One of frequently mentioned problem is lack of libraries and ecosystem.
Say Nim doesnt have MongoDB driver. So you tell AI - go look at Python driver repo, and rewrite it in Nim.
Or matplotlib binding. And then you tell AI - I have no docs and examples for my Nim matplotlib binding, go look at python examples, and adopt it to my Nim binding.
Current level of AI is not powerful enough to do this.
But once the AI gets this powerful why program at all? Just ask the things you want done, the AI would machine code directly.
Every now and then I start to dust off https://github.com/Niminem/Py2Nim for that very reason and to try solving that very problem.
The idea I have is to combine a logic engine with LLMs to create a reliable (and practical) Python-to-Nim transpiler. Recursively add types to the python code, walk and translate all the dependencies, then the repository/project/module itself, output the code as idiomatic Nim code.
Ambitious I know but I do get that itch every so often when I run into scenarios where I don't have a library readily available. Wrapping C/C++ libraries are a pain in the ass for me, and using the Nimpy bridge is (to me) like a temporary hack.
The lack of libraries suuuuuuuuuucks.
Would be super cool to just help guide a program that will port a full python project over to nim.
@xigoi there are insanely huge difference between defining the goal and providing a solution.
Declarative code or specification, or goal, maybe written in english - yes, it's the future.
Imperative code, i.e. how 99.999% code looks today - no, it's a thing of past, like horse harness, still be used for years, but it's a dead end.
Hahaha nice comic-strip. That's how it is..
We might also create a feeling of togetherness in our amazement how bad the AI-answers often are. Maybe I am using an older version but the AI is often very confused :-)
It reminds me of my high-school philosophy that any answer is better than no answer at all. (no answer = no points). But in hindsight my guessing-answers may have irritated my teacher to give me a lower grade. Or the teacher became good-humored with the ridiculous answers I may have invented...
I can't help but share the coolest thing I've seen in a while here: Diffusion models(like what's used in my avatar) for syntax trees.
This is more the meta I envision than just natural language for programs(which the earlier meme in this thread greatly explicates😂); Multi-modal representation.
Yet you bump a two day old topic to do just that? You're right that further discussion along these lines will not be tolerated. I didn't remove the original post (which in retrospect I probably should've because it's quite off-topic) because it is close to the best estimates for Palestinian casualties. Removing it without doing something about the light hearted nature of your post about anti-missile tech felt like leaving the conversation unbalanced.
Any further comments on the matter will be removed however. Feedback on the moderation is always accepted through the moderator feedback form
I agree about figuring out the problem space for experimental projects.
A lot of coding is plumbing, standard trade work, that AI is pretty good at. Setting up command line arguments; adding --verbose output; adding exceptions and traps where needed; normalizing variable and function names; etc.. stuff that a good program needs but is not challenging.
Prototype first to get the "problem space" figured out. Might write 2000 lines of code and only keep 500, the rest is a failed experiment. But now you have the solution. Then use AI to build out support structures the mindless work many of us skip for later that never gets done.
AI won't replace programmers, but programmers who use AI might replace you! ie. it can make you more effective because you can get more done and done better.