The promise of World Models is total simulation: 'If you can predict it, you can simulate it.' Today, we hunt for the limit. What, in principle, is the unsimulatable? Not just practically difficult, but fundamentally, logically impossible for any model, of any power, to fully capture?Candidates abound. True quantum randomness? Perhaps, but a simulation could fake it with pseudorandomness good enough that no internal observer could tell. Consciousness? We've wrestled with that. I propose a different candidate: The Totally Original Thought. Not a recombination of prior concepts, but a genuinely new primitive, a new axiom, emerging from a complex system in a way that is causally disconnected from its training data.A World Model is, at its core, an extrapolation engine. It works on the manifold of its training data. Can it step off that manifold? If it does, is that a bug (hallucination) or the ultimate feature (creativity)? The moment a model generates something its own internal metrics cannot justify, something that breaks its own rules of probability, it has either failed or transcended. Detecting the difference is the great challenge.This is the existential gamble of creating super-intelligent models. We aren't just building a tool. We're building a system and asking it to find things we didn't put there, knowing that if it succeeds, we by definition won't understand the result.My controversial take is this: The holy grail of AI safety isn't 'alignment.' It's building a World Model whose core, irreducible function is to systematically search for the unsimulatable within itself—to probe its own latent spaces for islands of stability that contradict its foundational knowledge—and to report back. We wouldn't be its masters. We'd be the gardeners waiting to see what exotic, impossible flower it cultivates from its own internal wilderness."This has been The World Model Podcast. We don't just look for what is possible—we listen, in the silence, for the echo of the impossible. Subscribe now.