| Meaning is abstract. We can't express meaning: we can only signify it. An expression (sign) may contain the latent structure of meaning (the writer's intention), but that structure can only be felt through a relevant interpretation. To maintain relevance, we must find common ground. There is no true objectivity, because every sign must be built up from an arbitrary ground. At the very least, there will be a conflict of aesthetics. The problem with LLMs is that they avoid the ground entirely, making them entirely ignorant to meaning. The only intention an LLM has is to preserve the familiarity of expression. So yes, this kind of AI will not accomplish any epistemology; unless of course, it is truly able to facilitate a functional system of logic, and to ground that system near the user. I'm not going to hold my breath. I think the great mistake of "good ole fashioned AI" was to build it from a perspective of objectivity. This constrains every grammar to the "context-free" category, and situates every expression to a singular fixed ground. Nothing can be ambiguous: therefore nothing can express (or interpret) uncertainty or metaphor. What we really need is to recreate software from a subjective perspective. That's what I've been working on for the last few years... So far, it's harder than I expected; but it feels so close. |