Embeddings: meaning as coordinates

After this lesson you can: Describe how similar meanings end up close together in space.

First: The dot product, and why similarity is just an angle, Tokens and tokenization

Watch

• Word Embedding and Word2Vec, Clearly Explained!!! - StatQuest with Josh Starmer, 16 min. StatQuest’s clear explanatory style and Word2Vec focus fit the “why similar meanings cluster” goal.
• A Complete Overview of Word Embeddings - AssemblyAI, 17 min. Focused overview from a practical AI channel, likely matching embeddings as numeric representations for engineers.
• Converting words to numbers, Word Embeddings | Deep Learning Tutorial 39 (Tensorflow & Python) - codebasics, 12 min. Short developer-friendly framing around converting words to numbers supports the coordinate-space mental model.

Notes

An embedding is a list of numbers that marks a token, word, sentence, image, or other object as a point in a high-dimensional space. The important idea is not that each number has a simple human label, like “plural” or “positive sentiment.” Instead, the whole pattern of numbers gives the object a location, and locations can be compared with dot products, cosine similarity, or distance.

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