The problem is that we have fuzzy data and concrete semantics, when what we really want is concrete data and fuzzy semantics.
What we really need is a new system of reason, where each expression implies meaning, and each meaning has implications; but where those implications don't have to be reducible to computable binary logic.
The problem with LLMs is that they are ignorant to their own implications. What follows from a prompt is not any system of reason: it's just a vague sense of familiarity. Even when we have them stumble through the topology of a logical deduction, they can only act out that logic as a vain performance.
Natural language is a system of relative subjects, each with subjective implications relative to the story. So far in computing, we have nothing remotely like that.
What we really need is a new system of reason, where each expression implies meaning, and each meaning has implications; but where those implications don't have to be reducible to computable binary logic.
The problem with LLMs is that they are ignorant to their own implications. What follows from a prompt is not any system of reason: it's just a vague sense of familiarity. Even when we have them stumble through the topology of a logical deduction, they can only act out that logic as a vain performance.
Natural language is a system of relative subjects, each with subjective implications relative to the story. So far in computing, we have nothing remotely like that.