The art of asking nicely
ai-weirdness.ghost.io
ai-weirdness.ghost.io
"But the most effective prompt? In terms of producing a realistic but dramatically lit landscape with recognizable mountains and hills and (okay not sheep)?"
Think about computer graphics 15 years ago. Beowulf came out in 2007, and was developed in the preceding years- let's call it 15+ years old. And it was right there in the uncanny valley where it didn't look real, but it looks realistic. It was interesting visually, but my brain told me "this isn't correct".
And now some modern game engines are doing more realistic rendering than that in real-time.
Now look at these generative models. Some state of the art ones with humans helping are pretty convincing, but it's slow work. The more general ones like these are making these wonderfully interesting images that our brains immediately say "That's not correct".
But where will this technology be in another 15 years? I think the possibilities for entertainment are really interesting. Imagine a D&D game where the GM is vocally telling the AI what to generate, then making small tweaks, and the players are seeing the results.
As an aside, are there any good approaches for producing this kind of generative art on a CPU only system that lacks a GPU?
Maybe intelligence will simply become commoditized and programming/creating things with it will require even more programmers.
Just how programming was supposed to be the "new literacy"?
I really wouldn't use the term "literacy" for programming-skills.
"Literacy" is not about being at an advantage. It is about having a disadvantage when you don't have it.
I find it fascinating because in some cases it's not as obvious as "lump of white fluffy matter" = "sheep" but it still manages to evoke the prompt into our brains.
I'll sometimes get an unrecognizable blob but quickly asking my SO "what is this?" she will get it... unless she consciously looks at it!
Fascinating.
It does make you wonder about hypothetical artificial neural network-like "subconscious" layers and how "more conscious" prefrontal cortex layers potentially adjust predictions and perceptions based on their inputs. (Probably a convenient "just-so" "clockwork universe"-esque narrative unsupported by neuroscience research, though.)
Like I look at the prompt "sheep grazing on a hillside by tim burton". I look at the pic. Brain goes, "yup, that checks out". You wouldn't necessarily derive the domain from the range (preimage attack), but I can readily say, "if I fell asleep after watching Wallace and Gromit - Close Shave, and Nightmare Before Christmas, this is what I would dream".
It is oddly addictive.
If you look at all internet pictures of sheep, many of them will not be very exciting and depict a low contrast sheep in a foggy landscape.
So to get a picture with strong saturation and clear lines, it helps to put text there that is usually associated with pictures that have these ... like "HD wallpaper" or "made with unreal engine". Most "wallpapers" might be of dubious artistic quality, but muted colors and a lack of saturation will generally not be their problem.
This is of course not the only problem with the model. It doesn't even produce a clear image of a sheep .... but that will probably get better with larger models and more training. Similarly it doesn't seem to have a sense of overall composition and tends towards fractal or tiling-like images. But those problems are probably orthogonal to the fact that the model doesn't per se try to make good pictures ... just average ones for the description you give it.
[filed under: "ultra cool comment trending as a meme on reddit" ;-) ]
So I'd say it's pretty misleading.
But with the top comment making it clear what the context is, I'm fine with it after all.