Stable Diffusion, every mention
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every year 2025 anyone comfyanonymous (Comfy) 29Shawn Wang 23Batuhan Taskaya 14Suhail Doshi 6Ben Firshman 5Alessio Fanelli 5RJ Honicky 3Jed Borovik 3Eugene Cheah 3Jeremy Howard 2
Verbatim, from the transcripts: the passages where Stable Diffusion comes up
⚡ Inside Google Labs: Building The Gemini Coding Agent — Jed Borovik, Jules + AIE CODE Preview
- ▶ 2:47 Jed Borovik You know, when Stable Diffusion came out, that to me was the first, like, Gen AI mode. 3 times in the scene
A Technical History of Generative Media
- ▶ 4:51 unnamed speaker You know, you cannot, I think everybody knows stable diffusion, you know, and then you have maybe, like, the flux models, and then you have Black Forest Labs.
- ▶ 4:59 Batuhan Taskaya History-wise, I think the biggest, like, the initial hit was stable diffusion 1.5, which is when we actually pivoted into this new paradigm of fall, generating media cloud. 3 times in the scene
- ▶ 5:32 Batuhan Taskaya Uh, Stable Efficient 2.1 came, it was a bit of a flop, so it didn't like, you know, got that much attention.
- ▶ 5:37 Batuhan Taskaya And then SDXL came, which was like the first major model. 3 times in the scene
- ▶ 5:51 Batuhan Taskaya People started fine-tuning their faces, their objects, whatever, and generations with this, like, LoRa's started to become very popular, and then after Stable Deficient XL, there was, like, a bit of a quietness around it, you know,…
- ▶ 7:26 unnamed speaker You know, it's not a trivial decision, but obviously the right one at the time, I would say like a lot of people were hosting stable diffusion, right? 3 times in the scene
- ▶ 10:59 Batuhan Taskaya So it's like, we were at like the right time, you know, the very, it was like, uh, the, the, actually like the, the, the space was actually so, so much worse than what we have today, where like the running basic, like stable diffusion, 1.5…
- ▶ 12:44 Batuhan Taskaya You know, when we first started, there was a single model, Stable Diffusion 1.5. 2 times in the scene
- ▶ 13:04 Batuhan Taskaya The next thing, like, you know, with the, like, with adding more models, you know, like Stable Diffusion XL was a different architecture, Pixart was a different architecture, all these, like, different architectures started coming around.
- ▶ 15:04 unnamed speaker Like, if I just take stable diffusion, right, and I put it.
- ▶ 26:18 unnamed speaker I was going to show, I'm going to pull up the Quinn MMDIT where there's like this dual streaming thing, which I last, I think SD three had it. 2 times in the scene
- ▶ 30:36 Gorkem Yurtseven And then people caught up within months and then stable diffusion was even maybe better or just as good as the lead, like a couple of months later and it was open source.
- ▶ 39:26 unnamed speaker Stability did not make money from stable diffusion.
- ▶ 47:56 Batuhan Taskaya You know, like when you see these cool LORAs, like you, like there's, we have like still a lot of people using STXL with their own LORAs because they're
- ▶ 50:54 Batuhan Taskaya The thing that we saw is, as the models get better, the, like Confu UI was a much bigger thing or like, you know, relatively much bigger thing in two years ago, like a year ago, when the models were like, you know, one of the biggest Confu…
AI Video Is Eating The World — Olivia and Justine Moore, a16z
- ▶ 0:56 unnamed speaker Latent Space itself was started because of Stable Diffusion, and then there was, like, yeah, improvements in, in image generators for a while.
