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Language models pack billions of concepts into 12k dimensions

In a recent 3Blue1Brown video series on transformer models, Grant Sanderson posed a fascinating question: How can a relatively modest embedding space of 12,288 dimensions (GPT-3) accommodate millions of distinct real-world concepts? The answer lies at the intersection of high-dimensional geometry and a remarkable…
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AI & Machine LearningMath & Algorithms2025

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Sep 15, 2025Language models pack billions of concepts into 12k dimensions by lawrenceyan368142

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