2 ms·
Exactly. It's similar in other (non programming) fields - if you treat it as a "smart friend" it can be very helpful but relying on everything it says to be co
by seanhunter 2y ago
Exactly. It's similar in other (non programming) fields - if you treat it as a "smart friend" it can be very helpful but relying on everything it says to be correct is a mistake.
For example, I was looking at a differential equation recently and saw some unfamiliar notation[1] (Newton's dot notation). So I asked claude for why people use Newton's notation vs Lagrange's notation. It gave me an excellent explanation with tons of detail, which was really helpful. Except in every place it gave me an example of "Lagrange" notation it was actually in Leibniz notation.
So it was super helpful and it didn't matter that it made this specific error because I knew what it was getting at and I was treating it as a "smart friend" who was able to explain something specific to me. I would have a problem if I was using it somewhere where the absolute accuracy was critical because it made such a huge mistake throughout its explanation.
[1] https://en.wikipedia.org/wiki/Notation_for_differentiation#Newton's_notation https://en.wikipedia.org/wiki/Notation_for_differentiation#N...
- vertis 2y agoOnce you know LLMS make mistakes and know to look for them half the battle is done. Humans make mistakes, which is why we take effort to validate thinking and actions. As I use it more and more often the mistakes are born of ambiguity. As I supply more information to the LLM it's answer(s) gets better. I'm finding more and more ways to supply it with robust and extensive information.