Semantic Fidelity Glossary
This glossary introduces semantic fidelity as a way to describe whether meaning survives transformation.
Modern language systems can remain fluent, coherent, and technically correct while losing intent, nuance, context, or cultural weight. Semantic fidelity names that gap. The difference between language that still sounds right and language that still preserves what was meant.
This project focuses on meaning degradation across compression, summarization, retrieval, rephrasing, and AI-generated text.
Core Documents
Primary Reference
- Semantic Fidelity Canonical Lexicon 2026 (PDF)
Expanded vocabulary for semantic fidelity, recursive AI systems, retrieval drift, agent drift, memory drift, and semantic infrastructure.
Original Glossary
- Semantic Fidelity Glossary 2015 (PDF)
Shorter foundational glossary defining the earliest core terms.
Concept Framework
- Semantic Fidelity Concept Framework (PDF)
Framework-level overview explaining how semantic fidelity relates to AI failure modes, drift, compression, and meaning preservation.
Key Concepts
- Semantic Fidelity — whether intent and nuance survive transformation
- Semantic Drift — how meaning shifts across repeated transformations
- Fidelity Decay — the gradual loss of semantic integrity over time
- Meaning Collapse — when outputs remain fluent but become hollow
Note: This page is part of the Semantic Fidelity Lab, a reference archive on meaning preservation, semantic drift, and evaluation failure in AI systems. It connects selected concepts and documents to the broader Reality Drift framework by A. Jacobs.