Every city already knows how to move people. Guide signs tell you where you're going. Warning signs tell you what's ahead. Work zones tell you someone is building and someone else is directing t...

Guest post by Ebenezer Isaac Veeraraju, MSc Systems Engineering for the Internet of Things, UCL. The project was developed through UCL's Industry Exchange Network (IXN), with academic supervision fro...

How This All Started So here’s the story. I just got back from a trip and had a pile of footage sitting on my laptop. Being the lazy (sorry, efficient) person I am, I fired up OpenCode and asked GP...

Every AI team today is balancing the same three pressures: cost, accuracy, and performance. Large language models excel at generating text, but the latest generation relies heavily on step-by-step re...

“How many patients are there?” is not a semantic-search question. Retrieving six relevant patient chunks and asking a language model to infer the total would be fast, fluent, and wrong. It is also un...

A streamed answer feels simple until two conversations run at once, the user changes screens, a token begins with a space, or the user presses Stop before the HTTP request has fully started. Add a be...

Vector search is excellent at finding related language. It is less reliable when a question hinges on an exact identifier, an uncommon drug name, or a clinical code. Full-text search has the opposite...

A health-record index is most vulnerable while it is being rebuilt. A source database can disconnect halfway through a large table. An embedding process can fail after thousands of rows. The applicat...

A RAG store is often introduced as a vector database. That description is too narrow for a real application. Retrieval needs text and vectors, but ingestion also needs checkpoints and publication sta...