In almost all cases very quickly. A LLM doesn’t have the ability to perform calculations but instead it feeds text tokens from the prompt into a model which pre

In almost all cases very quickly. A LLM doesn’t have the ability to perform calculations but instead it feeds text tokens from the prompt into a model which predicts what the next tokens should be. It can’t do basic maths but based on everything it’s been trained on it can give the impression it can. Recursive feedback isn’t likely to improve the prompt unless there is some testing and feedback provided in the Python script. You could play a game of chess and while the LLM knows the rules of chess it isn’t actually playing chess, it is calling upon patterns it has learned to predict text tokens that are appropriate for the given prompt. So opening moves will be sound, but it would quickly go off the rails and start hallucinating… Given how they work, it is amazing they give the appearance of knowing anything. Even asking “how did you do that?” gives generally compelling answers.