RESEARCH PROPOSAL: Geometric Cognitive Orchestration (GCO)
1. Executive Summary Current Large Language Model (LLM) architectures, specifically Transformers, exhibit a "behavioral stubbornness" due to their reliance on static mathematical weights and linear context buffers. As conversations grow in complexity, the system suffers from Contextual Entropy—the loss of logical cohesion and the "fading" of critical data points. This proposal introduces a Geometric Cognitive […]
read moreGeometric Context Graph + Timeline Orchestration Layer for LLM Systems
1. Executive Summary This proposal introduces a Geometric Cognitive Orchestration Framework for Large Language Model (LLM) systems. The system redefines AI interaction using a geometric abstraction of knowledge and execution, where: This transforms AI systems from: Unstructured prompt interaction into: Geometrically structured, stateful execution systems 2. Problem Statement Current LLM systems suffer from: 2.1 Context […]
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