# World Model Design

## World Model Design

**Core components:**

* Temporal Transformer with 12–24 layers.
* Latent dimension: 512–1024 depending on compute.
* Uses categorical latents with 1% unimix for KL stability.
* Shortcut forcing aligns long-term rollouts with physical realism.

**Training losses:**

* Symlog reconstruction
* KL with free bits = 1 nat
* Reward prediction via two-hot bins
* Continuation prediction via logistic head


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