Feature request: Semantic checkpoint in training loop

I propose adding a semantic checkpoint module to the Flax training loop.
This would allow models to reflect on intermediate outputs and reinforce conceptual alignment.

Motivation:

Flax is a flexible framework for JAX-based training.
A semantic checkpoint — using embeddings and memory — could help detect incoherence and improve epistemic stability.

Proposed Implementation:

- Embed intermediate outputs
- Compare with a conceptual memory bank
- Trigger revision or logging if semantic drift is detected

Inspired by https://github.com/elly99-AI/MarCognity-AI.git