7 ms·

I very much agree with the perspective that LLMs are not suited for “reasoning” in the sense of creative problem solving or application of logic. I think that

I very much agree with the perspective that LLMs are not suited for “reasoning” in the sense of creative problem solving or application of logic. I think that the real potential in this domain is having them act as a sort of “compiler” layer that bridges the gap between natural language - which is imprecise - and formal languages (sql, prolog, python, lean, etc) that are more suited for solving these types of problems. And then maybe synthesizing the results / outputs of the formal language layer. Basically “agents”. That being said, I do think that LLMs are capable of “verbal reasoning” operations. I don’t have a good sense of the boundaries that distinguish the logics - verbal, qualitative, quantitative reasoning. What comes to my mind is the verbal sections of standardized tests.

eru 2y ago
> I think that the real potential in this domain is having them act as a sort of “compiler” layer that bridges the gap between natural language - which is imprecise - and formal languages (sql, prolog, python, lean, etc) that are more suited for solving these types of problems. And then maybe synthesizing the results / outputs of the formal language layer. Basically “agents”. Well, if you do all that, would you say that the system has a whole has 'reasoned'? (I think ChatGPT can already call out to Python.)
- MacsHeadroom 2y ago
  The system as a whole has reasoned twice over, verbally and then logically.
  - eru 2y ago
    Well, pfisherman seems to disagree with that use of the word reasoning.