Hah—enjoy this rather excellent mash-up:

For comparison, here are the original White Lotus titles:

The whole community of creators, including toolmakers, continues to feel its way forward in the fast-moving world of AI-enabled image generation. For reference, here are some of the statements I’ve been seeing:

• ArtStation has posted guidance on “Use of AI Software on ArtStation.”
  • Projects tagged using “NoAI” will automatically be assigned an HTML “NoAI” meta tag.
  • Projects won’t be assigned this tag automatically, as the site wants creators to choose whether or not their work is eligible for use in training.
• Kickstarter has shared “Our Current Thinking on the Use of AI-Generated Image Software and AI Art.”
  • “Kickstarter must, and will always be, on the side of creative work and the humans behind that work. We’re here to help creative work thrive.”
  • Key questions they’ll ask include “Is a project copying or mimicking an artist’s work?” and “Does a project exploit a particular community or put anyone at risk of harm?”
• From 3dtotal Publishing:
  • “3dtotal has four fundamental goals. One of them is to support and help the artistic community, so we cannot support AI art tools as we feel they hurt this community.”
• Clip Studio Paint will no longer implement an image generator function:
  • “We received a lot of feedback from the community and will no longer implement the image generator palette.”
  • They “fear that this will make Clip Studio Paint artwork synonymous with AI-generated work” and are choosing to prioritize other features.
• The Society of Illustrators has shared their thoughts:
  • “We oppose the commercial use of Artificially manufactured images and will not allow AI into our annual competitions at all levels.”
  • “AI was trained using copyrighted images. We will oppose any attempts to weaken copyright protections, as that is the cornerstone of the illustration community.”

Check out the latest magic, as described by Gizmodo:

To make an age-altering AI tool that was ready for the demands of Hollywood and flexible enough to work on moving footage or shots where an actor isn’t always looking directly at the camera, Disney’s researchers, as detailed in a recently published paper, first created a database of thousands of randomly generated synthetic faces. Existing machine learning aging tools were then used to age and de-age these thousands of non-existent test subjects, and those results were then used to train a new neural network called FRAN (face re-aging network).

When FRAN is fed an input headshot, instead of generating an altered headshot, it predicts what parts of the face would be altered by age, such as the addition or removal of wrinkles, and those results are then layered over the original face as an extra channel of added visual information. This approach accurately preserves the performer’s appearance and identity, even when their head is moving, when their face is looking around, or when the lighting conditions in a shot change over time. It also allows the AI generated changes to be adjusted and tweaked by an artist, which is an important part of VFX work: making the alterations perfectly blend back into a shot so the changes are invisible to an audience.

Hah—check out this #ChatGPT discovery by Howard Pinsky:

Oh my gosh it just got better. I now asked it to write a ‘snarky’ tutorial on the Pen Tool. 😂 pic.twitter.com/PpuXZVscZx

— Howard Pinsky (@Pinsky) December 1, 2022

Among the many, many things for which I can give thanks this year, I want to express my still-gobsmacked appreciation of the academic & developer communities that have brought us this year’s revolution in generative imaging. One of those developers is our friend & Adobe veteran Christian Cantrell, and he continues to integrate new tech from his new company (Stability AI) into Photoshop at a breakneck pace. Here’s the latest:

Here he provides a quick comparison between results from the previous Stable Diffusion inpainting model (top) & the latest one:

In any event, wherever you are & however you celebrate (or don’t), I hope you’re well. Thanks for reading, and I wish all the best for the coming year!

A new (to me, at least) group called Kive has just introduced AI Canvas.

Here’s a quick demo:

To my eye it’s similar to Prompt.ist, introduced a couple of weeks ago by Facet:

I’m curious: Have you checked out these tools, and do you intend to put them to use in your creative processes? I have some thoughts that I can share soon, but in the meantime it’d be great to hear yours.

Christian Cantrell’s back & killing it as usual with the new version of his free Photoshop plugin:

He notes, “Custom, fine-tuned models are absolutely game-changing, and in the future will almost certainly represent the majority of diffusion-based creativity.” 👀 Seems like a non-trivial statement coming from the new VP of product at Stability.ai.

One of the sleeper features that debuted at Adobe MAX is the new Create Background, found under Neural Filters. (Note that you need to be running the current public beta release of Photoshop, available via the Creative Cloud app—y’know, that little “Cc” icon dealio you ignore in your menu bar. 🙃)

As this quick vid demonstrates, the filter can not only generate backgrounds based on text, it links to a Behance gallery containing images and popular prompts. You can use these visuals as inspiration, then use the prompts to produce artwork within the plugin:

Here’s the Behance browser:

I’m really excited to learn more about this development, which I’ve been eagerly awaiting. More control + more speed will make generative imaging truly, broadly useful. I’d like to understand how it compares to techniques like prompt editing.

Here’s a nice three-minute overview: