Assuming that LLMs hamper gaining true experience and mastery of a language, and further assuming that LLMs will play a significant part in development (especially for juniors)… it seems to me that new programming languages and frameworks will have a significantly greater hurdle to overcome going forward, compared to what they faced in the past.
The LLM works via language. It’s…in the name. If a programming language that is more understandeable for a particular domain comes out, then LLMs will be useful for it just like humans will further appreciate it. Some languages just seriously blow for certain domains. Keep iterating. If a lnaguage is hard for people to use, it’s especially hard for an LLM to use.
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Language choice for a solution does not have anything to do with LLM capabilities. For someone’s hobby project, maybe. Engineering departments do not work this way. Just because LLMs can write Java better than some other languages doesn’t mean the next big game engine will be in Java.
If we’re talking about a new language (as in, something that doesn’t have a lot of code available online to train language models), then it will have an impact on engineering departments. If new programmers struggle to learn it, it won’t be used. They might actually go back to Java because it’s easier to work with.
From what I’ve heard, German was still the go-to international language in academia until WW2, when it fell out of favor and US’ post-war boom took over. So it’s a bit more complicated.
I think that LLM’s ability to understand any language, programming or otherwise, is almost entirely a factor of how much training data it can get its claws on. In the cases of new programming languages, it probably won’t be able to do much of anything.
That’s a shit take, it’s assuming that the LLM has the same thought process for learning a programming language instead of being autocorrect no steroids.
I’m pretty sure LLMs will be shit at Lisp for the foreseeable future just because the language is sort of created by the programmer.
There’s more to languages than ease of use. D is often cited having a “poor library infrastructure”, by those who leave it. They often deal with Rust, Go, or even C/C++ instead of writing their own libraries and/or library bindings.
I don’t think this is linearly correlated. Despite being called a “Language Model”, it does not mean it processes language as humans do. If an LLM is good at supporting you with a programming language mainly depends on the amount of available training data.
Let’s take esoteric languages as an example - there are languages that only work via weird Unicode symbols or other cryptic commands. A human will have a hard time to understand that language, the LLM may not have any problem at all to give working comprehensive examples (as in will be useful).
Time to conquer Malbolge with ChatGPT.