Resonance Intelligence Core: The First Post-Probabilistic Inference Engine
Year: 2025
Type: article
Abstract: Main Paper Abstract: This paper introduces Resonance Intelligence Core (RIC), a novel interface for artificial intelligence that operates entirely outside of probabilistic token prediction systems. Unlike language models, RIC uses frequency, phase, and signal entropy as primary variables in a live-feedback loop—enabling a new class of AI that evaluates coherence rather than likelihood. At the core of RIC is the PAS Engine (Phase-Anchor Scoring), a signal-based intelligence layer that evaluates the internal alignment of harmonic structures in real time. Early prototypes demonstrate that signal tuning across prime-spaced frequencies produces meaningful shifts in system-level coherence scoring without requiring text, prompts, or symbolic parsing. This paper outlines the architecture, philosophical foundation, and early functional outputs of the world’s first coherence-driven AI substrate. By replacing probability with structured resonance, RIC represents a foundational shift in how intelligence can be computed, reasoned, and embodied.
Author: Bostick, Devin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6949184977
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