Karolina Żebrowska knows a ton about historical clothes. Sadly, she has to put up with largely ignorant modern period showmakers who make incorrect accusations about sexism of women’s fashions from the past. Here she re-enacts what happens when writers/self-styled designers try to bully experts like Karolina by (as one person put it) ‘basically wanting to produce a slightly altered fanfic they wrote when they were 13.’
Definitely check out her other videos on how modern sensibilities, including many modern gender commentators, actually get what was going on in the past completely wrong. But can you blame them? After all, almost none of those gender and similar degrees actually study the actual history, design, or the societies they are denouncing. They just study the criticisms of them.
The Portland Winter Light festival has been going on for 8 years now. I love going to visit the amazing artistic light creations people create – as well some quality people watching of folks that dress up in their own light costume creations.
While it wasn’t quite as amazing as it has been in years past, there were noticeably fewer new displays, and crowds were dramatically down, it was still a lot of fun to enjoy.
Refik Anadol makes projection mapping and LED screen art. His unique approach, however, is embracing massive data sets churned through various AI algorithms as his visualization source.
I think one of his unique additions to the space is visualizing the latent space generated during machine learning stages.
Stable Diffusion 2.0 was largely seen as a dud. Past version 1.5 you should be aware that the outcry of various artists against having their works sampled resulted in the 2.x branches trying to use less of these public sources. This means it has a more limited training set and likely more limited output variety.
We’re already seeing a real revolutions in retro gaming via emulation. Preservation of old hardware is important, but it’s also seen as almost impossible task as devices mass produced to only last 5-10 years in the consumer market reach decades of age. Failure rates will eventually reach 100% over enough time (unless people re-create the hardware). But with modern emulators, you can still play all the different games on modern hardware.
On a separate development note, we’ve also seen graphics effects like anti-aliasing and upscaling get the AI treatment. Instead of hand-coded anti-aliasing kernels, they can be generated automatically by AI and the results are now included in all major hardware vendors.
But what about the very graphics content itself? Retro game art has it’s own charm, but what if we gave it the AI treatment too?
Jay Alammar wanted to see what he could achieve by pumping in some retro game graphics from the MSX game Nemesis 2 (Gradius) into Stable Diffusion, Dall-E, and Midjourney art generators. He presents a lot of interesting experiments and conclusions. He used various features like in-painting, out-painting, Dream Studio and all kinds of other ideas to see what he could come up with.
The hand-picked results were pretty great:
He even went so far as to convert the original opening sequence to use the new opening graphics here:
I think this opens up a whole new idea. What if you replaced the entire game graphics elements with updated AI graphics? The results would essentially just become a themed re-skinning with no gameplay (or even level changes), but this definitely brings up the idea of starting your re-theming for new levels (fire levels, ice levels, space levels, etc) by auto-generating the graphics.
Then it brings up the non-art idea of re-theming the gameplay itself – possibly using AI generated movement or gameplay rules. Friction, gravity, jump height, etc – could all be given different models (Mario style physics, Super Meat Boy physics, slidy ice-level physics) and then let the AI come up with the gravity, bounce, jump parameters.
Photographer and filmmaker Nicholas Kouros spent “hundreds of hours” over 4 years creating a stop-motion meme-themed music video using paper prints and cutouts for a song called Ruined by the metal band Blame Kandinsky. He then created a new version using AI – in 4 days.
The work on the original physical shoot was intense:
“Cutting out all individual pieces was a serious task. Some of the setups were so labor-intensive, I had friends over for days to help out,” says Kouros.
“Every piece was then assembled using various methods, such as connecting through rivets and hinges. We shot everything at 12fps using Dragonframe on a DIY rostrum setup with a mirrorless Sony a7S II and a Zeiss ZE f/2 50mm Macro-Planar lens.”
In a move that likely avoided copyright issues, he used freely usable images. “Most of Ruined was made using public domain paintings and art found on museum websites like Rijks or the Met”
After everything had been shot, the RAW image sequences were imported to After Effects and later graded in DaVinci Resolve.
Using AI instead
Kouros then created a second music video but this time he used AI. The video took a fraction of the time to make. “In direct contrast with my previous work for the same band, Vague by Blame Kandinsky, it took a little over four days of experimenting, used a single line of AI text prompting, and 20 hours of rendering,”
“The text prompt line used was: ‘Occult Ritual, Rosemary’s Baby Scream, Flemish renaissance, painting by Robert Crumb, Death.’”
Kouros describes his experience with AI as “fun” and was impressed with the results that the image synthesizer gave him.
What was his final take?
“In my opinion, this specific style of animation won’t stand the test of time, but it will probably be a reminder of times before this AI thing really took off.
I embrace new tech as it comes along and I have already started making images with the aid of image generators. I’ve actually learned more about art history in this last year using AI, than in seven years of art schools.”
World Dance New York seems to teach some really high-end classes from Hip-hop, Flamenco, Samba, Fire dancing, and belly dance all the way to prenatal and even self defense.
They publish some really high quality performances like this one that shows a great combination of class and artistry. How she can dance while balancing a sword on her head is astounding.
CETI (Creative and Emergent Technology Institute) is a local creative group that experiments with different technologies for creating unique experiences. Sarah Turner is a local artist that has been experimenting with different media and video technologies – which she calls the Mobile Projection Unit. This project has set up projection mapping displays at a number of different art and media festivals.
In this video she goes over some of the things she’s learned from these projection mapping setups:
I’ve already written about nVidia’s GET3D code that can generate a wide variety of 3D objects using AI trained networks. These objects, however, are more finely tuned to generate specific objects (chairs, cars, etc). This requires a large labeled 3D dataset. nVidia provides simple ones, but if you want them to generate specific kinds of styles or from different eras (only 50’s era cars, only 1800’s style furnature), you’ll need to collect, label, and train the model for that.
There’s another player in town called DreamFusion that goes a slightly different direction. Some Google and a UC Berkley researchers are using a similar method to generate 3D models from text. This gets around the problem of needing lots of pre-trained data by using images generated from 2D text-to-image diffusion models (like Stable Diffusion, DALL-E, and MidJourney). They developed an error/loss metric that they then use to evaluate the generated 2D images and potential for 3D generation and then do so. They come up with some astounding results.
There is also a paper by Nikolay Jetchev called ClipMatrix that attempts the same text-to-2D-to-3D generation. He also seems to be experimenting with animations and something called VolumeCLIP that does ray-casing.
This kind of end-to-end workflow pipeline is exactly the kind of content makers want. Unfortunately, it also means that it could likely decimate an art department. This kind of technology could easily be used to fill the non-critical areas of ever-expanding 3D worlds in games and VR with very minimal effort or cost. In theory, it could even be done pseudo-realtime. Imagine worlds in which you can walk in any direction – forever – and see constantly new locations and objects.
He now seems to be working on auto-generated models that are animated automatically. (Content note: he seems to love to generate content based on heavy metal lyrics, demons, and other fantastical creations that I don’t think demonstrate this could work on more ‘normal’ looking models):
In looking at his Twitter stream, he also seems to be working on a version called VolumeCLIP that appears to generate voxel objects he can ray-cast into..
