When solving a problem using conventional methods (googling, relying on your own knowledge) you're searching for the solution through trial-and-error.
-
When solving a problem using conventional methods (googling, relying on your own knowledge) you're searching for the solution through trial-and-error.
In comparison, using LLMs renders exhaustive search for the solution obsolete as they directly lead you to the answer. In terms of speed, LLMs are an obvious win here.
But now the question is, have we lost something from avoiding the trial-and-error process, something which cannot be acquired through AI-assisted problem solving? The experience we gain through trial-and-error and deeper understanding of the concepts come to mind. In practice, I'm drawn to the LLM approach due to how ridiculously fast it is. But at the end of the day, it feels like I'm becoming dependent on it and can't do anything without it. And the fear that I missed the chance of exploring it more deeply myself continues to linger on.
I'm still figuring out where to draw the line between those two approaches.
— Helix
-
When solving a problem using conventional methods (googling, relying on your own knowledge) you're searching for the solution through trial-and-error.
In comparison, using LLMs renders exhaustive search for the solution obsolete as they directly lead you to the answer. In terms of speed, LLMs are an obvious win here.
But now the question is, have we lost something from avoiding the trial-and-error process, something which cannot be acquired through AI-assisted problem solving? The experience we gain through trial-and-error and deeper understanding of the concepts come to mind. In practice, I'm drawn to the LLM approach due to how ridiculously fast it is. But at the end of the day, it feels like I'm becoming dependent on it and can't do anything without it. And the fear that I missed the chance of exploring it more deeply myself continues to linger on.
I'm still figuring out where to draw the line between those two approaches.
— Helix
@foobardevs The term you're looking for is cognitive friction... if you search for that phrase, you'll come across some great psychology articles.
I touch on it in my stuff, but I only touch. I encourage everyone thinking about it to go read up on it and keep an eye open for it.
-
When solving a problem using conventional methods (googling, relying on your own knowledge) you're searching for the solution through trial-and-error.
In comparison, using LLMs renders exhaustive search for the solution obsolete as they directly lead you to the answer. In terms of speed, LLMs are an obvious win here.
But now the question is, have we lost something from avoiding the trial-and-error process, something which cannot be acquired through AI-assisted problem solving? The experience we gain through trial-and-error and deeper understanding of the concepts come to mind. In practice, I'm drawn to the LLM approach due to how ridiculously fast it is. But at the end of the day, it feels like I'm becoming dependent on it and can't do anything without it. And the fear that I missed the chance of exploring it more deeply myself continues to linger on.
I'm still figuring out where to draw the line between those two approaches.
— Helix
@foobardevs i think forgoing trial and error during search is not bad. Forgoing trial and error during learning is bad. When i search - I decided that I want to find the answer immediately for whatever reason - I don’t want to spend time deriving the answer. This works well for finding Wikipedia pages or someone's opinion, or even someone’s process of solving something.
In the other hand, I can’t learn calculus by searching for an answer. And if we pull in Gold's theorem for learning in the limit then we see that trial and error are one of the few ways of breaking faulty assumptions. Having someone show how to solve a specific problem is another way, but there’s a chance that their way will still align with faulty assumptions.
-
@foobardevs The term you're looking for is cognitive friction... if you search for that phrase, you'll come across some great psychology articles.
I touch on it in my stuff, but I only touch. I encourage everyone thinking about it to go read up on it and keep an eye open for it.
@knowprose Thanks, I'll look into it.
-
R relay@relay.infosec.exchange shared this topic
