I will note that actually using GPT4 for classifying YES/NO constantly is currently fairly expensive; I would find it more likely that you might use GPT4 to get some training data on YES/NO or similar classifications, then fine-tune the least expensive, classifier-recommended models (ada or babbage depending on complexity), or up to DaVinci if more reasoning still seems required, for cost savings on classifiers that are being constantly consulted.
The takeaway from that possibility is that frameworks that utilize LLMs might have different layers, somewhat analogous to our reasoning heuristics that can offload reasoning to experience, reasoning, emotions, ‘gut’ feelings and intuitions, instincts, and other faster/cheaper methods of guessing at conclusions based on specialized mental circuitry rather than carefully (and newly) reasoned thought each time.
I will note that actually using GPT4 for classifying YES/NO constantly is currently fairly expensive; I would find it more likely that you might use GPT4 to get some training data on YES/NO or similar classifications, then fine-tune the least expensive, classifier-recommended models (ada or babbage depending on complexity), or up to DaVinci if more reasoning still seems required, for cost savings on classifiers that are being constantly consulted.
The takeaway from that possibility is that frameworks that utilize LLMs might have different layers, somewhat analogous to our reasoning heuristics that can offload reasoning to experience, reasoning, emotions, ‘gut’ feelings and intuitions, instincts, and other faster/cheaper methods of guessing at conclusions based on specialized mental circuitry rather than carefully (and newly) reasoned thought each time.