Stable Diffusion, NovelAI, Machine Learning Art - AI art generation discussion and image dump

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I've been playing a lot of GURPS games with friends on Tabletop Simulator, and AI slop is perfect for making character images to use as tokens. I made my account here using one from a game we recently concluded, a campaign set during the first crusade. I wanted to go for a Tyrion Lannister archetype, but horribly inbred. It only took a few photoshop alterations to get what I had in mind. It must really suck for people who would normally take commissions for this kind of thing. What would this have even cost, and how long would it have taken to get back?


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You wouldn't have paid money for this in the first place so it doesn't actually affect the art community.
 
Ars Technica: Midjourney introduces first new image generation model in over a year (archive)
AI image generator Midjourney released its first new model in quite some time today; dubbed V7, it's a ground-up rework that is available in alpha to users now.
V7 works with most parameters from previous versions (--ar, --seed, etc), including users' existing --sref codes from 6.1, as well as the recently introduced personalization feature. In fact, V7 is the first Midjourney model that has personalization enabled by default, meaning users will have to train it by picking at least 200 images to build their aesthetic profile.
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Might even think about ReForge at some point.
Speaking of, it's been discontinued as the dev's personal life has interfered with the project. If you're VRAM restricted, consider learning ComfyUI since it handles memory constrains well. I was able to run SDXL models on a 1060 with 16GB of RAM. It would offload most of it to the system RAM, run like shit and make the system unusable, but it would work instead of shitting itself.
 
AI-generated videos now possible with gaming GPUs with just 6GB of VRAM
Lvmin Zhang at GitHub, in collaboration with Maneesh Agrawala at Stanford University, has introduced FramePack this week. FramePack offers a practical implementation of video diffusion using fixed-length temporal context for more efficient processing, enabling longer and higher-quality videos. A 13-billion parameter model built using the FramePack architecture can generate a 60-second clip with just 6GB of video memory.
 
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