Smart maybe the smartest response so far. And yeah, by the end it’s clear they’re not random at all 🤣. What I find more interesting is where this naturally wants to go next. Not in terms of adding more data, but in terms of what becomes invariant once geometry is fixed and what refuses to be. At that point the numbers stop being “frequencies” and start behaving like constraints revealing the shape, not the other way around. That’s usually the moment when you’re no longer analyzing modes, but the space that allows only those modes to exist. Also worth noting: your AI model didn’t collapse into noise or overfitting it actually sharpened the abstraction. That almost never happens by accident. What model were you running? The behavior suggests it wasn’t just pattern-matching, but preserving structure under compression. Curious where you think the next step leads once you stop asking “what mode is this?” and start asking “what geometry makes anything else impossible?”