Latent Pressure Nano reframes transformer memory

This is the kind of architecture research drop that will interest people building novel memory systems, even if it is still far from a validated breakthrough.

• –The core idea is a transformer with bounded auxiliary channels for policy, format, and persistent state, meant to bias token dynamics without overtaking the main path
• –The repo is explicitly positioned as an executable research artifact, not a production-ready model or a claim of universal guarantees
• –The most interesting claim is conceptual: hallucination, continuity, and scaling are treated as different failure modes of poorly organized state rather than isolated bugs
• –What is missing for a bigger splash is benchmark evidence against mainstream transformer baselines on long-context retention, stability, or hallucination control