Slaanesh and Tzeentch approve of this action.
EldritchFeminity
My nebulous understanding is that there's no specific reason saying that women can't be space marines, but I assume that it's probably tradition since all the Primarchs are male. But I do remember hearing that one of the key people in the program that created the Primarchs was upset that they were all men because there was no reason that they couldn't have been women other than "because the Emperor said so."
IIRC, Twitter had this issue as well (or was it Tumblr?), and they "solved it" by posting that constantly on Disney images so that the bots were infringing on Disney's copyrighted characters. I don't know if it actually did anything, but it was always funny to think of the mouse coming down hard on the chuds who ran those bots.
Reminds me of when I read about a programmer getting turned down for a job because they didn't have 5 years of experience with a language that they themselves had created 1 to 2 years prior.
The argument that these models learn in a way that's similar to how humans do is absolutely false, and the idea that they discard their training data and produce new content is demonstrably incorrect. These models can and do regurgitate their training data, including copyrighted characters.
And these things don't learn styles, techniques, or concepts. They effectively learn statistical averages and patterns and collage them together. I've gotten to the point where I can guess what model of image generator was used based on the same repeated mistakes that they make every time. Take a look at any generated image, and you won't be able to identify where a light source is because the shadows come from all different directions. These things don't understand the concept of a shadow or lighting, they just know that statistically lighter pixels are followed by darker pixels of the same hue and that some places have collections of lighter pixels. I recently heard about an ai that scientists had trained to identify pictures of wolves that was working with incredible accuracy. When they went in to figure out how it was identifying wolves from dogs like huskies so well, they found that it wasn't even looking at the wolves at all. 100% of the images of wolves in its training data had snowy backgrounds, so it was simply searching for concentrations of white pixels (and therefore snow) in the image to determine whether or not a picture was of wolves or not.
I think it also had to do with the fact that they're bottom feeders, as most fish spoil fairly quickly without proper care (though some are definitely worse than others - I think shark starts going bad literally as soon as the shark dies).
Like your second point, many bottom feeders are more likely to have parasites and, therefore, probably built up a reputation as being unfit for eating (though lobsters don't have any parasites that I'm aware of).
This is literally how the furries got started. Won't be long before they commission a $5,000 cosplay suit of their ice elemental.
Aye, I was shorthanding it.
Because we're talking pattern recognition levels of learning. At best, they're the equivalent of parrots mimicking human speech. They take inputs and output data based on the statistical averages from their training sets - collaging pieces of their training into what they think is the right answer. And I use the word think here loosely, as this is the exact same process that the Gaussian blur tool in Photoshop uses.
This matters in the context of the fact that these companies are trying to profit off of the output of these programs. If somebody with an eidetic memory is trying to sell pieces of works that they've consumed as their own - or even somebody copy-pasting bits from Clif Notes - then they should get in trouble; the same as these companies.
Given A and B, we can understand C. But an LLM will only be able to give you AB, A(b), and B(a). And they've even been just spitting out A and B wholesale, proving that they retain their training data and will regurgitate the entirety of copyrighted material.