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> The notion that we need to all program in the top 10 popular programming languages seems dead with the advent of LLMs. To my mind, to the contrary :( LLMs ge
by nine_k 1y ago
> The notion that we need to all program in the top 10 popular programming languages seems dead with the advent of LLMs.
To my mind, to the contrary :( LLMs get trained on corpora of existing texts, including source code. They become much better at massively used languages because of the plethora of training data, and struggle with more niche languages because of the dearth of good examples. It's a positive feedback loop for mainstream languages, because more stuff gets vibe-coded, or code-assisted when the AI does a better job at it. It's a negative feedback loop for niche languages because the opportunity cost of choosing them grows :(
- elcritch 1y agoThat hasn’t been my experience with Nim so far. Both Claude 4 and GPT5 both one shot Nim code almost perfectly now. They even made a Nim JavaScript app for me. On top of that I’ve been able to “vibe” code a couple of different libraries for Nim. The bigger limits with LLMs is still “deeper” and loosing track of what it’s doing. It helps that Nim doesn’t have much unique syntax requirements or paradigms like say Rust lifetime annotations. Some of the rarer Nim idioms like `set[Enum]` being castable to a cint aren’t used. But generally what you’d do in most C++ code works well in Nim, but with simpler syntax.
- apwell23 1y agoi had the same thought as you as i was reading GP comment but lately i've come across some videos on 'Interpretability' of llm output where they said llm store 'core ideas' in a abstract way and produce concrete output on the fly based on that core representation. This is very different from viewing llms are next token predictors which would imply what you said in your comment. https://www.youtube.com/watch?v=fGKNUvivvnc&t=2748s https://www.youtube.com/watch?v=fGKNUvivvnc&t=2748s