4 ms·
There are probably many, but the most glaring one is that LLMs has to write a word every time it thinks, meaning it can't solve a problem before it starts to wr
by Jensson 3y ago
There are probably many, but the most glaring one is that LLMs has to write a word every time it thinks, meaning it can't solve a problem before it starts to write down the solution. That is an undeniable limitation of current architectures, it means that the way the LLM answers your question also matches its thinking process, meaning that you have to trigger a specific style of response if you want it to be smart with its answer.
- p1esk 3y agoOk, so how do humans solve a problem? Isn’t it also a sequential, step by step process, even if not expressed explicitly in words? What if instead of words a model would show you images to solve a problem? Would it change anything?
- dkjaudyeqooe 3y agoNo, I don't know how other people think but I just focus on something and the answer pops into my head. I generally only use a step by step process if I'm following steps given to me.
- pixl97 3y ago>but I just focus on something and the answer pops into my head. It's perfectly valid to say "I don't know", because no one really understand these parts of the human mind. The point here is saying "Oh the LLM thinks word by word, but I have a magical black box that just works" isn't good science, nor is it a good means of judging what LLMs are capable or not capable of.
- deleted 3y ago[deleted]