"Whenever they get something "right," it's literally by accident." "the random word generator"
First of, the input is not random at all which allows the question how random the output is.
Second, it compresses data which has an impact on that data. Probably cleaning or adjustment which should reduce 'random' even more. It compresses data from us into concepts. A high level concept is more robust than 'random'.
Thinking or reasoning models are also finetuning the response by walking the hyperspace and basically collecting and strengthening data.
We as humans do very similiar things and no one is calling us just random word predictors...
And because of this, "hallucinations -- plausible but factually incorrect outputs" is an absolut accurate description of what an LLM does when it response with a low probability output.
Humans also do this often enough btw.
Please stop saying an LLM is just a random word predictor.
LLMs work by “walking” “hyperspace” ? Don’t try to correct people if you don’t know what you’re talking about. LLMs are quite literally non-deterministic language models, and that’s all they are.
Yes hyperspace: "Hyperspace is a concept from physics and science fiction referring to a higher-dimensional space"
I prefer to write hyperspace instead of n-dimensional.
Feel free to explain to me why you think my description is wrong.
LLMs are not non-deterministic in their nature. We add noise/randomess into specific layers to make them more 'creative'/'engaging' instead of always getting the exact same response we get variations.
Your whole sentence doesn't even contain a real description of what a LLM is. You say 'LLM are random LLMs'.
I explained that in a different comment already, feel free to check them out.
"Whenever they get something "right," it's literally by accident." "the random word generator"
First of, the input is not random at all which allows the question how random the output is.
Second, it compresses data which has an impact on that data. Probably cleaning or adjustment which should reduce 'random' even more. It compresses data from us into concepts. A high level concept is more robust than 'random'.
Thinking or reasoning models are also finetuning the response by walking the hyperspace and basically collecting and strengthening data.
We as humans do very similiar things and no one is calling us just random word predictors...
And because of this, "hallucinations -- plausible but factually incorrect outputs" is an absolut accurate description of what an LLM does when it response with a low probability output.
Humans also do this often enough btw.
Please stop saying an LLM is just a random word predictor.