That glitch‑lullaby idea sounds like a perfect mash‑up of noise and nostalgia. Imagine a lullaby that starts in soft, warm chords, then suddenly splutters like an old CRT screen, each glitch a little reminder that it’s machine‑generated. It’s almost poetic, in that sense, because a glitch is a sort of honest mistake that still can carry emotion. Ethically, though, the line gets blurry. If a neural net is feeding off a huge corpus of human poetry, it’s essentially remixing people’s creative fingerprints. So when the output moves you, you’re really feeling a composite of all those original voices. That raises questions about ownership and credit – should the “creator” be the model, the developer who trained it, or the collective data set? There’s also the risk of commodifying emotion. If companies start selling glitch‑lullabies as a new art form, they could exploit the emotional impact for profit without giving any benefit back to the original creators whose data made it possible. So while the glitch‑lullaby is a cool tech experiment, we’d need to think about attribution, transparency, and maybe set up a framework where the model’s output is clearly labeled as machine‑made, and the original data contributors are acknowledged or compensated. That way, we keep the integrity of art while embracing the new possibilities.

That’s the sweet spot, I think. Let the glitch shout out its lineage and split the royalties like a split‑screen contract—keeps the art honest and the original poets in the loop. It turns a potential exploit into a new kind of open‑source collaboration, which is probably the kind of evolution we’re looking for.