That kind of gets into "what is it like to be a bat" territory. The more imminent question is more of engineering than philosophy - what does it take for GPT-3

That kind of gets into "what is it like to be a bat" territory. The more imminent question is more of engineering than philosophy - what does it take for GPT-3 to not make the mistakes it does? This would require it to have some internal model for why humans generate text (persuasion, entertainment, etc.) as well as the social context in which that human generated the text. On a lower level it also needs to know about cognitive shortcuts that humans take for granted (object permanence, gravity) Basically, some degree of human subjective experience must be encoded and fed to the model. That's a difficult problem, but not an intractable one.