@rohanpaul_ai: Frozen LLMs still carry readable behavior signals deep inside their hidden states. And Proprioceptive AI has created Cy…

Frozen LLMs still carry readable behavior signals deep inside their hidden states. And Proprioceptive AI has created Cygnus, that lets LLMs sense their own internal thinking patterns and dramatically improve accuracy. This pushes Qwen-32B from 82.2% to 94.97% on ARC-Challenge using just one RTX 3090. So Cygnus equips frozen LLMs with self-sensing adapters that read their internal cognitive geometry. The adapters project hidden states into a mathematical space defined by gl(4,R) Lie algebra to isolate dark modes. Those dark modes hold the majority of accuracy-relevant signals erased by standard normalization. This design leads to substantial benchmark gains without any model retraining. Amazing how mathematical insights into activation geometry can improve reliability without full retraining. They currently host up to 50,000 users concurrently on their droplet.