Raw LLM Responses

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Comment
can you define "rich internal representation"? Do you just mean that the prompt gets transformed into a vector in high-dimensional space? And then that vector goes through the diffusion process based on representations learned during the training phase? And then the denoised vector is fed back in to the decoder which converts it from a numerical representation back into an image, right? woops! looks like I understand how your precious diffusion based models work, and somehow I still recognize it for what it is, which is inherently uninspired. You can make all the claims you want about being "a researcher" who has "published papers"—this does not give you any more credibility that your average person, because art isn't gatekept like that. That aside, anyone with half a brain can read up on this stuff (as I have, I've boned up on transformers and memory tokens and hallucinations and LoRAs and VAEs and all that kind of stuff) and understand that it's all just layers of complex computations that uncreative people feebly attempt to apply to art. No matter how much you wish it to be, it will never be equivalent to the organic process of a human mind allowing something to take shape under their hand as they move along the page. AI isn't going to create art. Accept it.
youtube 2025-06-23T03:4…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-27T06:24:53.388235
Raw LLM Response
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