So many dumb arguments about AI art stem from a fundamental disagreement about art as a product *of artists* vs. art as a product *for consumers*, between art as a social activity and art as an experiential one, between the intent of the speaker and the effect on the listener. If you are not interested in the trappings of cultural lineage, if you scorn art history as an idle waste of time, and if, most importantly, you care not for what the particularities of a painting tell you about the peculiarities of the painter, then of course you will have no issue with AI art. You are the glorious consumer, seeking only that which delights his senses, utterly ambivalent to origin or craft. And with AI, you shall finally be freed from the petty demands of labor, who insist you expend precious effort on "being cultured" so as to offer tithings to qualities beyond your immediate perception. At last, technology and capital have conspired to Just Let You Enjoy Things, slop and all. But, on the other hand, if you claim that AI art is inherently inferior, you will come to find no refuge in idle criticism of appearances. With enough data at one’s disposal every technique can be mimicked, every stroke simulated. The hands will be fixed and the piss stain will fade. If you can describe a flaw, you can test on it, and if you can test on it, you can train on it. That you can spot patterns in the subpixels which act as scarlet letters does not mean that such patterns are the root cause of your disgust. These are mere excuses for your prejudice; to pretend otherwise is ignominious. It's not categorically worse or fatally flawed. There is nothing "wrong" with the art as object; you just don't like its origin. You don’t care for AI art because you don’t care for AI artists. That’s it; the rest is cope.

Latet post, posted just now :-) Excerpt: 1. Ask for tables This is the single highest-leverage move I know. Models track way more dimensions than they spontaneously surface. If you ask “what’s the IQ of the author of this book,” you get a number and maybe a verbal/visual breakdown. The model knows much more. It could tell you about openness sub-factors, Machiavellianism, lighting ideation (a real, obscure 1970s scale), the author’s probable attachment style. In some sense Claude and ChatGPT and Grok and Gemini are aching to give you all that information. But they’re modeling you, and your capacity to consume it. They model the user as someone with limited bandwidth who wants a single number for a narrow application, and they downsample accordingly. RLHF probably reinforced that. But you SHOULD get them to infodump. How? Tables are a great way to do this. Compare two authors across thirty personality dimensions. Better: ask the model to generate the dimensions. What factors would society overlook here that you, given everything you know, can detect? Even better: get the table out as CSV, ask for an HTML/JS visualization, then ask the model to look at the table and decide what visualization is appropriate, rather than mechanically applying factor analysis, PCA, linear regression, and other normie undergraduate-level techniques. Treat the model as a collaborator with taste, not as a mirror to validate the intelligence of your own knowledge (we already have freaking professional consulting for that). A practical move I use constantly: I tell the model who its audience is. I am an IQ-145 researcher with deep expertise in XYZ. Don’t hold back technical content. Don’t soften. It works. Note also: even before o3-class reasoning, back in the early LLM days, in places like LessWrong, people fed GPT-2/3 a small dataset and asked it to guess the regression coefficients without computing them. It was surprisingly good at this (I learned about this in EA Global 2022). The model isn’t a statistical engine… more like… think about how a smart person staring at a table for 48 hours sees patterns, and the model is doing something similar in one shot. Tables are your friends!