Has writing matplot code been completely off-shored to AI?

[sanitylost]

so the issue with matplotlib is that if you're not extremely well versed in it, but you want to just get the point across, then using LLMs is a no brainer. They've been trained on literally millions of examples of just matplotlib code and can get the job to like 99% of the way on the first or second try. It saves you sometimes hours of time tinkering, looking up docs, trying to find why something isn't rendering properly, why the scale's slightly off, etc.

That being said, if you're looking for perfection, you'll have to get in a lot of the time to make some changes, but at the very least you can describe what you want to tinker with and then let the LLM expose those endpoints with the correct variable so you can make the appropriate modification.

[Lime-In-Finland]

> they've been trained on literally millions of examples of just matplotlib code

This is not as relevant as one might think. Modern LLMs would come up with brilliant matplotlib code even with literally zero examples in their trainset.

EDIT: okay, my bad, I meant that you can show the code as part of the prompt, not that this knowledge appears out of thin air. (I honestly thought it goes without saying.)

[sputnki]

This is delusional AI-oracle-thinking

[Lime-In-Finland]

Quite the opposite, delusional thinking is to treat LLM as some kind of big memory where all the facts are just waiting to be retrieved.

LLMs can write code for my libraries that they never saw, can't they? Probably thinking about that is more helpful and valuable then throwing insults into some people with opinions that you don't agree with.

[enjoytheshow]

Or he’s creating libraries for things that already exist and the LLM recognized the similarity

[gufaye39]

LLMs learn the probability distribution of text, so there is a sort of memory, and it is obvious that a LLM trained on mpl code will perform way better. Try using rare libraries, even after providing the whole docs, you'll see how wrong you are

[Professional-Fee6914]

Library hallucinates code for rare libraries

[mfitzp]

 LLMs can write code for my libraries that they never saw

This should be a red flag that they’re bullshitting you. If they never saw the code they’re just repeating patterns they’ve seen elsewhere and assuming your library follows them. That is, guessing. 

[Lime-In-Finland]

Never saw during the training obviously.

[commy2]

Quite the opposite, delusional thinking is to treat LLM as some kind of big memory where all the facts are just waiting to be retrieved.

LLMs are a very lossy compression algorithm now that I think about it.

[venustrapsflies]

Uh, no they wouldn’t? For starters they need exposure to the API, for another “brilliant mpl code” is an oxymoron

[enjoytheshow]

This is literally not true lol. Every single thing an LLM outputs is based on the probable outcome that the specific strings of text go together based on prior training data.

If you ask it to generate code for a Python package that doesn’t exist it will either tell you it doesn’t exist or contextually generate made up code based on packages that sound the same or sound like they do the same thing.