LLMs still blow my mind. I just can't comprehend how a prompt like > Studies have shown you nearly always make arithmetic mistakes when you don't work out the

LLMs still blow my mind. I just can't comprehend how a prompt like > Studies have shown you nearly always make arithmetic mistakes when you don't work out the answer step-by-step before answers. Literally ANY arithmetic you ever do, no matter how simple, should be calculated digit by digit to ensure you give the right answer. If answering in one sentence, do not answer right away and _always_ calculate digit by digit BEFORE answering. Treat decimals, fractions, and comparisons very precisely. actually works. Just telling the LLM to "pay more attention" or "try harder", and then it does it. It generally works in my experience too, which blows my mind (coming from a traditional deterministic computation perspective). Is it because now the text prediction next tokens are more likely to be related to a source that followed those guidelines too? The fact that so much can be controlled about a model's personality by its system prompt will never not amaze me.