141–150 of 1001 posts
Because AI creates unmaintainable messes in any language, and ergonomic ones help humans clean up.
Read the first few comments and surprised I didn’t see it, but training data. The voluminous amount of Python in the training data. I could write in brainfuck with ai, but I presume, wouldn’t get the same results than if going with python. My follow up question: with AI now, why care about a lang until you need to?
> A shipped app, in a language nobody on the team knew Great! Let's look back on this not too far in the future.
Read the first few comments and surprised I didn’t see it, but training data. The voluminous amount of Python in the training data. I could write in brainfuck with ai, but I presume, wouldn’t get the same results than if going with python. My follow up question: with AI now, why care about a lang until you need to?
I created a big Python codebase using AI, and the LLM constantly guesses arguments or dictionary formats wrong. Unit tests and stuff like pydantic help, but it's better to avoid that whole class of runtime errors altogether.
Read the first few comments and surprised I didn’t see it, but training data. The voluminous amount of Python in the training data. I could write in brainfuck with ai, but I presume, wouldn’t get the same results than if going with python. My follow up question: with AI now, why care about a lang until you need to?
"I could write in brainfuck with ai" Well, go on and do the experiment! Perhaps LLMs can right code as well in BF as Python but I don't recommend it because hallucinations are really hard to notice in BF. If you are going to worry about high level computer languages and AI, you are going to have to start with getting to grips with machine code and assemblers and that. Once you know how say some Python code ends up be…
Earlier quoted context omitted.
Training data can't be the whole answer. LLMs are really good at translating to different programming languages. This makes sense, given that they are derived from text translation systems. I'm getting great results in languages with comparatively small bodies of freely available code. The bigger hurdle is usually that LLMs tend to copy common idioms in the target language and if it is an "enterprise-y" language like…
> LLMs are really good at translating to different programming languages. ...for which ample training data is available. > This makes sense, given that they are derived from text translation systems. ...for languages with ample training data available. Yes, LLMs can combine information in novel ways. They are wonderful in many respects. But they make far more mistakes if they can't lean on copious amounts of training…
An experienced Rust developer is going to be in a better position to drive an agent to generate useful Rust code than a Python programmer with little or no Rust experience. Not sure I agree with the author that everyone should just generate reams of Rust now.
At least if your get paged at 3am to fix the 300k AI-generated Django blog you’ll have a chance at figuring things out. Good luck to you if Claude is down at the same time. But still better than if it was in Rust if you have no experience with that language.
Read the first few comments and surprised I didn’t see it, but training data. The voluminous amount of Python in the training data. I could write in brainfuck with ai, but I presume, wouldn’t get the same results than if going with python. My follow up question: with AI now, why care about a lang until you need to?
> I could write in brainfuck with ai, but I presume, wouldn’t get the same results than if going with python. https://esolang-bench.vercel.app/
Read the first few comments and surprised I didn’t see it, but training data. The voluminous amount of Python in the training data. I could write in brainfuck with ai, but I presume, wouldn’t get the same results than if going with python. My follow up question: with AI now, why care about a lang until you need to?
I still read the generated code, so I'm not quite willing to give up on Python yet though.