That part is correct, but not consistent with others.
My problem is not that GPTs are too often wrong, it's that they always prioritize syntax over facts since they are _language_ models.
The sentence "Colorless green ideas" always make more sense to LLM than "Water is wet", simply because the latter is syntactically invalid, and that would be problematic for many use cases including Podcast replacement. Sometimes us humans want AI to say "water is definitively wet", and that has been attempted by forcing LLM to accept that factoids are more syntactically correct, but that isn't a solution and it's still an architectural problem for these pseudo-AGI apps.
My problem is not that GPTs are too often wrong, it's that they always prioritize syntax over facts since they are _language_ models.
The sentence "Colorless green ideas" always make more sense to LLM than "Water is wet", simply because the latter is syntactically invalid, and that would be problematic for many use cases including Podcast replacement. Sometimes us humans want AI to say "water is definitively wet", and that has been attempted by forcing LLM to accept that factoids are more syntactically correct, but that isn't a solution and it's still an architectural problem for these pseudo-AGI apps.