Machine learning#

Embeddings#

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. The ML technology that might end up having the biggest impact on technical writing is embeddings. What embeddings offer to technical writers is the ability to discover connections between texts at previously impossible scales.
Bookmarks. Embeddings-related papers, projects, etc.

Stateful docs site assistants. GenAI chatbot assistants might be very useful if they can serve as companions for the entire journey that readers take when visiting my docs sites.
Evaluating quality in RAG systems. How do you measure whether your retrieval-augmented generation system is improving over time?
Playing nicely with GenAI. Early ideas about how to author docs that work well with generative models.
Re: “10 principles for writing for AI”. My response to Tom Johnson’s “10 principles for writing for AI” post.
Generating summaries with HuggingFace models. Initial experiments around summarizing text with HuggingFace models.
Fine-tuning an LLM into a style guide editor. How and why one might fine-tune a generative model into a style guide editor.