Discover how the Core Alignment Model (CAM) uses a Dynamic Attractor and Semantic Distillation to transform noisy LLM outputs into purpose-driven, ethically sound responses. By filtering through layered adaptive processes, CAM...
Author - John Deacon
As the Semantic Distillation process moves through each layer, CAM progressively channels raw LLM output from a broad, often noisy initial state toward a refined, high-integrity response. Each layer’s unique role allows it to act as a...
The Core Alignment Model (CAM) functions as an attractor between LLMs, the human mind, and the real-time environment, aligning outputs with user intent and adapting dynamically to changes in context. CAM operates as a semantic...