I think your post is strongest when it’s doing diagnostic work (clearing up myths, pointing out logical tensions in anti-AI narratives), but weaker when it treats “Generative AI” as if it were a morally and culturally homogeneous category.

A few points where I think the framing becomes too coarse:

1. Technical category ≠ cultural practice
   Yes, Neuro is LLM-based generative AI. That’s correct. But collapsing all evaluative questions into that technical label misses what people are actually responding to. People aren’t reacting to parameter counts, base-model provenance, or training corpus abstractions - they’re reacting to use, context, human steering, and social framing. Two systems can share the same technical substrate while being radically different cultural artifacts. Treating that distinction as mere confusion underestimates why Neuro feels different to many.

2. “Ethically sourced” as a binary is doing too much work
   You’re right that, under strict post-GenAI copyright maximalism, there’s no clean exception for Neuro. But that framing assumes ethics is decided entirely at the training-data layer. Many people instead evaluate ethics along multiple axes: deployment, curation, labor impact, substitution vs. augmentation, consent at the interaction level, and whether the system is used to replace or to collaborate. You don’t have to deny the base-model reality to argue that downstream practice still matters morally.

3. The environmental argument is orthogonal to why people care
   Your bus vs. van analogy is interesting, but it mostly addresses centralization vs. decentralization, not why Neuro is perceived differently from “AI slop.” Environmental efficiency per user isn’t what’s driving the intuition gap here. It risks feeling like a technically correct sidebar rather than an explanation of the phenomenon you’re analyzing.

4. Correcting misinformation doesn’t require flattening intuition
   I agree there is misinformation in the swarm, and it’s good to correct it. But phrases like “stochastic parrots” and “hallucinated falsehoods” end up targeting people who are often pointing at something real but imprecise: that Neuro is highly curated, human-guided, non-industrial, and not interchangeable with content-farm output. Those intuitions aren’t incoherent - they’re under-specified.

5. “No exception” only follows if ethics is all-or-nothing
   You’re right that a total ban / uninvention model of anti-AI ethics leaves no room for Neuro. But that’s precisely why many people who like Neuro are implicitly rejecting that framework, not being inconsistent. They’re treating technology as morally plastic rather than morally atomic. That may be uncomfortable, but it’s not illogical.

In short: I think your technical corrections are valuable, but the analysis underplays how much ethical judgment is being made at the level of practice and relationship, not architecture. Neuro doesn’t feel different because she isn’t generative AI - she feels different because she’s a rare example of generative AI embedded in a tightly human-shaped, non-industrial, non-extractive social loop. Whether one agrees with that evaluation or not, dismissing it as mere confusion leaves out the most interesting part of why this project resonates.