I like that blog, I had not read it before.

On first read, I think this is pretty close to how I feel about generated content. This portion, in particular, is largely where I have landed (although I'm not 100% in agreement that definition of creativity and novelty, exactly):

> If creativity and novelty is about learning or increasing compression rates, then AI-generated outputs are, in a rigorously objective sense of predicting its contents, grossly inadequate because once you guess the minimal prompt (eg. “a confused economist” or “a happy dog”), there is no more learning to be done. You can predict the image contents after just a few bits. Then the image, however big and however filled with pseudo-details, provides no more learning.

The criticism I often have of LLM generated stuff is that the prompt is the only original part. To me it feels like being presented with the results of a google search, just in a different form. Once I know roughly what the query was, I know what the core question was, and I can go get my own information. I don't need anyone to hand me the search results.

I don't necessarily phrase it in terms of learning, but it's the same principle. Why should I read a 10 paragraph response from chatGPT when the unique part is the prompt? If the prompt is only a paragraph long, then it's just adding additional work that I have to do to work backwards and understand what someone was originally trying to communicate.

Similarly, the only times I have enjoyed generated images are when my friends have used them for set pieces for a D&D campaign. They didn't really add any useful information, just being static images of bosses and locations, but because they were highly tuned to the exact events in our campaign they enhanced the overall experience.

>AI slop is unsatisfying because there is no there there. It is intellectual junk food that mimics nutrition but delivers only empty calories. Satisfying AI outputs must embed dense information and compute to actually reward a reader's attention. You inject this value through brute-force search, non-trivial prompting, and rigorous curation, ensuring the final result reflects genuine algorithmic effort rather than the zero-shot 'WYSIWYG' default.

I don't agree with this at all. You can prompt all you want, but if you don't have the actual skills to make good art, you won't really know if what you're generating is good or not. This is to say nothing of the "hollow-ness" of outsourcing your voice to generative algorithms.

> Me too, but I would be careful about being too dismissive, because I would totally bet that at some point the models will be able to write top tier stories.

Maybe. I'm not certain that the mathematical average of writing is ever going to be all that great. However I'm willing to update my stance the day an LLM writes a story that makes me cry. Until then I am going to be a bit stubborn about it.

Let's also not forget that humans are more than capable of creating tons of 'slop' far worse than any current SOTA model would create, and I would argue the majority of what people write is in this category.

Models are still improving, and if you can't tell whether one was behind what you're currently reading 100% of the time (which I'm sure you know you can't), the distinction no longer matters except in very specific cases, and you have to go to a lot more effort to uncover that distinction.