3 ms·
Is this inherent to LLMs by the way, or is it a training choice? I would love for an LLM to talk more slowly when it is unsure. This topic needs careful consid
by hengheng 2y ago
Is this inherent to LLMs by the way, or is it a training choice? I would love for an LLM to talk more slowly when it is unsure.
This topic needs careful consideration and I should use more brain cycles on it. Please insert another coin.
- wizzwizz4 2y agoIt's fairly inherent. Talking more slowly wouldn't make it more accurate, since it's a next-token predictor: you'd have to somehow make it produce more tokens before "making up its mind" (i.e., outputing something that's sufficiently-correlated with a particular answer that it's a point of no return), and even that is only useful to the extent it's memorised a productive algorithm. You could make the user interface display the output more slowly "when it is unsure", but that'd show you the wrong thing: a tie between "brilliant" and "excellent" is just as uncertain as a tie between "yes" and "no".
- fragmede 2y agoTelling the LLM to walk through the response, step by step is a prompt engineering thing though.
- deleted 2y ago[deleted]
- wizzwizz4 2y agoIt is. Studied in the literature under the name "chain of thought" (CoT), I believe. It's still subject to the limitations I mentioned. (Though the output is more persuasive to a human even when the answer is the same, so you should be careful.)