🧠 Brain-like Predictive Coding Code World Model

This model uses a hierarchical predictive coding network inspired by the brain's cortical hierarchy:

• L1 (Sensory): Processes code token embeddings like primary visual cortex
• L2 (Hidden): Learns associative patterns like inferotemporal cortex
• L3 (Context): Maintains sequence context like prefrontal cortex

Brain-like features:

• LIF (Leaky Integrate-and-Fire) neurons
• PES (Prescribed Error Sensitivity) learning — error-driven weight updates
• Top-down predictions from higher layers
• Prediction errors drive learning (free-energy principle)
• Numba JIT acceleration for fast CPU inference