A similarity-search representation used to retrieve related items from an embedding index.
35 · Memory & Learning
Vector memory
in GenOS.
A similarity-search representation used to retrieve related items from an embedding index.
DEFINITION AND SCIENCE
What it means
in GenOS.
Vector search retrieves items by proximity in an embedding space. That is a learned geometric representation, not a biological memory mechanism; semantic similarity can return related but incorrect records.
A similarity-search representation used to retrieve related items from an embedding index.
For normalized vectors x and q, cosine similarity is s(x,q)=x·q. Top-k retrieval returns the k greatest scores; a similarity score alone is not truth confidence or evidence strength.
ANIMATED DIAGRAM · INTERACTIVE MODEL
01 / 03Explore the mechanism: Vector memory
A qualitative teaching model of this concept. It does not run GenOS or validate its implementation.
01Embed a query and recordsINPUT
02Compute vector similarityMECHANISM
03Check retrieved candidatesCONDITIONAL OUTCOME
Current transition · Step 1Embed a query and records
The modeled transition may proceed. Change the assumption and move through the stages to inspect the decision path.
PROCESS AND USE
How it works
at a glance.
Embed a query and records
A similarity-search representation used to retrieve related items from an embedding index.
Compute vector similarity
For normalized vectors x and q, cosine similarity is s(x,q)=x·q. Top-k retrieval returns the k greatest scores; a similarity score alone is not truth confidence or evidence strength.
Check retrieved candidates
Check retrieved candidates. Vector search retrieves items by proximity in an embedding space. That is a learned geometric representation, not a biological memory mechanism; semantic similarity can return related but incorrect records.
RUNTIME IMPLEMENTATION
What is connected,
and how far.
The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.
Vector search adapters and contracts are tested; retrieval quality and tenant-wide behavior require broader evaluation.
Failure modes have not yet been separately cataloged for this entry; follow the source and evidence links before relying on the mechanism.
PRIMARY RESEARCH · MECHANISM LEVEL
The mechanism
behind the analogy.
Neural networks and physical systems with emergent collective computational abilities
John J. Hopfield · Proceedings of the National Academy of Sciences 79(8), 2554–2558
Shows a dynamical network that retrieves stable patterns; it is a mechanism reference, not evidence that GenOS vector search reproduces neural memory.
Open publication ↗Primary research describes the cited mechanism; specific technologies may instead cite their original technical documentation. These sources provide context and do not validate the GenOS implementation.
EVIDENCE AND LIMITS
Scope and validation boundaries
The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.