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I have made the same point elsewhere to AI enthusiasts friends of mine. The fact that defining the same task in natural language to an AI is easier than writin
by never_inline 4y ago
I have made the same point elsewhere to AI enthusiasts friends of mine.
The fact that defining the same task in natural language to an AI is easier than writing it in formal language, means the formal language lacks expressiveness [0], vocabulary, or more likely, both.
But if they are both at same level of expressiveness and vocabulary, formal language wins, because it can spot and prevent ambiguity.
The question is how scalable it is to implement such vocabulary into formal language.
[0] - The line is often blury. How many languages allow to straightforwardly express `clamp m between 1.0 and 2.0`? You can argue this is vocabulary, or this is expressiveness.
- js8 4y ago> How many languages allow to straightforwardly express `clamp m between 1.0 and 2.0`? You can argue this is vocabulary, or this is expressiveness. And I think it would be a great place for AI in programming - automated refactoring. For example, it would see a code that clamps the value and could be replaced with a library function call clamp(m,1,2). (And it would also, presumably, made sure that the code is indeed the same.) So it could help you understand the vocabulary. Or, if it sees you are doing this frequently, and it's not in the standard library, it would create the function. But instead, this AI (more like artificial stupidity) will just suggest you the same thing you wrote because you don't know any better in your code base. That's not helping.
- never_inline 4y agoGood point. But I think current approach of large scale generative AI models is not sufficient for this.