3 ms·
Getting pretty tired of this narrative. It's a very GPT-4 2023 era take that LLM's are just introducing untold amounts of bugs. People need to seriously learn t
by jatora 1y ago
Getting pretty tired of this narrative. It's a very GPT-4 2023 era take that LLM's are just introducing untold amounts of bugs. People need to seriously learn their AI tooling and stop repeating this nonsense.
At the most generous I will allow, it's an illusion where producing 20-50x the amount of code/hour introduces a higher raw count of bugs relative to what you are used to in that timeframe - but this notion of AI coders being more bugprone than humans is utter nonsense. The only way thats not true is on very niche systems or when the human has conceptualized and planned out their code extensively beforehand - in which case AI would still be the superior next step.
- gf000 1y ago> the only way thats not true is on very niche systems Are these very niche? Yeah, there is a category of coding where what you are doing is essentially translating from English to some high-level language with high-level APIs. This is not significantly different than translating to Spanish, of course LLMs will be successful here. But there are endless other domains with complex reasoning where LLMs absolutely suck. Like please tell me how will an LLM reason about concurrent access. And prompting it so that it will reply with "Oh you are right, here is Atomic blahblah" is not reasoning, it's statistical nonsense. Don't get me wrong, I do think LLMs are a very useful tool, but it is as much overhyped by some as it is underhyped by others.