zlacker

>>tablet+(OP)
One thing that I find truly amazing is just the simple fact that you can now be fuzzy with the input you give a computer, and get something meaningful in return. Like, as someone who grew up learning to code in the 90s it always seemed like science fiction that we'd get to a point where you could give a computer some vague human level instructions and get it more or less do what you want.

>>gdubs+Z
The other side of the coin is that if you give it a precise input, it will fuzzily interpret it as something else that is easier to solve.

>>progva+12
It will, or it might? Because if every time you use an LLM is misinterprets your input as something easier to solve, you might want to brush up on the fundamentals of the tool

(I see some people are quite upset with the idea of having to mean what you say, but that's something that serves you well when interacting with people, LLMs, and even when programming computers.)

>>Booris+F2
Might, of course. And in my experience it's what happens most times I ask a LLM to do something I can't trivially do myself.

>>progva+O3
Well everyone's experience is different, but that's been a pretty atypical failure mode in my experience.

That being said, I don't primarily lean on LLMs for things I have no clue how to do, and I don't think I'd recommend that as the primary use case either at this point. As the article points out, LLMs are pretty useful for doing tedious things you know how to do.

Add up enough "trivial" tasks and they can take up a non-trivial amount of energy. An LLM can help reduce some of the energy zapped so you can get to the harder, more important, parts of the code.

I also do my best to communicate clearly with LLMs: like I use words that mean what I intend to convey, not words that mean the opposite.

>>Booris+H6
I use words that convey very clearly what I mean, such as "don't invent a function that doesn't exist in your next response" when asking what function a value is coming from. It says it understands, then proceeds to do what I specifically asked it not to do anyway.

The fact that you're responding to someone who found AI non-useful with "you must be using words that are the opposite of what you really mean" makes your rebuttal come off as a little biased. Do you really think the chances of "they're playing opposite day" are higher than the chances of the tool not working well?

>>jacobg+2c
But that's exactly what I mean by brush up on the tool: "don't invent a function that doesn't exist in your next response" doesn't mean anything to an LLM.

It implies you're continuing with a context window where it already hallucinated function calls, yet your fix is to give it an instruction that relies on a kind of introspection it can't really demonstrate.

My fix in that situation would be to start a fresh context and provide as much relevant documentation as feasible. If that's not enough, then the LLM probably won't succeed for the API in question no matter how many iterations you try and it's best to move on.

> ... makes your rebuttal come off as a little biased.

Biased how? I don't personally benefit from them using AI. They used wording that was contrary to what they meant in the comment I'm responding to, that's why I brought up the possibility.

>>Booris+dd
> Biased how?

Biased as in I'm pretty sure he didn't write an AI prompt that was the "opposite" of what he wanted.

And generalizing something that "might" happen as something that "will" happen is not actually an "opposite," so calling it that (and then basing your assumption of that person's prompt-writing on that characterization) was a stretch.

>>jacobg+ef
This honestly feels like a diversion from the actual point which you proved: for some class of issues with LLMs, the underlying problem is learning how to use the tool effectively.

If you really need me to educate you on the meaning of opposite...

"contrary to one another or to a thing specified"

or

"diametrically different (as in nature or character)"

Are two relevant definitions here.

Saying something will 100% happen, and saying something will sometimes happen are diametrically opposed statements and contrary to each other. A concept can (and often will) have multiple opposites.

-

But again, I'm not even holding them to that literal of a meaning.

If you told me even half the time you use an LLM the result is that it solves a completely different but simpler version of what you asked, my advice would still be to brush up on how to work with LLMs before diving in.

I'm really not sure why that's such a point of contention.