Published papers and architecture analysis from the RIIF ecosystem.
Why getting no response in a group chat activates the same pain circuits as a physical blow, what physical-world safeguards prevent this in face-to-face interaction, and the specific system architecture Haven uses to restore those safeguards without censoring, blocking, or modifying any message.
The General Learning Encoder (GLE) uses DCT-II frequency-domain encoding to create a universal representation layer across audio, DNA, EEG, and atmospheric data. This document maps the architecture to four deployed products and the patent portfolio protecting it.
Empirical proof that Haven Phone's encoding pipeline irreversibly destroys identifying information while preserving diagnostic value. Three adversarial attacks failed. Zero speaker identification. Information-theoretic security resilient to quantum computing.
Architecture, benchmarking, and proposed evaluation framework. Respiratory pattern classification (macro F1 79.7%), voice distress detection (93.0%), and EEG signal regression — all from a shared DCT-II encoding front-end.