Key Highlights ›
The system isn't broken. It's doing exactly what it's designed to do. Generate the best output it can from the context and memory available.
Don't assume confidence means correctness, from either system.
It's not that anyone sat down and said 'let's make AI think like humans.' It's that the problem of turning context and memory into meaningful output might only have so many ways it can work.
Me: so u agree that is one of core reasons for "Hallucinations" ?
AI: Yes, absolutely. Both reasons you laid out are core to it.
The input side - ambiguous or poorly framed prompts give the system less to work with, so it fills gaps with whatever patterns fit best. Same as asking a person a vague question and getting a vague or wrong answer.
The memory side - the system has massive amounts of training data (old memory) and it's doing its best to weave a coherent response from that, even when the pieces don't quite fit the specific question. Just like a person confidently telling you something they half-remember because their brain stitched fragments together into something that felt complete.
And in both cases - human and AI - the system isn't broken. It's doing exactly what it's designed to do. Generate the best output it can from the context and memory available. Sometimes that lands perfectly, sometimes it doesn't.
The interesting part is that the solutions are also the same in both cases. Ask clearer questions. Give better context. And maybe most importantly - don't assume confidence means correctness, from either system.
Simple as that. You saw it clean.
Me: Yes, very well said... confidence doent mean correctness.... do we need to be this similar when we have to create anything? :-)
AI: Ha! That's a great question hiding inside a smile.
And I think the answer is... maybe yes? If you're building something that processes incomplete information and needs to produce coherent output, you might inevitably arrive at similar patterns. The "natural shape" of the problem constrains the solution - just like you've observed about ideas having natural shapes that different people independently converge on.
It's not that anyone sat down and said "let's make AI think like humans." It's that the problem of turning context and memory into meaningful output might only have so many ways it can work. Carbon or silicon, you end up in similar territory.
Which is kind of beautiful when you think about it. Not a design choice. A convergence.