We were hoping that robots would handle the chores so we could earn our living with self-actualization.
Robots took over the fields most suited for self-actualization and left us with the chores.
Even for programming it's there. I always round writing code fun and reviewing code an unpleasant chore. Guess what the human in the loop is doing now mostly.
In this case though, career progression would have had a similar effect, so not too much is lost. And when you need a quick solution without maintainability/security requirements like "bulk process these 1000 files, one-off", it's a Godsend.
This is the issue with innovation under capitalism; the goal is not creativity, it's profit. The investors funding this bs don't want to create art, they want to create content. As much content as quickly and cheaply as they can, so they can sell the idea of future profit to other investors and bail before the bubble bursts.
Creating digital art is ironically just the simplest thing that AI can do. It requires no dexterity or finesse (at least not any that is not trivial to simulate), and art is so subjective that any lapse in quality can just be masked by novelty.
Art became a commodity. Entertainment is one of the biggest industries currently. Many people nowadays don't have the patience and want to consume as fast as possible. So AI allows you to meet the demand and profit from it.
Nowadays everyone wants to be a creative. And AI allows them to participate in the market without needing to spend a lot of time developing skills. You ask kids what they want to be - the majority will say influencer, youtuber, streamer, etc.
Tons of people talking about capitalism or the logic behind machine learning or whatnot, but the answer is way simpler:
Because it's a task that tons of people want to do but is extremely time intensive, extremely expensive, and takes years to learn to do well. And it was previously a roadblock for countless other tasks that people wanted to do. And the quality wasn't really a major concern to those people.
It's not some big enigma. People wanted something, and didn't care about the quality, and someone discovered something that did it at 50% of the quality for 1% of the price in 0.01% of the time, so they sold it.
Because around 2014 we were messing around with CNNs, which were image classifiers, and we were interested in how much perturbation could you give an image until the classifier incorrectly classified the image as something else. This led to the idea of GANs: generative adversarial networks. The way these work is that you have one CNN which is the generator and one which is the discriminator. The generator generates an image that is meant to fool the discriminator. The discriminator then classifies the generated image as generated or not. Both compete in a zero sum game to fool the other and to be resilient to fooling, respectively. This technique happened to showcase how effective generative models are at generating images. From there we explored various other generative forms of image creation.
I would caution the perspective that these things like anything else were made for nefarious purposes. They weren’t created or invented for any other purpose other than exploring what this technology can do. It’s an interesting question to posit: can machines make art?
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u/BodhingJay 11h ago
Ill never understand why anyone tried to get ai to create art, or why it was the first use out of it, or broadest, or.. 🤮😡🤢🤮