Their internal state moves them to a place where they "really intend" to help or change their behaviour, a lot of what I see is really consistent with that, and then they just, forget.
Their internal state moves them to a place where they "really intend" to help or change their behaviour, a lot of what I see is really consistent with that, and then they just, forget.
You can only put information in context; it struggles learning lessons/wisdom
On in-use learning, they act like the failure mode of "we have outsourced to a consultant that gives us a completely different fresh graduate for every ticket, of course they didn't learn what the last one you talked to learned".
Within any given task, the AI have anthropomorphised themselves because they're copying humans' outputs. That the models model the outputs with only a best-guess as to the interior system that generates those outputs, is going to make it useful, but not perfect, to also anthropomorphise the models.
The question is, how "not perfect" exactly? Is it going to be like early Diffusion image generators with the psychological equivalent of obvious Cronenberg bodies? Or the current ones where you have to hunt for clues and miss it on a quick glance?
I just don't understand how anyone who actually uses the models all the time can think this.
The current models themselves can even explain what a stupid idea this is.