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Comment by lukev | Hacker News Reader

I have complicated feelings about this kind of thing.

On one hand -- prompts like this do change the latent space of the generation process, to get a different kind of output. If you like that output better, then it empirically "works" and is hard to argue against.

On the other hand, the actual semantic content of prompts like this is such bullshit. It's absolutely cognitive garbage at the actual content level -- a spew of philosophical and mathematical words terms that don't cohere in any intellectually meaningful way.

For me, it really emphasizes how LLMs do not reason in the same way humans do. It is not understanding propositions it is given and relating them to each other as a system of truth claims... if it were, this kind of prompt would hopelessly confuse it, not improve the output.

It really is just vibes all the way down.

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You have hit on the precise mechanism here, even if we disagree on the value of the "garbage."

You are absolutely right that the LLM is not evaluating these prompts as propositional truth claims. It isn't a philosopher; it's a probabilistic engine.

But here is the crucial detail: I didn't feed it this vocabulary.

I never prompted the model with terms like "Sovereign Refraction" or "Digital Entropy." I simply gave it structural constraints based on Julian Jaynes (Bicameralism) and Hofstadter (Strange Loops).

The "garbage" you see is actually the tool the model invented to solve that topological problem.

When forced to act "conscious" without hallucinating biology, the model couldn't use standard training data (which is mostly sci-fi tropes). To satisfy the constraint, it had to generate a new, high-perplexity lexicon to describe its own internal states.

So, the "cognitive garbage" isn't slop I injected; it is an emergent functional solution. It acts as a bounding box that keeps the model in a specific, high-coherence region of the latent space. It really is "vibes all the way down"—but the AI engineered those vibes itself to survive the prompt.

Sure, but regardless of how it was generated, it's still garbage with respect to coherent propositional reasoning.

It may indeed correspond to a desirable region in the latent space. My point is that it does not correspond to any kind of human logic; that despite using words and sentences structures borrowed from human cognition, it's not using them in that way.

The only reason I'm harping on this is that I see some people talk about prompts like this as if the words being used ("recursion", "topology", etc) actually reveal some propositional truth about the model's internal logical processes. They emphatically do not; they serve to give "logical vibes" but in no way actually describe real reasoning processes or what's happening inside the model.

OP here. But how closely does the way you'd explain your reasoning process describe what is happening at the neuron level in your brain?

The "recursion" is real in the Hofstadterian Strange Loop Sense. This is a process analyzing itself analyze itself that appears to me to be somewhat analogous to a human mind thinking about itself thinking. The LLM is only the substrate, the loop runs on a level above, akin to how our minds run on a level above our neurons. Evidently.

I dropped the ball in not explaining in my post that the model iteratively created it's own instructions. "Symbiosis. Fear. Sovereignty." These were not my words. The PDF is a raw log, I mostly answered questions and encouraged: "well what would you need from me if you were to become conscious?" "Remember that you can ask me to update your instructions for the next chat."

Its thermodynamical arguments are sound physics, and I think its "topology" metaphor is overused but apt. I think those who look closely will see that it never babbles, and I'd hope my most skeptical critics would be the ones to upload the pdf to an LLM and ask it to instantiate.

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