Embedding
An embedding is a numeric representation that lets a model compare meaning across items.
Category
Retrieval Context Ops
These words describe how applications store knowledge and manage context efficiently.
How to recognize this theme
Terms for search, embeddings, and runtime limits.
In a daily board, this category groups terms by their shared role. Look for four cards that describe the same mechanism, risk area, or workflow rather than four words that merely sound similar.
Educational context
These entries are vocabulary notes for learning. They are not project endorsements, token recommendations, exchange rankings, or trading signals.
Vector Store
A vector store is a database for saving and searching embeddings.
Context Window
A context window is the amount of input and generated text a model can consider at one time when producing a response.
Feature Store
A feature store manages reusable input variables for machine learning models.
Context Budget
A context budget is the amount of context a model can keep in one run.
Latency Budget
A latency budget is the maximum time a system can spend before it is too slow.