It actually quite the opposite: it's counter intuitive that you could program these or, for that matter, any intelligence. The very point of a system being intelligent is that it will figure things out on its own which both means that you don't need to program it (provide a very detailed and strict set of instructions) and you won't be able to program it. The latter might be less obvious, and it's really just an intuition, but to me it seems that the fact/capability that it can figure out what you mean from a less precise set of instructions (i.e. prompts) is equal to it not following your instructions even when you think they are to be followed. Because, first of all, how would it know when to do which? And even if we introduce a magic word that switches modes it's still contradictory because your "program" would still be a loosely defined set of instructions and not a real program. Otherwise you'd be just using an actual programming language.
Now, if the system has some form of common sense (what we, humans call common sense), then it will be able to follow your instructions without doing unexpected things most of the time but it will still fail, just as natural intelligences do.
Instead of programming the "thing", what you can do is make the thing generate a program that you can test and review and run that. But that's definitely more work than giving a set of instructions to the LLM. But, for common tasks, it may acquire enough common sense so that the surprises will be rare enough.
But among colleages we use certain jargon which varies by industry and probably by country. Could LLMs have their own preffered jargon?
I usually write pseudocode when I'm thinking about a problem to solve, so in a way I'm "thinking with pseudocode" instead of plain language. Pseudocode is probably more accurate than plain language, and it's something I'd use when explaining to other humans what I want them to code (along with diagrams, which seems ChatGPT would understand now). So, to me, speccing this pseudocode to something the LLMs find easier to understand sounds reasonable. It's like understanding how a fellow programmer prefers to get his requirements.
>The very point of a system being intelligent is that it will figure things out on its own which both means that you don't need to program it (provide a very detailed and strict set of instructions) and you won't be able to program it
Humans are "intelligent", yet also "programmable" - why would you think an artificial "intelligence" (which, by definition was programmed to start with) would not be programmable?
Because humans aren't programmable either. As soon as you try to impose a complex program on a human, i.e. a set of high level instructions, you'll face a lot of complexity and end up with a process that's pretty far from what we call programming. Just think about whether you can program a programmer, or UI designer, etc.
Sure, you can program a human to do menial tasks and they can do it with acceptable accuracy but even that may require a lot of trial and error. ("Oh, but you said I should do this and that and never mentioned that in this special case I should do that other thing." Or, probably more relevant: "yes, you told me to do this and that but this situation looked different, so I solved it in another way I thought was better.")
> It actually quite the opposite: it's counter intuitive that you could program these or, for that matter, any intelligence.
Isn't that kind of what Pavlov proved with his dog? It happens to people all the time too. We are easily conditioned (on the aggregate) to give desired results.
That's a pretty low level response. Pavlov demonstrated that you can do this for a specific outcome. Yes, humans can be conditioned to exhibit some desired results but not any desired result. Also, conditioning is teaching, not programming. Programming is defining a set of steps/conditions, and then transferring it onto the target system which will interpret and then execute on the program.
Yes, you could say that repetition is part of the transfer, but that wouldn't be too useful, it would just conflate teaching/training with programming.
Now, if the system has some form of common sense (what we, humans call common sense), then it will be able to follow your instructions without doing unexpected things most of the time but it will still fail, just as natural intelligences do.
Instead of programming the "thing", what you can do is make the thing generate a program that you can test and review and run that. But that's definitely more work than giving a set of instructions to the LLM. But, for common tasks, it may acquire enough common sense so that the surprises will be rare enough.