# Latent Space **Domain:** Machine Learning / Representation Learning **Doc Type:** Technical Concept Node **Maturity:** Established **Related:** [[Distributed Relational Compression]], [[Semantic Traversability]], [[Variational Autoencoder]], [[Superposition]] --- ## Definition A **latent space** is an internal representation in which observed data is encoded as positions or directions along learned dimensions. Those dimensions may capture features, relations, styles, causal regularities, or statistical structure not explicitly labeled in the source data. ## Continuity relevance Latent representation demonstrates that meaning can be distributed and traversed rather than stored as isolated propositions. It does not establish autobiographical ownership, consciousness, or personal continuity.