- ▶ 1:41 Justine Moore Generative media, too, with Stable Diffusion in, I think it was, like, September, 20, twenty-two-ish, and it's grown so quickly since then, and Olivia and I talk about this all the time, because it used to be, um, that our friends in…
The Agent Network — Dharmesh Shah, Agent.ai + CTO of HubSpot
- ▶ 1:33:59 Dharmesh Shah So he's kind of gone deep on, uh, stable diffusion and the algorithms and things like that. 2 times in the scene
AI Engineering for Art - with comfyanonymous
- ▶ 0:50 Shawn Wang I would say that when I first got started with Stable Diffusion, the star of the show was Automatic one-eleven, right? 2 times in the scene
- ▶ 7:46 comfyanonymous (Comfy) Like for example, you couldn't use like Excel and SD 1.5, because those have a different latent space, but 2 times in the scene
- ▶ 7:46 comfyanonymous (Comfy) Like for example, you couldn't use like Excel and SD 1.5, because those have a different latent space, but
- ▶ 8:06 comfyanonymous (Comfy) That's the problem that that's the, the reason why stable diffusion actually became like popular, like, cause was because of the latent space.
- ▶ 8:47 comfyanonymous (Comfy) So the, the reason I was hired is because they were doing, uh, SDXL at the time and they were basically, SDXL, I don't know if you remember, it was a base model and then a refiner model. 3 times in the scene
- ▶ 9:11 Shawn Wang But they didn't, they didn't pursue it for, like, SD three.
- ▶ 10:08 Alessio Fanelli So stable diffusion obviously is the most known. 4 times in the scene
- ▶ 10:17 comfyanonymous (Comfy) Well, the, the latest, uh, state of the art, at least, yeah, for images, there's, uh, yeah, there's Flux, uh, there's also SD 3.5. 4 times in the scene
- ▶ 11:31 Shawn Wang There's a lot of community discussion about the transition from SD 1.5 to SD two and then SD two to SD three. 3 times in the scene
- ▶ 11:31 Shawn Wang There's a lot of community discussion about the transition from SD 1.5 to SD two and then SD two to SD three. 2 times in the scene
- ▶ 11:31 Shawn Wang There's a lot of community discussion about the transition from SD 1.5 to SD two and then SD two to SD three. 6 times in the scene
- ▶ 17:08 Shawn Wang And then like, there was like other methods like textual inversion that was popular at the early SD stage. 2 times in the scene
- ▶ 19:29 comfyanonymous (Comfy) That we're trained for SD 1.5. 3 times in the scene
- ▶ 19:31 comfyanonymous (Comfy) They also kind of work on SDXL because SDXL has the, has two text encoders and one of them is the same as the, as the SD 1.5 clip L. 2 times in the scene
- ▶ 19:42 comfyanonymous (Comfy) So those, they actually would, they don't work as strongly because they're only applied to one of the text encoders, but, uh, and the same thing for SD three, three, SD three has three text encoders. 3 times in the scene
- ▶ 20:44 comfyanonymous (Comfy) So, but the hack that, uh, like you've, if you use stable diffusion 1.5, you've probably noticed, oh, it still works if I, if I use long prompts, prompts longer than 77 words. 2 times in the scene
- ▶ 42:04 comfyanonymous (Comfy) It's basically, what they did is they took SD two, and then they added some temporal attention to it, and then, uh, trained it on videos, you know.
- ▶ 43:55 comfyanonymous (Comfy) There's one that released at the same time as SD, 3.5, same day, which is why I don't remember the name. 2 times in the scene
- ▶ 46:14 comfyanonymous (Comfy) Then I made, basically, yeah, they hired me because they wanted the SDXL, so I got the SDXL working very well in ConfiUI because, yeah, they were experimenting with it. 4 times in the scene
- ▶ 49:44 comfyanonymous (Comfy) Like stable effusion models, like at least the, the open source side, and like, it's going to be best way to run or models locally, but we will have a few, like a few things to, to make money from it, like, uh, cloud inference or like that…
2024 Year in Review: The Big Scaling Debate, the Four Wars of AI, Top Themes and the Rise of Agents
- ▶ 48:07 Shawn Wang So there's no need for the stable diffusion or comfy UI workflow of like mask here and then like infill there and paint there and all that, all that stuff. 2 times in the scene