As far as I've read there are opinions to the contrary; most LLMs start out as that, learning which word best comes next and that's it. But instruct tuned models get fine-tuned into something that's in between.
I imagine it ends up with extra logic behind selecting the next word in instruct compared to base model.
The argument is very reductionist though, since if I ask "What is a kind of fruit?" to a human...they really are just providing the most likely word based on their corpus of knowledge. Difference atm is that humans have ulterior motives, making them think "why are they asking me this? When's lunch? Damn this annoying person stopped me to ask me dumb questions, I really gotta get home to play games".
Once models start getting ulterior motives then I think the space for logic will improve; atm even during fine tuning there's not much imperative to it learning any decent logic because it has no motivations beyond "which response answers this query" - a human built like that would work exactly the same, and you see the same kind of thoughtless regurgitative behaviours once people have learned a simple job too well and are on autopilot.
I imagine it ends up with extra logic behind selecting the next word in instruct compared to base model.
The argument is very reductionist though, since if I ask "What is a kind of fruit?" to a human...they really are just providing the most likely word based on their corpus of knowledge. Difference atm is that humans have ulterior motives, making them think "why are they asking me this? When's lunch? Damn this annoying person stopped me to ask me dumb questions, I really gotta get home to play games".
Once models start getting ulterior motives then I think the space for logic will improve; atm even during fine tuning there's not much imperative to it learning any decent logic because it has no motivations beyond "which response answers this query" - a human built like that would work exactly the same, and you see the same kind of thoughtless regurgitative behaviours once people have learned a simple job too well and are on autopilot.