Embeddings: The Future of Technical Writing?
This article explores how embedding technology could revolutionize technical writing. Unlike text generation models, embedding technology compares the semantic similarity of texts by converting them into high-dimensional vectors (embeddings). The article explains how embeddings are generated, their cost, and the differences between different models, using the Voyage-3 model as an example to illustrate its advantages in handling large texts. The author uses the analogy of map coordinates to explain how embeddings are represented in high-dimensional space and, using Word2vec as an example, demonstrates the ability of embedding technology to capture semantic relationships. Finally, the article introduces the application of embedding technology in recommending related pages on documentation websites and looks ahead to its enormous potential in technical writing.
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