> Generative AI got a lot more useful when I started seeing it abstractly. I put data in, it finds correlations in its neural network, and produces different da

> Generative AI got a lot more useful when I started seeing it abstractly. I put data in, it finds correlations in its neural network, and produces different data. I have to be intentional in interpreting that data to figure out what to do with it. In my opinion this is a mischaracterization just as you stated others have "raged" [0] about. The simple question for you is: how do you know how to interpret? When precision and/or depth has no critical bearing I agree with your sentiment. However shades of grey appear in the simplest of prompts, often, quick. People who do not already have the skill to "interpret" the data, as you stated, can (and probably will) assume it is correct. That end user is also not constantly reminded of the age of the underlying data the model was trained on, nor are they aware how an LLM foundationally works or if it is reasoning or not - amongst many other unknowns. Yes, while I feel as though the Microsoft report can have an air of "yes, that's the condition we expect" you're also not considering other, very important, inputs to that trivial response. Read the paper in the context of middle and high school students and now how does the "rage" feel? Are you a parent on a school board seeing this happen first hand? Not everyone has the analytical pedigree of people like yourself and the easy access to LLMs is pissing people off as they watch a generation being robbed via the easy (and oft wrong) button. [0] "It really has been a sight watching the loudest anti-AI people flog this around, then turn to rage when you clarify the range of the actual conclusion."