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🧠 Natural Language Processing

Explore a live 3D word-embedding space: watch how tokenization turns words into vectors, how similar meanings cluster together, and how vector arithmetic solves word analogies.

AI & Machine Learning3DAdvanced60 FPS

A live 3D word-embedding space where semantically related words cluster together, nearest-neighbor links reveal which words a model considers "close" in meaning, and a vector-arithmetic demo shows how embeddings encode analogies.

🔬 What It Demonstrates

How tokenized words become numeric vectors whose geometric position captures meaning — related concepts cluster, and directions between points can represent relationships like gender or royalty.

🎮 How to Use

Filter by semantic category, drag the similarity threshold to reveal or hide neighbor links, click a word to highlight its nearest neighbors, and toggle the king−man+woman analogy vectors.

💡 Did You Know?

The famous king − man + woman ≈ queen result from Word2Vec (2013) showed that simple vector arithmetic on learned embeddings can capture real semantic relationships.

⚙ Under the hood

Explore a live 3D word-embedding space: watch how tokenization turns words into vectors, how similar meanings cluster together, and how vector arithmetic solves word analogies.

machine learningnatural languageword embeddingsnlpartificial intelligencedata analysisThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install