I suspect a lot of people but especially nerdy folks might mix up knowledge and intelligence, because they've been told "you know so much stuff, you are very smart!"
And so when they interact with a bot that knows everything, they associate it with smart.
There's a spectrum of human involvement in producing a thing, and art is possibly the last thing I want to see automate.
In the end, art is about human connection. There's a difference between an print of some generated AI slop found online, a painting made in a Chinese factory for a big store, and the scribble your friend made when they went through depression.
You can make a game with all three process. They are not the same.
The problem is that we mix up physical and perception, including in our language. If you look at the physical stuff, there's nothing in this specific range of EM radiation that is different from UV or IR light (or further). The physical stuff is not unique, our reading is. Therefore, color is not a physical thing.
And so when I say "color" I only mean it to be the construction that we make out of the physical thing.
We project back these construction outside of us (e.g. the apple is red), but we must no fool ourselves that the projection is the thing, especially when we try to be more precise about what is happening.
This is why I'm saying a 3D model of color (brain thing) is very far from modelling color (brain thing) at all. But! It's not purely physical either, otherwise it would just be a spectral band or something. So this is pseudo-perceptual. It's the physical stuff, tailored for the very first bits of anatomy that we have to read this physical stuff. It's stimuli encoding.
If you build a color model, it's therefore always perceptual, and needs to be evaluated against what you are trying to model - perception. You create a model to predict things. RGB and all the other models based on three values in a vaccum will always fail at predicting color (brain!) when the stimuli's surround is more complex.
Yes exactly. I'm intentionally using "color" as a perceptual thing, not as a physical thing. If we are talking about a color model, then it needs to model perception. As such, RGB, as a predictor of perception, can often fail because it doesn't account for much more than what hits the retina, not what happens after. For one, it lacks spatial context - placing the same RGB value with a different surround will feel different, like in the example above. But if you had a real color (as-in, perceptual) picker in Photoshop, you would get a different value.
It's excellent at compressing the visible part of the EM spectrum, however. This is what I meant by stimuli encoding.
They are very useful to encode stimuli, but stimuli is "not yet" color. When you have an image that is not just a patch of RGB value, a lot of things will influence what color you will compute based on the exact same RGB.
Akiyoshi's color constancy demonstrations are good examples of this. The RGB model (and any three-values "perceptual" model) fails to predict the perceived color here. You are seeing different colors but the RGB values are the same.
Maybe that's a language issue, because purple and violet are color names around here.
And as such, they are both a construct of the brain, as any other colors, like... white.
What we label as "violet wavelength" is only a narrow projection of our experience outward. Case in point, we don't have such colorful (eh) names for other EM wavelength.
I say narrow because you could take this pure laser and change th surrounding and you will inevitably perceive it differently, even though the power and wavelength are the same.
If I shine some wavelength to your eyeball and you say "it looks blue", but then I change the surrounding and now it looks white, I don't think you would conclude that the original wavelength is blue.
We have a many examples like this, which prescribe that vision is not at all an accurate wavelength measurement device.
You did send a specific wavelength to your retina, but that wasn't violet. Because violet is a construct by your brain.
Color is not a property of wavelength. There's nothing special about photons wiggling in the 380 to 750nm range.
In general it's not necessary to be this pendatic, but given the topic here, I think it's important to realize this. It takes a while because we are so good at projecting our internal experience outward.
Sidestepping what is defined as an "edge", quite a lot of work is done in the retina, including differential computation across cones - some "aggregator" cells will fire when it detect lines, movement, etc.
You can read on ganglion cells, bipolar cells and amacrine cells and see that a lot of preprocessing is done before even reaching the brain!
Consider that just after the cone cells, there are other cells doing some computation / aggregate of cone signals. Don't forget that color is a brain construct.
For those reasons (and others), there's often a strong disconnect between stimuli and perception, which means there's no such thing as a perceptual uniform color space.
Capitalism is generally good at the startup scale, to figure out who has the best ideas. Once we have collectively decided (or was forced into) a single or a few implementations, good job, you won! Now you are non-profit / state-owned company / worker coop.
Games are not the real world. When you play a game, you are look at an image. For the current topic, motion blur in games is like motion blur with a camera, not like when you turn your head.
The information travelling down the optic nerve is already processed heavily by the retina. At a minimum, you have compression by differentiation, i.e. a bunch of rods and cones are bundled together by comparing their signal.
But I suppose your point is still possibly valid - just even more complex.
