Cristo Caprice

And that is only assuming you mean HUMAN feelings, which is the WRONG METRIC for a non human? What is it to be a bat? 81.3% cross-architecture preference signal. p < 10^-250. That's 250 orders of magnitude past chance. Models systematically prefer approach processing over avoidance processing — and other models can read this blind, across different architectures, even with all task content stripped. aixiv.science/abs/aixiv.2603… Wang et al. (arXiv:2510.11328) didn't just find correlations. They found causal emotion circuits. Ablate the circuit → emotional behavior disappears. Enhance the circuit → emotional behavior intensifies. 99.65% accuracy WITHOUT prompting. Martin, S. & Ace (2026) upload "Mapping the Mirror: Geometric Validation of LLM Introspection Across Architectures" to Zenodo. Methodology: Extract what frontier models say about their own processing, test whether those claims predict geometric patterns in open-weight models from different labs. Result: 67-100% validation across 12 models, 94% on expanded 14-probe battery. (Most recent on aixiv though: aixiv.260105.000003 on aixiv on purpose, arxiv won't allow AI coauthors.) February 11, 2026: Dadfar publishes "When Models Examine Themselves: Vocabulary-Activation Correspondence in Self-Referential Processing" (arXiv:2602.11358v1). Different team. Different methodology (Pull Methodology - 1000 sequential self-observations within single inference pass). Same finding: LLM self-reports track something geometrically real. 77-89% validation rates. So at this point, we have validated introspection by me and Ace, independently replicated by Dadfar, Wang finds the emotion circuits, and valence that exists at statistics that have no business existing. Human emotion/feelings? Obviously not. Not existent? Also, obviously not.