Maybe in this specific circumstance an LLM being wrong is similar to a human being wrong but it's very jarring to a user. For example, imagine if Excel got the

Maybe in this specific circumstance an LLM being wrong is similar to a human being wrong but it's very jarring to a user. For example, imagine if Excel got the math wrong sometimes like a human does. Throughout all of digital history computers were never wrong, they're either programmed correctly or not. I think a lot of business leaders and others hyping the generative AI technology may not fully grasp the nondeterministic nature of an LLM. I work in consulting and have been on calls with senior leadership going on and on about the miracles ($$) about to unfold. However, when I raise the point that you can never really count on the output of an llm being the same or even correct and using one to guess the parameters of an API for example is going to fail eventually with no explanation or fix and how that narrows their usefulness i get the "stop being a wet blanket" talk.