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Embeddings
What Is an Embedding?
Meaning Becomes Geometry
Learning an Embedding Space
Similarity Is a Decision
Dimensions Do Not Mean What You Think
Neighborhoods and Hubs
How Many Dimensions Does Meaning Need?
The Shape of an Embedding Space
From Similarity to Search
The Nearest Neighbor Can Be Wrong
Hard Negatives
Retrieval Is a Policy
How Do You Evaluate an Embedding?
Calibration
Is Similarity One-Dimensional?
Change the Model, Change the Universe
Versioning the Space
Can One Embedding Space Be Translated Into Another?
Alignment
The Embedding Bridge
Did the Bridge Preserve the Space?
Retrieval Is Not Geometry
What Should a Translation Preserve?
Can a Smaller Representation Preserve a Larger One?
From Deltas to Operators
Building an Embedding Runtime