Il n'y a pas de questions bêtes
Tips on generative AI, LLMs, RAG and vector databases.
On a chatbot running on a local council website, a very simple question produced a wrong answer: who looks after the finances? The bot replied with a name, a role, and the present tense. The name was real. The role was correct, but it was correct in 2019: the person had left the executive at … Read more
My chatbot answers well from its knowledge base, but it has no idea how hot it is right now. Ask it “how many degrees is it?” and the model happily makes up a number. To give it live data, I reached for LLM tool calling. How LLM tool calling works With LLM tool calling, the … Read more
Imagine someone who has read every university library in Switzerland. They can answer almost any general knowledge question. But if you ask them what happened at your place last week, or what’s in your internal documents, they have no idea. They weren’t there, and no one showed them. That’s RAG explained simply: the gap this … Read more
How to prevent LLM hallucination on contact data by injecting a verified registry into the system prompt.