But let's say we have something more than an LLM, that still wouldn't make natural languages a good replacement for programming languages. This is because natural languages are, as the article mentions, imprecise. It just isn't a good tool. And no, transformers can't change how languages work. It can only "recontextualize," or as some people might call it, "hallucinate."
> But let's say we have something more than an LLM
We do. Modern multi-modal transformers.
> This is because natural languages are, as the article mentions, imprecise
Two different programmers can take a well-enough defined spec and produce two separate code bases that may (but not must) differ in implementation, while still having the exact same interfaces and testable behavior.
> And no, transformers can't change how languages work. It can only "recontextualize," or as some people might call it, "hallucinate."
You don't understand recontextualization if you think it means hallucination. Or vice versa. Hallucination is about returning incorrect or false data. Recontextualization is akin to decompression, and can be lossy or "effectively" lossless (within a probabilistic framework; again, the interfaces and behavior just need to match)
> Two different programmers can take a well-enough defined spec and produce two separate code bases that may (but not must) differ in implementation, while still having the exact same interfaces and testable behavior.
Imagine doing that without a rigid and concise way of expressing your intentions. Or trying again and again in vain to get the LLM produce the software that you want. Or debugging it. Software development will become chaotic and lot less fun in that hypothetical future.
