swap out BigGAN with VQGAN, or what if I tweak these parameters to see if we can get a better output, and people were just forking all these things like crazy. And that's where this really interesting initial text-to-image community came from, and we saw this and we were just like, this is really interesting. The time is really low quality, the images took like 15 minutes to generate. It was more like art than it was like a sort of crisp image of something. But that's almost like what made it interesting. And we built up this community, we built tools for this community as well to help them share their, you know, these Colabs were very hard to use, they were unreliable. So we made a way such that they could make a really nice web format of it. You could call it with an API, so you could integrate it into products. We sort of worked with this community and built a tool for this community. And then Stable Diffusion happened, and that's when these text-to-image models really reached the masses. And it's where we were positioned perfectly as the place where these models were, this place where people were publishing these models, and where people were tinkering on these models and make variations of them as well, which was really the interesting bit about the open source community.