AI로 어떤 유형의 코드를 생성해야 합니까?
hackernews
|
|
📰 뉴스
#오픈소스
원문 출처: hackernews · Genesis Park에서 요약 및 분석
요약
나(그리고 많은 사람들)는 'AI를 활용하여 할 수 있는 가장 좋은 작업은 무엇인가'에 대해 많이 생각해 왔습니다. 제가 사용해 온 개인 프레임워크는 다음과 같은 경우 AI를 사용하여 코드를 생성해야 한다는 것입니다. 1. 코드는 <i>검증하기 쉽습니다</i> 2. 인간이 이해하는 것은 중요하지 않습니다.<p>AI가 생성하는 가장 좋은 것은 순수 함수 수준에 있는 것입니다(검증하기 쉽고 인터페이스를 이해하는 한 구현을 이해하는 것이 반드시 중요하지는 않음). 나는
본문
I (and many people) have been thinking a lot about "what are the best tasks to do using AI."
My personal framework I've been using is, you should use AI to generate code when:
1. The code is <i>easy to validate</i>
2. It is not important that a human understands it<p>I find that the best thing to AI generate is something on the level of a pure function (easy to validate + not necessarily important to understand implementation as long as you understand the interface).
I've tried doing things like generating whole services or applications, but those often violate rule 1 - it's <i>hard</i> to validate an entire application behaves "correctly" when "correctly" isn't really well defined - i.e., are there memory leaks, is it secure, is it able to be monitored, etc.</p><p>I'm curious of others thoughts on this topic. The larger the task you complete using AI, the more time savings, but also the more likely that a catastrophic error exists in the generated code.
A side effect of following these rules is there is not that much of a productivity gain - maybe 20-30% at most.</p><p>I'm really interested if anyone has found a way to strike a balance here - significant speedup without losing correctness.</p>
My personal framework I've been using is, you should use AI to generate code when:
1. The code is <i>easy to validate</i>
2. It is not important that a human understands it<p>I find that the best thing to AI generate is something on the level of a pure function (easy to validate + not necessarily important to understand implementation as long as you understand the interface).
I've tried doing things like generating whole services or applications, but those often violate rule 1 - it's <i>hard</i> to validate an entire application behaves "correctly" when "correctly" isn't really well defined - i.e., are there memory leaks, is it secure, is it able to be monitored, etc.</p><p>I'm curious of others thoughts on this topic. The larger the task you complete using AI, the more time savings, but also the more likely that a catastrophic error exists in the generated code.
A side effect of following these rules is there is not that much of a productivity gain - maybe 20-30% at most.</p><p>I'm really interested if anyone has found a way to strike a balance here - significant speedup without losing correctness.</p>
Genesis Park 편집팀이 AI를 활용하여 작성한 분석입니다. 원문은 출처 링크를 통해 확인할 수 있습니다.
공유