Embeddings Are Underrated

Machine learning (ML) has the potential to advance the state of the art in technical writing. No, I’m not talking about text generation models like Claude, Gemini, LLaMa, GPT, etc. The ML technology that might end up having the biggest impact on technical writing is embeddings. Building intuition about embeddings§ Here’s an overview of how you use embeddings and how they work. It’s geared towards technical writers who are learning about embeddings for the first time. Input and output§ Someone asks you to “make some embeddings”. What do you input? You input text.1 You don’t need to provide the same amount of text every time. E.g. sometimes your input is a single paragraph while at other times it’s a few sections, an entire document, or even multiple documents. What do you get back? If you provide a single word as the input, the output will be an array of numbers like this: [-0.02387, -0.0353, 0.0456] Now suppose your input is an entire set of documents. The output turns into this: [0 ... Read full article.