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How to Implement a Cosine Similarity Function in TypeScript
Learn how to build an efficient cosine similarity function in TypeScript for comparing vector embeddings. This step-by-step guide includes code examples, performance optimizations, and practical applications for semantic search and AI recommendation systems
OpenAI’s latest embedding models like text-embedding-3-large have up to 3,072 dimensions, capturing extremely nuanced semantic relationships between words and concepts. Understanding vectors and cosine similarity provides practical tools that empower you to work effectively with modern AI features. The interactive visualizations we’ve explored help you build intuition about these mathematical concepts, while the TypeScript implementation gives you the tools to apply them in real-world scenarios.
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