Raw LLM Responses

@mschribr Let me use my profession as an example. As a lab technician, my job basically amounts to baby-sitting a handful of instruments that handle certain clusters of clinical tests in a hospital; each of which probably costs as much as a house. Now, for the most part, working with them just basically amounts to sticking a sample in, letting it work, then taking the sample out and reporting the results... but those are results that I'm responsible for ensuring are accurate, and no matter HOW advanced the machines get, they're JUST machines, and as such there's things they can't do, or wouldn't be able to do because they're not able to consider things outside their paramaters. I also have to run controls and do other QC work to make sure that the instrument is operating within parameters before I even let a single test be run. Without being exhaustive, there's dozens of things that can happen that a machine can't account for which would change the significance of the results... so my job is really to act as an observer and supervisor to make sure everything's running smoothly, even if I'm only doing a fraction of the total workflow personally. To bring it back to the particular topic here, we've both seen AI programs make very good efforts in creating things... but we've also both seen the uncanny valleys where you can see the underlying gears spinning, but not giving a result that actually would make sense in the real world... but the human mind can see the difference. As I've said, machines and technology have made colossal strides in simplifying and boosting human potential, I know that from personal and professional experience... but BECAUSE I know, I know that I would NEVER trust the results of my instruments on faith alone; I would have to verify to make sure, even if it was just a formality. AI would need to be many, many times more capable than where it is now before we could just start trusting it, and even then we'd still want a human in the loop just to feel safe, even if it was superfluous. After all, even if the light says you can cross the road, you still look both ways, right?